Record January/February 1997 Volume 35, Number 1 JANUARY/FEBRUARY 1997 Volume 35, Number 1 Cover Photo: The SPACE Program data determined that a flat application profile resulted in dry donuts forming around each sprinkler with this new million-dollar irrigation system. An embarrassing situation can arise if the turf is still plagued with problems after a new irrigation system is installed. See page 1. Record 1 Irrigation Design, Rocket Science, and the SPACE Program Selecting sprinklers and determining the spacing is not rocket science. Not when using the SPACE program to model coverage and distribution. By Mike Huck 8 Checking Your Sand — Quality Control Begins at Home A quick check of sand with your own testing equipment can help avoid problems later. By James F. Moore 10 KTURF: A Pesticide and Nitrogen Leaching Model A computer model available on the Internet and World Wide Web helps turfgrass managers predict pesticide and nitrogen leaching. By Dr. Steve Starrett, Dr. Shelli Starrett, Judy Hill, and Greg Adams 13 Battling the Bermudagrass Blitz Several key practices can help you win the war against bermudagrass encroachment. By Chris Hartwiger 16 The Living Dead Dead trees offer habitat and sustenance to all living things. By Ron Dodson 17 Buyer... Beware Products without active ingredients may not be active! By Stanley J. Zontek 18 Green Section Education Conference: Teaching Young Dogs Old Tricks 19 1997 Green Section National & Regional Conferences The red-headed woodpecker is a primary cavity-nesting species. See page 16. 20 The Proof of a Golfer By Edgar Guest 22 Turf Twisters All too often, problems with sprinkler coverage come to light when the turf is faced with drought conditions. Irrigation Design, Rocket Science, and the SPACE Program Selecting sprinklers and determining the spacing is not rocket science. Not when using the SPACE program to model coverage and distribution. by MIKE HUCK IT DOESN’T TAKE a rocket scientist to determine that the effectiveness and efficiency of an irrigation system is more greatly influenced by the distribution uniformity of comple­ menting sprinklers than the high-tech computer controlling the system. In this era of space-age technology, count­ less dollars and hours are spent evalu­ ating and installing state-of-the-art irrigation control systems that turn water off and on with split-second accuracy. At the same time, however, very little time or effort is invested in evaluating the actual performance of sprinklers, spacings, and nozzle com­ binations. All too often problems with sprinkler coverage are not identified until it is too late, after they are buried in the field. With the price of new irrigation systems exceeding a million dollars, a very frustrating and embar­ rassing situation can arise if after a new irrigation system is installed the turf is still plagued with wet spots, dry spots, or, even worse yet, donuts. Sprinkler performance has long been evaluated with statistical calculations such as Christiansen’s Coefficient of Uniformity (CU) and Distribution Uniformity (DU). Both CU and DU are estimates of complementing sprinklers’ application uniformity that were origi­ nally developed to evaluate agricultural irrigation. The ideal CU or DU is 100%; however, this is unattainable because even rainfall does not fall with 100% uniformity. A closer examination of CU and DU reveals why they alone do not guarantee success with regard to evalu­ ating turfgrass irrigation. This is due to their methods of evaluating the under- and over-watered areas. CU: Christiansen’s Coefficient of Uniformity on an average of the entire area. It treats over-watered and under-watered areas in the same way. Since it is an average, it offers no indication of how poor the coverage may be in localized areas. CU = 100 (1-D/M) D = (1/N) 3 *Xi - M* M = (1/N) 3 Xi Where: CU = Christiansen’s Coefficient of Uniformity (%) D = Average Absolute Deviation M = Mean Application Xi = Individual Application Amounts N = Number of Individual Application Amounts 3 = Symbol for summation The CU statistically analyzes the sprinkler pattern for uniformity based * * = Symbol for absolute value of quantity between the bars JANUARY/FEBRUARY 1997 1 Irrigation Efficiency Analysis Poor Coverage Example Sprinkler Name: Poor Coverage Sprinkler Model: A3 Nozzle Size: A3 Flow Rate (gpm): 34.00 Date/Time of Test: 02/01/91 02:41 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 1.30 Record Number: 1003 Irrigation Efficiency Analysis Good Coverage Example Sprinkler Name: Good Coverage Sprinkler Model: A1 Nozzle Size: A1 Flow Rate (gpm): 25.00 Date/Time of Test: 02/01 /91 12:47 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 3.00 Record Number: 1001 Sprinkler Radius of Throw per ASAE Standard S398.1:61 Feet Sprinkler Radius of Throw per ASAE Standard S398.1: 71 Feet 2.0' = 0.265 4.0' = 0.250 6.0' = 0.326 8.0' = 0.345 10.0'= 0.331 12.0' = 0.335 14.0' = 0.326 16.0'= 0.312 18.0' = 0.302 20.0' = 0.279 22.0’ = 0.279 24.0' = 0.269 26.0' = 0.269 28.0' = 0.274 30.0' = 0.295 32.0' = 0.279 34.0' = 0.288 36.0' = 0.307 38.0'= 0.321 40.0'= 0.321 42.0' = 0.295 44.0' = 0.288 46.0' = 0.269 48.0' = 0.260 50.0' = 0.236 52.0' = 0.208 54.0'= 0.189 56.0'= 0.137 58.0' = 0.092 60.0' = 0.033 2.0' = 0.585 4.0' = 0.468 6.0' = 0.468 8.0' = 0.478 10.0'= 0.459 12.0'= 0.424 14.0'= 0.415 16.0'= 0.400 18.0'= 0.390 20.0' = 0.346 22.0' = 0.327 24.0' = 0.278 26.0' = 0.254 28.0' = 0.239 30.0’= 0.215 32.0' = 0.200 34.0'= 0.180 36.0'= 0.171 38.0'= 0.159 40.0'= 0.151 42.0’= 0.132 44.0’= 0.122 46.0’= 0.117 48.0’= 0.112 50.0'= 0.107 52.0'= 0.107 54.0’= 0.102 56.0' = 0.093 58.0' = 0.088 60.0' = 0.088 62.0' = 0.076 64.0'= 0.061 66.0' = 0.049 68.0' = 0.034 70.0'= 0.015 The Profile Report shows graphically and quantitatively the precipitation amounts and their relative distance from the sprinkler to the terminal point that the water is thrown. Irrigation Efficiency Analysis Uniformity Evaluation Poor Coverage Example Sprinkler Name: Poor Coverage Sprinkler Model: A3 Nozzle Size: A3 Flow Rate (gpm): 34.00 Date/Time of Test: 02/01/91 02:41 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 1.30 Record Number: 1003 Irrigation Efficiency Analysis Uniformity Evaluation Good Coverage Example Sprinkler Name: Good Coverage Sprinkler Model: A1 Nozzle Size: A1 Flow Rate (gpm): 25.00 Date/Time of Test: 02/01 /91 12:47 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 3.00 Record Number: 1001 Distr. Uniformity: 76% CU (Christiansen): 88% Sched. Coeff. (5%): 2.2 Min. (In./Hr.): 0.253 Mean (In./Hr.): 0.762 0.895 (Theor.) Max. (In./Hr.): 0.952 Spacing Equilateral 65.0' x 56.3' Distr. Uniformity: 84% CU (Christiansen): 89% Sched. Coeff. (5%): 1.2 Min. (ln./Hr.): 0.477 Mean (ln./Hr.): 0.613 0.658 (Theor.) Max. (In./Hr.): 0.915 Spacing Equilateral 65.0' x 56.3’ Data Grid in 0.001 Inches/Hour Data Grid in 0.001 Inches/Hour 265 257 283 416 468 555 602 635 708 738 754 786 807 934 843 852 831 831 852 843 834 807 786 754 738 708 635 602 555 468 416 283 257 265 257 253 311 473 541 605 647 675 702 718 725 748 800 826 834 843 819 819 843 834 826 800 748 725 718 702 675 647 605 541 473 311 253 257 286 364 413 522 576 643 687 716 745 752 755 770 778 800 806 814 783 783 814 806 800 778 770 755 752 745 716 687 643 576 522 413 364 286 446 438 463 547 616 683 718 734 756 764 775 791 801 828 839 840 811 811 840 839 828 801 791 775 764 756 734 718 683 616 547 463 438 446 540 528 493 583 643 690 727 748 771 781 796 811 820 851 867 859 838 838 859 867 851 820 811 796 781 771 748 727 690 643 583 493 528 540 608 610 594 591 648 696 740 761 777 799 807 819 830 855 883 868 856 856 