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thesis entitled

USING GEOMEMBRANES TO IMPROVE THE STORAGE EFFICIENCY OF
RUNOFF CATCHMENT PONDS IN THE COMMUNITY OF EL RINCON,
IN QUERETARO, MEXICO: A BENEFIT-COST ANALYSIS

presented by

Christopher M. Purdy

has been accepted towards fulfillment
of the requirements for

Masters of Science dqyfein Resource Development

 

 

 

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_————____—_____————-—-——

USING GEOMEMBRANES TO IMPROVE THE STORAGE EFFICIENcY OF
RUNOFF CATCIIMENT PONDS IN THE COMMUNITY OF EL RINCON, IN
QUERETARO, MEXICO: A BENEFIT-COST ANALYSIS
By

Christopher M. Purdy

A THESIS
Submitted to
Michigan State University
in partial fulfilhnent of the requirements for the degree of
MASTERS OF SCIENCE

in Resource Development

2002

ABSTRACT
USING GEOMEMBRANES TO IMPROVE THE STORAGE EFFICIENCY OF
RUNOFF CATCHMENT PONDS IN THE COMMUNITY OF EL RINCON, IN
QUERETARO, MEXICO: A BENEFIT-COST ANALYSIS
By

Christopher M. Purdy

This study presents a benefit-cost analysis of using geomembrane liners to
improve the water storage efficiency of four runoff catchment ponds for one case study in
Quere'taro, Mexico. The lining technique is intended to help increase irrigation capacity
(agricultural production) by eliminating the infiltration loss of stored pond water. The
study uses rainfall, evaporation, and animal consumption data to calculate rainfall runoff
(potential catchment) and each source of stored water loss from the four ponds. After
determining that rainfall runoff is sufficient to fill the ponds on an annual basis, the study
calculates project-generated water savings by comparing rates of runoff accumulation and
evaporation loss for the critical dry season carry-over. The value of this water is
calculated by predicting its yield-enhancing efl‘ect on two crops: irrigated (“punta de
riego”) corn and cempasuchil. A net present value and benefit-cost ratio is calculated for
each of the four ponds to determine the project’s cost-effectiveness.

This study concludes that for the ponds and crops studied, the installation of
geoemembranes is not a cost-effective means of increasing agricultural production.
However, Geomembranes should not be fully discounted as a potential water
management tool for the site without further study as to their cost-effectiveness and

overall feasibility.

ACKNOWLEDGMENTS

The author would like to sincerely thank the following people without whose
collaboration and support, this study would not have been possible:
My advisor: Dr. Scott G. Witter, Professor and Acting Chairperson, Department of
Resource Development, Michigan State University.
My Committee Members at Michigan State University:
Dr. Cynthia Fridgen - Department of Resource Development
Dr. James Oehmke — Department of Agricultural Economics
Dr. Scott Whiteford — Department of Latin American & Caribbean Studies
Sergio Perez and David Bergdorf of the Michigan - Natural Resource Conservation
Service
Dr. Rafil Pineda - Department of Biology, La Universidad AutOnoma de Querétaro
Eduardo Garcia —— Agricultural Engineer, SEMARNAP-FAO Project, Liaison to El
Rincén
Dr. Karen Wayland — great friend and confidant
Elizabeth Lozada - great fi'iend and supporter
Friendly students at the AUQ, especially: Oefelia and Marco Vinicio

My loving family: James D. and Mary Purdy, and my grandmother Rilla Stewart

iii

TABLE OF CONTENTS

LIST OF TABLES .................................................................................. vii

LIST OF FIGURES ................................................................................. xii

CHAPTER 1

INTRODUCTION .................................................................................... 1
1.1 The Problems of Food Demand and Water .......................................... 1
1.2 F arm-Scale Water Harvesting/ Storage Systems .................................... 4
1.3 Water Storage in Querétaro, Mexico ................................................. 5
1.4 Statement of the Research Problem ................................................... 7
1.5 Research Objective ..................................................................... 8
1.6 Research Design ......................................................................... 8
1.7 Study Significance ....................................................................... 9
1.8 Study Organization .................................................................... 10

CHAPTER 2

LITERATURE REVIEW .......................................................................... 11
2.1 Introduction ............................................................................. 11
2.2 Literature Search ....................................................................... 12
2.3 Introduction to Geomembrane Technology ........................................ 15
2.4 Geomembrane Materials .............................................................. 17
2.5 Geomembrane Construction ......................................................... 19
2.6 Geomembrane Installation ............................................................ 19
2.7 Geomembrane Lifetimes ............................................................. 19
2.8 Other Sources of General Information ............................................ 19
2.9 Summary of Like Cases ............................................................... 21
2.10 Conclusions about the Geomembrane Literature Base

Pertinent to this Study ................................................................ 24

2.11 Introduction to Rainfall Runoff Modeling ....................................... 24
2.12 Rainfall ................................................................................. 25
2.13 Loss Functions ........................................................................ 27
2.14 SCS Curve Number Method ........................................................ 28
2.15 Computer Models ..................................................................... 29
2.16 Conclusions Regarding Runoff Calculation Modeling .......................... 30
2.17 Introduction to Benefit-Cost Analysis ............................................. 30

CHAPTER 3

SITE DESCRIPTION .............................................................................. 32
3.1 Introduction ............................................................................. 32
3.2 History of the Diagnostic Report .................................................... 32
3.3 Study Site ............................................................................... 32
3.4 Physical Geography ................................................................... 34

iv

3.5 Climate .................................................................................. 34

3.6 Economic Activities ................................................................... 35
3.7 Agriculture .............................................................................. 36
3.8 Agricultural Extension ................................................................ 38
3.9 Corn ...................................................................................... 38
3.10 Punta de Riego (Irrigation Cover) .................................................. 39
3.11 Environmental & Natural Resource Problems .................................... 40
3.12 Water Storage Ponds ................................................................. 41
3.13 Conclusions ........................................................................... 42

CHAPTER 4

STUDY METHODS ................................................................................ 43
4.1 Overview ................................................................................ 43
4.2 Data Collection ........................................................................ 44
4.3 Site Selection ........................................................................... 45
4.4 Pond Selection & Measurement ...................................................... 46
4.5 Rainfall Analysis ....................................................................... 51
4.6 Calculation of Runoff ................................................................. 54
4.7 Catchment Area ........................................................................ 54
4.8 Calculation of Excess .................................................................. 56
4.9 Curve Number Selection .............................................................. 57
4.10 Substitution of Precipitation Totals ................................................ 60
4.11 Conversion ofExcess to Runoff61
4.12 Comparison of Runoff to Pond Capacity .......................................... 61
4.13 Calculation of Stored Water Loss .................................................. 65
4.14 Calculation of Stored Water Loss Due to Evaporation .......................... 66
4.15 Calculation of Animal Consumption .............................................. 69
4.16 Calculation of Stored Water Loss Due to Infiltration ........................... 74
4.17 Comparison of Stored Water Loss ................................................. 76
4.18 Re-Calculation of Evaporation Under Project Conditions ...................... 76
4.19 Calculation of Project-Generated Water Surplus ................................. 81
4.20 Calculation of Production Land Base as a Function of Project-Generated

Water Surplus ...................................................................... 84

4.21 Calculation of Production Values (i.e. Project Income) ........................ 89
4.22 Calculation of Crop Production Costs ............................................. 89
4.23 Calculation of Geomembrane Installation Costs ................................. 94
4.24 Liner Installation Costs ............................................................ 105
4.25 Liner Maintenance Costs .......................................................... 106
4.26 Calculation of Project Budgets ................................................... 107

CHAPTER 5

RESULTS .......................................................................................... 120
5.1 Without-Project Results (Rain-fed Corn) ......................................... 120
5.2 With-Proj ect Results (Punta de Riego Corn and Cempasuchil) ............... 121

CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS ............................................ 122
6.1 Conclusions ........................................................................... 122
6.2 Project Recommendations .......................................................... 124
6.3 Summary (Assumptions/Limitations of the Study) .............................. 124
6.4 Recommendations for Further Study: ............................................. 127
6.5 Final Thoughts ........................................................................ 130

APPENDIX A

GEOMEMBRANE INFORMATION CONTINUED ........................................ 131

APPENDIX B

SITE DESCRIPTION CONTINUED ........................................................... 138

APPENDIX C

INTRODUCTION TO CEMPASUCHIL AND ITS PRODUCTION ..................... 145

APPENDIX D

RAINFALL ANALYSIS ......................................................................... 148

BIBLIOGRAPHY ................................................................................. 171

vi

Table 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Table 9

Table 10

Table 1 1

Table 12

Table 13

Table 14

Table 15

Table 16

Table 17

Table 18

Table 19

LIST OF TABLES

Study Pond Characteristics ........................................................... 48
Aggregated Rainfall Data (mm/mo.) 1971-1991 ................................. 55
Rainfall Runoff Available for Catchment in Cu. M. — Ponds 1 & 4 ........... 62
Rainfall Runoff Available for Catchment in Cu. M. — Pond 2 .................. 63
Rainfall Runoff Available for Catchment in Cu. M. - Pond 3 ................... 64
Evaporation Pan Coefficients ........................................................ 67
Evaporation Surface Area Coefficients ............................................. 68
Evaporation Loss from Pond Surface in Cu. M . - Pond 1 ....................... 70
Evaporation Loss from Pond Surface in Cu. M. — Pond 2 ........................ 71
Evaporation Loss from Pond Surface in Cu. M. — Pond 3 ........................ 72
Evaporation Loss from Pond Surface in Cu. M. — Pond 4 ........................ 73
Animal Consumption Loss in Cu. M. — Pond 1 .................................... 75
Animal Consumption Loss in Cu. M. — Pond 2 .................................... 75
Animal Consumption Loss in Cu. M. — Pond 3 .................................... 75
Animal Consumption Loss in Cu. M. — Pond 4 .................................... 75

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 1 — Average Runoff Year ...................................................... 77

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 1 - Highest Runoff Year ....................................................... 77

Zero Water Balance-Producing Infiltration Rate in Cu. M. -
Pond 1 — Lowest Runoff Year ....................................................... 77

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 2 — Average Runoff Year ...................................................... 78

vii

Table 20

Table 21

Table 22

Table 23

Table 24

Table 25

Table 26

Table 27

Table 28

Table 29

Table 30

Table 31

Table 32

Table 33

Table 34

Table 35

Table 36

Table 37

Zero Water Balance-Producing Infiltration Rate in Cu. M. ——
Pond 2 - Highest Runoff Year ....................................................... 78

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 2 — Lowest Runoff Year ....................................................... 78

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 3 — Average Runoff Year ...................................................... 79

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 3 — Highest Runoff Year ....................................................... 79

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 3 — Lowest Runoff Year ....................................................... 79

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 4 —- Average Runoff Year ...................................................... 80

Zero Water Balance-Producing Infiltration Rate in Cu. M. —
Pond 4 — Highest Runoff Year ....................................................... 80

Zero Water Balance-Producing Infiltration Rate in Cu. M. -
Pond 4 — Lowest Runoff Year ....................................................... 80

Re-Calculation of Ave. Evaporation for Lined Pond in Cu. M. —
Ponds 1&4 .............................................................................. 82

Re-Calculation of Ave. Evaporation for Lined Pond in Cu. M. — Pond 2. . . ...82

Re-Calculation of Ave. Evaporation for Lined Pond in Cu. M. -— Pond 3. . ....82

Calculation of With-Project Water Surplus in Cu. M. — Pond 1 ................ 85
Calculation of With-Project Water Surplus in Cu. M. — Pond 2 ................ 85
Calculation of With-Project Water Surplus in Cu. M. — Pond 3 ................ 86
Calculation of With-Project Water Surplus in Cu. M. — Pond 4 ................ 86
Calculation of Production Land Base as a Function of Surplus Water... . . ....88
Calculation of Crop Surplus Values - Pond 1 ..................................... 90
Calculation of Crop Surplus Values —- Pond 2 ..................................... 90

viii

Table 38
Table 39
Table 40
Table 41
Table 42
Table 43
Table 44
Table 45
Table 46
Table 47
Table 48
Table 49
Table 50
Table 51
Table 52
Table 53
Table 54
Table 55
Table 56
Table 57
Table 58
Table 59
Table 60

Table 61

Calculation of Crop Surplus Values - Pond 3 ..................................... 90
Calculation of Crop Surplus Values — Pond 4 ..................................... 90
Equipment Depreciation — Rain-F ed Corn — Pond l .............................. 92
Equipment Depreciation — Rain-F ed Corn — Pond 2 ............................. 92
Equipment Depreciation — Rain-F ed Corn — Pond 3 .............................. 92
Equipment Depreciation - Rain-Fed Corn — Pond 4 .............................. 92
Equipment Depreciation — Punta de Riego Corn - Pond 1 ....................... 93
Equipment Depreciation -— Punta de Riego Corn — Pond 2 ....................... 93
Equipment Depreciation -— Punta de Riego Corn - Pond 3 ....................... 93
Equipment Depreciation — Punta de Riego Corn — Pond 4 ....................... 93
Production Budget for Rain-F ed Corn — Pond 1 ................................... 95
Production Budget for Rain-F ed Corn — Pond 2 ................................... 96
Production Budget for Rain-Fed Corn - Pond 3 ................................... 97
Production Budget for Rain-Fed Corn - Pond 4 ................................... 98
Production Budget for Punta de Riego Corn — Pond I ........................... 99
Production Budget for Punta de Riego Corn — Pond 2 .......................... 100
Production Budget for Punta de Riego Corn — Pond 3 .......................... 101
Production Budget for Punta de Riego Corn — Pond 4 .......................... 102
Pond Preparation Costs in Pesos — Pond 1 ....................................... 104
Pond Preparation Costs in Pesos — Pond 2 ....................................... 104
Pond Preparation Costs in Pesos - Pond 3 ....................................... 104
Pond Preparation Costs in Pesos — Pond 4 ....................................... 104
Liner Installation Costs .............................................................. 105
Annual Liner Maintenance Costs .................................................. 106

ix

Table 62

Table 63

Table 64

Table 65

Table 66

Table 67

Table 68

Table 69

Table 70

Table 71

Table 72

Table 73

Table 74

Table 75

Table 76

Table 77

Table 78

Table 79

Table 80

Table 81

Table 82

Table 83

Table 84

Table 85

Production Budget without Project - Pond l — Rain-Fed Corn ............... 108
Production Budget with Project - Pond 1 — Punta de Riego Corn ............. 109
Production Budget with Project - Pond 1 — Cempasuchil ..................... 1 10
Production Budget without Project - Pond 2 - Rain-Fed Corn ............... 1 11
Production Budget with Project - Pond 2 - Punta de Riego Corn ............. 1 12
Production Budget with Project - Pond 2 — Cempasuchil ..................... 113
Production Budget without Project - Pond 3 — Rain-Fed Corn ............... 114
Production Budget with Project - Pond 3 —- Punta de Riego Corn ............. 115
Production Budget with Project - Pond 3 — Cempasuchil ..................... 116
Production Budget without Project - Pond 4 — Rain-Fed Corn ............... 117
Production Budget with Project Pond 4 - Punta de Riego Corn ............... 1 18
Production Budget with Project - Pond 4 — Cempasuchil ..................... 1 19
Net Present Values for Project Scenarios ......................................... 120
Benefit-Cost Ratios for Project Scenarios ........................................ 120
Rainfall Data (mm/mo.) - Granja Carnation ..................................... 149
Rainfall Data (mm/mo.) - Amealco I ............................................. 149
Rainfall Data (mm/mo.) - San Miguel Tilaxcalte ............................... 150
Rainfall Data (mm/mo.) - Las Palmillas .......................................... 151
Factor for Adjusting Amealco I Rainfall Data .................................... 152
Factor for Adjusting SMT Rainfall Data .......................................... 152
Factor for Adjusting Las Palmillas Rainfall Data ................................ 153
Monthly Averages for Aggregated Rainfall Data (mm/mo.) .................. 154
Rainfall Excess in Meters .......................................................... 156
Monthly Runoff Totals within Catchment Zone in Cu. M. -— Pond 1 ......... 157

X

Table 86

Table 87

Table 88

Table 89

Table 90

Table 91

Table 92

Table 93

Table 94

Table 95

Table 96

Table 97

Table 98

Table 99

Table 100

Table 101

Table 102

Table 103

Table 104

Table 105

Table 106

Monthly Runoff Totals within Catchment Zone in Cu. M. — Pond 2 ......... 158
Monthly Runoff Totals within Catchment Zone in Cu. M. — Pond 3 ......... 159
Monthly Runoff Totals within Catchment Zone in Cu. M. — Pond 4 ......... 160
Yearly Runoff within Catchment Zone in Cu. M. — Pond 1 .................... 162
Yearly Runoff within Catchment Zone in Cu. M. — Pond 2 .................... 162
Yearly Runoff within Catchment Zone in Cu. M. -— Pond 3 .................... 162
Yearly Runoff within Catchment Zone in Cu. M. — Pond 4 .................... 162
Yearly Runoff within Catchment Zone in Cu. M.

Reduced by 50% - Pond 1 ........................................................... 164
Yearly Runoff within Catchment Zone in Cu. M.

Reduced by 50% - Pond 2 ........................................................... 164
Yearly Runoff within Catchment Zone in Cu. M.

Reduced by 50% - Pond 3 ........................................................... 164
Yearly Runoff within Catchment Zone in Cu. M.

Reduced by 50% - Pond 4 ........................................................... 164
Evaporation Data (mm/mo.) — Granja Carnation 1979-1989 .................. 165
Evaporation Data (mm/mo.) — San Miguel Tilaxcalte 1976-1988 ............ 165

Adjustment Factors and Adjusted Evaporation Data (mm/mo.) — SMT. . . ..166
Adjusted Evaporation Data (mm/mo.) — GC & SMT .......................... 166
Distribution of Total Annual Stored Water Loss by Source — Pond 1 ....... 167
Distribution of Total Annual Stored Water Loss by Source — Pond 1 ....... 167
Distribution of Total Annual Stored Water Loss by Source — Pond 1 ....... 167
Distribution of Total Annual Stored Water Loss by Source - Pond 2 ....... 167
Distribution of Total Annual Stored Water Loss by Source — Pond 2 ....... 167

Distribution of Total Annual Stored Water Loss by Source - Pond 2 ....... 168

xi

Table 107

Table 108

Table 109

Table 110

Table 111

Table 1 12

Distribution of Total Annual Stored Water Loss by Source — Pond 3 ....... 168
Distribution of Total Annual Stored Water Loss by Source — Pond 3 ....... 168
Distribution of Total Annual Stored Water Loss by Source — Pond 3 ....... 168
Distribution of Total Annual Stored Water Loss by Source — Pond 4 ....... 168
Distribution of Total Annual Stored Water Loss by Source — Pond 4 ....... 169

Distribution of Total Annual Stored Water Loss by Source — Pond 4 ....... 169

xii

LIST OF FIGURES

Figure 1 Map of Querétaro ...................................................................... 3 3
Figure 2 Cross-Section View of Ponds ......................................................... 50
Figure 3 Map of Weather Stations .............................................................. 53
Figure 4 Evaporation Data Adjustment Coefficients ......................................... 69
Figure 5 Monthly Averages for Aggregated Rainfall Data (mm/mo.) .................. 154
Figure 6 Yearly Rainfall Totals for Aggregated Data 1971-1991 (mm./mo.) ........... 155
Figure 7 Monthly Runoff Totals within Catchment Zone in Cu. M. - Pond 1 .......... 157
Figure 8 Monthly Runoff Totals within Catchment Zone in Cu. M. -— Pond 2 .......... 158
Figure 9 Monthly Runoff Totals within Catchment Zone in Cu. M. — Pond 3 .......... 159
Figure 10 Monthly Runoff Totals within Catchment Zone in Cu. M. — Pond 4 .......... 160

xiii

LIST OF ABBREVIATIONS

AMST American Materials Standards and Testing

AUQ — Autonomous University of Querétaro

Cu. - Cubic

FAO — Food and Agriculture Organization (of the United Nations)

GC — Granja Carnation (weather station)

GIS - Geographic Information Systems

HEC - Hydrologic Engineering Center

INEGI - Instituto Nacional de Estadistica Geografia y Informatica (National Institute of
Statistics, Geography, and Information)

INIFAP - Instituto Nacional de Investigaciones F orestales Agricolas y Pecuarias
(National Institute of Agri-Forestry and Fishery Investigations)

IRR — Internal Rate of Return

LDPE - Low Density Polyethelene

LP — Las Palmillas

M. - Meters

MI — NRCS — Natural Resource Conservation Service of Michigan

Mo. — Month(s)

MSU — Michigan State University

NPV- Net Present Value

NRCS - Natural Resource Conservation Service (formerly SCS)

NWC — National Water Commission of Mexico

PE - Polyethylene

PR — Punta de Riego

PVC — Polyvinyl Chloride

RRA — Rapid Rural Appraisal

SCS — Soil Conservation Service (now NRCS)

SAGAR - (Secretaria de Agricultura, Ganaderia y Desarrollo Rural (Secretary of
Agriculture, Animal Husbandry, and Rural Development)

SEMARNAP - Secretaria de Medio Ambiente, Recursos Naturales, y Pesca (Secretary of
the Environment, Natural Resources, and Fisheries)

SMT - San Miguel Tilaxcalte

USDA — United States Department of Agriculture

Symbols

A - Change (in)
It - Pie (approx. 3.14)

xiv

Chapter 1: Introduction

1.1 The Problems of Food Demand and Water

To meet the projected food demand for a world population expected to reach 8.4
billion by 2025 (World Bank, 1992), global agricultural productivity will have to nearly
double (McCalla, 1994). To feed an additional 80 million people per year, and satisfy
demand for diversified diets created by rising incomes, will require annual increases in
grain production of 26 million tons — or 71,000 tons per day (Brown, 1998). As 90% of
future population growth will occur in developing nations, such countries will have to
increase agricultural productivity between 1.8 and 2% annually to keep pace with
demand (McCalla, 1994). For these countries, achieving and maintaining such
productivity levels will be extremely difficult for several reasons:

1.) Most nations have little or no remaining fertile land that can be added to the
production base (Brown, 1998). In many countries, population pressure and urban sprawl
are pushing production onto marginal lands that are unsuitable for cultivation and prone
to environmental degradation. World-wide, the quantity of grain land per person has
declined from .23 ha/person in 1950 to .12 ha/person in 1997, and will further decline to
.08 ha/person by 2030 (Brown, 1998). As the quantity of production land per person
continues to decrease, agricultural intensification will be the only option for producing
enough food.