868 883 855 830 819 807 799 777 761 740 696 648 591 594 610 608 685 664 645 665 686 698 750 759 776 802 811 828 846 874 901 887 882 882 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783 754 731 729 726 668 689 710 721 721 710 689 668 726 729 731 754 783 807 822 836 856 883 900 902 904 882 887 901 874 846 828 811 802 776 759 750 698 686 665 645 664 685 685 664 645 665 686 698 750 759 776 802 811 828 846 874 901 887 882 856 868 883 855 830 819 807 799 777 761 740 696 648 591 594 610 606 608 610 594 591 648 696 740 761 777 799 807 819 830 855 883 868 856 838 859 867 851 820 811 796 781 771 748 727 690 643 583 493 528 540 540 528 493 583 643 690 727 748 771 781 796 811 820 851 867 859 838 811 840 839 828 801 791 775 764 756 734 718 683 616 547 463 438 446 446 438 463 547 616 683 718 734 756 764 775 791 801 828 839 840 811 783 814 806 800 778 770 755 752 745 716 687 643 576 522 413 364 286 286 364 413 522 576 643 687 716 745 752 755 770 778 800 806 814 783 819 843 834 826 800 748 725 718 702 675 647 605 541 473 311 253 257 257 253 311 473 541 605 647 675 702 718 725 748 800 826 834 843 819 831 852 843 834 807 786 754 738 708 635 602 555 468 416 283 257 265 265 257 283 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579 574 563 554 546 529 5C6 506 529 546 554 563 574 579 575 575 575 579 574 563 554 546 529 506 485 512 527 541 550 561 576 578 574 576 587 591 581 569 555 536 519 519 536 555 569 581 591 587 576 574 578 576 561 550 541 527 512 485 490 500 515 528 537 551 568 581 584 587 590 597 595 579 564 553 540 540 553 564 579 595 597 590 587 584 581 568 551 537 528 515 500 490 486 478 499 514 533 549 563 584 594 591 595 603 604 603 596 592 601 601 592 596 603 604 603 595 591 594 584 563 549 533 514 499 478 486 487 485 477 510 530 544 563 583 596 603 603 617 638 635 627 616 628 628 616 627 635 638 617 603 603 596 583 563 544 530 510 477 485 487 486 487 481 504 523 546 563 576 595 615 631 636 644 653 654 650 669 669 650 654 653 644 636 631 615 595 576 563 546 523 504 481 487 486 488 487 491 487 516 538 551 568 602 635 645 653 671 682 677 684 693 693 684 677 682 671 653 645 635 602 568 551 538 516 487 491 487 488 479 481 488 484 492 525 547 578 616 636 661 684 683 686 682 698 708 708 698 682 686 683 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Critical 5% Window Size Mean ln./Hr.: 0.762 Sched. Coefficient: 2.2 Window Size 7 Min. Window ln./Hr.: 0.343 Max. Window In./Hr.: 0.905 Min. Window % of Mean: 45% Max. Window % of Mean: 119% 7 179'2 Critical 5% Window Size Mean In./Hr.: 0.613 Min. Window ln./Hr.: 0.493 Min. Window % of Mean: 80% Sched. Coefficient: 1.2 Max. Window In./Hr.: 0.797 Max. Window % of Mean: 130% Window Size 7 7 179'2 The Grid Listing Report analyzes the synthesized numeric coverage of a sprinkler overlap pattern. 2 USGA GREEN SECTION RECORD DU: Distribution Uniformity DU represents the average of the lowest 25% of the application rates in the sprinkler pattern divided by the average application rate of the entire pattern. This method sorts all values from the lowest to highest; the average of the lowest 25% of catchments is then divided by the mean value of the entire area. This method, however, does not take into account the location of the individual values or any benefit that may be derived from values immedi­ ately adjacent to the low values. In other words, the lowest 25% of catch­ ments could be dispersed throughout the pattern and not necessarily be in the same localized area. Therefore, a bene­ fit may be derived from an over-watered area immediately adjacent to an under­ watered location. DU = 100(l-[LQ/M]) Where: DU = Distribution Uniformity (%) LQ = Average of the Lowest % of the Irrigation Amounts M = Average of the Irrigation Amounts Golf course irrigation designers recognize that sprinklers with high CU or DU ratings could still develop sig­ nificant wet or diy areas when irrigating turf. This, in turn, required many de­ signers to rely upon past field experi­ ence when selecting sprinklers and appropriate spacings. Now, however, the advent of the personal computer has created another method. Sprinklers now can be evaluated before they are installed in the field with the SPACE program. No, this has nothing to do with rocket science; SPACE is an acronym for Sprinkler Profile And Coverage Evaluation. The SPACE program is personal computer software developed by the Center for Irrigation Technology (CIT), at the California State University, Fresno, California. Capabilities of SPACE Using the SPACE program, one can evaluate the distribution and uni­ formity of sprinklers either at one’s own site or, for a small fee, in the CIT labo­ ratory. This is accomplished through a combined analysis of statistical, numerical, and graphic data, all based on the actual application of water collected from one sprinkler. This can be accomplished before installing the equipment in the field. The SPACE program is capable of evaluating two distinctly different types of data. The first type of evaluation is known as a single-leg profile analysis, while the second is a grid analysis. The single-leg profile analysis is used when a sprinkler is being selected either for a new system design or for a retrofit or upgrade of an existing system. The single-leg profile data are then used to create overlaps and reports that simu­ late how one can expect the sprinkler to perform in the field. The grid analysis is used to field audit the efficiency of existing systems or examine wind effects on a single sprinkler. By follow­ ing a step-by-step procedure, a great deal can be learned about an existing or proposed system. Single-Leg Profile, Overlaps, Multiple Spacing Analysis, and Associated Reports Creating a Single-Leg Profile: To create a single-leg profile, raw data from a single sprinkler are collected from a single row of catchments placed in a straight line on 1-foot or 2-foot inter­ vals from the sprinkler outward. The sprinkler is operated at a specified pressure for a period of time sufficient to collect a representative amount of water in each catchment. The water in each catchment is measured to the nearest hundredth of an inch and entered into the computer. The time the sprinkler is allowed to run (in minutes), along with other data such as sprinkler make, model, nozzle size, operating pressure, flow rate (gpm), arc (degrees of rotation), test date, and minutes per revolution, are collected to become part of the test record. Overlaps: Once a profile has been developed, overlaps can be generated with SPACE. Overlaps simulate perfor­ mance and coverage using the single­ leg profile data, based on spacings and configurations determined by the com­ puter operator. Spacings of up to 100 feet can be selected, with available configurations including square, rec­ tangular, triangular, equilateral tri­ angles, offset rows, single row, and single head. Reports: Once an overlap is gener­ ated, a variety of information can be viewed from the monitor or printed as individual one-page reports. Profile, Grid Listing, Densogram, Histogram, Sliding Window, and Multiple Spacing reports are available. Profile Report: The profile report represents both graphically and numerically the water collected in the single row of catchments. The graphic portion represents the accumulation of water plotted on an X- and Y-axis. By studying this graphic, areas of low and high precipitation can be observed as to their relative positioning from the sprinkler to the terminal point that water is thrown. Quantitative data for each catchment are also represented in inches per hour and reported numeri­ cally with a reference for the location of each catchment in the row. The most ideal profile for turfgrass irrigation is wedge shaped, as this will deliver the most uniform distribution when over­ lapped at a proper spacing. The wedge- shaped pattern is also the most for­ giving and maintains more uniform coverage where slight spacing adjust­ ments are required around greens, bunkers, and trees. Grid Listing Report: Numeric data representing the overlapped pattern are termed a grid listing. A table of numbers represents each calculated value of the simulated catchments within the overlap matrix. Each num­ ber depicts the amount of water applied within that area when the sprinklers are spaced at the selected distance and configuration. All data are represented in inches per hour. Histogram Report: The histogram report is a bar graph depicting the application rates of each data point from the overlap, categorizing them from 100% below the mean to 100% above the mean in 5% increments. This report represents graphically both the percent variation from the mean and the number of simulated catchments falling into each range. The most ideal results are represented by the least variance from the mean application in both categories. Densogram Reports: The denso­ gram report is a two-dimensional dot matrix graphic of the grid listing show­ ing the relative wet and dry areas within the pattern. Darker areas repre­ sent wetter portions, and lighter areas represent drier portions of the overlap. Perfect uniformity would be repre­ sented by a uniformly shaded printout. Sliding Windows Report: The slid­ ing window examines a 1%, 5%, and 10% area of the overlap pattern in both its wettest and driest locations. Values for mean inches per hour, minimum window inches per hour, minimum window percent of mean, maximum window inches per hour, maximum window percent of mean, and scheduling coefficient are calculated for each size window. Mean Inches Per Hour: This value is the average application rate of the entire pattern. Each catchment in the JANUARY/FEBRUARY 1997 3 entire pattern is added together and divided by the total number of catch­ ments. Minimum Window Inches Per Hour: This value represents the area of the pattern that receives the lowest application rate. The value listed is the lowest average of catchments found in the selected window size. Minimum Window Percent of Mean: This value is the percentage of the mean application rate of the entire pattern that the average application rate of the catchments in the window size receive in the area receiving the lowest application rate. Maximum Window Inches Per Hour: This value represents the area of the pattern that gets the highest appli­ cation rate. The value listed is the highest average of catchments found in the selected window size. Maximum Window Percent of Mean: This value is the percentage of the mean application rate of the entire pattern that the average application rate of the catchments in the window size receive in the area receiving the highest application rate. Scheduling Coefficient: This value is the mean application rate of the pattern area, divided by the average application rate found in the driest window area. The scheduling coefficient is used as a run time multiplier as it relates to the driest portion of the entire pattern. This is based on the value 1.0 being perfec­ tion. (A 1.0 is impossible to obtain, as even rain does not fall this uniformly!) Multiple Spacings Analysis: The SPACE program has other capabilities, including that it can (1) evaluate a given sprinkler over a range of spacings, (2) examine which spacing is most efficient, and (3) determine how per­ formance will suffer where adjustments in spacing must be made. A series of values are calculated by the computer based upon the range of spacings selected by the computer operator. The result is a graph that plots continuous values for the Scheduling Coefficient (SC), Coefficient of Uniformity (CU), and Distribution Uniformity (DU) and can be displayed or printed as a report. Numerical data listing the spacings, CU, DU, SC (based on a 5% window), minimum inches per hour, mean inches per hour, theoretical inches per hour (based on gpm of sprinkler, configura­ tion, and spacing), and maximum inches per hour are also provided. The program selects the best spacing based upon the lowest SC. Grid Analysis and Associated Reports A grid analysis is a combination of graphic and data reports based upon a conventional catch-can test. Grid analysis can be performed for two different evaluations. The first is to performance test or audit an existing irrigation system. This test determines the system’s overall efficiency. The second is where a single sprinkler is tested to use this data in generating overlaps. (This can demonstrate the effects of wind on the pattern of a single sprinkler.) The overlaps that follow this test are similar to those of the single­ leg profiles discussed earlier, with the exception that raw data are gathered from the entire area influenced by the sprinkler as opposed to a profile. Grid Analysis of an Existing System: Data collection for grid analysis of an existing system begins with the layout of catchments between two rows of sprinklers. The catchments are laid out in square arrangements, at a predeter­ mined distance, uniformly spaced throughout the area influenced by the Histograms are used to represent the irrigation distribution in 5% increments. The frequency of each synthesized catchment occurs in the Grid Listing Report. 4 USGA GREEN SECTION RECORD On-site profile data gathered on new sprinklers or nozzle combinations with single row of catchments are later used in the SPACE Program evaluation process. overlap of the sprinklers. Any number can be used, with a maximum of 60 rows by 60 columns for a possible total of 3600 catchments. The more catch­ ments used, the more precise the analysis. (It is suggested by irrigation texts that the maximum spacing for catchments be 5 feet by 5 feet if sprinkler spacing is less than 60 feet, and 10 feet by 10 feet if sprinklers are spaced over 60 feet.) The area selected for testing should be representative of the entire system and conducted in wind conditions typical of those found during normal irrigation. An ideal way to perform this test is to set up the catchments the evening before and allow the sprinkler system to operate automatically. A minimum of 15 minutes run time is suggested to obtain an adequate amount of water in the catchments. For the sake of the test, run times of all stations influencing the catchments must be set to operate for the exact same amount of time while collecting data. The water collected in the catch­ ments is then measured to the nearest hundredth of an inch and entered into the computer. Data such as sprinkler run time in minutes, sprinkler make, model, nozzle size, operating pressure, flow rate (gpm), arc (degrees of rota­ tion), test date, and minutes per revo­ lution are recorded. These data become part of the permanent test record. Single Sprinkler Grid: Grid data of a single sprinkler are collected much the same way as for an existing system, but the capability of operating only one sprinkler must be available. To arrange the catchments for collecting data, the radius of the sprinkler coverage must be known. After obtaining this informa­ tion, the catchments are laid out in a square arrangement with the sprinkler located in the center and catchments positioned uniformly throughout as far as water is thrown. Data are then collected and entered into the computer in the same manner as with an existing system. The differ­ ence is that these data can be over­ lapped, similar to a single-leg analysis, to examine different spacings and con­ figurations. The data can then be viewed or printed as a grid listing, densogram, histogram, or sliding win­ dows report for either the single head or a selected overlap. Interpretation of Data and Summary Interpretation of the final data and reports requires some time, and all the data must be taken into consideration. The final sprinkler selection should not be based on any one numerical or graphic representation alone. A good place to start, however, is with the profile. The more wedge-shaped the profile, the more uniform the coverage can be expected. Looking beyond the profile, one needs to examine the wet­ test and driest areas through the mini­ mum and maximum values presented on the sliding windows report, deter­ mine how significant these might be­ come, look for the lowest Scheduling Coefficient in combination with the highest CU and DU, most uniform Densogram, narrowest range of varia­ tion on the Histogram, and, finally, compare how well the sprinkler per­ forms across a range of spacings. The JANUARY/FEBRUARY 1997 5 Irrigation Efficiency Analysis Uniformity Evaluation Poor Coverage Example Sprinkler Name: Poor Coverage Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Sprinkler Model: A3 Nozzle Size: A3 Set Screw Setting: 0 Degree of Arc: 360 Flow Rate (gpm): 34.00 Date/Time of Test: 02/01/91 02:41 Minutes/Revolution: 1.30 Testing Facility: User Created Comment: Record Number: 1003 Irrigation Efficiency Analysis Uniformity Evaluation Good Coverage Example Sprinkler Name: Good Coverage Base Pressure (psi): 80.0 Sprinkler Model: A1 Riser Height (inches): 0.0 Nozzle Size: A1 Set Screw Setting: 0 Degree of Arc: 360 Flow Rate (gpm): 25.00 Date/Time of Test: 02/01/91 12:47 Minutes/Revolution: 3.00 Testing Facility: User Created Comment: Record Number: 1001 Distr. Uniformity: 76% CU (Christiansen): 88% Sched. Coeff. (5%): 2.2 Min. (In./Hr.): 0.253 Mean (ln./Hr.): 0.762 0.895 (Theor.) Max. (In./Hr.): 0.952 Spacing Equilateral 65.0' x 56.3' Distr. Uniformity: 84% CU (Christiansen): 89% Sched. Coeff. (5%): 1.2 Min. (In./Hr.): 0.477 Mean (In./Hr.): 0.613 0.658 (Theor.) Max. (In./Hr.): 0.915 Spacing Equilateral 65.0' x 56.3' Critical 1 % Window Size Mean In./Hr.: 0.762 Min. Window In./Hr.: 0.260 Min. Window % of Mean: 34% Max. Window ln./Hr.: 0.941 Max. Window % of Mean: 123% Sched. Coefficient: 2.9 Critical 5% Window Size Mean In./Hr.: 0.762 Min. Window In./Hr.: 0.343 Min. Window % of Mean: 45% Max. Window ln./Hr.: 0.905 Max. Window % of Mean: 119% Sched. Coefficient: 2.2 Critical 10% Window Size Mean In./Hr.: 0.762 Min. Window ln./Hr.: 0.439 Min. Window % of Mean: 58% Max. Window ln./Hr.: 0.885 Max. Window % of Mean: 116% Sched. Coefficient: 1.7 Window Size 3 „ 33* Window Size 7 7 179* Window Size 10 in 365* Critical 1% Window Size Mean In./Hr.: 0.613 Min. Window ln./Hr.: 0.485 Max. Window ln./Hr.: 0.873 Sched. Coefficient: 1.3 Min. Window % of Mean: 79% Max. Window % of Mean: 142% Critical 5% Window Size Mean ln./Hr.: 0.613 Min. Window ln./Hr.: 0.493 Max. Window ln./Hr.: 0.797 Sched. Coefficient: 1.2 Min. Window % of Mean: 80% Max. Window % of Mean: 130% Critical 10% Window Size Mean ln./Hr.: 0.613 Min. Window In./Hr.: 0.509 Max. Window ln./Hr.: 0.769 Sched. Coefficient: 1.2 Min. Window % of Mean: 83% Max. Window % of Mean: 125% Window Size 3 3 33* Window Size 7 7 179* Window Size 10 10 365* The Sliding Windows Report analyzes the most wet and dry 1, 5, and 10% areas of the overlap. Irrigation Efficiency Analysis Uniformity Evaluation Poor Coverage Example Sprinkler Name: Poor Coverage Sprinkler Model: A3 Nozzle Size: A3 Flow Rate (gpm): 34.00 Date/Time of Test: 02/01/91 02:41 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 1.30 Record Number: 1003 Irrigation Efficiency Analysis Uniformity Evaluation Good Coverage Example Sprinkler Name: Good Coverage Sprinkler Model: A1 Nozzle Size: A1 Flow Rate (gpm): 25.00 Date/Time of Test: 02/01 /91 12:47 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 3.00 Record Number: 1001 Distr. Uniformity: 76% CU (Christiansen): 88% Sched. Coeff. (5%): 2.2 Min. (In./Hr.): 0.253 Mean (In./Hr.): 0.762 0.895 (Theor.) Max. (In./Hr.): 0.952 Spacing Equilateral 65.0' x 56.3' Distr. Uniformity: 84% CU (Christiansen): 89% Sched. Coeff. (5%): 1.2 Min. (In./Hr.): 0.477 Mean (InJHr.): 0.613 0.658 (Theor.) Max. (In./Hr.): 0.915 Spacing Equilateral 65.0' x 56.3' The Densogram graphically shows the synthesized coverage of overlap area. The lighter shaded areas indicate drier areas and the darker areas are more wet. The small square locates the critical dry area within the overlap pattern. 6 USGA GREEN SECTION RECORD more consistent the results are at vary­ ing spacings, the more uniform the coverage will be where spacing adjust­ ments are required. In the case of new installations, it would be prudent to send one sprinkler for testing prior to the design phase to select the best spacing. During the system installation, sprinklers should be tested at the start of the project and then again one-third and two-thirds through completion of the project as a quality-control measure. Checking several sprinklers during the project will help insure that the manufacturer has not made any drastic change in the product or that problems with molding or machining nozzles have not occurred. This small investment could help avoid many headaches down the road. There is a case to be made for per­ forming on-site testing, especially at high elevations where thin air will affect the distribution pattern by how far water is thrown. You cannot expect information obtained at Fresno, Cali­ fornia, at near sea level, to be com­ pletely valid in the Rocky Mountains at 10,000 feet elevation. Additionally, the effects of wind, temperature, relative humidity, and other unknown variables on sprinkler distribution are not yet completely known. However, the Center for Irrigation Technology is busy working with lasers to analyze actual droplet size in relationship to wind and drift. In the future, wind effects may become more predictable. It must also be recognized that a nozzle one size larger or smaller can result in a drastic change in the shape of a profile. Some nozzles have also shown a great sensitivity in their per­ formance with only slight variations in operating pressure. Evaluating sprinklers alone cannot guarantee success, but it may prevent certain failure. A system still needs to be properly designed hydraulically and then installed correctly. Laboratory evaluation of sprinklers is better than any other method of selection currently available, especially compared to the old-fashioned way of just sticking them in the ground and finding donuts upon completion. So don’t let sprinkler selec­ tion be rocket science. Test before you invest, and put data from the SPACE program to work for you! (SPACE is available for either DOS or Windows. For more information on SPACE or laboratory testing, contact the Center for Irrigation Technology, California State University — Fresno, 5370 North Chestnut Avenue, Fresno, California 93740-0018, or phone 209- 278-2066.) References Irrigation, Fifth Edition, The Irrigation Association, 1983. Landscape Irrigation System Evaluation and Scheduling for Southern California, U.C. Cooperative Extension, 1992. SPACE for DOS User’s Guide, Center for Irrigation Technology, 1989. SPACE for Windows Installation and Operation Manual, Center for Irrigation Technology, 1993. Turfgrass Water Conservation, Cooperative Extension, University of California, Divi­ sion of