2.) Yield growth responses to the Green Revolution formula of improved grain
varieties, fertilizer, and irrigation appear to be diminishing (Brown, 1998). Between

1950 and 1990, agricultural productivity grew an average rate of 2.1% per year; between

1990 and 1995, the rate of grth dropped to 1% per year (Brown, 1998). While five
years does not constitute a trend, grain varieties may be reaching the outward limits of
efficiency in photosynthetic energy conversion (Brown, 1998). If yields continue along
the same course, the Green Revolution strategy will prove insufficient for meeting the
next generation of food demand. It is unclear if biotechnology will be effective and
affordable to farmers in developing nations.

3.) Water scarcity is increasing world-wide, a factor that Brown (1998) deems the
most “underrated” problem confronting us in the coming millennium. Since 1950, global
water use has tripled, 70% of it used for agricultural production, and water tables are
dropping on every continent (Brown, 1998).l Brown (1998) warns that while water and
food scarcity are often treated as distinct problems, they are not. A future marked by
scarcity in water will be a future of scarcity in food.

If arid and semi-arid countries (regions) continue to pump water from their aquifers
unsustainably for irrigation purposes, they will eventually be forced to remove irrigated
regions from their production base and offset production losses with increased grain
imports (Brown, 1998).2 Countries such as China, Egypt, India, Iran, Mexico, Pakistan,
and Saudi Arabia are among the most prominent of nations likely to gamble on this
tradeoff (Brown, 1998).3

However, as Paarlberg (1994) notes, reliance on world markets for grain imports
has historically not worked well for developing nations. He warns that even while food

prices decreased over the past 30 years, 700 million people in the developing world

 

' Water tables are falling in the following regions: southern and southwestern U.S., southern Europe, North
Africa, southern Africa, the Middle East, Central Asia, the Indian subcontinent, and central and northern
China (Brown, 1998).

2 Importing 1 ton of grain is the equivalent of importing 1,000 tons of water (Brown, 1998).

remain hungry because of distances to markets and low income. If the fore-mentioned
nations “go-for-broke” with their irrigation water supplies and begin to compete with
each other in the world grain markets, poorer nations will soon be priced out of the
market.

The beginning of this process may already be taking place. Between 1950 and
1993, the world prices of wheat, corn, and rice fell in real terms by 67%, 83%, and 88%
respectively (Brown, 1998). Since 1993, the trend has reversed. Between 1993 and
1996, the price of wheat rose 39%, rice 30%, and com 58% (Brown, 1998). If arid and
semi-arid countries deplete their aquifers and forgo food self-sufficiency in favor of
imports, millions may be left malnourished or starving.

In short, the world is on the verge of unprecedented demand for food at a time when
its tools and natural systems are questionably inadequate to the task. The food problem
will be especially acute in arid and semi-arid environments, regions comprising one-third
of the earth’s surface (Branson, et a1. 1981) and exhibiting signs of increasing water
scarcity and soil degradation (Siegert, 1993). Intensifying cultivation in these fragile
environments jeopardizes future production capacity through the urination of watersheds,
soil nutrients, and range lands (Paarlberg & Breth, 1994). Meeting the growing demand
for food will depend on increasing productivity while improving soil and water
conservation strategies (Goodrich and Simanton, 1995). If arid and semi-arid nations are
to maintain some level of food security through self-sufficiency in production, they must

reduce aquifer use to sustainable levels and invest in water conservation systems.

 

China and India are number one and three grain producers in the world (Brown, 1998).

1.2 Farm-Scale Water Harvesting/Storage Systems

To increase production in the context of decreasing water resources, small farmers
in semi-arid environments need better systems for harvesting and storing water more

efficiently (Sanchez Cohen, et al.1995). Because rainfall in semi-arid regions is
both erratic and minimal, rain-fed agriculture carries a high risk of yield failure (Sanchez
Cohen, et a1. 1995), and limits productivity. To maximize productivity in arid and semi-
arid regions while alleviating dependency on irrigation wells, farmers need better water
harvest and storage systems.

Water harvesting is defined as the “collection of runoff for its productive use”, and
includes the collection of rainwater (rooftop and runoff) and floodwater (Siegert, 1993).
Though ancient in practice (Frasier, 1993), water harvesting is receiving increased
attention as a method for augmenting agricultural water supply (Siegert, 1993). Water
may be harvested using various kinds (shapes) of microcatchments, bunds, ridges, or
dams (Siegert, 1993), depending on local conditions and resources. Harvested water can
be stored as “soil storage” or in “deep ponding”, which is long-term storage using any
variety of basins including dams, reservoirs, and man-made tanks (Siegert, 1993).

The key to the effective carryover of water is the creation of impermeable storage
structures. Soil-based retention barriers are ineffective in the absence of impermeable
soils such as clay. Coarse, sandy, and porous soils make poor water retention barriers. In
areas where water-retaining soils are absent, farmers need an affordable, yet effective
alternative for making storage basins impermeable. One technique that merits
investigation as a tool for constructing such storage is the installation of geomembranes

in earthen water ponds.

Geomembranes are low permeability synthetic liners made from various plastic
polymers and fibers, and are used for the control of fluids in “man-made project
structure[s] or system[s]” (GeoSource, 1998). Geomembranes have a variety of
environmental applications, including the lining of landfills and wastewater treatment
ponds. Little scholarship has focused on the use of liners as a tool for improving the
water management capacity of small farmers in semi-arid regions of developing
countries. As water scarcity increases the challenge of meeting food demand for poor
farmers around the world, scholarly studies are needed to help find effective, accessible,
and affordable alternatives for increasing the capacity of small farmers to manage and use
water efficiently.

To contribute case study information to the body of knowledge available to farmers,
project planners, and scholars concerning potential tools for increasing water storage
capacity, this research examines the economics of using plastic liners in water storage
ponds in the Central-Mexican state of Querétaro. This case study uses data from existing
ponds and agricultural production practices in the community of E1 Rincén, Querétaro to
calculate the financial costs and benefits of lining water ponds with geomembranes to
create water-tight storage basins.

1.3 Water Storage in Querétaro, Mexico

The community of El RincOn provides a useful context for the study of pond
improvement for several reasons. First, the Central Mexico region exemplifies the
difficulty of increasing small-farmer water management capacity (Pineda LOpez, 1996),
despite massive public sector investment in farm-scale systems for water harvest and

storage. During the mid-1980’s, the Mexican National Water Commission constructed

thousands of ponds to capture and store rain runoff for agricultural use (Garcia, 1998).
Many of those ponds, however, are largely ineffective because of structural deficiency
(use of coarse soils in pond construction) and/or poor positioning relative to drainage
courses (Pineda LOpez, 1996). Water scarcity remains one of the primary constraints to
agricultural production in the region (Garcia, 1998), and most farmers do not have
adequate or reliable year-round supplies of water (Pineda LOpez, 1996).

Secondly, the region is useful contextually because it illustrates the relationships
between agricultural practice and land degradation. As with other semi-arid regions,
poverty-induced agricultural practices (mono-cropping, overgrazing, over-reliance on
chemical fertilizers and pesticides) have resulted in natural resource and environmental
degradation (Pineda LOpez, 1996). In as much as harvesting and storing water effectively
is important to improving agricultural productivity, it has the potential to help alleviate
pressure to intensify production unsustainably.

Finally, the El RincOn case is compelling because it exemplifies the potential for
collaboration that exists between community, national, and international institutions for
investigating and solving community problems. Teams of scholars from the Autonomous
University of Querétaro (AUQ) have partnered with community members to investigate,
discuss, and pose solutions to agricultural, natural resource, environmental, and
socioeconomic problems (Pineda LOpez, 1996). This partnership has included
collaboration with Michigan State University, and the Natural Resource Conservation
Service of Michigan (MI-NRCS). Such multi-level and multi-disciplinary collaboration
between institutions lends new power to the solving of natural resource and agricultural

production challenges.

It is through such collaboration that problems associated with water pond
effectiveness in El Rincén came to the attention of visiting professionals from MSU and
the MI-NRCS. During a recent visit to the community (1998), a team of professionals
from MI-NRCS responded to farmer complaints about water infiltration loss by
proposing the installation of geomembranes in pond basins (Burgdorf and Pérez, 1998).
The presence of coarse soils, and in some cases, rocky substrate in pond floors, facilitates
water seepage into the sub-surface (Pineda LOpez, 1996). Under ideal circumstances,
ponds are designed to provide water carry over from the rainy season (J une-September)
to allow for a one-time irrigation (or soaking) of the fields in April or May (about one
month prior to planting) in the following crop cycle (Garcia, 1998). In ponds where
infiltration rates are high, the combination of evaporation and infiltration dries the pond
out by the month of November or December, making no water available for irrigation.
Consequently, agricultural productivity remains low.

While the installation of geomembranes in storage ponds would likely allow
farmers to produce more food and fiber, no data exist as to likely increments in water
supply or agricultural production, nor as to the costs of liner installation and maintenance.
Such data need to be collected and analyzed to determine the frnancial feasibility of
lining ponds with geomembranes to boost agricultural productivity. The goal of this
study is to collect such information to determine the advisability of such an investment.
1.4 Statement of the Research Problem

To increase agricultural production, small farmers in semi-arid Central Mexico need
efficient systems for capturing and storing rainfall for crop and animal production. To

address this need, the Mexican NWC constructed thousands of water storage ponds in

Central Mexico during the mid-1980’s. Many of those ponds are ineffective, however,
and do not provide water to farmers because of water loss through coarse and sandy soil-
based pond basins. Lining inefficient ponds with geomembranes may reduce or eliminate
water loss due to infiltration. Because no data is available regarding the financial costs
and benefits of using geomembranes in small scale, semi-arid farming scenarios, this
analysis uses a case study approach to calculate such costs and benefits.
1.5 Research Objective

The objective of this research is to determine the cost-effectiveness of lining farm
ponds with geomembranes through the completion of a financial benefit-cost analysis.
1.6 Research Design

This study includes the following areas of analysis:
1.) Calculation of Rainfall Runoff and Pond Catchment
2.) Calculation of Stored Water Loss
3.) Calculation of Crop Production Yields and Budgets
4.) Calculation of Project Investment and Operating Costs
5.) Benefit-Cost Analysis

The study uses local pond and agricultural production data to calculate the financial
benefits and costs of lining four selected study ponds with geomembranes. A projected
water surplus is calculated by calculating rainfall runoff and catchment, as well as stored
water loss — including evaporation, animal consumption, and estimates of infiltration. An
economic value for the proj ect-generated water surplus is calculated by estimating its

production increasing effect for corn and cempasuchil‘. Project investment costs are

 

4 Cempasuchil (or Tagetes erecta Linnaeus Compositae) is a traditional ornamental flower used as a food
coloring and additive to poultry feed (INEGI, 1997a).

calculated using estimates of site preparation time, local wage and contractor rates, and
liner installation price quotations. Costs and benefits are calculated using a lS-year farm-
level budget for each pond that includes a yearly and incremental (or cumulative) net
benefit.

A project net benefit is calculated by subtracting the production (Operating) costs
and project investment costs from the market value of the crop (gross returns). A net
present value for the project is calculated by discounting the future value of the benefit
stream over the project life-cycle (15 years in this case). Future benefits are discounted
by the opportunity cost of capital or the interest rate used for borrowing capital.

If, for the conditions of the case study, the project is shown to be cost-effective, this
study will conclude that the technique merits further investigation as a potential water
management tool for small farmers in E1 Rincén and the larger surrounding region. More
importantly, the summary data will be shared with the community members and leaders
of E1 Rincén, so that they can make informed decisions about the potential investment.
1.7 Study Significance

The study is designed to determine the financial feasibility of the liner technique for
farmers in the El RincOn case, but also contribute case study data about liner feasibility to
a larger body of information about farm-scale water storage systems as a means for
increasing agricultural production in semi-arid regions. To the degree that the conditions
of this study site may resemble those of other semi-arid agricultural regions, the findings
of this study have potential application to other communities in Central Mexico and
abroad. If the liner technique is found to be cost-effective for the production conditions

of the case, geomembranes may become an important tool for helping small farmers in

semi-arid regions conserve water and increase food production. The results of the study
can help farmers and development professionals make informed decisions about
investment in this water management option.
1.8 Study Organization

This study is organized in five chapters. Chapter One presents the problem
background and analysis, framing the research problem and objectives in the larger
context of farm-scale water management in semi-arid agriculture. Chapter Two presents
a problem-focused review of the literature pertinent to the financial feasibility of
geomembranes in the Central Mexico Region. Chapter Three provides a description of
the study site, including insight into the agricultural production and natural systems.
Chapter Four outlines the study methods and calculations. Study results are presented in
Chapter Five, and Chapter Six provides a summary of the study, conclusions, and
recommendations for further investigation. Appendices A, B, C, and D present additional
information on geomembranes, the study site, cempasuchil, and local rainfall analysis,

respectively.

10

Chapter 2: Literature Review

2.1 Introduction

This research problem involves the potential infusion of a capital-intensive
technology into a resource and capital constrained, low input agricultural system that is
dependent upon highly variable rainfall. The implication for such an investment is the
potential risk of the agricultural production system not keeping pace with the debt service
in the case of one or a series of crop failures. Thus, the major consideration is not only
whether liners would augment the efficiency of water storage ponds, but whether the
benefits of such an investment outweigh the costs, and to what degree.

In an effort to create more insight into issues related to the cost-effectiveness of
liners in the El Rincén case, a problem-focused literature review was conducted
addressing the following questions:

0 What are geomembranes and how are they made and used?

0 Have farmers in other low-input agricultural systems had experience

with geomembranes as pond liners? Under what circumstances?

0 What were the outcomes of those experiences?

0 Did the farmers receive financial assistance or pay for the liners themselves?

0 Were the projects cost-effective? Under what circumstances?

0 What problems were incurred? How were they dealt with?

o What parallels can be made between those adoption cases and the case of E1

RincOn?

11

Because this study also relies on hydrological and benefit-cost analysis, those
areas were also included in the literature review.

Unfortunately, upon examination of literature bases in the areas of agriculture,
development, engineering, and natural resource conservation, it became apparent that
very few studies chronicle the use of geomembrane liners in water storage ponds in
developing agriculture, and no studies were found addressing the economics of such an
investment. In short, what is known about geomembranes in agriculture appears to be
primarily in the domain of technical design and performance. The economics of
geomembrane use in scenarios such as that of El RincOn appear to be relatively
unstudied. It is not clear why this is the case.

2.2 Literature Search

The literature search conducted for this study includes the following topic areas,
titles, and years of publication (in the case of journals, generally the most recent 10 years
of the stated title were reviewed):

Agriculture:

Agricultural Water Management: An International Journal (1988-99)

AMA — Agricultural Mechanization in Asia, Afiica, and Latin America (1989-98)

American Journal of Agricultural Economics (1990-98)

Irrigation Science (1987-1994)

Journal of Irrigation and Drainage Engineering (1989-98)

Journal of Production Agriculture (1989-99)

Benefit-Cost Analysis:

Economic Analysis of A griculture Projects, Gittinger (1996)

12

The Principles of Practical Cost-Benefit Analysis, Sugden & Williams (1978)
Miscellaneous Class Notes from ABC 865, Agricultural Benefit-Cost Analysis,
Crawford & Oehmke (1998)
Development:
Grassroots Development (1990-97)
Miscellaneous publications by: The World Bank (“Technical Papers”), FAO,
UNDP, USAID
Engineering:
Geosynthetics Engineering (miscellaneous years)
Geosynthetics International (miscellaneous years)
Miscellaneous publications by: The Bureau of Reclamation and Army Corps of
Engineers
Hydrology
Agricultural Compendium For Rural Development in the Tropics and Subtropics,
Elsevier (1989)
Applied Modeling in Catchment Hydrology, Singh (1981)
Computer-Assisted Floodplain Hydrology & Hydraulics, Hoggan (1989)
Contemporary Hydrology, Wilby (ed.) 1997
Design Hydrology and Sedimentology for Small Catchments, Haan, Barfield, and
Hayes (1994)
Global Hydrology: Processes, Resources, and Environmental Management, Jones
(1997)

Hydrology and Floodplain Analysis, Bedient & Huber (1 98 8)

13

Land Surface Evaporation, Management & Parameterization, Schmugge &
Andre (eds) (1991)

Management of Water Use in Agriculture, Tanji & Yaron (eds) (1994)

Rain and Stormwater Harvesting in Rural Areas, UNEP (1983)

Rainfall Runofir Relationship, Singh (ed.) (1981)

Runofif Infiltration and Subsurface Flow of Water in Arid and Semi-Arid Regions,
Issar & Resnick (eds) (1996)

Semiarid Soil and Water Conservation, F inkel (1986)

Water Resources Management in the Face of Climatic/Hydrologic Uncertainties
(1996)

Water Saving Techniques for Plant Growth, Verplancke, Strooper, and De Boodt
(1992)

Watershed Hydrology, Black (1990)

Miscellaneous Internet Resources

Natural Resources:

Ambio (1989-99)
Journal of Soil and Water Conservation (1987-98)
Resources (1993-99)

As part of the search, the following data bases were referenced in an Electronic

Resources Library at Michigan State University: CAB, Agricola, Soil and Water. These

data bases produced several potentially relevant articles, copies of which could not be

procured, including:

14

Plastics and Control of Water and Storage of Liquids in Agriculture, Comite des
Plastiques en Agriculture, Paris, France. 1992 (French)
Proceedings of the International Study Day about Waterproofing Water Basins, Societa
Solvay, Milan, Italy, 1983 (Italian)
Proceedings of the 12:}. International Congress of Plastics in Agriculture, CEPLA,
Granada, 1992.
Third World Conference on Geosynthetics Use in Rural Engineering, Galan-Lopez
2.3 Introduction to Geomembrane Technology
For purposes of identification and description, a brief introduction to
geomembranes is presented here. Additional information — including geomembrane
properties pertinent to project design and liner selection are presented in Appendix A.
For more information regarding geomembranes, their properties, and project design
considerations, see: Robert M. Koemer’s, Designing with Geosynthetics 3rd ed. (1998).
As director of the Geosynthetics Research Institute at Drexel University, and author of
numerous articles and texts on geosynthetics, Koemer is one of this nation’s pre-eminent
scholars on geosynthetics and geosynthetic design. More recent publications of Koemer
and the Institute may be found through the Institute’s intemet address:

www.drexel.edu/gri/backgmdhtml . Unless otherwise cited, this overview of

 

geomembrane technology (section 2.3 and Appendix A) summarizes information taken
from Koerner’s treatment of geomembranes in his 1998 text Designing with
Geosynthetics 3'rd ed (pages 1-45, 362-510).

Geomembranes are one group of a family of geosynthetic products that combine

synthetic materials with geoenvironmental design for application in areas such as

15

geotechnical and environmental engineering, heavy construction, building construction,
and hydrogeology (Koemer, 1998). Geosynthetics include plastic polymers, and other
materials such as rubber and fiberglass, and thus tend to be non-degradable, durable,
versatile, light-weight, transportable, low maintenance, and often less expensive than
alternatives (Koemer, 1998). Koemer identifies five principal geosynthetic functions:
soil separation, soil reinforcement, soil filtration, water drainage, and moisture
containment. Based on those functions and material design, Koemer breaks the family of
geosynthetics into six categories based on design and function:

1.) Geotextiles — similar to cloth textiles in form; woven, knited, or matted with synthetic
(plastic) fibers; may be used for any of five geosynthetic functions

2.) Geogrids - panels of grid-shaped plastic rods; used primarily for soil
separation and reinforcement

3.) Geonets - nets made of plastic or “polymeric ribs”; used exclusively for drainage
applications

4.) Geocomposites - combinations of geo-textiles, grids, nets, or membranes; or one of
those products in combination with other materials such as deformed plastic
sheets, steel cables, or steel anchors; may be designed and used for any of the five
major geosynthetic functions.

5.) Geomembranes - “impervious thin sheets of rubber or plastic material used primarily
for linings and covers of liquid (or solid) storage facilities”

6.) Geo-Others - a vast array of newer geosynthetic innovations not easily categorized
because of their diversity; include “threaded soil masses, polymeric anchors, and
encapsulated soil cells”; used for any of the five geosynthetic functions.

This study focuses exclusively on geomembranes and borrows a slightly more

detailed definition provided by GeoSource ( www.geosource.com) (1998):

 

Geomembranes are very low permeability synthetic membrane liners or barriers used
with any geotechnical engineering related material so as to control fluid migration in a
man-made project structure or system. Most geomembranes are made from extruded or
co-extruded polymers such as HDPE, PP, CPE, PVC, EPDM, etc. [High Density
Polyethylene, Polypropylene, Chlorinated Polyethylene, Polyvinyl Chloride, and

16

Ethylene Propylene Diene Monomer] that are extruded in large sheets which are welded
or glued together in the field. Some extruded geomembranes are reinforced with high
tenacity fibers to increase their tensile strength, while others are embossed, roughened, or
co-extruded with geotextiles to increase their frictional resistance to sliding.