Agriculture and Natural Resources, 1985. “The Facts Hold Water,” Alfred S. Cline, CGCS, pp. 84-86, Golf Course Manage­ ment Magazine, Volume 64, No. 7, July 1996. MIKE HUCK is an agronomist in the Green Section’s Western Region. He con­ ducts TAS visits from the California coast to the peaks of the Rocky Mountains. Irrigation Efficiency Analysis Uniformity Evaluation Poor Coverage Example Sprinkler Name: Poor Coverage Sprinkler Model: A3 Nozzle Size: A3 Flow Rate (gpm): 34.00 Date/Time of Test: 02/01/91 02:41 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 1.30 Record Number: 1003 Irrigation Efficiency Analysis Uniformity Evaluation Good Coverage Example Sprinkler Name: Good Coverage Sprinkler Model: A1 Nozzle Size: A1 Flow Rate (gpm): 254.00 Date/Time of Test: 02/01/91 12:47 Testing Facility: User Created Comment: Base Pressure (psi): 80.0 Riser Height (inches): 0.0 Set Screw Setting: 0 Degree of Arc: 360 Minutes/Revolution: 3.00 Record Number: 1001 Equilateral Spacing Coefficient of Uniformity --------- Distribution Uniformity --------- Scheduling Coefficient (5%) --------- Coefficient of Uniformity --------- Distribution Uniformity --------- Scheduling Coefficient (5%) --------- Best Spacing (Lowest SC): 60 x 52 Best Spacing (Lowest SC): 60 x 52 Multiple Spacing Graphics display the consistency or lack of consistency of the Christiansen’s Coefficient of Uniformity (CU), Distribution Uniformity (DU), and scheduling coefficient over a range of spacings. JANUARY/FEBRUARY 1997 7 Checking Your Sand — Quality Control Begins at Home A quick check of sand with your own testing equipment can help avoid problems later. by JAMES F. MOORE O EVALUATE the suitability of sands used in the construction of greens or bunkers, samples should be submitted to a physical soil testing lab for analysis. The laboratory has the very specialized equipment necessary to determine the amounts of silt and clay in the sand, as well as other factors such as total porosity, water retention, etc. However, every super­ intendent should have a nest of soil sieves and an accurate scale to monitor the consistency of sizing of the sand being delivered for topdressing and A nest of sieves is mounted on a power shaker like that used by professional labs. This is a nice accessory if you can afford it. If not, manual shaking will suffice. 8 USGA GREEN SECTION RECORD topping off bunkers. Sands can vary widely in their makeup, even from the same source. As a rule, sand size specifications for golf course use are much tighter than in other industries. A quick screening of sand as it is delivered will prove well worth the initial cost of the equipment. Numerous companies sell soil sieves and scales, so be sure to check around for the best price. In this office, we acquired our equipment from the com­ pany listed below. Thomas Scientific Box 99 Swedesboro, NJ 08085-0099 (609) 467-2000 Both 8-inch and 4-inch sieves are available. We use the 8-inch sieves since they are more accurate and we test materials regularly. The 4-inch sieves should be fine for golf course use if you want to save a few dollars. You should acquire the following sieves: Mesh Millimeters 10 18 35 60 100 140 270 Pan Cover 2 1 0.5 0.25 0.15 0.1 0.05 You also need an accurate scale or balance capable of measuring to within 1 gram or 0.1 ounce. We use a scale called “Lume-O-Gram” (Model D1001- BA) from Ohaus that we also pur­ chased from Thomas Scientific (cata­ log no. 1367-H32). The digital scale doubles as a letter scale if you like. The cost was $89.00. Sieves vary in cost depending on the mesh. While most of our 8-inch sieves were about $35.00 apiece, the 270 mesh was $63.00. There are many different methods of sieving. The procedure we use in this office is as follows. Keep in mind that When collecting sand for testing, be sure to remove samples from the inside of the pile rather than from the surface. This will ensure the sample is more representative of the entire pile. your sand must be very dry for your numbers to be accurate. 1. Select a small container for the sand. We use the container that came with our scale. You need something that will hold about 3 cups of sand (700 to 800 grams). Place the container on the scale and adjust it to zero. 2. Put your sand in the container and record the weight. Let’s assume you have 700 grams. 3. Build your nest of sieves by placing the largest screen (2.0mm) on top and getting progressively smaller as you go down, ending with the pan on the bottom. 4. Add the sand to the top sieve and cover. Shake the nest of sieves for five minutes. 5. Make sure the container is clean. Empty the sand from the top sieve into the container and record the weight. 6. Empty the container and clean. Empty the sand from the next sieve and record the weight. Repeat this pro­ cedure for each sieve and the pan. 7. Divide the weight retained on each screen by the total weight (700 grams in this case). This gives you the percentage of each fraction, as illustrated below. Percentage Retained on Screen (Retained Weight/ (Grams) 0 21 175 385 49 35 21 14 Total Weight) 0 3 25 55 7 5 3 2 Mesh 10 18 35 60 100 140 270 Pan Before you accept delivery of a load of sand, take the time to perform this Simple test. It may not be practicable to test before the delivery is made. How­ ever, be sure you have an agreement with your supplier that you will not submit payment for any load that does not meet your specifications. On many of today’s courses, sand is used on greens in quantities second only to the amount of water applied. This simple equipment and test can help protect your course’s most valu­ able physical asset — the greens. Although you might be discouraged with the inconsistency of your sand supply, in this case, what you do not know can definitely hurt you. JAMES E MOORE is director of Construc­ tion Education Programs of the USGA Green Section. JANUARY/FEBRUARY 1997 9 KTURF: A Pesticide and Nitrogen Leaching Model A computer model available on the Internet and World Wide Web helps turfgrass managers predict pesticide and nitrogen leaching. by DR. STEVE STARRETT, DR. SHELLI STARRETT, JUDY HILL, and GREG ADAMS THE USE OF PESTICIDES on golf courses may have some potential negative impacts, in­ cluding groundwater contamination. As the golf industry continues to grow, the proper management of pesticides grows in importance. KTURF is a computer model, developed at Kansas State University and funded by the USGA, that estimates the percentage of applied nitrogen or pesticide that leaches through 50cm (20 inches) of turfgrass-covered soil in specific cir­ cumstances. KTURF was developed to allow golf course superintendents access to these models on the internet. KTURF models are available via the internet and the world wide web (www) at the following URL: http. //www. eece. ksu.edu/~starret/KTURF/ Because KTURF is located on the www, any superintendent with internet access can use the latest version of the model and the mathematical software required by the models. The models can be accessed at any time of day and do not require that the software be downloaded to the user’s computer. The user simply enters the conditions that pertain to the situation and clicks a button. Within a minute or so, the results appear on the screen. The KTURF Models The KTURF models were developed using artificial neural networks (ANNs), a form of artificial intelligence. ANNs are trained using experimental data from lab tests. The ANN learns the relationships between the inputs 10 USGA GREEN SECTION RECORD and the output. Once the models are developed (trained), those relation­ ships can be applied to other sites to make predictions about the output, in this case the percentage of nitrogen or pesticide leached. The KTURF models were trained using data from USGA- funded projects. Although completely accurate, use- able models for turfgrass-covered soil have yet to be developed. KTURF does a very good job of predicting pesticide and fertilizer leaching based upon the results of USGA research. The actual results will vary from site to site, but KTURF provides an approximation of the nitrogen or pesticide leached based on four readily determined input vari­ ables. Figures 1 and 2 are KTURF’s pesticide leaching predictions com­ pared to measured values. The results from 16 test cases for the nitrogen model are shown in Figures 3 and 4. KTURF did a good job of estimating the percentage of applied pesticide and nitrogen leached for the test cases. For more information about the method­ ology used to obtain the training data for the ANNs, refer to Starrett et al. 1996,1995a, 1995b, and 1995c. Developing the KTURF Website The web files were written in Hyper­ Text Markup Language (HTML), a programming language specific to the world wide web to be accessible by web browers such as Netscape Navigator, Mosaic, or Internet Explorer. Combin­ ing text with tags that indicate format changes, the web browser presents the documents in the desired format. Research lysimeters generate data to form the basis of the KTURF model. HTML tutorials and examples are available via the world wide web, and several books are also available about this subject (National Center for Super­ computing Applications 1996a, Smith 1995). At the KTURF website, program­ ming scripts written in languages other than HTML were needed to perform the interactive data processing and calculation. HTML is used to execute the scripts that do the calculations. The user inputs data about a golf course’s pesticide or nitrogen use on an HTML form, and the HTML script executes an intermediate script using the data input. The intermediate programming script that KTURF uses is written in Practical Extraction and Report Language (PERL). PERL, a useful language for Common Gateway Interface (CGI) programming or interactive web pro­ gramming, processes data submitted by a remote user. Some of PERL’s web applications include guestbooks where users can leave comments about a site, access counters that count the number of times a web page is displayed, and shopping carts that allow users to buy objects for sale. The KTURF PERL script assigns the submitted data from the HTML form to variables, opens MATLAB=AE (the mathematical soft­ ware used to write the ANN model), receives the data back from MATLAB= AE, and creates another form using embedded HTML to display the results. Several informative websites about PERL are available via the internet (NCSA 1996b), and several books have also been written that describe the basics of PERL scripting (Schwartz 1993). Using the KTURF Website Two interactive models are currently available at the KTURF website: one predicting the nitrogen leaching and the other predicting pesticide leaching through 20 inches of turfgrass-covered soil. The nitrogen model predicts the per­ centage of applied nitrogen leaching through 20 inches of turfgrass-covered soil. It is applicable to conditions on both fairways and greens. The user must supply four input variables to compute the predicted result: the sand content of the soil, the irrigation applied to the soil, the form of nitrogen applied, and the period of time after the nitrogen application that the leached output is calculated. To illustrate the use of the interactive nitrogen model, the following data set was entered into the input form: Sand content of the soil: 65%. Irrigation rate: two .5" applications per week. Nitrogen form: liquid urea. Time (in days): 14. The submit button, located at the bottom of the form, is pressed and, after approximately one minute, the result­ ing web page should appear. The predicted percentage of nitrogen leached during the 14 days after appli­ cation for this case is approximately 2%. The exact nitrogen leached will vary from site to site depending on the conditions present. The pesticide model currently avail­ able is applicable only to fairway con­ ditions. It predicts the percentage of applied pesticide that leaches through 20 inches of turfgrass-covered soil. The irrigation rate and the time (in days after pesticide applications) are neces­ sary input variables. In addition, two characteristics of the pesticide — the water solubility and the sorption co­ efficient — must be input. Because the water solubility and sorption coeffi­ cient may be unknown, a table of common pesticides used is provided and accessed with the click of a button. However, if a pesticide used is not listed, your pesticide sales representa­ tive can provide this information. As an example of the interactive pesticide model, the following data were input into the pesticide form: Pesticide name: Dicamba. Water solubility of pesticide: 400,000 mg/L. Sorption coefficient of the pesti­ cide: 2. Irrigation rate: two .5" waterings per week. Time (in days): 14. After submitting the data, the follow­ ing result was calculated: Output: 2%. The output forms also display the variables entered to ensure the sub­ mitted data were correct. The output value provided is an estimated percen­ tage of how much of the applied pesti­ cide leached. A model applicable for pesticide leaching under green conditions is currently under development. Range of Application KTURF was developed from experi­ mental data collected primarily in Figure 1 Comparing KTURF with Measured Pesticide Leaching Values Test Case Number Figure 2 Comparing KTURF with Measured Pesticide Leaching Values Test Case Number JANUARY/FEBRUARY1997 U Iowa. The soil used was in an undis­ turbed condition; therefore, many macropores (earthworm burrows, soil cracks, etc.) existed. The soil moisture content was at field capacity. If your soil moisture conditions are extremely dry, then little of the applied irrigation will leach below 50cm. If your soil moisture conditions are near saturation, then most of your applied irrigation will leach below the rootzone. KTURF was not developed with these extreme con­ ditions; therefore, its predictions will not be realistic for those conditions. Conclusion Using the interactive version of KTURF is advantageous compared to other more traditional distribution methods that are available. Accessing KTURF via the internet allows the user to use the most up-to-date versions Figure 3 Comparing KTURF with Anticipated Nitrogen Leaching Values 12 USGA GREEN SECTION RECORD available. Program changes are avail­ able instantaneously, rather than wait­ ing for a diskette to be mailed. Also, responses to user feedback will be provided more quickly by e-mail than by postal letter or telephone. The KTURF model is an accurate, reliable method to approximate the percentage of applied pesticide and nitrogen that will leach through turf­ grass-covered soil. Used as an assess­ ment tool, KTURF can help to reduce pesticide leaching by allowing users to experiment with different pesticide/ irrigation schemes. Turfgrass managers can thus optimize their practices to reduce the likelihood of pesticide leaching beyond the rootzone. The KTURF site is located at: http://www. eece. ksu. edu/~starret/KTURF/ References National Center for Supercomputing Appli­ cations. 1996a. http://ncsa.uiuc.edu/ General/Internet/WWW/HTMLPrimer. html. National Center for Supercomputing Appli­ cations. 1996b. http://ncsa/uiuc.edu/ General/Training/Perllntro/. Randal L. Schwartz. 