Per Koemer (1998), the first geomembranes were made from butyl rubber and
Hypalon during World War II and were used as pond liners for potable water. Today,
geomembranes have many uses, all of which involve the blockage or entrapment of
liquids, vapors, or even solids. Several identified by Koemer (1998) include:

0 Storage of potable water and reservoir water

0 Storage of waste and radioactive waste liquids

o Lining of water conveyance canals

- Lining/capping of solid-waste landfills

o Containment of odors and/or vapors

0 Control of expansive or frost-susceptible soils

0 Blockage of water infiltration into sensitive areas

According to Koemer (1998), one of the potential growth areas for liner use is in
the lining of irrigation canals. Koemer states, “when properly designed, constructed, and
maintained, geomembrane materials should have a positive impact on the canal lining
industry”. No mention is made of the current status of liner use in irrigation or runoff
catchment ponds either in industrialized or developing nation agriculture.

2.4 Geomembrane Materials

All geomembranes are made of one of three types of plastic polymer: amorphous

thermoplastic, semicrystalline thermoplastic, or thermoset (Koemer, 1998). Amorphous

thermoplastic polymers exhibit plasticity when heated, and thus can be repeatedly heated

and molded without changes in “inherent” properties. Semicrystalline thermoplastic

l7

polymers are aligned in crystallite shapes, the number of which affect how the polymer
behaves. Increased crystallinity increases hardness, heat resistance, tensile strength, and
chemical resistance. Conversely, it reduces permeability, elongation potential, flexibility,
impact strength, and crack resistance. Thermoset polymers are polymers that once made,
are set, and cannot be re-heated without burning and degradation of the polymer.

Koemer (1998) categorizes specific liner types as follows - all of which he
indicates constitute “candidate materials” for the “conveyance of domestic or agricultural
water”.

Thermoplastic Polymers

Polyvinyl chloride (PVC)

Polyethylene (V LDPE, LDPE, LLDPE, MDPE, HDPE) — very low, low, linear

low, medium, and high density
Chlorinated polyethylene (CPE)
Elasticized polyolefin (CPE)

Ethylene interpolymer alloy (EIA)
Polyamide (PA)

 

Thermoset Polymers

Isoprene-isobutylene (IIR), or butyl
Epichlorohydrin rubber

Ethylene propylene diene monomer (EPDM)
Polychloroprene (neoprene)

Ethylene propylene terpolymer (EPT)
Ethylene vinyl acetate (EVA)

 

Combinations

PVC-nitrile rubber

PE-EPDM

PVC -— ethyl vinyl acetate

Cross-linked CPE

Chlorosulfonated polyethylene (CSPE), also called Hypalon

 

Koemer indicates that the majority of geomembranes in use today are of the

thermoplastic variety.

l8

2.5 Geomembrane Construction

Geomembrane sheets are manufactured in one of three ways (Koemer, 1998).
The most basic involves the melting of raw materials and extrusion of a single ply
membrane ranging in thickness from S to 200 mils (0.13 to 5.10 mm). A second method
involves the lamination of two or more plies together with or without a fabric scrim
reinforcement sandwiched between the membrane layers. A newer method called spread
coating, involves pouring molten polymer evenly across a geo-textile base. Because the
latter two methods use reinforcing material, these membranes exhibit higher tensile
strength and resistance to tears, impact, and puncture. Reinforced liners also tend to be
more expensive.
2.6 Geomembrane Installation (See Appendix A)
2.7 Geomembrane Lifetimes

To-date there is not a good quantifiable method for measuring how long
geomembranes will last - especially in relation to the potential synergistic effects of
membrane degrading forces such as ultra-violet light, radiation, chemicals, extreme heat
or cold, fungi and animals. Koemer (1998), offers that if properly protected (i.e. covered
with soil), the lifetimes of liners for agricultural water storage are “often approximately”
twenty years.
2.8 Other Sources of General Information

More information about geomembranes may be found in the fore-mentioned
Koemer text, as well as: Koemer, Durability and Aging of Geosynthetics, 1989; and
Rollin and Rigo, Geomembranes Identification and Performance Testing, 1991. As well,

the AMST (American Materials Standards and Testing) publishes descriptions of

19

membrane testing and classification. See: The Annual Book of ASTM Standards or the
A ST M Geotechnical Testing Journal.

According to Koemer (1998), The Bureau of Reclamation, Army Corps of
Engineers, and US. Department of Agriculture were influential in the early development
and use of geomembranes and have published extensively regarding their experiences
with the material. The Bureau of Reclamation and USDA have focused on geomembrane
use in irrigation canals and reservoirs. The Army Corps of Engineers’ use of
geomembranes has historically focused on the areas of dams, reservoirs, canals, and road
construction. Because many of these projects are of a massive scale, involve heavily
industrialized construction or agriculture, and have been subsidized by government funds,
they tend to offer little insight into the research question at hand. For project
descriptions, see: Use of Geomembranes in Bureau of Reclamation Canals, Reservoirs,
and Dam Rehabilitation, Morrison, 1995; or Bureau of Reclamation Research, The
Bureau of Reclamation, 1992. The Bureau of Reclamation homepage can be found at:

www.usbr.gov/main/ . USDA publications can be found through the USDA homepage:

 

www.usdagov.

GeoSource( www.geosource.com) provides on-line advertising and resource

 

information for a number of geomembrane manufacturers, distributors, and engineering
firms. The PVC Geomembrane Institute provides research and education for PVC liner

use. The Institute may be contacted on-line at: pgi-tp@uiuc.edu. Another on-line source

 

for geomembrane publications is the Geosynthetics Bookstore at: GuideMe.com
Geosynthetics Bookstore. Other potential sources of information for geomembranes

include the following journals: Environmental Engineering Science, Geosynthetics

20

International, Geotechnical Engineering, Geotextiles & Geomembranes, Journal of
Applied Polymer Science, Journal of Geotechnical and Geoenvironmental Engineering,
Journal of Hydrologic Engineering, Journal of Polymer Science, Journal of Reinforced
Plastics and Composites, Journal of Polymer Science, Modern Plastics, Plastics
Engineering, Plastics Technology, Polymer, Polymer Engineering and Science, Polymer
— Plastics Technology and Engineering, Water Environment Research, Water,
Environment, and Technology
2.9 Summary of Like Cases

In contrast to the great number of studies available regarding the technology and
engineering of geomembranes, no studies were found addressing the economics of
geomembranes in the context of developing country agriculture. While the World Bank
and F AO have published extensively on irrigation and water harvesting, virtually no
treatment is given to geomembranes as water conservation tools

One potential explanation for this absence of treatment is the relative infancy of
geomemrbane use in geo-technical engineering. Koemer (1998), indicates that sales
projections for geomembrane sales are “extremely strong due to their only becoming
recently known to many civil engineers”. Thus, if geomembranes are just catching on in
industrialized nations, a lag in adoption would be expected for use in developing
countries. The absence of trials and publications for geomembranes in deveIOping
country agriculture may simply reflect the relative newness of the technology. The few
references found in the literature relevant to this study are highlighted here:

Blanco et. a1. (1998) provide an historical account of geomembrane use (PVC

mostly) in Spanish agriculture, including project initiatives in the Canary Islands and

21

Iberian Peninsula. While Blanco et. al., describe geomembrane types and project design
considerations, they fail to address economic or other feasibility considerations related to
pond liners. No mention is made of intended water use, project beneficiaries or
financing, benefit-cost streams, or other feasibility considerations. Other works by
Blanco are available in: Ingenieria Civil (Civil Engineering) (1993) [Spanish];
Proceedings of the Ibero-American Congress of Construction Pathology and Quality
Control, 1995 [Spanish]; and Spanish Dam Works, 1996 [Spanish].

Lakshmana Rao et. a]. (1990) provide a brief case study of using an LDPE
membrane (Low Density Polyethelene) to rehabilitate a masonry fish pond for an inland
fishery in Kamataka, India. Though their analysis is more concerned with seepage loss
rates than economics, they do mention that the installation of LDPE is about 40% cheaper
than constructing a stone masonry pond of equal size. Otherwise, no insight is given into
project economics, intended beneficiaries, or liner integration into the agricultural
production and natural systems.

Monticelli (1979) makes general reference to the use of geomembranes in
irrigation water storage in L ’ Irrigazione. This dated article, however, makes no
reference to economics or specific project initiatives.

Kraatz (1977), in his FAO publication on canal lining, provides an overview of
design considerations for using geomembranes as canal liners. He indicates that PVC ,
PE, and butyl rubber have been the most commonly used materials. He indicates that as
of 1977, PE was the most economical of membrane materials for “buried flexible canal
lining”. Kraatz (1977) does provide some specific examples of canal lining projects, but

again, coverage is from a design perspective. No references are made to pond lining.

22

Kumar (1993) describes the use of polyethylene to line rain catchment ponds for
irrigation use in Garhwal Himalaya. The author indicates that cost analysis was done for
the lining project, and states that the liner proved to be “economically viable” for “low
economic status” farmers. No details were provided as to the type of agricultural
production under which this proved to be true. Neither was information provided about
project financing, ownership, nor the distribution of benefits.

Gonzalez-Ruiz (1992) does provide some insight into the historical and potential
use of geomembranes for agricultural water management in Mexico with a description of
geomembranes used for irrigation canal rehabilitation. Gonzalez-Ruiz (1992) states that
only since the early 1990’s has Mexico begun to use liners as a viable alternative to lining
canals with masonry, cement, or compacted clay — materials which can be expensive to
transport and install, and are susceptible to seismic activity. He suggests that plastic
liners provide an effective alternative that can be installed quickly and at lower costs. He
further indicates that PVC is an appropriate material for use in Mexico because of:

0 its flexibility and manageability

0 its availability in large sheets - reducing time and labor needed for installation

seaming

0 its potential for conformity to changes in underlying base material

0 its wide-spread and successful global use in canal rehabilitation

The article makes only brief reference to irrigation ponds when the author
suggests that by reducing or eliminating sedimentation and the need for pond
reconstruction, pond lining projects may pay for themselves in a very short time. No

indication is given as to the agricultural production conditions under which this might be

23

true. Nor is information provided regarding specific projects, project costs or financing,
amortization schedules, or the distribution of benefits.
2.10 Conclusions about the Geomembrane Literature Base Pertinent to this Study

The absence of information provided by similar studies makes it difficult to
anticipate all of the factors that may affect the cost-effectiveness of installing liners in El
RincOn ponds. Though determining factors are ultimately site-specific, the findings of
other case studies would be useful for creating a greater depth of understanding of if and
how such a technology adoption can be made. Studies such as this one will hopefully
better inform both scholars and practitioners addressing the conservation and more
efficient use of agricultural water.
2.1] Introduction to Rainfall Runoff Modeling

Because quantifying rainfall runoff is central to the accounting of costs and
benefits for this study, it is useful to review briefly some of the basic theories and
methods available for computing runoff. The number of approaches available relates to
the complexity and number of variables inherent to rainfall-runoff processes — variables
that make calculation and modeling especially difficult (Hoggan, 1989). Per Jones
(1997), runoff is part of a hydrological balance that can be expressed as:

Runoff =_ Precipitation — Evaporation +/- A Storage

(evaporation and storage change are often referred to as loss functions (Hoggan,

1989))

Precipitation minus abstractions or total loss is called rainfall excess, or effective rainfall,
and is equal in volume to storm water runoff, or the amount of flow occurring during and

immediately after a precipitation event (Hoggan, 1989).

24

Rainfall events tend to vary in intensity over time and space within a watershed
(Hoggan, 1989). This temporal and spatial variability greatly affects runoff, but is often
not represented in available data (Hoggan, 1989). Evaporation involves moisture being
taken back into the atmosphere from soil, water, and vegetation surfaces, and is often
treated in conjunction with transpiration loss (plant uptake), and thus referred to as
evapotranspiration (Hoggan, 1989, and Jones, 1997). Evapotranspiration is affected by
such variables as land use, vegetation, and atmospheric conditions (Jones, 1997). Storage
change is infiltration into soil and rocks (Jones, 1997), the rate of which is affected by
variables such as land use, soil properties (permeability), soil moisture content, vegetative
cover, and rainfall intensity and duration (Hoggan, 1989).

Runoff may be calculated for single rainfall events or for extended time periods
depending on the purpose of quantification (Hoggan, 1989). It may also be calculated in
total volumes, peak volumes, or as hydrographs (distribution of flow over time) (Hoggan,
1989, and Olivera, 1999). Hydrograph methods are useful for the design of runoff
handling infrastructure such as drains, sewers, canals, reservoirs, etc. that must handle
peak volumes of storm flow. There exist a number of approaches for creating
hydrographs, however, as this research is interested only in the total quantity of flow, and
not its distribution over time, such methods are not addressed here. In short, runoff
estimation involves quantifying rainfall, loss, and often the distribution of flow over time,
and for each of these calculations, there exist a number of methods.

2.12 Rainfall
Rainfall is “fundamental” to any rainfall-runoff model, but its accurate temporal

and spatial representation across a basin is ofien hindered by a sparseness of data

25

(Hoggan, 1989). It is common to calculate an average of precipitation data collected
from various points within a basin. Three basic approaches include a simple arithmetic
mean, the Thiessen Polygon Method, and the Isohyetal Method (Hoggan, 1989).

Calculation of a simple mean is the most basic of approaches, however, because
of the potential for spatial and temporal variability in rainfall, such an average may
misrepresent actual rainfall distribution across a watershed (Hoggan, 1989). Hoggan
(1989) states that calculating a simple arithmetic mean from gauge data is “satisfactory”
if gauges are “unifomrly distributed and topography is flat”.

The Thiesen Polygon Method can be used where rainfall data is taken from points
unevenly distributed across a basin (Hoggan, 1989). The method uses bi-sectors to
divide a basin into polygons corresponding to data collection points, the size of which
determine the weight of each data point’s contribution to a basin-wide average (Hoggan,
1989)

The Isohyetal Method assumes that because of topographical features, a particular
gauge does not necessarily best represent the rainfall of the area closest to it (Hoggan,
1989). The technique uses contour lines to connect data points of equal rainfall amounts.
An average for each area of constant rainfall (isohyet) is calculated, weighted by the size
of its corresponding area, and then combined with others to create an overall average
(Hoggan, 1989).

The temporal dimension of rainfall events can be accounted for by using
recording precipitation gauges which measure rainfall amounts according to time, the
results of which can be represented in a mass curve (Hoggan, 1989). Ofien however,

rainfall is available only from non-recording or standard gauges providing a 24-hour total

26

(Haan, et. al., 1994). Such is the case with data available for the El RincOn region.
However, because this analysis is more interested in total volumes of runoff and not its
distribution over time, the absence of timed data is not problematic.
2.13 Loss Functions

Haan, et. al. (1994) provide a slightly more detailed compilation of loss functions,
sometimes called abstractions, including: interception, evaporation, bank storage, surface
storage and detention, and infiltration. Interception is rainfall captured on vegetation
surfaces before it hits the ground - a very small portion of loss for individual storm
events (Haan, et. al., 1994). Per Haan, et. al., (1994). evapotranspiration is “generally a
minor factor and not included in storm water computations” (it is more important to
calculation of runoff over longer time periods). Bank storage is actually only a delay in
runoff that occurs when water saturates and is held temporarily in stream banks until
stream water levels subside (Haan, et. al., 1994). Surface storage and detention is the
amount of water that fills ground surfaces and depressions before overland flow (runoff)
can begin. Per Haan, et. al. (1994), this source of loss is extremely difficult to measure.
Haan et. al. (1994) state that infiltration is the major source of precipitation loss, and as
such, infiltration loss approaches to estimating runoff (called Hortonian approaches) tend
to be the most common of methods for calculating runoff (Haan et. al., 1994).

Infiltration loss approaches include the Richards Equation, Horton’s Equation,
Holtan’s Equation, and the Green-Ampt Equation (Haan et. al., 1994). Because these
methods involve empirical measurement of infiltration rates and soil hydraulic

conductivity, and such data is not available in the El RincOn region, these methods are

27

not viable approaches for estimating runoff for this study. As such, they are mentioned
only briefly here.

The Richards Equation calculates infiltration loss as a function of change in
infiltration rate measured under conditions of given soil moisture content and constant
precipitation (Haan, et. al., 1994). Similarly, Hortan’s Equation calculates infiltration
loss by calculating the rate of decrease in infiltration through comparisons of initial and
final infiltration rates (empirically measured) (Haan, et. al., 1994). Holtan’s Equation
calculates infiltration by basing the rate of loss on the unfulfilled capacity of soil to hold
water — information provided for many soil types by the USDA (Haan, et. al., 1994).
The Green-Ampt Equation calculates infiltration rates base on hydraulic conductivity,
depth of soil that absorbs moisture, and the depth of surface ponding. (Haan, et. al.,
1994)

2.14 SCS Curve Number Method

One of the simplest and most widely used methods for calculating precipitation
loss is the US. Soil Conservation Service (SCS) (Now the Natural Resource
Conservation Service) Curve Number Method (Hoggan, 1989). The method was
developed primarily as a way of studying the effects of early soil conservation practices
in the US. (Hoggan, 1989). It uses curve numbers developed through empirical study of
small watersheds to represent runoff-affecting variables such as land use, land cover, soil
type, hydrologic condition, and “antecedent runoff conditions” (Hoggan, 1989). The
method has proven popular because of its simplicity — requiring only precipitation data
and selection of a curve number based on land conditions. According to VP. Singh

(1982), the method is generally reliable. Because of its simple data requirement, it is the

28

method chosen for this study, and is described in more depth in the methods section
(chapter 4) of this study.
2.15 Computer Models

Computers have increased the sophistication, ease, and data management
capabilities of rainfall-runoff modeling (Olivera, 1999). Computer models provide
several method options for representing precipitation, loss, and flow so that input of
precipitation and basin data yield runoff hydrographs of a specified variety. Two
pioneering agencies in the development of hydrological and hydraulic modeling software
are the Hydrologic Engineering Center (HEC) at the US. Army Corps of Engineers, and
the Soil Conservation Service (Olivera, 1999). The Hydrolgic Engineering Center has
developed an extensive array of hydrology and hydraulic modeling software with a
variety of functions and applications (Hoggan, 1989). Its principal rainfall-runoff
modeling software package is HEC-1 (now available in a Windows version — HEC
HMS), which calculates “discharge hydrographs” for historical or hypothetical single
storm events using basin input parameters such as basin boundaries, precipitation data,
and runoff routing information (Hoggan, 1989, and Olivera 1999). The program includes
options for calculating runoff in overland flow plains or in channels (Olivera, 1999).
More information about the sofiware can be found on the HEC web page at: www.wrc-
hec.usace.army.mil/

The US. Soil Conservation Service SCS TR-20 (and more basic cousin TR-5 5)
models rainfall-runoff for single events using “design storms” as rainfall input (Olivera,
1999). Runoff hydrographs are computed using the SCS curve number method based on

land use conditions and soil type (Olivera, 1999). TR-20 has been widely used by SCS

29

engineers to conduct urban and rural watershed planning, predict flood risks, and design
reservoirs and channels (Olivera, 1999). More information about this program can be

found at the NRCS web site at: www.mcs.usda.gov/

 

Geographic Information Systems (GIS) are gaining importance in the area of
hydrological modeling, especially in providing more sophisticated spatial analysis in
runoff (Olivera, 1999). Whereas programs such as HEC-1 and TR-20 average or “lump”
rainfall for an entire basin, GIS allows for more spatial definition in rainfall input
(Olivera, 1999). Grid systems are especially useful for modeling runoff flow in basins
where flow direction is greatly influenced by topographical features (Olivera, 1999).

Two such programs are ESRI Arc/Info — GRID and the US. Army Corps of Engineers’
GRASS program (Olivera, 1999). More information about these programs can be found

at the HEC web site (www.wrc-hec.usace.army.mil/) or the ESRI web site

 

(www.csri.com/).

 

2.16 Conclusions Regarding Runoff Calculation Modeling

Because very little data is available for the El RincOn site, and because this study
seeks only to determine if runoff is generally sufficient to fill the study ponds, the study
requires a simplistic approach to estimating runoff. The majority of approaches including
infiltration methods and computer models require more data than is available here. As
such, the SCS Curve Number Method was chosen to calculate runoff based on the data
available for precipitation and land use in this site.
2.17 Introduction to Benefit-Cost Analysis

Benefit-cost analysis is a tool used in economic analysis that involves an

organized and systematic accounting of financial/economic gains and losses to allow for

30

comparison between alternative projects or “ways of using resources” (Sudgen &
Williams, 1978). Grounded in social welfare economics, the technique assumes that
private and public entities such as farm families, businesses, or societies have a basic
interest in increasing their own welfare — often expressed in financial terms such as an
increase in net economic benefit or income (Gittinger, 1997). It also assumes that
through efficient allocation of society’s scarce resources, certain projects can improve the
well-being of particular groups without hurting others (a Pareto Improvement), or in such
a way that the benefits accrued to beneficiaries outweigh the costs borne by other
segments (a Potential Pareto Improvement) (Gittinger, 1997).

Benefit-cost analysis involves quantification and summation of costs (aspects of
the project that hinder the project objective) and benefits (aspects that advance the
objective) (Gittinger, 1997). In financial terms, benefits and costs can be described as
inflows and outflow respectively. Once summed and discounted (stated in present
values), benefits and costs can be presented as a ratio (benefit-cost ratio) or in terms of a
net present value (net income minus net expenditures) (Gittinger, 1997). Projects with a
benefit-to-cost ratio greater than one or with a net present value that is positive are said to
be cost-effective. A third descriptor, the internal rate of return, is the maximum rate of
interest that a project could repay and still break even (i.e. the discount rate that produces
an NPV of zero). Generally, projects are chosen that have an IR equal or higher than
the opportunity cost of capital.

The benefit-cost approaches used in this study are taken from the Michigan State
University graduate course: “Agricultural Benefit-Cost Analysis” (AEC 865) taught by

Eric Crawford and Jim Oehmke, 1998.

31

Chapter 3: Site Description

3.1 Introduction

The following description of the study area, unless otherwise cited, is summarized
from the AUQ team’s report entitled “Rural Participation Diagnostic of the El Rincén
(Aguacate) Watershed” (1996). The site description is also augmented by information
gathered during two site visits by this author and from other publications as well.
Additional site information is available in Appendix B.
3.2 History of the Diagnostic Report

The rural participation diagnostic is the product of a collaborative relationship

between the Autonomous University of Querétaro and the El RincOn community. The
participatory diagnostic represents the AUQ’s primary contribution to a joint project
between The Secretaria de Medio Ambiente, Recursos Naturales, y Pesca (SEMARNAP)
and the Food and Agriculture Organization of the United Nations (F AO) entitled
“Development of the El Aguacate Watershed, Ejido El Rincén”. As is stated in its
introduction, the diagnostic was designed to create a preliminary image of the watershed
community, including its interest in resource conservation, perceptions related to the
SEMARNAP-FAO project, and levels of community commitment to project activities].
3.3 Study Site

El Rincén is one of thousands of ejidos created as part of the post-revolution land

reform which broke up large haciendas and endowed the land to its peasant occupants

 

' Conducted in September, 1996, the RRA included interviews of 45 households using questions about
community lifestyles, production and leisure activities, and problems related to those activities. Included
were group discussions about community problems and potential solutions (Pineda Lopez, 1996).

32

(IN EGI, 1998 a). As with all ejidos, El Rincbn includes three types of land use
categories: human settlement areas (villages), common use zones (e. g. pasture and
forest), and parceled lands (farmers’ fields) (INEGI, 1998 a).

El Rincén includes an area of 9 sq. km. occupied by 1,242 inhabitants (Garcia,
1998), and is located in the southern most municipality (Amealco de Bonfil) of the
central-Mexican state of Querétaro (See Figure 1). More specifically, the ejido is located
10 km. northwest of the city of Amealco, 40 km. southeast of the state capital Santiago de
Querétaro, and 140 km. northwest of Mexico City (INEGI, 1986).

Figure 1 Map of Querétaro

    
  

San Luis Potosi

fl---~.-

o
..... 0"

Michoacan de Ocampo

33

3.4 Physical Geography

Both the ejido and larger region can be characterized as a contrasting geography
of mountains, hills, and valleys created by the intersection of several mountain chains
including, “Pinal de Zamorano”, “Pinal de Amoles”, “El Doctor”, and “Sierra Madre
Orien ” (INEGI, 1997 b). Elevations in the site range from 2,850 m. on the western
side to 2,400 m. in the eastern valley. The INEGI soil map classifies the El RincOn
topography as low hills and mountains with grades ranging between 8 and 20% (IN EGI,
1982). E1 Rincbn is part of the soil geologic region described as New-Volcanic with
acidic ignaceous bedrock (50-100 cm. deep), giving rise to yellow and brown Luvisol
soils (INEGI, 1997 b) of medium texture (INEGI, 1982) and some clay content.

Pineda — Lopez, (1998) describes the upper elevations of the ejido as forest
comprised primarily of pine and oak. The middle elevations of the ejido are dedicated
primarily to parceled fields. The lowest regions of the ejido consist mostly of pasture
land (Pineda-Lopez, 1998).

3.5 Climate

El Rincén’s climate is listed as “temperate sub-humid” with stable temperatures of
between 12 and 18 degrees Celcius (54-64 degrees Farenheit) (INEGI, 1997 b). The
warmest temperatures occur between April and June. Precipitation is low, with a
municipality average of 659.5 mm/year (INEGI, 1997 a). The highest year of
precipitation listed for the municipality for the period 1945-86 is 1,252.8 mm/year, and
the lowest is 447 mm/year (INEGI, 1997 a). July is the wettest month (160 mm ave.) and
February is the driest (10 mm.) (INEGI, 1997 b). Droughts are most intense (or

common) between November and June, frosts between November and March, rains

34

between June and September, winds between February and April, and hail between June
and November (Pineda-Lopez, 1996).
3.6 Economic Activities

According to the AUQ publication (1996), El Rincén community members are
vocal about what they perceive as a lack of local economic/employment opportunities,
and have cited the need for creating alternative sources of employment. Local leadership
has expressed concern over high levels of economically-forced emigration (as much as
one third of the entire community population), and its negative impact on community
development initiatives that are participatory in nature.

Agriculture is the principal economic activity of the region (Pineda-Lopez, 1996),
but is often supplemented by other sources of off-farm income generated by the farmers
themselves, their children, or both (Purdy, 1999)2. According to the AUQ report, men
generally work as farmers, day laborers, construction workers, or students. Women work
as homemakers, domestic servants, store clerks, or students. Women and children also
help with farm work, mostly as caretakers of grazing animals.

Local rural wage rates are described as “low” (i.e. $40 Pesos or $4 U.S./day for
farm labor at the time of the 1999 site visit) and consequently, the purchase of food
consumes nearly 100% of locally earned income. AS such, it is common for young and
middle aged men (between the ages of 15 and 45) of the ejido to go to the US. in search

of employment.

 

2 Many of the interviewed farmers have worked and have children working in the US.

35

3.7 Agriculture

Local agriculture consists of both crop and livestock production. The 45
households interviewed for the RA reported land holdings totaling 170 hectares (a mean
of 3.78 ha./family). Approximately 60% of this land is dedicated to rain-fed crop
production; the remaining 40% is cultivated under a process called “punta de riego”
(cover irrigation). In both cases, the crop cycle reflects the precipitation cycle. Planting
is done in April or May when the rains begin, and harvest takes place in the dry season
(November or December).

Corn is the principal crop of the watershed area, indeed of the entire municipality,
however, two-thirds of the respondents are said to plant corn in association with other
crops such as kidney beans, pumpkins, peas, and broad beans3. Agricultural
mechanization is described by the report as “incipient” with 7 ejido members using
tractors, 13 using backpack sprayers, and 22 using teams of horses, mules, or oxen. Most
agricultural inputs are purchased in Amelco, and crops (if sold) are taken there as well.

Nineteen of the 45 respondents reported that they consider the soil to be “fertile”,
seventeen reported that they felt it was not. One explanation offered for this difference is
the location of fields, as soil depths tend to vary between .15 and 1 meter.

Farmers indicate that crop yields are “low and variable” with two major risks
threatening plant growth: pests and drought. Lack of water is considered not only a
problem related to agricultural production, but to the completion of all daily activities.
The community has emphasized the importance of better capturing water during the rainy

season for use during the dry season. It has solicited funds for the construction of a dam

 

3 Amealco (the “corn municipality”) provides about 30-40% of all corn grown in Querétaro (Garcia, 1999).

36

(with no success to-date), but has also discussed the possibility of building more runoff
catchment ponds with greater care to ensure that they are well-built and effective at
retaining water.

The most common pests are: “Gallina Ciega” (Blind Worm) 40% and “Gusano
Soldado” (Soldier Worm) 31%. The use of herbicides is reportedly more frequent than
insecticides, both are applied at excessively high rates, and neither are said to be used in
conjunction with appropriate safety measures. The most common herbicides are
Herbarnina, Gesaprin, and Esteron, used by 58%, 29%, and 38% of RRA respondents
respectively. The most commonly used insecticides are F uradan and Basudin, used by 18
and 20% of the respondents respectively.

Residents report corn yields ranging from zero to 3 tons per hectare (generally
considered the maximum attainable yield). The average 1994-95 corn yield for the entire
municipality was 2.8 tons/hectare (INEGI, 1997 a). The following yield data obtained
from the office of the Secretaria de Agricultura, Ganaderia, y Desarrollo Nacional
(Secretary of Agriculture, Livestock Production, and Rural Development) in the city of

Amealco shows how El RincOn yields compare to those of the larger municipality for the

 

year 1998.

0 Corn:

El RincOn:

Rain-fed: 598.35 tot. ha. planted 1 ton/ha (obtained yield) 598.35 tons tot.
prod.

Punta de Riego: 170.25 tot. ha. planted 1.8 tons/ha (obtained yield) 306 tons tot.
prod.

Entire Municipality:

Rain-fed: 10,579.09 tot. ha planted 1.6 ton/ha (estimated yield) 16,926.54 tot.
prod.

37

Punta de Riego: 5,824 tot. ha planted 4 tons/ha (estimated yield) 23,2964 tons

 

 

tot. prod.
o Cempasuchil:
El Rincén: no data avail. — none planted.
Entire Municipality:
1,200 tot. ha. planted; 15 ton/ha. (ave. yield); 37 ton/ha (max.

yield); 12 ton/ha. (min. yield)

3.8 Agricultural Extension
Eduardo Garcia Cordoba, an independent agricultural engineer contracted by the

SEMARNAP-FAO project, has worked in the community for three years and is its
primary resource for agricultural extension education. He seems to have established
quite good raport with many, if not most of the local farmers and families (Purdy, 1999).
The diagnostic report indicates that while the majority of respondents complain that
agricultural extension is insufficient, they do indicate that they consider Eduardo to be an
important resource and have requested that his presence in the community be maintained.

According to Eduardo, the three biggest limitations to local crop production are:
l.) insufficient water, 2.) acidic soils, and 3.)pests (Purdy, 1999). He also states that the
upper layer of soil is thin with very little organic matter. Eduardo has worked with
several farmers to treat acidic soils with calcium carbonate, and indicates that in some
cases, yields have as much as doubled with this treatment. (Purdy, 1999).
3.9 Corn

The production of corn (Zea mays) dwarfs the production of all other crops. For
example, in 1994-95, 47,838 tons of corn were harvested in the Amealco municipality
(INEGI, 1997 a). The next most commonly produced crop was wheat with a harvest of

898 tons (INEGI, 1997 a). Eduardo (1999) estimates that approximately 90% of the

38

household economy is based on corn production. Corn is consumed by families (1—2 tons
per year per family) in the form of tortillas (Purdy, 1998).

Despite the availability and promotion of numerous high yielding corn hybrids,
the farmers included in this study rely on indigenous varieties known as “criollo”. These
varieties are locally adapted and require less water to reach maturation. Corn yields for
rain fed corn are typically in the 1-2 tons per hectare range depending on the levels of
precipitation and pests.

Production activities for corn generally follow the following calendar, which is
applicable to other crops as well.

Plowing/Disking (“Barbecho”) - January

Raking (“Rastreo”) — March — April

Ridging (“Surcado”) — April — May

Planting (Siembra) — April -— May

Weeding (“Escarda”) - May - June

Fertilizer l — April — May

Fertilizer 2 - June - July

Irrigation 1 (optional) — April - May

Irrigation 2 (optional) — June — July

Irrigation 3 (optional) — July

Herbicide/Pesticide Application — May

Harvest — November — December

Collection of Stalks — November — January

Corn is usually sold in the city of Amealco at one of any number of grain dealers
or agricultural product stores. During the 1999 site visit, shelled corn was being
purchased for $1.40 Pesos per kilogram ($1,400 Pesos or $140 US. per ton).

3.10 Punta de Riego (Irrigation Cover)
Punta de riego is essentially rain-fed crop production with the addition of a one-

time irrigation applied to fallow fields in March or April (approximately one month prior

to the planting of criollo varieties). The local practice involves siphoning water from

39

catchment ponds using plastic hoses, and distributing the water over fields during a 12-24
hour period. Soaking the ground in this manner gives the crop a head start by providing
sub-soil moisture for early plant germination, emergence, and growth, (Garcia, 1999).

Punta de riego is practiced only by those farmers whose ponds effectively capture
the rains of one season (June/July) and carry it over to the following planting cycle
(April). Thus, for the practice to offer any real advantage, there must be adequate
rainfall, effective runoff capture, and minimal storage loss. No cases were reported of
farmers using well or spring water for irrigation (Purdy, 1999).

Though the technique gives the crop a head start, harvest yields are still dependent
on levels of seasonal rainfall and other production factors such as pests. Eduardo (1999)
indicates that in good years, the punta de riego technique can double yields. In years of
low rainfall, the technique may offer no real advantage.
3.11 Environmental & Natural Resource Problems

The diagnostic report identifies a number of natural resource and environmental
problems including: over-grazing, excessive use of agri-chemicals, water erosion,
deforestation, over-hunting, and improper disposal of garbage. The report states that
while community members recognize these problems, they tend to look externally for
solutions rather than generating and promoting them from within.

According to the report, overgrazing of pasture (especially by horses) is endemic,
and both a major limitation to livestock production and a leading cause of soil erosion.
Because pasture resources are generally open-access, all farmers may use them to graze
their animals. This, in combination with limitations in crop production, results in severe

overgrazing with no incentive for farmers to conserve the resource. During the author’s

40

1999 visit, the community was in the process of dividing (fencing) common pasture areas
into private holdings in an effort to create incentive for more sustainable management
(Purdy, 1999). It remains to be seen if this will result in better pasture management.
Water erosion is considered a critical problem, especially in relation to the
formation of gullies in the upper and middle areas of the micro-watershed. It is also the
major cause of top soil loss. Some efforts have been made to reduce erosion by
constructing filter barriers of rock or branches to slow water travel through erosion
gullies. The report states, however, that while the community expresses interest in
programs designed to repair or prevent erosion, it does not readily take initiative to
prevent erosion.
3.12 Water Storage Ponds

The ponds in El Rincén are embankment ponds, which are defined in an NRCS
Agricultural Handbook Publication entitled “Ponds — Planning, Design, Construction”
(1997) as ponds created by “building an embankment or dam across a stream or
watercourse where the stream valley is depressed enough to permit storing 5 feet or more
of water”. According to local farmers, the ponds were built in the early to mid 1980’s by
bulldozing earthen embankments across natural drainage courses (Purdy, 1999). There
are a total of 18 such ponds in El RincOn, of which only 10 retain water effectively.

The eight non-functioning ponds tend to have beds consisting of fractured rock or
soil that is excessively permeable (i.e. low in clay content). Such factors were reportedly
not considered by project engineers during site selection (Purdy, 1999). The farmers
indicate that some ponds lose water through infiltration in the pond floor itself, and others

lose water through the plane of contact between the base of the embankment and the

41

existing grade (Purdy, 1999). One pond owner stated that he has seen water emerging
from the ground approximately 100 meters down-grade from the pond, what he believes
to be seepage loss from the pond (Purdy, 1999).

With the exception of one pond which has a large section removed from its earth
embankment, the four farmers selected for the study indicate that their ponds do fill with
water4 (Purdy, 1999). One farmer indicated that his pond can fill in one night, but can
also drop 40 cm. in one day due to what he believes is primarily infiltration (Purdy,
1999). The farmers recognize that evaporation also causes water loss, but feel it may
account for only 10% of total loss. The other 90%, they believe is caused by infiltration
(Purdy, 1999). Because the ponds do not effectively conserve water, they are essentially
used only to water livestock.

3.13 Conclusions

In sum, the people of El Rincbn experience economic hardship as both a function
and cause of natural resource depletion. Because water scarcity is a major limitation to
agricultural production, the site is representative of the larger region, and thus, a good site

for studies on water conservation techniques such as this one.

 

’ The berm was opened to allow water flow to the farmer’s fields.

42

Chapter 4: Study Methods

4.1 Overview

This study measures the cost effectiveness of using geomembranes in runoff ponds
to create a water surplus for use in agricultural production. To determine the proj ect-
generated water surplus, the study uses a 21-year aggregated rainfall data history with the
SCS Runoff Curve Number Equation to calculate monthly excess for the 21-year data
history. The values of excess were then multiplied by the size of the pond catchment
areas (in square meters) to determine the total surface runoff within each pond catchment
area. This historical look at runoff provides insight into the quantity of runoff available
for capture and a starting point for calculation of stored water loss.

While a lack of infiltration data prevents exact calculation of stored water loss, the
study does use evaporation and animal consumption data to create a framework for
modeling plausible infiltration rates. The proj ect-generated water surplus will be
assumed to equal the quantity of runoff water lost to infiltration from a full pond (or some
portion thereof).

The proj ect-generated water surplus is valued by calculating the market value of
increased crop yields for one traditional crop (corn) and one alternative crOp
(cempasuhcil) over a 15-year project cycle. A net present value for each pond was
calculated by subtracting the sum of discounted costs from discounted benefits using a
discount rate of 10% (the opportunity cost of capital). The results of the benefit-cost

calculations are presented in Chapter 5.

43

I: ..

4.2 Data Collection

In addition to research conducted at Michigan State University, two week-long
trips were made to the Querétaro region to gather the following types of data:
meteorological, site background, agricultural production, environmental-natural resource,
and agricultural input/crop prices. Between the two trips, approximately 5 visits were
made to the El RincOn study site, as well as numerous visits to the AUQ, various
governmental agencies, local markets, and agricultural supply stores.

Topographical, land use, and soil maps, as well as aerial photos and annual
statistical information were purchased from INEGI (the Instituto Nacional de Estadistica
Geografia y Informatica) in the city of Querétaro’. All meteorological data (including
daily & monthly precipitation and evaporation totals) used in this study was procured
from one weather station in the city of Querétaroz. Crop yield data for El Rincbn and the
Amealco Municipality was obtained from the office of SAGAR (Secretaria de
Agricultura, Ganaderia y Desarrollo Rural) in the municipal city of Amealco.
Information on regional crop and animal production was provided by INIFAP (the
Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias). Several visits
were made to the AUQ library where literature was obtained on local agricultural
production, the Mexican ejido system, natural resource and environmental issues, and
food security. Interviews were conducted with Eduardo Garcia (local extensionist), Rar’rl
Pineda LOpez (AUQ biologist and author of the rural participation diagnostic), Miguel
Angel Domingez (hydrologist at the AUQ), various farmers and community leaders in El

RincOn, agricultural supply store owners, and various officials from the fore-mentioned

 

' INEGI is a good starting point for any subsequent research endeavors of this type in Mexico.
2 Copies of data from the stations used in this study were available at the Querétaro Station

44

agencies.
4.3 Site Selection

Though the inclusion of multiple study sites in this research would allow for an
insightful inter-site comparison, it was decided to use one site because of limitations of
time and financial resources. The El Rincén site was selected after visiting several rural
communities around the city of Querétaro in August, 1998 (including La Barreta along
Highway 49 north of Querétaro, and the community of Huimilpan south of Querétaro).
The study site is actually one of several communities peripheral to the Amealco
municipal city that is referred to as El Rincbn. The particular community described here
is known locally as “E1 Rincbn — El Aguacate” — referring to the name of the watershed
in which it is located.

El Rincén was selected over other potential study sites based in-part upon the
recommendation of Dr. Rafi] Pineda LOpez of the Biological Resources Department at the
AUQ. His recommendation encompasses the following considerations:

0 The existing rapport between AUQ faculty (especially Dr. Rail] Pineda) and

community members i

o The existence of a published study of the community conducted by students and

scholars from the AUQ

o The facilitative and supportive influence of Eduardo Garcia who has special

rapport with the community and extensive knowledge of local agricultural
and natural resource issues

0 The community’s organizational strength, and interest and history in community

development.

45

In addition to Dr. Pineda’s suggestions, other considerations included:
0 The fertility of El Rincbn soils relative to other sites visited in the region,
increasing the potential for a cost-effective return on investment.
0 The region’s importance in corn production for the state of Querétaro.
0 Existing awareness and interest in the liner technique based in-part upon the
previous visit of the MSU/NRCS team to the area.
0 Relatively easy access to the site by road
The first visit to El RincOn made in August of 1998 was facilitated by Eduardo
Garcia, so that during subsequent visits, the author was recognized by the community and
free to move independently about the micro-watershed area. In all instances, community
members were extremely friendly, gracious, and helpful in providing information.
4.4 Pond Selection & Measurement
Approximately 15 ponds were visited in August of 1998, of which four were
selected to serve as the basis for calculations and analysis. The ponds were not selected
randomly, but rather as a function of owner interest and willingness to provide
information and host pond visits. Through the help of Eduardo Garcia, the author was
able to attend a regular meeting of the ejido (8/98), explain the nature of the study, and
make contact with farmers who expressed interest in having their ponds studied3.
Though it was carefully explained to the farmers that the purpose of the study was
to gather data and provide analysis (and did not constitute an initiative to have the ponds

lined) it is nonetheless presumed that the farmers were motivated to collaborate in-part by

 

3 To maintain their privacy, the names of the farmers are not stated in this study.

46

the hope that such a study might lead to a project proposal and external financing. It was
further explained that the results of the study would be made available to interested
community members in both a thesis format (English) and condensed report format
(Spanish), and that any further action with regard to lining the ponds would have to be
initiated by the community itself.

The four ponds selected to serve as models for analysis vary in size, shape, area of
runoff catchment, and quantity of adjacent crop land (i.e. the total quantity of land owned
by the pond owner that is down-grade from the pond, and could potentially be irrigated
using a siphon and gravity flow). However, all ponds chosen for study are reported by
the owners to exhibit high (but unknown) rates of infiltration loss. Table 1 (facing page)
provides a basic summary of the pond characteristics. .