1993. Learning Perl. O’Reilly and Associates. Mike Smith. 1995. http://snowwhite.it. brighton.ac.uk/-mas/mas/courses/html/ htmLhtml. S. K. Starrett, N. E. Christians, and T. Al Austin. 1996. Comparing Dispersivities and Soil Chloride Concentrations of Turfgrass- Covered Undisturbed and Disturbed Soil Columns. J. of Hydrology. 180:21-29. S. K. Starrett, N. E. Christians, and T. Al Austin. 1996. Movement of Pesticides Under Two Irrigation Regimes. J. Environ. Qual. 25:566-571. S. K. Starrett, N. E. Christians, and T. Al Austin. 1995. Fate of Nitrogen Applied to Turfgrass-Covered Soil Columns. J. Irr. and Drain. Engg. 121:390-395. S. K. Starrett, N. E. Christians, and T. Al Austin. 1995. Fate of Amended Urea in Turfgrass Biosystems. Commun. Soil Sci. Plant Anal. 26:1595-1606. S. K. Starrett, N. E. Christians, and T. Al Austin. 1995. Comparing Chloride Trans­ port in Undisturbed and Disturbed Soil Columns Under Turfgrass Conditions. Commun. Soil Sci. Plant Anal. 26:1283- 1290. DR. STEVE STARRETT is Assistant Professor in the Kansas State University Civil Engineering Department. He guides the scholastic efforts of civil engineering students Judy Hill and Greg Adams. Dr. Shelli Starrett is an Assistant Professor in the KSU Electrical and Computer Engi­ neering Department. Battling the Bermudagrass Blitz Several key practices can help you win the war against bermudagrass encroachment. by CHRIS HARTWIGER Hybrid bermudagrass can encroach rapidly into a putting green. MINIMIZING bermudagrass encroachment into bentgrass or bermudagrass putting greens is a constant challenge for golf course superintendents in warm-weather cli­ mates. The aggressive hybrid bermuda- grasses commonly used on green sur­ rounds can outcompete the bentgrass or bermudagrass used on the greens and often encroach into the putting surface. When this happens, playability can be affected and the original con­ tours of the putting green perimeter can be lost. A variety of chemical and cultural approaches have been used over the years in an attempt to manage en­ croachment problems. Unfortunately, many of these methods have had limited success. This article reviews the problems associated with bermuda­ grass encroachment and discusses the relative effectiveness of different en­ croachment control strategies. Understanding Bermudagrass Encroachment It is easy to understand why ber­ mudagrass encroachment is a problem on bentgrass and bermudagrass greens in southern climates. In the summer months, when bentgrass growth is slowed by high temperatures and/or humidity, the conditions for bermuda­ grass growth are optimal. Bermuda­ grass can and does encroach rapidly into bentgrass putting greens. Ber­ mudagrass greens themselves do not offer much more resistance to encroach­ ment. A more coarse and aggressive hybrid bermudagrass such as Tifway can move into a Tifgreen or Tifdwarf putting surface. After several years of encroachment, the size of a green can decrease and the original design will be lost. Collars Superintendents often select the grass for putting green collars based on its resistance to encroachment. Zoysiagrass and bentgrass are popular choices on bentgrass greens. These grasses do not eliminate encroachment, but act as a buffer between the bent­ grass putting surface and the bermuda­ grass surrounds to slow the movement of bermudagrass into the greens. Before selecting a grass for the collar, it is important to understand the char­ acteristics of each grass type. A bent­ grass collar provides an excellent playing surface most of the year, but is more difficult to maintain in the summer than a zoysia or bermudagrass collar. Specifically, a higher mowing JANUARY/FEBRUARY1997 13 collars. To discourage encroachment, most new courses and renovated courses have extended the bermuda­ grass variety used on the greens and collar at least five feet beyond the col­ lar on all sides of the green. On some new bermudagrass courses designed with closely mowed green slopes in hot climates, the entire green complexes have been established with Tifdwarf. Encroachment in this scenario is highly unlikely. Encroachment Control Measures The type of grass used on collars will dictate the encroachment control methods that are available. Outlined below are several encroachment con­ trol methods currently being used throughout the South today. Chemical Control: Chemicals such as Tupersan, Cutless, or Prograss have been used for many years to suppress bermudagrass encroachment in a bentgrass green. Dr. Bob Carrow and Dr. B. J. Johnson wrote an excellent article on this topic in the November/ December 1991 issue of the Green Section Record. Remember that these chemicals offer a means to suppress bermudagrass in a bentgrass green or collar, but they will not eliminate the bermudagrass. Further, these chemical applications normally result in varying degrees of bentgrass thinning or dis­ coloration. Fusilade is the primary chemical used to suppress bermudagrass in a zoysiagrass collar. Initial use of this product on zoysiagrass collars has given excellent suppression of en­ croaching bermudagrass. Cultural Methods: A wide variety of cultural methods have been used to and will be less competitive with the encroaching bermudagrass. The use of bermudagrass on collars arguably will provide the best playing conditions with the lowest level of management intensity. A hybrid ber­ mudagrass such as Tifway performs well at collar height, thrives on variable soil conditions, and recovers rapidly from injury. Historically, bermudagrass has not been a popular option due to the aggressive encroachment of the bermudagrass into putting greens. In the upper portion of the transition zone, winter injury on bermudagrass collars is a periodic problem as well. However, bermudagrass may become a more popular choice for putting green collars with the development of a new barrier system that is discussed later in this article. On courses with bermudagrass greens, bermudagrass is the over­ whelming and logical choice for the The Greens Encroachment Barrier System is installed in 100-foot sections using a vibratory plow. height on a bentgrass collar will result in a higher evapotranspiration rate. If the root system is limited and cannot meet the plant’s demand for water, wilting can becoming an ongoing problem. This problem may be magnified by the composition of the soil under the collar. If the rootzone mix is tapered from the green to the collars, the varying mix depth will cause a change in available water to the plant. If some or all of the collar is grown on native soil, a similar water availability problem can occur. Putting green and collar water management under these circumstances is time con­ suming and labor intensive. The use of zoysiagrass on collars has become popular in recent years. A properly maintained zoysiagrass collar is aesthetically pleasing and does not detract from playability. Since zoysia­ grass is a warm-season grass, the water management difficulties associated with bentgrass are not as great a concern. If a zoysiagrass collar is estab­ lished, there are a few challenges a superintendent must meet. First, the addition of a zoysiagrass collar creates an environment whereby there are three grasses with three different man­ agement requirements within a span of four to five feet. Balancing the water and nutrient needs of each grass within this small area is difficult. Excessive fertilization and watering are common problems on zoysiagrass collars. The slow recuperative rate of zoysiagrass is another concern that must be addressed. Effective