The approximate plan shapes of the ponds were determined by locating the ponds
on an aerial photo purchased from the INEGI office in the city of Querétaro’. Based on
the determination of shape (circle, ellipse, parabola, etc.) the appropriate area/volume
formulas (taken from Appendix A of an NRCS publication entitled “Ponds — Planning,
Design, and Construction”) were used to calculate the ponds’ surface area and volume.
Pond dimensions were measured by pacing their length and width (or radius where
appropriate), where the author’s pace is equal to approximately one meter. The volume
of each pond was calculated by multiplying the product of its surface area and maximum

depth (or the highest point of the earth embankment) by one-half. The one-half

 

‘ All four ponds are visible on “ORTOFOTO” No. FI4C76, scale 1:5,000

47

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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48

multiplier was used to reflect the change in pond depth from back (up-grade) to front
(down-grade) which is triangular shaped in a profile view. See figure 2 (facing page).
The area and volume calculations for ponds 1-4 were made as follows:
PEEL

Surface Area (one-half circle) = .5 (1t r2) or .5(3.14 x (432)) = 2,902.93 sq.

meters

Volume = .5(surface area x depth) = .5(2,902.93 x 1.8) = 2,612 cu. meters
£01312;

Surface Area (full ellipse) = (1t/4)(W)(L) = (3.14/4)(40)(63) = 1,979 sq. meters

Volume = .5(surface area x depth) = .5(1 ,979)(2) = 1,979 cubic meters
MI

Surface Area (the area of 1 rectangle + 2 triangles) = [(WxL) + .5(WxL) +

.5(WxL)] = (75)(75) + .5(70)(75) + .5(70)(25) = 9,125 sq. meters

Volume = .5(surface area x depth) = .5(9,125)(2) = 9,125 cubic meters
291$

Surface Area (parabola) = .67(L)(W) = .67(58)(58) = 2,253.88 sq. meters

Volume = .5(2,253.88)(1.8) = 2,028.5 cu. meters

It is important to note that to some degree, the ponds defy exact measurement and
size calculation because of irregularities in pond surfaces and boundaries, and the
occasional presence of erosion gullies. The shape classifications listed in Table l were
selected as the “best-fit” representation of the pond shapes as determined using aerial
photography. In some cases, pond boundaries are not clearly defined, and none of the

ponds match their shape classification perfectly. As well, because the pond dimensions

49

 

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mason mo 32> groom 380 .N 83mm

50

were paced and not measured with a tape, their measure is not exact. Nonetheless, the
figures listed in Table 1 are good approximations and Should be sufficient for the
completion of a sound benefit-cost analysis.

Also, this study includes the re-shaping of ponds (making them deeper and tighter
in diameter to reduce evaporation loss) as part of the cost of preparing sites for liner
installation. For purposes of study however, it will be assumed here that any re-shaping
will result in no net change in pond volume (from. their current state), and the said pond
dimensions are thus used for all hydrological calculations.

4.5 Rainfall Analysis

This study generates in-part from farmer-made assertions that annual rainfall and
runoff are sufficient for the filling of ponds on an annual basis. To test this assertion, the
study uses local rainfall data to create an historical picture of rainfall and rainfall excess.

In the absence of an historically complete rainfall record (data tends to be spotty
and inconsistent), a 21-year span of data was created by aggregating rainfall data from
four different meteorological stations located in the region. To do so, data was taken
from the following stations listed in the order of preference by which their data was used:

Station Distance from Site Avail. Data

 

Granja Carnation 7 km. 1978-1989
Lat: 20 deg, 13’ 23”/ Alt: 2,650 m.
Long: 100 deg., 09’ 10”

Amealco I 11 km. 1988-1991
Lat: 20 deg., 11’ 05”/ Alt: 2,648 m.
Long: 100 deg., 08’ 44”

San Miguel Tilaxcalte 20 km. 1975-1989

Lat: 20 deg., 08’ 32”/ Alt: 2,420 m.
Long: 100 deg., 04’ 00

51

Station Distance from Site Avail. Data

 

Las Palmillas 25 km. 1971-1991
Lat: 20 deg., 19’ 32”/ Alt. 2,148 m.
Long.: 99 deg., 56’ 13”

Figure 3 (facing page) shows the location of the four weather stations relative to
the study site. Tables 76-79 (Appendix D) show the rainfall data available from each of
the four contributing stations:

As the station closest to El RincOn (7 km.), Granja Carnation data was selected to
represent the rainfall of the study site (i.e. For this study, it was assumed that the rainfall
of El Rincén and Granja Carnation were the same). Because no data exists for the study
site itself, there is no way to test this assumption without further data collection.

The rainfall data above reveal quantitative differences between stations (see
monthly averages), which if applied to an aggregated total, would potentially
misrepresent the monthly and annual rainfall patterns of El RincOn. Thus, before rainfall
data was taken from the Amealco 1, San Miguel Tilaxcalte, and Las Palmillas stations and
applied to the aggregate, it was first adjusted by a correction factor so as to better
represent the rainfall patterns of the study site. Station and month-specific correction
factors were created by comparing the monthly rainfall averages of each of the stations to
those of the Granja Carnation station, where: Adjustment Factor = M0. Average of
Granja Carnation /Mo. Ave. of Comparison Station

The correction factors were subsequently multiplied by the corresponding rainfall
data and then added to the Granja Carnation base to create the 21-year data history. In

the cases where data were missing for individual months, it was taken from the next

52

Figure 3. Map of Weather Stations

Las Palmillas

 

San Miguel Tilaxcalte

53

closest station. Tables 80-82 (Appendix D) indicate the correction factors used for each
weather station and month. Table 2 (facing page) presents the 21-year aggregated rainfall
data with the contributions of each meteorological station color-coded to indicate their
origin. Graphical representation of monthly averages and annual totals for the aggregated
data are presented in Table 83 and Figures 5 & 6 in Appendix D.
4.6 Calculation of Runoff

The quantity of runoff generated within the catchment area of each pond was
calculated for every month of the 21-year rainfall data cycle by multiplying rainfall
excess in meters (difference between total precipitation and soil infiltration) by the area
of each catchment zone (in square meters). It is important to note that this value (runoff)
represents the total quantity of water available for capture, not actual quantities of
capture. For certain months, more runoff will be generated than can be held by the
ponds, in which case, the ponds will overflow and the excess runoff will drain away
down-slope.
4.7 Catchment Area

The boundaries of the catchment area corresponding to each of the four ponds
were determined by examining contour lines on an INEGI topographical map (1:50,000
scale), and studying drainage patterns on a rectified aerial photo (IN EGI, 1999). As well,
video footage of the catchment zones taken during site visits was used in certain instances
to help determine the direction of drainage slopes. Final decisions concerning the
boundaries of catchment areas were made under the direction of Dr. Scott Witter at
Michigan State University, who has extensive experience in the hydrological

interpretation of aerial photos. Once determined, the boundaries of each catchment area

54

 

 

 

 

 

 

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55

were outlined on the aerial photo. To calculate the surface area of the catchment zones,
the photo’s scale was used to measure and superimpose a grid pattern of squares
(representing 125 x 125 meters) over the four delineated areas on the photo.

The area of each zone was calculated by totaling the number of squares (15,625
m2 each) within its boundaries (partial squares were added with other partial squares to be
counted as one). The size of each is listed below:

Pond Catchment Area (sq. m.)

 

1 78,125
2 46,875
3 343,750
4 78,125

These figures represent the size of the areas within which rainfall excess is diverted to
each of the four study ponds.
4.8 Calculation of Excess

The rainfall excess corresponding to the 21-year aggregated rainfall data was
calculated by applying a curve number and daily precipitation totals to the SCS Runoff
Curve Number Equation. As stated in the literature review, the SCS method was selected
for its simplicity and minimal requirement for data (curve number and precipitation
totals). Using the SCS equation, the quantity Q of excess for individual rainfall “events”
was calculated where:

Q = [(P - .28)2] / [P + .88] and s = lOOO/CN — 10 and:
Q = Runoff in inches
P = Rainfall in inches
S = Potential maximum retention after rainfall begins

CN = The curve number selected based on soil type and land use (Hoggan, 1989)

56

4.9 Curve Number Selection

A curve number is used in the SCS equation to represent the “land use, cover, soil
classification, hydrological conditions, and antecedent runoff conditions” of a study site
(Hoggan, 1989). A curve number may be selected from one of several SCS-provided
charts that correspond with different kinds of land use. This study uses a curve number
of 80 to calculate monthly excess for all four of the ponds and all 21 years of rainfall
data. This number was selected from the “Cultivated Agricultural Lands” chart and
reflects the following land use and soil type designations within that particular chart.
Land Use Chart: “Cultivated Agricultural Landsz”

Cover Type: “Row Crops”
Cover Description: Combination of “Straight Row” and “Contoured”
Hydrologic Soil Group: Group B (moderate infiltration rate)
Hydrologic Condition: “Poor” (with factors that tend to “impair
infiltration”)

(NRCS, 1997)

The “Cultivated Agricultural Lands” chart was selected (as opposed to “Urban
Areas”, “Other Agricultural Lands”, or “Arid/Semi-Arid Rangelands”)(NRCS, 1997)
because the catchment areas in question are dedicated almost exclusively to corn
production (with the exception of some narrow grass and bare strips between corn plots)
(Purdy, 1998). The “Row Crops” cover type was selected for the same reason (as
opposed to “small grains”, “meadow”, or “legumes”) (N RCS, 1997).

The SCS chart provides four “Hydrologic Soil Groups”: (Hoggan, 1989)

Group A: low runoff potential; high infiltration rates; deep, well — to excessively

57

drained sands or gravels; high rates of water transmission .3 in./hr.

Group B: moderate infiltration rates; moderately-deep to deep, moderately well-
drained to well- drained soils with moderately- fine to moderately-coarse
textures; moderate rate of water transmission: .15-.3 in/hr.

Group C: low infiltration rates; soils with a layer that impedes downward
movement of soils; moderately-fine to fine texture; low rate of water
transmission .05-.15 in./hr.

Group D: high runoff potential; very low infiltration rates; clay soils, soils
with a permanent high water table, or soils with a clay pan layer at or near
the surface; very low rate of water transmission 0-.05 in./hr.

Based on a description of the El Rincén soils provided by an INEGI Soils Map,
the Group B Hydrological Condition was selected to represent the study sites. According
to the INEGI map (1974), El RincOn soils are “medium” textured Luvicos of the
Phaeozem Family. The topography is characterized as low hills and mountains, with
slopes ranging between 8 and 20 degrees, and “deep” bedrock between 50 and 100 cm in
depth. Because the hard pan layer is deep (allowing more percolation), the soils
“medium textured”, and the slope gradual, it was decided that the type B class would best
represent El RincOn.

The SCS chart (1997) provides two options for a soil’s hydrological condition
“good” and “poor”. According to the chart, the “poor” condition pertains to soils that
have “factors [that] impair infiltration and tend to increase runoff”. Conversely, soils in

“good” hydrologic condition have “factors [that] encourage average and better-than

 

5 Map may be referenced as “Carta Edafologica”; La Estancia F -l4-C-76; Scale: 1:50,000.

58

average infiltration and tend to decrease runoff” (N RCS, 1997). Those factors include

the following — the increase of which causes higher infiltration and decreased runoff

(NRCS, 1997).

a.) “density and canopy of vegetative areas”

b.) “amount of year-round cover”

c.) “amount of grass or close-seeded legumes in rotations”

d.) “percentage of residue cover on the land surface (good 3 20%)”

“degree of surface roughness”

(NRCS, 1997)

The “poor” hydrologic condition was selected to represent El RincOn soils for
several reasons:

1.) The catchment areas in question are canopied with low-density vegetation during
only 5 months of the year (i.e. mid to latter part of the corn growth cycle; June —
October) (Purdy, 1998).

2.) The catchment areas do not include grass or legumes in substantial quantity
(estimated 5 5% of catchment area) (Purdy, 1998).

3.) The soils of El RincOn are low in organic matter (Garcia, 1998 and Pineda Lopez,
1996) because farmers remove corn stalks during or soon after harvest to feed to
livestock. (_<_20% coverage)

4.) The existence of erosion gullies in bare areas would tend to indicate a “poor”
condition.

Within the “row crops” category, one of several “treatment” options may be

9’ 6‘

selected, including “straight row , contoured”, “terraced”, “bare soil”,

6‘

crop residue”, or

59

combinations thereof (NRCS, 1997). Because the fields comprising the catchment zones
of each pond tend to include both contoured fields (curve number = 81) and straight row
fields (curve number = 79) with little crop residue (Purdy, 1998), the average (or
“weighted curve number”) (80) of the two treatment options was selected for this study.
Because of similarity in land use and soil conditions between the four ponds, and for the
sake of simplicity, this number was used to calculate excess for all four of the pondsé.
Substituting the curve number 80 in the equation:
Q = (P - .2S)2 / P + .88 where S =(1000/CN) - 10 = (1000/80) — 10 = 2.5
Yields: Q = (P - .2(2.5))2 / P + .8(2.5)
Substitution of the remaining variable P yields the quantity Q of excess.
4.10 Substitution of Precipitation Totals
As Hoggan (1989) notes, spatial and temporal parameters are important for
modeling rainfall-runoff relationships, however, a “sparseness” of data can often make
exact definition difficult. Because the rainfall data available in the study region are
presented as daily totals only, some assumptions had to be made about the time and space
dimensions of the rainfall. Lacking information about the number and duration of
individual rainfall events within a 24-hour period, it was decided to use daily totals to
represent individual rainfall events. Similarly, daily precipitation totals for contiguous
days of rainfall were totaled and treated as one event. For instance, 2 inches of rainfall
falling each day for three contiguous days would be entered into the equation as one

rainfall event of 6 inches.

 

6 More in-depth soil studies might result in selection of different curve numbers for each pond.

60

Because the SCS formula is designed to receive and provide data in inches
(NRCS, 1997), data from the various weather stations were converted from millimeters to
inches prior to substitution in the equation. Daily rainfall totals were taken from the
appropriate contributing stations (described earlier), adjusted by the station and month-
specific adjustment factor (where appropriate), converted to inches, and entered into the
SCS equation. These conversions and calculations were performed in a simple program
created in Microsoft Excel (Microsoft Inc., 1997) to calculate excess from precipitation.
4.11 Conversion of Excess to Runoff

Table 84 (Appendix D) shows rainfall excess (in meters) for each month of the
21-year rainfall data. These values were treated as a constant for calculating total runoff
within each pond catchment area. To convert excess to runoff, the excess values were
multiplied by the area of catchment corresponding to each of the four ponds (Belcher,
1999). The product of these two is the quantity of runoff available for capture each
month (not necessarily the actual amount captured).

Tables 3-5 (facing pages) present rainfall runoff (in cubic meters) available for
catchment. Note: Because Ponds 1 & 4 have the same sized catchment area, one table is
used to represent runoff values for both ponds.

4.12 Comparison of Runoff to Pond Capacity

While ignoring briefly the forces of pond water loss (evaporation, infiltration, and
consumption), is enough runoff generated each year to fill the study ponds? If so, what
percentage of the time and based on how many months of runoff? Are there any singular

months of runoff sufficient to fill the ponds?

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To answer these questions the calculated values for monthly and annual runoff
were compared to the holding capacity of each pond. For the sake of simplicity, the
monthly comparison uses monthly totals for years of high, low, and average runoff
instead of trying to graph monthly totals for all 21 years. This comparison helps illustrate
the maximum possible range of monthly runoff values and the number of months
necessary for the ponds to fill. The annual comparison compares yearly totals for all 21
years to holding capacity. A third comparison was done to test the runoff calculations for
sensitivity to error. If the methods used to calculate runoff for this study resulted in over-
statement of runoff quantities, how much can the calculations be off before the study
ponds would not fill? For this comparison, runoff values were halved and compared to
the ponds’ holding capacities. The results of these comparisons are presented in
Appendix D. Note: For purposes of continuing, the calculations do reveal
that for all 21 years of available data, total annual runoff was sufficient to fill the ponds.
As well, during the 21-year data span, there occurred years where runoff from singular
months was sufficient to fill the ponds.

4.13 Calculation of Stored Water Loss

Having established that the ponds can and do fill, the study looks at how much water
is currently lost from the ponds once captured. Stored water is lost from the ponds in the
following ways:

0 Evaporation (from surface)

0 Infiltration (through pond floor and berm)

- Animal Consumption (when water available & animals allowed access)

0 Irrigation (not currently practiced in the case of the four selected ponds because

65

of water deficiency)

Because the farmers indicate that the ponds are always dry by the months of
November or December, this study will assume that total annual loss is greater than total
runoff catchment (not necessarily greater than total annual runoff generation within the
catchment area) 100% of the time. To determine the water benefit to be generated by
lining the ponds, this study quantifies each source of loss.

4.14 Calculation of Stored Water Loss Due to Evaporation

Similar to rainfall data, evaporation data is not widely available and tends to be
discontinuous in its record (i.e. recorded for some years, but not others). To create a data
record corresponding to the 21-year rainfall record, evaporation pan data was aggregated
from the Granja Carnation and San Miguel Tilaxcalte weather stations. Tables 97 & 98
(Appendix D) show the data available from the two stations.

Again, because of its proximity to the study site (7 km.), the Granja Carnation
data was selected to represent the evaporation conditions of El Rincon. To adjust for
differences in evaporation rates between the two stations, a comparison was made of the
monthly averages of each station to calculate month-specific adjustment factors, where
the adjustment factor = Granja Carnation data / San Miguel Tilaxcalte data. Table 99
(Appendix D) shows the calculation of these factors. The factors were subsequently used
to adjust the San Miguel Tilaxcalte data. Once adjusted, the San Miguel Tilaxcalte data
was added to the Granja Carnation data, creating a data history for the years 1976-1988.
The monthly averages of this aggregated data were then used to represent missing data
for the years (1971-1975 and 1989-1991). Table 100 (Appendix D) shows the aggregated

data.

66

To represent the evaporation loss occurring in a larger body of water such as a
pond or lake, evaporation pan data from a US. Class A Pan is normally adjusted by a
coefficient of .7 (Sharp, 1984). This coefficient reflects differences in evaporation rates
between a large body of water such as a lake and a small metal pan — which tends to heat
up faster, increasing the water temperature and evaporation rate). The .7 coefficient is
used in this study as well, however, because the volume of water contained in each pond
changes as a function of seasonal runoff, two adjustments were made to the data
(Belcher, 1999).

The month-to-month changes in stored water volume affect not only the surface
area of water exposed to evaporation forces, but also the rate of evaporation as a function
of temperature differences (Belcher, 1998). For the months when the ponds are estimated
(based on farmer reports) to be full (June - August), the .7 coefficient is used. During the
months when the ponds contain less water, a higher coefficient should be used to reflect
higher water temperatures (i.e. higher evaporation rates). Thus, it is assumed that the
more empty the pond, the more evaporation loss will resemble that of a metal pan
(approaching a coefficient of 1.0). Dr. Harold Belcher (1999), an agricultural engineer at
Michigan State University, suggested using a coefficient of .85 for those months when
the ponds are near empty. To account for the gradual change between maximum and
minimum pond capacity (Oct.- Jan. and May- July), the difference between .7 and .85
was divided incrementally among the intervening months. Table 6 below shows the
coefficient used for each month.

Table 6 Evaporation Pan Coefficients

[Em—Emma TWETT¥Q

 

 

 

 

 

 

 

 

 

 

67

To account for monthly changes in the surface area of water exposed to
evaporation forces, percentage estimates of the maximum pond surface area were
assigned to each month. For the months when the ponds are estimated to be full (June -
August), the pan coefficient and data are applied to 100% of each pond’s maximum
surface area. For the months when the ponds are estimated to be empty or near empty,
the pan coefficient and data are applied to only 10% of the total surface area. Again, the
difference between the two percentage extremes was distributed incrementally among the
intervening months to reflect gradual increases and decreases in water volume (from the
rainy season to the dry season). Table 7 (below) shows the month-specific coefficients

used to adjust pond surface area:

 

 

 

 

 

Table 7 Evaporation Surface Area Coefficients
u o u (11 u u 1 1 1 u

 

 

 

 

 

 

 

 

 

 

 

 

Thus, as pond volume increases, the area exposed to evaporation increases, but
the rate of evaporation decreases. This inverse relationship is illustrated in Figure 4
(facing page).

All adjustment factors and coefficients were subsequently applied to the 21-year
evaporation pan data, and then multiplied by the total surface area of each pond to
calculate evaporation loss in cubic meters. The 21-year monthly totals for evaporation
loss are presented in Tables 8-11 (pages 70-73). Note: These tables are set up to
correspond to the tables of runoff totals). These values represent the amounts of stored
water lost each month from evaporation, which can in turn, be subtracted from values of

total runoff for corresponding months).

68

Figure 4. Evaporation Data Adjustment Coefficients

 

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4.15 Calculation of Animal Consumption

Because the farmers own relatively few livestock that consume water from the
ponds during only those months when water is available, consumption loss is quite low
relative to evaporation and infiltration. Lacking data about the numbers of livestock
owned by each farmer for the period 1971-1991, it was decided to calculate consumption
based on the number of animals owned currently and use consumption as a constant for
all 21 years.

Monthly and annual consumption totals were calculated using daily water
requirements for the kinds and number of livestock accessing the ponds and estimated
number of days of access. By doing so, this study assumes that during those months
when water is available, the animals meet 100% of their daily water requirement from the
ponds. This is likely not the case as the animals are ofien free to roam and may have
access to other water sources. As well, the data used for daily consumption rates pertains

to livestock in the US. Those of El Rincén tend to be smaller and less well nourished —

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therefore likely to consume less water per day. This potential overstatement of
consumption loss is likely balanced by the possibility of animals from neighboring
farmers consuming water from the study ponds. Without more accurate data, the stated
technique represents a best guess scenario of consumption patterns. Animal consumption
loss in cubic meters is presented for each pond in Tables 12-15 (facing page).
4.16 Calculation of Stored Water Loss Due to Infiltration

In the absence of empirical data for soil infiltration rates, this study estimates
infiltration loss as a multiple of evaporation using calculated quantities of runoff,
evaporation, and livestock consumption, in conjunction with anecdotal evidence about
year-end pond water levels as parameters for a calculation model. Because the farmers
indicate that their ponds consistently go dry between the months of November and
January every year, it can be assumed that total annual loss (evaporation plus infiltration
plus consumption) is greater than total annual runoff capture for any given year (i.e.
storage carryover between years is zero). Thus, the combined quantities of evaporation,
infiltration, and consumption must be greater than the quantity of runoff capture for the
May -— November period. (Again, it is important to distinguish between total runoff and
total capture as more runoff may occur than that which is actually captured.) The
assumption made here is that an infiltration rate that produces an empty pond (zero water
balance) would approximate actual infiltration rates were such empirical data available.

For each month, monthly totals for evaporation and livestock consumption were
subtracted from either total monthly runoff or maximum pond capacity - in cases where
monthly runoff exceeds capacity. An estimated value for infiltration was also subtracted

from runoff. The difference between capture and loss was treated as a carry-

74

Table 12 Animal Consumption Loss in Cu. M. - Pond 1

No. GalJMo. No. Mo. GalJYr. Cu. Mtrs.

1 300 I 12 21600

 

Total 8 109

Table 13 Animal Consumption Loss in Cu. M. - Pond 2
No. GalJMo. No. GalJYr. Cu. Mtrs.

450 12 5 400
otal

 

Table 14 Animal Consumption Loss in Cu. M. - Pond 3

No. GalJMo. No. Mo. GalJYr. Cu. Min.

 

 

 

 

 

  
   

   

 

300 1' 12 3600 14
1m ’ 136
Table 15 Animal Consumption Loss in Cu. M. - Pond 4
Animal IGaIJoay No. GalJMo. 1N0. Mo. GalJYr. lea. m.
”ine- I 1 i 3,150] 12‘ 37,800!” , ,1"
Equine ] 15| 4| 1,3001 12] 21,aoo|

 

    

Total 15.9409

75

over value and added to the runoff quantity of the subsequent month. These calculations
for loss and carryover were performed for each month using different infiltration rates to
find a zero water balance by the months of November to December. To find the
maximum possible range of infiltration loss without performing these laborious
calculations 84 times (4 ponds x 21 years of rainfall runoff data) infiltration rates were
modeled for three different kinds of years: the year of highest total runoff, the year of
lowest total runoff, and the year of average runoff for the 21 years. Tables 16—27 (facing
pages) show the zero-producing infiltration multiples calculated for each pond for the
three types of runoff years.
4.17 Comparison of Stored Water Loss

Having calculated totals for all three sources of stored water loss, a comparison
was made to illustrate how water is lost from the ponds. Again, instead of comparing
values for all 21 years, a comparison was made for high, low, and average runoff years
for all four ponds. The results of these comparisons are presented in Appendix D.
4.18 Re-Calculation of Evaporation Under Project Conditions

In a lined pond scenario, evaporation from pond surfaces will be different than
from unlined ponds since more water will retained in lined ponds — and thus a greater
surface area will be exposed to the evaporation forces of sun and wind. However,
because there is more water in the ponds, its temperature will also be cooler as the sun’s
energy is distributed over a greater mass. Thus, to create a more accurate picture of a
water surplus created by lining ponds, it is necessary to adjust the coefficients for
evaporation. Note: This study also proposes re-shaping the ponds in preparation for

lining, making them deeper with less exposed surface area, with no net change in volume.

76

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However, since final dimensions are unknown, this study relies on the current dimensions
to re-calculate evaporation. This should affect study results only by slightly overstating
evaporation loss and thus slightly understating the potential water surplus created by
liners.

The same calculation models used to model infiltration loss (see Tables 16-27),
show that for most months, runoff generated within the pond catchment areas is greater
than evaporation alone (i.e. by eliminating infiltration and consumption, ponds will stay
full because more water is supplied to ponds in runoff each month than is lost due to
evaporation). Thus, for purposes of calculation, it is assumed here that under project
conditions, evaporation will take place from ponds that are full, or close to full. As such,
pan evaporation data was re-adjusted by the .7 pan evaporation coefficient to calculate
evaporation loss for project conditions (i.e. the recommended coefficient for larger bodies
of water). Also, because under project conditions, the ponds will stay closer to full, the
adjusted evaporation data was multiplied by 100% of the pond surface area (versus the
changing percentage of total surface area used in previous calculations). Because pan
evaporation data was not available for all 21 years corresponding to rainfall data, the
monthly averages of the available data were used in these calculations. These annual
evaporation totals (see Tables 28-30 facing page) were then used as yearly constants for
the calculation of a project-generated water surplus (i.e. the same quantities of total
annual evaporation were used every year in the calculation of water surplus).

4.19 Calculation of Project-Generated Water Surplus
Having quantified runoff and all sources of loss, it is now possible to quantify a

hydrological benefit provided by eliminating one or more sources of loss -— infiltration in

81

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this case. Thus, the project-generated surplus (or quantity of water available for
agricultural use in May) will equal some quantity of runoff catchment from the previous
year minus some quantity of evaporation. The results of the monthly runoff analysis (see
Appendix D) indicate that for an average year, September is the last month during which
runoff of a singular month is sufficient to fill the ponds. Similarly, the models used to
calculate infiltration (Tables 16-27) show that Total Runoff — Total Loss is almost always
greater than holding capacity for the month of September. Therefore, it is assumed here
that under project conditions, ponds will be full at the end of every September, and any
water surplus will equal the full pond value minus the difference between total runoff and
total evaporation for the months of October — April. Note: Animal consumption is not
factored as loss in the lined pond scenario since lining ponds necessitates fencing out
livestock who can damage the liners. In years where October — April runoff is greater
than evaporation, the project surplus will equal pond capacity (since additional runoff
cannot be held by an already full pond). For years where October — April runoff is less
than evaporation, the project surplus will equal pond capacity minus the net quantity
(positive) of evaporation.

A value for year-end water surplus was calculated for each pond and all 21 years.
For the sake of simplicity, it was decided to make the average of the 21-year surpluses
represent the average with-project water surplus. In other words, using 21 different
surplus values to calculate changes in crop production would be more work than possible
for this particular study. The 21-year average of these yearly totals was used as a best

predictor of project-generated benefits, as well as for the calculation of agricultural

83

production under project conditions. Tables 31-34 (facing pages) show the calculation of
the project-generated water surpluses.
4.20 Calculation of Production Land Base as a Function of Project-Generated

Water Surplus

Economic values for the project-generated water surpluses were calculated by
estimating their production enhancing effects on two crops: corn and cempasuchil. The
interviewed farmers as well as Eduardo Garcia have indicated that when practiced, punta
de riego typically produces corn yields of 34 tons per hectare, and per his
recommendation a value of 3.6 tons/ha. was used for this study. While no data is
available as to how much water is applied (required) per hectare to produce such corn
yields, the farmers have indicated that a punta de riego water application typically lasts
12-24 hours per hectare. This study assumes that such an application might constitute the
equivalent of a 3 inch rainfall, which is 81,462 gallons (or 762 cu. m.) of water applied
per hectare (NRCS, 1997). Thus, it is assumed here that to produce 3.6 tons of corn per
hectare requires a one-time application of 762 cubic meters of water per hectare. Thus, to
calculate the quantity of corn-producing land that could be irrigated with proj ect-
generated water, the surplus amount for each pond (21-year average) was divided by 762.

Calculating the water requirement for cempasuchil production is slightly more
complex. Production of the crop involves the creation of a small seed germination plot
and the eventual transfer of seedlings to larger growing plots. According to INEGI,
(1997), the total process of preparing germination plots and harvesting seedlings requires
a total of 12 irrigations — though not particularly heavy ones. To calculate the total water

requirement for germination plots, this study uses the recommended plot size of 25 x 25

84

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86

meters INEGI, (1997), and assumes that each irrigation might constitute the equivalent of
1.5 inches of rainfall. Thus, one-half of a three inch rainfall (762 cu. m./hectare) for a
625 sq. meter area would be 22.86 cu. m. per irrigation — or 274 cu. m. of water needed
for the establishment of cempasuchil seedlings.

Generally, five cempasuchil crops (cuttings) can be harvested from each plot per
season with one irrigation after each cutting. Thus, this study calculates the water
requirement for five growing plot irrigations. Unlike the punta de riego process which
involves one heavier irrigation (assumed equal to 3 inches), cempasuchil requires more
irrigations spaced evenly over the growing period. For that reason, it is assumed here
that each irrigation needn’t be as heavy as 3 inches per hectare. Instead a figure of 1.5
inches per application is used to calculate the water requirement for the growing plots.
Thus, the water requirement per application would be one-half of the 762 cu. m., or 381
cu. m. Five applications would require 1,905 cu. m. Thus, producing a annual
cempasuchil crop consisting of five cuttings would require 2,179 cu. m. of water per ha.
per year. To calculate the amount of land that could be dedicated to cempasuchil
production based on available water, the proj ect-generated water surplus for each pond
was divided by 2,179.

In several cases, the amount of land actually available for production (owned by
the pond owner) near each pond is less than what could be irrigated based on the amount
of available water. In these cases, crop production calculations were based on the
maximum amount of available land. Table 35 (facing page) presents the calculation of
the production land bases for each crop and each pond based on proj ect-generated water

surpluses.

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4.21 Calculation of Production Values (i.e. Project Income)

The following yield rates were selected as best predictors of crop yields under
project conditions, and were used to calculate market values for crop surpluses.

Rain-fed Corn = 2 tons per hectare (per local farmers and Eduardo Garcia, 2000)

Punta de Riego Corn = 3.6 tons per hectare (per local farmers and Eduardo

Garcia, 2000)

Cempasuchil = 16 tons per hectare (Eduardo Garcia, 2000).
Market values for crops were calculated based on market price information obtained
during the March 1999 visit to Querétaro where:

Corn = $1,400 Pesos/ton

Cempasuchil = $1,300 Pesos/ton

Tables 36-39 (facing page) show the calculation of market values for corn and
cempasuchil crops corresponding to each pond. These market values were then used to
represent total financial inflow for each year of the 15-year project budget.
4.22 Calculation of Crop Production Costs

Because corn production costs are specific to each locale and each particular
farmer’s production traditions, and no such cost data were available for the El Rincon
site, crop production budgets were prepared for rain-fed and punta de riego corn based on
information solicited during farmer interviews. Farmers provided estimates of time and
labor for each procedure, as well as the type and quantity of other inputs that were used to
calculate total production costs.

Because no local tradition exists for cempasuchil production, and general

production cost data were available for this study, such data were used in lieu of site-

89

Table 36

Calculation of Crop Surplus Values - Pond 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Prod. Base Yield. Mrkt. Price Prod. Value
Crop l-la. Tonsil-la. Pesos Pesos
Rain-Fed Corn 1.0 2.0 $1,400 $2,800
P. de Riggo Com 1.0 3.6 $1,400 $5,040
Cempasuchil 1.0 16.0 $1,300 $20,800
Table 37 Calculation of Crop 8mm Values - Pond 2
Prod. Base Yield. Mrkt. Price Prod. Value
Crop l-la. TonsIHa. Pesos Pesos
Rain-Fed Com 1.5 2.0 $1.400 $4.200
‘ P. de Rigo Com 1.5 3.6 $1,400 $7,560
Cempasuchil 0.6 16.0 $1,300 $15,808
Table 38 Calculation of Crop Surplus Values - Pond 3
Prod. Base Yield. Mrkt. Price Prod. Value
Crop l-la. TonsIHa. Pesos Pesos
Rain-Fed Com 4.5 2.0 $1,400 $12,600
P. de Riego Com 4.5 3.6 $1,400 $22,680
Cempasuchil 3.7 16.0 $1,300 $76,336
Table 30 Calculation of Crop Sumlus Values - Pond 4
Prod. Base Yield. Mrkt. Price Prod. Value
Crop Ha. Tons/Ha. Pesos Pesos
Rain-Fed Com 2.3 2.0 $1,400 $6,384
. P. de Riego Com 2.3 3.6 $1,400 $11,491
Cempasuchil 0.8 16.0 $1,300 $16,640

 

 

 

90

 

specific production budgets. Using these cost data assumes that they offer the best
prediction of actual costs for cempasuchil production in E1 Rincon. A list of the
recommended cultivation procedures for cempasuchil is provided in Appendix C.

Budgets for rain-fed corn were prepared for each pond and then adjusted to
account for any additional procedures necessary for the production of punta de riego
corn. Such adjustments were made under the advisement of the local extensionist
Eduardo Garcia (1999). All labor was valued at $40 Pesos per day (the reported rural
daily wage rate). Values for inputs such as fertilizers, pesticides, and herbicides were
calculated using price information procured from local agricultural supply stores in the
city of Amealco (where most inputs are purchased).

Values for farm equipment were calculated based on the following locally

procured price data and depreciation schedules:

 

I_tg_n_1_ Cost Depreciation Schedule
Plow/Planter $2,000 10 years
Rake $900 10 years
Backpack Sprayer $503 5 years
Horse $10,000 20 years

Note: The plow/planter implement is used for plowing, ridging, planting, and
weeding. The rake is used for both raking and leveling.

The value of equipment portioned to the project land base was calculated by
dividing the cost of the equipment by its estimated life span in years as well as the
number of hectares under production for each farmer (i.e. total land over which
implement is used annually). This quantity was then multiplied by the production base in
hectares for rain-fed and punta de riego corn (see Table 35). Tables 40-47 (facing pages)

show the calculation of equipment depreciation for each of the four ponds. Equipment

91

Table 40 Equipment Depreciation - Rain-Fed Corn - Pond 1

Cost Lifetime Land Base Prod. Base Cost/Use
Pesos

Rake 2 1
2 1

 

" Plow used for 2 weedings only ’Sprayer used for insect. 8. herb. Appl.

Table 41 Equipment Depreciation - Rain-Fed Corn - Pond 2

Cost Lifetime Land Base Prod. Base CostIUse

Rake 1 3 1 .5
5 3 1

 

*Plowusedforsoilprep.82medir'Sprayerusedforlnseot.&lierb.Appl.

Table 42 Equipment Depreciation - Rain-Fed Corn - Pond 3

Cost Lifetime Land Base

Rake . 4
2 4.5

 

" Plow used for 2 weedings only “Sprayer used for insect. 8 herb. Appl.

Table 43 Equipment Depreciation - Rain-Fed Corn - Pond 4

Cost Lifetime Land Base Prod.

Rake 7 2.28
7 2.28

 

*PlowusedforZweedingsonly 'Spmyerusedforinseot.&herb.Appl.

92

Table 44 Equipment Depreciation - Punta de Riego Corn - Pond 1

Cost Lifetime Land Base Prod. Base Cost/Use
Pesos

Rake 1O 5 1
5 2 1 10

 

' Plow used for 2 weedings only *Sprayer used for insect. 8. herb. Appl.

Table“ EquipmentDepreclatlon-PuntadeRiegoCorn-Pondz

Cost Lifetime Land Base Base CostIUse
Pesos

Rake 1 1
5 3 1

 

‘leusedforsoilprep.82weedir'Sprayerusedforinsect.&herb.Appl.

Table“ EquipmentDepreciation-PunhdeRiegoCom-Ponds

Cost thetimeLandBase Base

Rake 4
4

 

‘PlowusedforZweedingsonly ‘Sprayerusedforinsect.&herb.

Table47 EquipmentDepreciation-PuntadeRiegoCorn-Pond4

Cost Lifetime Land BIS. CostIUse

 

for2weedinqsonly 'Sprayerusedforinsect.&herb.Appl.

93

values were then included in the calculation of production costs for both rain fed and
punta de riego corn. See Tables 48-55 (facing pages). Note: The budgets reflect some
variance in task-specific costs due to differences in reported time/labor requirements for
same tasks.

The calculation of cempasuchil production costs for each pond were made using
data taken from the INEGI (1997) publication. According to INEGI (1997), annual
production costs for cempasuchil range between $9,900 and $10,500 Pesos per ha. Thus,
this study uses the average of that range, or a per hectare cost of $10,200 P. This rate per

hectare figure yields the following totals for production costs.

 

Pond Prod. Base (ha.) Cempasuchil Prod. Cost 1P)
1 1 $10,200

2 .76 $7,752

3 3.67 $37,434

4 .80 $8,160

The production costs calculated for this study were subsequently used as
constants for every year of a 15-year project budget (the duration being a function of liner
life span — see Appendix A). By treating production costs as constants, it is assumed that
once changed to reflect the use of surplus water, production techniques will not change
significantly over a 15-year project cycle.

4.23 Calculation of Geomembrane Installation Costs
Total installation costs reflect three major components:
0 Site Preparation (one-time, local labor)

0 Liner Installation (one-time, professional contractor)

o Liner Maintenance (on-going, local labor)

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102

This portion of the installation process entails all tasks necessary to take the ponds
from their current state and make them ready for the placement of liner material by
professional contractors. It is estimated (by this author) that proper preparation would
include the following procedures, which could be performed by local laborers and
grading contractors:

1.) Re-shaping of the ponds, making them deeper with less exposed surface area
(assuming no net change in volume), by excavating soil from the pond floor and
reducing total diameter].

2.) Grading and compacting pond floors and wall surfaces (to prevent shifting and
settling)

3.) Smoothing and clearing all surfaces of debris potentially damaging to an installed
geomembrane (rocks, sticks, roots, and other foreign objects)

4.) Cleaning and re-shaping pond intake channels and installing anti-sediment curtains
(dams of piled rocks or branches) to reduce the washing of soil sediment into
ponds.

It is estimated that steps one and two would require the use of a contracted
bulldozer ($650 P/hr.), whereas step three would require use of a smaller row crop tractor
($300 P./hr.) in conjunction with disk, harrow, and roller implements. Cost estimates for
these procedures were based on local contractor rates and rough estimates (by this author)
of the time necessary to complete each task. All human labor was valued at the local

rural wage rate of $40 Pesos per day. Tables 56-59 (facing page) show the calculation of

 

7 Care would need to be taken to not excavate the pond floor lower than the level of the fields down-grade
to be irrigated.

103

Table 56 Pond Preparation Costs in Pesos - Pond 1

Pond Size - 2,903 sq. m.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Procedure Labor/Equip. Rate/Hr. No. Hrs. Materials Tot. Cost
Re-Shape Pond Bulldozer $650.00 8 $5,200.00
Grade 8. Compact Bulldozer $650.00 4 $2,600.00
Surface Grade Tractor/Disk $300.00 2 $600.00
Smooth/Roll Tractor/Roller $300.00 2 $600.00
Clear Debris Human $5.00 4 $20.00
ln-Take Channels Human $5.00 16 $80.00
Constr. Filter Dams Human $5.00 24 $120.00
Fences Human $5.00 40 $ 500.00 $700.00
Total $9,920.00
TableG'I Pond Preparation CoetelnPeeoe-Pondz Pond Size- 1,979 sq. m.
Procedure Labor/Equip. Rate/Hr. No. Hrs. Materials Tot. Cost
*Re-Shape Pond Bulldozer $650.00 8 $5,200.00
Grade & Compact Bulldozer $650.00 3 $1,950.00
Surface Grade Tractor/Disk $300.00 2 $600.00
Smooth/Roll Tractor/Roller $300.00 2 $600.00
Clear Debris Human $5.00 4 $20.00
In-Take Channels Human $5.00 16 $80.00
Constr. Filter Dams Human $5.00 24 $120.00
Fences Human $5.00 40 $ 500.00 $700.00
‘includes replacement of berm section Total $9,270.00

Table“ PondPreperafionCoeteinPeeoe-Ponds

Pond Size - 9,125 sq. m.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Procedure Labor/Equip. Retell-1r. No. Hrs. Mehriele Tot. Cost
Re-Shape Pond Bulldozer $650.00 16 $10,400.00
Grade & Compact Bulldozer $650.00 6 $5,200.00
Surface Grade Tractor/Disk $300.00 4 $1,200.00
Smooth/Roll Tractor/Roller $300.00 4 $1 ,200.00
Clear Debris Human $5.00 6 $40.00
ln-Take Channels Human $5.00 16 $80.00
Constr. Filter Dams Human $5.00 24 $120.00
Fences Human $5.00 60 $1,000.00 $1,400.00
Total $19,640.00
TableflPondPrependonCoeteinPeeoe-Pond4 PondSlze-2,2543q.m.
Procedure Labor/Equip. Rate/Hr. No. Hrs. Materials Tot. Cost
Re-Shape Pond Bulldozer $650.00 6 $5,200.00
Grade 6 Compact Bulldozer $650.00 4 $2,600.00
Surface Grade Tractor/Disk $300.00 2 $600.00
Smooth/Roll Tractor/Roller $300.00 2 $600.00
Clear Debris Human $5.00 4 $20.00
ln-Take Channels Human $5.00 16 $80.00
Constr. Filler Dams Human $5.00 24 $120.00
Fences Human $5.00 40 $ 500.00 $700.00
Total $9,920.00

104

 

 

 

estimated site preparation costs for all four ponds. Site preparation costs were used in the
project budgets as one-time expenditures.
4.24 Liner Installation Costs

Projected costs for liner installation were calculated using price quotations
procured from several geomembrane contractors both in the US. and Mexico. The
material selected for cost calculations for this study is 20 mil PVC (.5 mil thickness).
This material and grade was selected based on recommendations made in the Koemer
text (see Appendix A) as well as information provided by geomembrane distributors.
The final price quotation selected for use in this study ($100 P. per square meter) was
offered by the Soluciones Ambientales (Environmental Solutions) firm in Mexico City
and includes the cost of material, transport to site, deployment, and seaming of material,
as well as per diem allowances for installation workers. This quotation was selected
because it was the only cost quotation received that offered a “final cost”, whereas other
quotations excluded import and in-country freight costs, or the cost of actual installation.
Thus, to avoid understating potentially hidden costs, the Soluciones Ambientales quote
was selected to represent actual costs for professionally installing liners in this site.

Table 60 (below) shows the final installation cost for each pond.

 

Table 60 Liner Installation Costs in Pesos
Pond No. Surface Area sq. m. Installation Cost (Pesos)
1 2,903 $ 290,300
2 1,979 $ 197,900
3 9,125 $ 912,500
4 2,254 $ 225,400

105

4.25 Liner Maintenance Costs
Projected costs for annual liner maintenance were calculated using estimates of the
number of days per month that farmers may have to dedicate to properly caring for liners
and ponds. Such maintenance might include:

o Patching punctured or torn geomembranes

o Removing debris from pond areas and water entrance channels

0 Cleaning ponds when empty

0 Repairing filter dams and fences

o Replacing soil cover on side slopes

It is estimated that the fore-mentioned activities might require one half-day per
month or 6 days of labor per year for general maintenance, plus one day per year for a
more thorough cleaning of the pond, for a total of 7 days per year. Two days per year
were added to the work requirement for pond number three because of its larger size
(9,125 sq. m.) Maintenance labor costs were calculated based on the $40 Peso per day
rural wage. Also included in the annual maintenance costs is one gallon of patching
adhesive at a cost of $45. Total annual maintenance costs for each pond are presented in
Table 61 (below). Maintenance costs were treated as annual expenditures for all 15 years

of the project budget.

Table 61 Annual Liner Maintenance Costs

 

Materials = 1/2 gallon liner adhesive per year

106

4.26 Calculation of Project Budgets

Three kinds of production budgets were prepared for each of the four ponds: rain-
fed corn, punta de riego corn, and cempasuchil. The budgets use project income
(inflows) and expenditures (outflows) to calculate a “net benefit before financing”, or
difference between project income and expenditures (i.e. annual net income). Future
income is discounted (stated in present terms) at a rate of 10% (or the estimated
opportunity cost of capital). The sum of the discounted net income stream (1 S-year)
yields the net present value (NPV) of the project — or its worth stated in today’s terms.
Benefit-cost ratios were calculated for each project scenario by dividing total discounted
benefits by total discounted expenditures. Project budgets are presented in Tables 62 —
73 on the facing pages. Results of the benefit-cost calculations are presented in Chapter 5

(Results).

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119

Chapter 5: Results

Tables 74 and 75 below present the results of the net present value and benefit-

cost ratio calculations performed for this study.

Table 74 Net Present Values for Project Scenarios
in Pesos

 

Table 75 Benefit-Cost Ratios for Project Scenarios

 

The results show a negative return on investment (negative NPV’s and Benefit-
Cost Ratios) for all project cases except the production of rain-fed corn at pond no. 2.
5.1 Without-Project Results (Rain-fed Corn)

Results of the benefit-cost calculations indicate that when the value of human
labor is included as a production cost, rain-fed corn production yields a negative return
on investment (with the exception of pond no. 2). Pond No. 2 earns a positive return of
$1.06 P., whereas ponds 1,3, and 4 earn negative returns of $.87, $.87, and $.52 on the

Peso respectively. NPV’s for rain-fed corn range from - $43,957 to $ 1,745.

120

5.2 With-Project Results (Punta de Riego Corn and Cempasuchil)

Results of the benefit-cost calculations for corn and cempasuchil production
indicate a negative return on investment for all cases. Benefit-cost ratios for punta de
riego production range from .13 to .18 (or a $.13 to $.18 centavo return on each Peso
invested). NPV’s for punta de riego range from - $168,679 P. to - $ 799,526 P.

Results for cempasuchil production indicate slightly better returns on investment
(however, still negative) ranging from $.44 to $.51 centavos on the Peso. Net present

values for cempasuchil production scenarios range from - $132,885 to - $560,862.

121

Chapter 6: Conclusions and Recommendations

6.1 Conclusions

Based on the results of the benefit-cost calculations performed in this analysis, this
study concludes that a.) for the ponds studied, and b.) for the assumptions and conditions
described:

1.) Installation of the specified geoemembranes as pond liners is not a cost-effective
means of increasing agricultural production for punta de riego corn or
cempasuchil, and:

2.) Using liners under the given conditions would not be cost-effective even allowing for
a 50% margin of error in the calculation of project-generated water surplus, yield
increases, or market prices.

3.) Due to the level of disparity between project-generated production increases and
investment costs, geomembranes appear initially not to be a financially
appropriate (cost-effective) tool for increasing agricultural production in general,
unless a much higher-yielding and market value crop or production system can be
found, however:

4.) Geomembranes should not be fully discounted as a potential water management tool
for the site without further exploration of alternative agricultural production
systems (crops and animals) and alternative uses in industry or supply to the city
of Querétaro.

The results of the NPV and Benefit-Cost Ratio calculations in the with-project

cases indicate that geomembranes are not a cost-effective investment for the production

122

of corn and cempasuchil for the four ponds studied. The risk of price or crop failure not
withstanding, the project-generated increases in crop production are not sufficient to
recuperate investment and production costs. Even in the case of cempasuchil, which
provides the greatest increase in production value, project income is only 44-51% of what
is required to break even at the end of a 15-year cycle. In other words, even if the price
of cempasuchil doubled, projects relying on cempasuchil production would just break
even at the lS-year mark provided that no failure occurred in crop yields or price. As
well, such levels of income would be insufficient to account for liner depreciation and
replacement costs. This great disparity between project income and expenditure suggests
that generating production values sufficient to service debt will be extremely difficult,
even in optimum conditions. Thus, based on these initial results, it appears that lining
ponds with geomembranes may not be financially feasible in any production scenario.
Again, more studies should be conducted before final conclusions are made.

The results of the study also indicate that when the value of human labor is
included as a production cost, growing rain-fed indigenous corn varieties is in most cases,
not cost-effective (the exception being pond no. 2). If the farms selected for study are
representative of the site, (which is not established) it appears that a certain percentage of
farmers may be producing rain-fed corn at a net loss when the value of their own labor is
considered. It would seem that given the percentage of residents seeking off-farm
income (both in Mexico and the US), seasonal com production is a subsidized activity.
This phenomena begs for further investigation into the perceived benefits (i.e. value) of
growing and storing/securing one’s own corn and maintaining a connection to food

production. If, from a purely financial perspective, farmers are being under-compensated

123

for their efforts, they might be better served to invest their efforts elsewhere. This
finding may help explain the high rates of economically-forced emigration from the site.
6.2 Project Recommendations

Based on the results obtained in this study, it is recommended that no investment
in pond liners occur in the El Rincon case without further study unless such investment
were to occur on a trial basis with the support of outside institutions, whereby any
financial burden/risk to participating farmers would be eliminated, or at least minimized.

Secondly, before any final conclusions are made regarding the financial feasibility
of geomembranes as water management tools in local agriculture, it is recommended that
a number of further studies be conducted addressing both their cost-effectiveness and
overall feasibility.

6.3 Summary (Assumptions/Limitations of the Study)

Due in no small part to severe limitations in the availability of data pertinent to
the research question, as well as the number of resulting assumptions, the conclusions of
this study are not 100% conclusive. First, the study is quite limited in scope in that it is
makes calculations for only four ponds in only one of thousands of agricultural
communities in the region. Therefore, apart from any data considerations, the results of
this study may or may not be generalizeable to the larger community and region. As
such, the study should be regarded as merely a beginning point for addressing pond water
conservation methods and agricultural water management in regional agriculture.

Secondly, the study is limited in that it addresses two crops (punta de riego corn
and cempasuchil), that are either not currently grown in the site (cempasuchil), or for

which no yield or production cost data exist apart from that which is anecdotal. Thus,

124

final conclusions regarding the use of liners in the production of corn or cempasuchil
should not be made without integrating stronger data into calculations.

Thirdly, because the hydrolocial phenomena of the site are largely unstudied, it
cannot be established conclusively that sufficient runoff can be effectively and
consistently captured and stored to generate necessary levels of production. Because no
local data is available for rainfall or sources of pond water accumulation and loss (runoff,
evaporation, infiltration, animal consumption, and use), calculation of project-generated
water surplus is made extremely difficult, making subsequent benefit-cost assertions
necessarily inconclusive. As well, the potential for high variability in rainfall trends
makes historical data less than a perfect predictor of the future.

Fourth, the modeling used to quantify the project-generated water surplus, apart
from relying on limited data, is in itself quite simplistic. This simplicity, while an asset
for capitalizing on limited data, necessitates using conclusions as guideposts rather than
as final and comprehensive. In short, better hydrological data should be collected and
analyzed before final conclusions are made about the hydrologic feasibility of the project
proposal.

The assumptions and data constrictions described here necessitate that the
conclusions of this study be limited to this study with the said conditions, and not be
generalized to all cases. As well, the conclusions made here are best used as an initial
indication as to the financial feasibility of liners, but more importantly as a means of
highlighting variables most critical to the research question. While the conclusions of the
study are limited, the disparity between income and expenditure evidenced in the

calculations do help illuminate the challenge and critical variables inherent in finding an

125

agricultural production scenario under which lining ponds with geomembranes would be

warranted financially - or alternatively, finding a water conservation tool that is

appropriate to local agricultural production systems and levels of income.

Other assumptions/limitations of this study relate to the following:

0 Are the selected study ponds representative of the larger population of ponds in the
site?

0 Lack of like-case information in literature that can be brought to bear in El Rincon

0 Poor spatial/temporal representation of rainfall data

0 Simplistic model (SCS) for calculating runoff relying on estimations of soil conditions

0 Estimation of pond shape used to calculate size and capacity

0 Would on-going sedimentation create added costs, affect storage (and loss), or
eliminate the use of ponds alltogether.

0 Use of temperature/surface area coefficient to calculate evaporation loss based on an
estimation of seasonal changes in pond volume

0 Estimation of animal consumption

0 Model for calculation of infiltration based on anecdotal evidence (when ponds go dry)
and the estimation used to calculate evaporation

0 Use of a 21-year average to calculate project-generated water surplus, and subsequent
crop production per ha.

0 Use of estimation of water requirement for punta de riego application

0 Estimation of water requirement for cempasuchil production

0 Corn yields calculated based on anecdotal information

o Cempasuchil yields/costs based on outside data

126

o Estirnations concerning nature, quantity, and cost of work necessary to prepare ponds
for installation of liner material
0 Estimation of liner maintenance costs

6.4 Recommendations for Further Study:

Before any action or decision is made regarding geomembrane use in El Rincon, a
number of other studies should be conducted. Such studies should include:
1.) More localized and in-depth studies of rainfall:
0 Collect rainfall data in-site, create an historical picture of precipitation
0 Compare local data to regional data
0 Calculate runoff rates
0 Collect evaporation pan data
0 Calculate evaporation rates
0 Determine the probability of drought

2.) Studies of pond water accumulation and loss

0 Measure changes in pond water levels throughout seasons and between years
and compare to rainfall- runoff/evaporation rates

0 Determine annual probability of ponds filling with runoff rain water

0 Measure pond levels before and after irrigation application to determine

application rates/requirements

0 Collect data on the numbers of animals consuming from ponds and
months/frequency of consumption

3-) Corn production studies

0 Collect annual yield data (rain-fed and punta de riego)

127

0 Compare hybrid varieties with indigenous varieties for like conditions
0 Compare corn yields to rainfall for both punta de riego and rain-fed corn
0 Determine the probability of corn crop failure
0 Collect corn market price data and determine monthly/annual fluctuations and
probability of failure
0 Explore alternative markets for corn
4.) Studies of alternative crops, integrated production systems, and their markets
0 Conduct trials of cempasuchil production (or other crops) and/or collect data for
similar sites
0 Look at the feasibility of creating integrated systems of crop and animal
production
0 Study the feasibility of fruit/vegetable production
0 Determine barriers to change in agricultural production
5.) Studies of geomembranes
0 Explore alternative grades, materials, sources of purchase, and price
0 Explore alternatives to geomembranes as liners
0 Study geomembrane durability/life-span in-site
6.) Study institutional context or levels of support (including development agencies
potentially willing to fund trial)
0 Access to equipment, financing, training, information
0 Subsidies
7.) Debt Service

0 Determine credit interest rates

128

0 Determine levels of financial risk
0 Determine the immediacy/distribution of benefits through time
0 Determine re-investment costs for liners
8.) Studies of potential effects on the environmental and natural resource systems
0 Changes in regional hydrology
o Re-charge of acquifers
o Erosion
o Salinization of crop land
9.) Studies of social/cultural/political variables
0 Levels of farmer interest and concern, and prioritization of goals
0 Levels of cooperation in cases of joint investment
10.) Study alternative sources/uses of water
0 Wells and dams
0 Agricultural vs. industrial use
0 Market for sale of water to industry or municipalities?
0 Compensation to farmers for non-use of water in order to help re-charge
Querétaro city aquifers?
0 Removal of ponds altogether
11.) Explore other options for off-farm income (or land uses — e.g. recreation)

6.5 Final Thoughts

While it appears initially that geomembranes may not represent a cost-effective
means of increasing the availability of water for agricultural production in El Rincén, the

results of this study should be used as a point of entry for more in-depth studies that

129

address the financial and overall feasibility of geomembranes. Subsequent studies should
attempt to gather and incorporate data that is more accurate so as to develop a better
picture of local hydrology and agricultural production, allowing potential tools to be
measured against a more concrete backdrop of conditions and variables. This study does
provide a starting point for helping local farmers make decisions regarding options for
water management on their own farms and helps contribute to a larger discussion of the
problem of increasing water availability for agricultural production in zones similar to
that of Querétaro.

The study provides initial insight into the financial feasibility of the liner technique
for farmers in the E1 Rincon case, but also contributes case study data about liner
feasibility to a larger body of information about farm-scale water storage systems as a
means for increasing agricultural production in semi-arid regions. The results of this and
subsequent studies can help farmers and development professionals make informed

decisions about investment in this water management option.

130

Appendix A: Geomembrane Information Continued

The following information expands on that presented in Chapter 2 and is
abstracted from Koemer Designing with Geosynthetics, 3rd. ed., 1998.
1.) Considerations for Liner Selection: Geomembrane Properties

Depending on their material composition and construction, geomembranes exhibit
a broad range of performance properties. It is these properties along with performance
testing and standards that inform project design. Koemer (1998) organizes geomembrane
properties as follows:

0 Physical Properties
Thickness
Density
Mass per Unit Area (weight)
Water Vapor Transmission
Solvent Vapor Transmission
0 Mechanical Properties
Tensile Behavior
Seam Behavior
Tear Resistance
Impact Resistance
Puncture Resistance
Geomembrane Friction
Geomembrane Anchorage
Stress Cracking
0 Chemical Properties
Swelling Resistance
Chemical Resistance
Ozone Resistance
UV Light Resistance
0 Biological Properties
Resistance to Animals
Resistance to Fungi
Resistance to Bacteria
0 Thermal Properties
Warm Temperature Behavior
Cold Temperature Behavior
Coefficient of Thermal Expansion

131

0 Identification Properties
Therrnogravimetric Analysis (TGA)
Differential Scanning Calorimetry (DSC)
Therrnomechanical Analysis (TMA)
Dynamic Mechanical Analysis (DMA)
Melt Index
Molecular Weight Determination
Seven of these properties seem especially pertinent to selection of a liner material
for El Rincén and are expanded upon here.
2.) Thickness
Any membrane installed in El Rincon is likely to undergo a number of
environmental stressors. Because the strength of liners relates in-part to their thickness,
which in-tum affects project costs, this aspect is important to a benefit-cost analysis. To
help protect against damage that might be caused during transport, handling, and
installation (when liners are most susceptible to damage), Koemer (1998) recommends
using a liner of 20 mils (.5 mm) regardless of project goals. For irrigation canal lining in
Mexico, Gonzalez- Ruiz also recommends a liner thickness of 20 mils, which he
indicates has been shown to last up to 30 years in trials. Based on these
recommendations, a 20 mil. Grade liner was selected for computing the cost portions of
this study (see 4.26 Liner Installation Costs).
3.) Water vapor transmission
Though liners are not 100% impermeable and some sweating of contained liquids
through the membrane material does occur, the rates are low enough in the context of this
hypothetical project goal that this is not a major consideration for liner selection. Liners

are assigned a vapor transmission number depending on thickness (typical values of

impenneability range from 10-10 to 10’13 ferinute) (Koemer, 1998). For example, 20

132

mil PVC allows the permeation of 2.9 grams per square meter per day (Koemer, 1998).
The loss per day from a 50x50 m. pond would be 1.9 gallons per day, or about 2.6 cubic
meters per year. For this study, such a quantity will be considered negligible. In short,
any liner of the 20 mil suggested thickness should provide a more than adequate moisture
barrier for this project.
4.) Tensile behavior

Tensile behavior is an important consideration for large (deep) reservoir projects
where the weight of the installed liner on basin side slopes exerts a tremendous
downward pull against its own composition. Because the side slopes of the ponds in El
Rincon are shallow (1-2 meters), tensile strength should not be an important factor here.
5.) Seam Behavior

Seam behavior per se (i.e. the performance of membrane seams under certain
kinds of stressors) is likely not as important a consideration as the kind of geomembrane
and seam selected for the project. Any of the seaming techniques is likely to offer a seal
sufficient to the goal of drastically reducing seepage loss from the catchment ponds.
There is, however, reason to believe that if farmers in El Rincon are to be able to
successfully maintain and repair liner systems over an extended period of time, they must
have easy access to the tools and resources necessary to patch and/or re-seam the
membrane material. Searning techniques involving expensive or locally unavailable
equipment or materials (i.e. thermal methods) may preclude this ability.
6.) Resistance to Tears, Impact, and Puncture

Because of the project conditions at El Rincon, liner resistance to damage is an

especially important consideration. Geomembranes may be torn by equipment or wind

133

uplift. The impact of falling objects can pierce membranes, causing leaks and firrther
tearing. Geomembranes may also be easily punctured by rocks, sticks, or other debris
lying on the soil sub-grade (Koemer, 1998).

The tear resistance of thin non-reinforced membranes is quite low — from 4 to 30
pounds (Koemer, 1998). Tear resistance values for geomembranes reinforced with fabric
scrims are somewhat better — 20-100 pounds. Typical values for puncture resistance are
10-100 pounds for thin nonreinforced membranes, and 50 — 500 pounds for reinforced
membranes. Generally, the thicker the membrane is, the more resistant it is to tearing,
puncture, and impact. Reinforced membranes exhibit higher resistance to damage than
nonreinforced, and underlaying geomembranes with a geotextile greatly increases its
resistance to all of these. If carefully handled during installation, a non-reinforced
geomembrane covered with adequate soil should perform adequately for the application
at hand. Again, following the installation guidelines can substantially reduce the risk of
liner damage.

7.) Ultra-violet resistance

Long-term exposure to ultra-violet light is known to cause degradation of exposed
polymeric materials (Koemer, 1998). Because liners installed in Central Mexico will
face high levels of sun exposure, this is an important consideration to membrane
selection. Different base materials perform very differently in response to UV ray
exposure - a range of resistance that Koemer terms “enormous”. For example, non-
reinforced PVC is more sensitive to ozone and ultra-violet light exposure, and thus must
be covered with soil to prevent embrittlement and cracking. Conversely, CPE and CSPE

show more resistance to ultraviolet degradation. Koemer (1998) indicates that the best

134

protection against ultra-violet degradation is covering liners with at least 12 inches of soil
— a recommendation integrated in the selection of liner for this analysis.
8.) Resistance to animals

Buried membranes are susceptible to animals burrowing through them, however,
the degree to which they are susceptible is not well known (Koemer, 1998). There are no
well established test procedures and the theoretical maxim holds that the thicker, harder,
and stronger membranes are, the less susceptible they are to this type of damage
(Koemer, 1998).

The likely greater potential for animal damage in El Rincon would be that caused
by horses or cattle walking on exposed liners in the pond area. Such damages can be
eliminated both by covering the material with soil and constructing a fence around the
perimeter of the ponds to keep animals out of the pond area. Both measures are included
in project costing.

9.) Liner Installation

Generally, membranes are manufactured by one firm and installed by another.
Proper installation is key to creating an effective liner system. While the specifics of
proper installation are project-specific, a few generalities apply.

Liners are susceptible to damage during transport, handling, and deployment.
Great care should be taken during these stages to ensure that the liner is not damaged.
Secondly, the surface area to be lined should be graded, compacted, smoothed, and
cleared of all debris that may exert stress or puncture the liner once placed. Koemer
(1998), recommends installing a geotextile underlayment beneath the geomembrane to

help absorb the stress of intruding debris or shifis in the sub-grade.

135

One of the major quality control aspects of liner installation is the seaming or
joining of membrane sheets. Because geomembranes are manufactured and transported
to project sites in sheets or rolls, they must be seamed together to form a single
continuous liner that fits the size and contour of the pond basin. Thus, the integrity of
any liner systems is only as good as the seams that hold its pieces together. Faulty seams
will usually result in water seepage through the liner system.

There are two types of seams — those made in the factory, and those made in the
field. Because factory seams are made in controlled environments, their quality is more
consistent. Because field seams are made under less controllable environmental
conditions, they represent the greater risk for seam failure. The quality of field seams
may be compromised by irregular preparation surfaces, dirt, temperature changes, air
pockets, or moisture.

Field seaming may be done with solvents, adhesives, hot air, hot knives or
wedges, and tapes. Solvents, used primarily with thermoplastic liners, actually dissolve
the membrane edges which are then joined together under pressure and allowed to re-
harden as a bonded surface. Contact adhesives can be used with most any of the
membrane types and cause the membranes to stick together without breakdown of the
polymer. Thermal methods such as hot air or hot knives/wedges can be used on
thermoplastic and semi-crystalline geomembranes. Heat is used to melt the membrane
edges into a semi-liquid state so they may be joined together under pressure and allowed
to cool and re-harden into a contact seam. Extrusion welding, used only with
polyethylene materials, involves using a ribbon of molten polymer between the surfaces

(which are also slightly melted by an electrode). Tapes and mechanical seams can be

136

used where 100% water-tight seals are not required. Single sided tape can be used over
the top of overlapping edges, or two sided tape can be used between the edges. Certain
kinds of clamps and sewing techniques can also be used.

Because the kind of membrane material selected has implications for the seaming
techniques used for installation and repair (i.e. equipment and costs), this is an important
consideration for a project environment like El Rincon where farmers have limited
financial resources and access to special equipment.

Once deployed and seamed, a geomembrane should be secured in place by
anchoring Grurying) its edges in an anchor trench excavated around the perimeter of the
basin. Koemer (1998), also recommends that the membrane material be covered with
soil to protect it from ultra-violet rays and other damage-causing agents. Another general
consideration for liner installation in a rural context such as El Rincon, is the construction
of a fence around the pond perimeter to keep out livestock that might otherwise tread on,

and damage the membrane material.

137

Appendix B: Site Description Continued

The following information expands on that presented in Chapter 3 and is taken
from the AUQ Report described in Chapter 1.
1.) Local Economics

Of 45 households interviewed by the AUQ team, there were 58 cases (27%)
reported of men who had worked or were currently working in the US. Men were said to
make their first trip between the ages of 15 and 18, and to work almost exclusively as
agricultural laborers, but in some cases as construction workers or store clerks as well.
The most common destinations are the states of California, Montana, Oregon,
Washington, and Georgia, and in some cases, families do not know where members have
gone. The duration of any one stay in the US. ranges between 4 months and 3 years.
At the time of the RRA, one family reported that 5 of its 15 members were working in the
US. There were also 5 reported cases of men who had legal documentation to live in the
US. for at least part of the year. According to the report, these men live in El Rincén
during the agricultural growing season (6-8 months), and spend the rest of the year
working in the US.

The report indicates that those who work in the US. are generally able to earn
higher wages ($3.50 - $10/hr. in 1996) which are sufficient for the purchase of extra

items such as land and farm equipment, and new or improved homes'.

 

' Many vehicles in the community have U.S. license plates.

138

2.) Economic Alternatives

Alternative sources of income within the community are seemingly few. The
majority of women make cross point napkins, carpets, and embroidery. According to the
report, however, these hand crafts are generally not viewed as opportunities for extra
income. Reportedly, few families sell these items for a minimal price and there is no
immediate market for their sale.

As one economic alternative, community members have expressed interest in the
development of a tourism or picnic area in the community to provide jobs and
recreational opportunities. The report states that El Rincon is already a popular site for
weekend day trippers. During the author’s March 1999 visit to El Rincon, work was
being completed on a small garment assembly factory within the ejido, which according
to several residents, will employ 2030 individuals from the community. To-date, the
more common alternative seems to be short or long-term migration to the US. in search
of employment (Purdy, 1999).

3.) Food

The AUQ team found that families in the ejido eat two to three meals per day,
consisting mostly of corn tortillas and beans. Meat consumption is low. The report
concludes that ejido members generally take advantage of locally available fruits and
vegetables, but that nutritional education would benefit the community’s overall nutrition
status — the report cites excessive consumption of soft drinks and junk food such as
cookies and chips.

Levels of fruit and vegetable consumption depend on season and climate. The

community is reportedly well suited for the production of apples, pears, figs, and

139

peaches, as well as vegetables such as greens, beets, pumpkins, string beans, and
mushrooms. To a small degree, people supplement their diets with foods taken from the
forest including prickly pears (“nopales”), greens, and edible mushrooms.

Whatever food consumed that is not grown or collected locally, is usually
purchased in the city of Amealco where there is some variety and prices are lower than
those offered in local stores. A few families, however, do buy food in the smaller local
stores within the ejido, where they sacrifice price and selection for the sake of
convenience.

The overall picture of food security is not made clear by the report. No mention
is made of cases of chronic hunger or malnutrition, though it is indicated that a free
breakfast is offered at school to those children who are on need-based scholarships.

4.) Health

Very little information is presented in terms of community health and health
resources. According to the report, only 30% of local families (interviewed) participate
in local vaccination and parasite treatment campaigns. Eight families reported that they
seek treatment/vaccinations one time per year, and 7 families reportedly seek such
treatment twice per year. This wide-spread failure to seek preventative medical treatment
is considered by the AUQ team to have a negative impact on community health,
especially with regard to children. The report also indicates a need for more recreation
activities for youth, the lack of which is associated with the clandestine sale of alcohol to

minors in the community.

140

5.) Education

Of the 45 households interviewed, the highest level of education reported is the
completion of secondary school. The community has facilities for kindergarten
(CONAFE), primary, and televised secondary school (lessons are televised to eliminate
the need for students to travel to other communities to receive a secondary education).
Twenty-nine adults reported having no formal education and the inability to read or write.
The report does not indicate if community members perceive any relationship between
education levels/resources and employment opportunities.
6.) Community Leadership, Perceptions, and Participation

Community leadership consists of a municipal delegate and an ejido
commissioner who may also represent ejido matters at the municipal level. Community
members may serve on committees — regardless if they are actual ejido members or
private land holders. One such committee deals exclusively with the procurement and
management of potable water service. As one project, this committee facilitated the
building of a new spring deposit and contributed labor and materials to its construction.
Local leadership has expressed concern over a lack of local employment opportunities,
high rates of emigration, low agricultural production due to drought and pests, and a lack
of governmental support in community development. Leaders feel that better community
organization is needed and identify the following initiatives as key to fostering cohesion
and participation.

0 The purchase of a Catepillar D8 tractor

0 Soil conservation measures

0 Reforestation measures

141

o The prevention of erosion gullies

The report indicates that community members exhibit an increasing lack of faith
in development programs due to past failures and decreasing production. Consequently,
people tend to include themselves, but not participate in projects until such time that
resource become available or the project appears to be successful. The AUQ team cites a
need for more careful project planning where short- and medium-term benefits are
demonstrated through pilot projects. Also cited is the need for better communication of
project goals to the entire community.

One project cited as successful in generating participation is Eduardo Garcia’s
involvement in creating farmer interest in treating soils with calcium carbonate through
proven results in pilot trials. By working with a few farmers and producing demonstrably
favorable results, Eduardo has developed increased interest in the technique.

7.) Forest Resources

The major problems identified with regard to forest resources are:

0 Deforestation

0 Over- Hunting

0 Forest pests

0 Excessive use of agri-chemicals

o Improper garbage disposal

The families of the ejido rely on the open-access forested areas primarily as
sources of firewood for cooking and heating their homes. While the AUQ study was
unable to determine the exact quantity of firewood consumed by families, it does indicate

that most families cook with a combination of butane gas and firewood (families prefer

certain foods cooked with wood).

142

Between 1984 and 1994, the community experimented with assigning quotas for
tree cutting, where each family was assigned a determined number of trees, which could
be cut for personal consumption. Between 1993 and 94, families were granted
permission to sell their allotted wood. During other years, it was designated for personal
use only. Since 1994 (2 years previous to the release of the AUQ report), there has been
no use of the forest. Community members express a desire for renewed access to the
forest and would like to learn how to select trees that may be pruned or cut for firewood.

Locals residents also hunt armadillo, rabbits, coyote, birds, and fish on a year-
round basis. According to the report, these animals present a very limited resource for
alternative food because of their diminishing numbers, reportedly the product of over-
hunting and overuse of chemicals in agricultural production. The hunting of predatory
animals, such as coyote has been increasing as the reduction of their natural food sources
has forced them to prey on domesticated fowl and rabbits around people’s homes.

The report states that the community recognizes the need for soil and forestry
conservation, but perceives itself as lacking the decision making and technical expertise
needed to design and implement conservation measures. As well, there exists a tendency
to view the government as ultimately responsible for providing solutions to the problem.
8.) Agricultural Alternatives

During the workshop portion of the rural diagnostic, community members
expressed interest in the following agricultural alternatives: the raising of rabbits, the
introduction of deer into the woods with permission to hunt them, the raising of dairy

cows, the raising of fish in ponds, the cultivation of mushrooms, family gardens, and the

143

creation of agro-micro-enterprises such as bottling jams and marmalades made from a
local fruit called tejocote. To-date, none of these have been tried.
During site visit interviews conducted as part of this study, several farmers expressed

interest in growing cempasuchil if the ponds could be improved to provide sufficient

water.

9.) Local Hydrology

Querétaro is divided into two hydrologic drainage regions. The larger known as
“El Panuco” drains into the Gulf of Mexico, and the smaller “Lerma-Chapala—Santiago”
drains into the Pacific (INEGI, 1997d). The majority of the Amealco Municipality,
including El Rincon, is situated in the E1 Panuco region, and thus all surface runoff from
the site drains toward the Gulf of Mexico (INEGI, 1997a).
El Rincén is part of the “El Aguacate” micro-watershed, located within the “Drenaje
Caracol” (Snail Drain) Sub-Watershed of the greater watershed known as “Rio
Moctezuma” (INEGI, 1997a). The ponds selected for study are adjacent to the “Los
Tules” and “El Aguacate” streams which drain into the “Paso de Vigas River”; that river

flows into the “River Las Zunigas”, and eventually into the “Constitution 1917 Dam”

(INEGI, 1996).

144

Appendix C: Introduction to Cempasuchil and its Production

According to INEGI (1997), cempasuchil, known locally as “flor de los muertos”,
(flower of the dead) is a traditional plant of pre-Colombian origin grown and used by the
Aztecs in religious ceremonies to honor the spirits of the deceased. The cempasuchil
flower is still used as an ornament in the celebration of Dia de Los Muertos, however, the
majority of modem-day cempasuchil production goes toward the manufacture of food
coloring and as an ingredient in poultry feeds (INEGI, 1997). The flower extract can be
used to enhance the yellow color of poultry carcasses and egg yolks. The plant is grown
either in the spring-summer or fall-winter seasons, and can produce as many as five crops
or cuttings (of the flower) per season, and as many as 16 metric tons per hectare (Garcia,
2000). Soils rich in clay produce the best crops with larger and more abundant flowers,
while light and sandy soils make the management of soil moisture and fertility more
difficult. Buyers in the Querétaro region include “Alcosa”, “Bioquimex” and “Piveg”.
The current market price is $1,300 Pesos per metric ton (wet).

According to INEGI (1997), cempasuchil production offers the following
advantages in comparison to other crops:

0 Better return on investment compared to crops of similar production cost

0 More secure market and price

0 Rapid recuperation of investment (lst cutting 3 months post-transplant)

0 Doesn’t deplete the soil as rapidly as other crops — allowing for 2 or 3 crops per
season, depending on the zone

0 Plant can be tilled back into soil for reincorporation of organic material

145

o Cempasuchil roots release a substance that helps keep soil free of certain
parasites

According to INEGI (1997), the production of cempasuchil includes the following

tasks:

Establishment of Seedlings:

0 Selection of nursery plot (25m x 25m) and soil preparation (should be pulverized -
devoid of all soil clumps)

o Disinfectant of soil (use 1 kg. Dazomet with 6 kg. Basamid per hectare) and
incorporate into soil

0 Three irrigations

0 Soil cultivation (wait 7 days to plant)

0 Fertilizer application (18-46-00) or 00-46-00) and incorporate

o Planting (.75 kg. seed/ha.)

0 Covering of seeds with uniform layer of animal manure mixed with sand and soil

0 Light irrigation every 3 days

0 Transplant to field plot after 20-25 days (at 12-15 cm height)

Field Plot Preparation:

0 Plowing/disking of soil to 30 cm. depth

0 Two rakings to eliminate all clumps

0 Cultivation of soil into ridges

o Fertilizer application (P-K-N)

146

o Transplant of seedlings (keeping roots moist during transplant)

0 Planting of seedlings on ridges @ 30 cm. spacing

0 First irrigation 4 days post-transplant with consecutive inigations every 15-20 days

0 Cultivation of weeds at 20, 40, and 60 days post-transplant

o Fertilizer application at 40 days post-transplant

0 Hand weeding if necessary

0 First harvest (cutting) when 80-90% of plot is in flowered state (usually 90-100 days
post- transplant)

0 Irrigate after each cutting

0 Cut every 12-15 days for 5 total cuttings

147

Appendix D: Rainfall Analysis

1.) Rainfall Data from Contributing Stations

Tables 76—79 (pages 164-166) show the rainfall data taken from each of the four
weather stations (Granja Carnation, Amealco I, SMT, and Las Palmillas) contributing to
the 21-year aggregated rainfall data. Tables 80-82 (pages 167-168) show the adjustment
factors used to adjust the data from the Amealco I, SMT, and Las Palrrrillas stations to
create the 21-year aggregated total (presented in Chapter 4).

Table 83 and Figure 5 (page 169) present the monthly averages of the aggregated
rainfall data where it is evident that May-September is the critical period for rainfall
capture, July consistently being the month of highest rainfall totals. The variability in
annual rainfall totals is evident in a between-year comparison for the aggregated data (see
Figure 6 page 170).

The yearly average for the 21-year aggregated data is 906.2 mm. — a figure that
contrasts somewhat with an average listed for Querétaro of 549.3 mm. for the period
1921-1995 (INEGI — Cuad. Est. Munic. 1998). Thus, it appears that the rainfall of the
study site is somewhat greater than that of the state as a whole.

Values for calculated rainfall excess are presented in Table 84 (page 171)

2.) Comparison of Monthly Runoff Totals to Pond Capacity

Tables 85-88 and Figures 7-10 (pages 172-175) show monthly runoff totals within
the four pond catchment zones for each of three kinds of runoff years: high, low, and
average. Not surprisingly, runoff directly reflects seasonal rainfall so that, just as July is

consistently the highest month of rainfall, so too is it the highest month of runoff, August

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the second highest, and September the third. For years of average runoff, there are four
months (June-Sept.) where the runoff generated within an individual month is greater
than pond capacity — this is true for all four ponds. Thus, in an average year, the runoff
of any month between June and September would be enough to fill the ponds.

Ironically, during the year of highest runoff (1 990-91), there were only three
months (July-Sept.) during which the runoff of a singular month was sufficient to fill the
ponds. Because extra rainfall is not necessarily distributed over time, the extra may be
lost due to pond overflow. For the year of lowest runoff accumulation (1972-73), July
was the singular month where runoff was sufficient to fill the ponds.

This picture of monthly runoff is reassuring as it indicates that, even without
considering the cumulative collection of runoff over several months, there are singular
months within any given year where enough runoff is generated to fill the study ponds.
This is true even for years of low rainfall/runoff. The implication is that, if a pond is
altered such that the stored water losses are eliminated, local rainfall is sufficient to
generate enough runoff flow to fill the ponds on an annual basis. The challenge then
becomes to reduce stored water loss from the ponds.

3.) Comparison of Yearly Runoff Totals to Pond Capacity

A look at annual runoff totals for the 1971-92 period (See Tables 89-92 facing
page) reinforces the conclusion that local runoff is sufficient to fill the four study ponds.
The runoff data indicate that for all 21 years, annual totals are more than sufficient to fill
the ponds. The following figures indicate the percentage of pond capacity generated in
runoff for an average year.

Pond 1 — Total annual runoff = 1,061% of pond capacity
Pond 2 — 841%

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Pond 3 -— 1,337%

Pond 4 — 1,367%
4.) Sensitivity of Runoff Calculations to Error

Before making a final conclusion that local runoff is sufficient to fill the study
ponds on an annual basis, it is worthwhile to examine the possibility of error in the
calculation of runoff (i.e. the case where actual runoff is less than calculated). To test
this possibility, annual runoff was reduced by 50% and compared to the pond capacities.
The data (See Tables 93-96 facing page) show that even if the runoff values calculated
for this study overstate actual runoff by 50%, annual runoff is still sufficient to fill the
ponds on an annual basis. Thus, the runoff calculations performed for this study allow
for a 50% margin of error, and it seems safe to conclude that the study ponds do fill with
water on a consistent basis.
5.) Evaporation Loss

Tables 97 & 98 (page 180) show the evaporation data taken from the Granja
Carnation and San Miguel Tilaxcalte stations. Table 99 (page 181) shows the adjustment
factors used to adjust the SMT data. Table 100 (also page] 81) shows the 21-year
aggregated evaporation data.
6.) Comparison of Stored Water Loss

Tables 101-112 (pages 182-184) present a comparison of the three sources of
stored water loss. The data show that during years of high, low, and average runoff,
infiltration is responsible for approximately 80-90% of annual stored water loss.
Evaporation is the next greatest source of loss with about 10-15% of total share. Animal

consumption loss is quite minimal with approximately 1-3% of the annual total. (Note:

163

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] Var ] 02-03 03-04 04-00 | 0000 00-07 07-00 00-00 00404 00-01 01-02 | 9
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166

Table 101
Distribution of Total Annual Stored Water Lose by Source - Pond 1

Average Runoff Year A
[Eurce [Cu MJYrJ % of Tot. ]
FEvaporation ] 1.855] 9.78%]

 

 

 

[Infiltration ] 16.693] 88.03%]

[finsumption] 416] 2.19%]
18.983

Table 102

Distribution ofTotalAnnualStoredWaterLoeebySomce-Pondf

H nest Runoff Year
Source TCu. MJYrDt of Tot]
[Evaporation L 1.855] 13.84%]

 

 

 

flnflnration | 11,129] 83.06%]
[Consumption] 416] 3.10%]

13,399
T8bh103

DietibuflonofTotalAnnualStoredWaterLoeebySouce-Pondl

Lowest Runoff Year A

[Source [Cu. MJYr.[% of Tot. I
[Evaporation ] 1.855] 13.64%]
[filtration ] 1 1.129] 83.06%]
[Consumption] 416] 3.10%]
7 13,3997 7

Table 104
Distribution of Total Annual Stored Waur Loss by Source - Pond 2

Am Runoff Year
[Source ]Cu. MJYr.] % of Tot]
[Evaporation [ 1,264] 9.87%]

 

 

 

 

Wltration ] 11,379] 88.65%]

[Consumption] 164] 1.26%]
12.807

Table 105

Dietrlbutlon of Total Annual Stored Wan L000 by Source - Pond 2

Runoff Year
Cu. . % of.
1 10.

    

Infiltration 1 1 15
1 1 .42%
1 1 .543

167

Table 106
Distribution of Total Annual Stored Water Loss by Source - Pond 2

Lowest Runoff Year

[Source [Cu. MJYr.] % of Tot.
[Evaporation ] 1.264] 16.31%
Mfinration [ 6,322] 81.57%

 

 

 

 

Ribnsumptionl 164] 2.11%
7.750
Table 107

DistributionofTotalAnnualStoredWahrLossbySouce-Ponds

Avera Runoff Year
[Source [Cu. MJYr.[% of Tot]
[Evaporation [ 5.830] 8.32%]

[I nflltration 1 64.130] 91 .4996]
[Consumption] 136] 0.19%]
70.096

 

 

Table 108
Distribution ofTotal Annual StoredWaber bySource-Pond 3

H hest Runoff Year A
Source [Cu. MJYr.[ % of Tot. [
@aporation [ 5.830] 8.32%]
mifimation J 64.131] 91.49%]
Eonsumption] 136] 0.19%]
7 70,0977

 

Table 109
Distribution of Total Annual Stored Water Loss by Source - Pond 3

Lowest Runoff Year

Source [Cu. MJYr.] % of Tot. [

[Eva&ration L 5.830] 14.24%]

Eflnration [ 34.960] 85.43%]

[Consumption] 136] 0.33%]
40,947

Table 1 10
Distribution of Total Annual Stored Water Loss by Source - Pond 4

Avera Runoff You
[Source [Cu. MJYr.[ % of Tat]

[Evaporation ] 1.440] 8.96%]
[Infiltration [ 14,401] 89.64%]
[Consumption [ 225] 1 .40%[

16,066 7

 

 

168

Table 111
Distribution of Total Annual Stored Water Loss by Source - Pond 4

H best Runoff Year

Source [Cu. MJYr.[ % of Tot. [

[Evaporation [ 1.440] 13.97%]

[Infiltration ] 8,641] 83.84% J

[Consumption L 225L 2.18%]
10.3067 7

 

Table 1 12
Distribution of Total Annual Stored Water Loss by Source - Pond 4

Lowest Runoff Year A A

[Source [Cu. MJYr.[ % of Tot. [

[Evaporation [ 1.440] 13.97%]

Mfiltration [ 6.641] 83.84% [

[Consumption] 25] 2.18%]
10,306

 

 

 

169

Because the quantities of loss presented here are annual totals, their sum is greater than
pond capacity for each respective pond). Thus, it appears that as the farmers have
indicated, infiltration is the primary source of stored water loss. For this reason, this

study will concentrate on the use of geomembranes to line ponds and not cover them.

170

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