management of mower and foot traffic during the fall, winter, and spring is essential to main­ taining a high-quality zoysiagrass collar. Weak zoysiagrass will be slow to recover during the warmer months 14 USGA GREEN SECTION RECORD The 8-inch depth of the barrier blocks rhizome movement into the green and can act as a wicking barrier between green rootzone material and the soil in the surrounds. prevent bermudagrass encroachment into bentgrass and bermudagrass greens. If a bermudagrass collar is in place, these methods traditionally have been the only means to manage en­ croaching bermudagrass since chemi­ cal control is not an option. Mechanical Edging: Mechanical edging is a labor-intensive task that must be performed regularly through­ out the bermudagrass growing season to maximize its effectiveness. This process can be performed in several ways. Some superintendents physically remove by hand any stolons encroach­ ing into a green. Other superintendents prefer to use a mechanical edger to cut into the soil around the perimeter of the green to sever encroaching stolons or rhizomes. One of the inherent prob­ lems associated with mechanical edging is the creation of a new ber­ mudagrass plant when a stolon or rhizome is severed. The majority of the severed stolons can be physically removed from a green or collar, but any severed rhizomes cannot be removed efficiently from beneath the soil. If this occurs, the severed rhizomes can initiate new roots and begin growing in the putting green or collar. When mechanical edging is used, it is ex­ tremely difficult to maintain the original perimeter of the green. Resodding: Other golf courses have resigned themselves to periodic strip­ ping of contaminated collars, followed by fumigation to eradicate the ber­ mudagrass. Following fumigation, the contaminated areas are resodded. Sur­ prisingly, some areas of bermudagrass may remain following fumigation. Con­ sidering the expense and disruption to play, this approach is not a practical and cost-effective solution for most courses. Physical Barriers: Theoretically, the installation of a physical barrier would offer an effective means to control en­ croachment. Materials such as con­ crete, aluminum, plastic, and wood have all been used in attempts to stop bermudagrass encroachment. Until recently, the major problem associated with these barriers has been movement following installation and a subsequent disruption to play. The Greens Encroachment Barrier System developed by Tom Waite appears to be an alternative to the older barrier methods. Mr. Waite has devel­ oped a heavy plastic barrier that will block encroachment. When installed, this molded plastic barrier extends eight inches into the soil. The molded barrier is characterized by a small “V” or channel. This patented system corrects the previous problems associated with physical barriers. Mr. Waite overcame displacement problems by installing the barrier with a vibratory plow in 100- foot sections. Typically, three sections are needed for a green, and these sec­ tions are securely fastened together. Once the barrier is installed, it is extremely difficult to move. The eight­ inch depth blocks the movement of rhizomes into the green. A reciprocat­ ing edger is used once or twice per week to prevent stolons from en­ croaching above the barrier. Currently, many courses throughout the Southeast have installed the Greens Encroachment Barrier System. The barrier offers several other benefits in addition to providing an excellent means of encroachment control. Be­ cause the barrier is made of a heavy plastic, it can serve as a wicking barrier and help reduce the loss of water from sandy soils when they have direct contact with a clay or other fine-tex­ tured soil. Further, the permanent nature of the barrier ensures that the perimeter of the green will not be lost. Mowing patterns will be more accurate and the green will retain its intended shape much longer than a green with no barrier. Finally, the barrier offers a realistic means to have a bermudagrass collar with little fear of encroachment. At a cost of approximately $2,000 per green, the barrier is an excellent long­ term investment and can eliminate the need for other expensive, time-con­ suming, and labor-intensive encroach­ ment control measures. Conclusion Battling bermudagrass encroach­ ment is difficult for all superintendents in warm climates. Battling encroach­ ment begins with selecting an appro­ priate grass for the collars, understand­ ing the methods available for control, and implementing a sound strategy. CHRIS HARTWIGER splits his time as a USGA Green Section agronomist between the Southeastern and Florida Regions. JANUARY/FEBRUARY1997 15 ON COURSE WITH NATURE THE LIVING DEAD Dead trees offer habitat and sustenance to all living things. by RON DODSON DEAD TREES? Why, you may (wonder, shouldn’t those dead trees on your golf course be cut down? What possible function can a dead tree serve? For wildlife, dead or partially dead standing trees (also called snags) serve as sites for nesting, shelter, and food for the living. Leaving dead and dying trees standing when they don’t pose a safety concern will provide valuable resources to a wide range of wildlife species. Dead trees can also be used to mount bird houses, and by creating more nesting sites, you can increase the breeding success of cavity­ nesting birds. Two main groups of wildlife can benefit from a tree snag program — primary cavity nesters and secondary cavity nesters. Primary cavity nesters are those species that must make their own cavity nest by drilling or pecking it out of the wood of a tree. Secondary cavity nesters make their homes either in cavities made by primary cavity nesters or in holes that have been created by the process of natural decay or damage caused by wind or lightning. It’s good to leave as many snags on the golf course as possible. As a good rule of thumb, some forest managers recommend up to five dead or dying trees per acre. Some golf course man­ agers, with guidance from the Audubon Cooperative Sanctuary System and by educating themselves, have started their own snag manufacturing projects. One method involves cutting away a strip of bark and some of the pithy underlying tissue of a tree to kill it. Others have pruned trees back to such an extent that they will die because of the lack of foliage. These snags become areas of insect activity, fungal growth, and overall decay. This will attract insect-eating wildlife species, some of which will be primary cavity nesters. This could in­ clude all of the woodpecker species or nuthatches. Secondary cavity nesters, like chickadees, tufted titmice, brown creepers, as well as several species of larger birds such as the screech owl Gull Lake View Golf Course (Michigan) left cavity nesting trees standing during construction. 16 USGA GREEN SECTION RECORD and American kestrel, will also use these trees. Some of the larger trees, such as the shagbark hickory, also provide roosting and resting places for several species of bats. Bats are the single most important form of insect­ eating wildlife that flies at night. All of this insect-eating activity is just one benefit of a tree snag program — nature’s own way of controlling pests. Once a snag falls to the ground, it continues to be beneficial to wildlife as a source of food and shelter, and it returns important nutrients to the soil. You may be able to use a fallen snag and other downed limbs, twigs, and debris as part of a brush pile, provid­ ing additional wildlife shelter and protection. Do wildlife a favor and start a snag conservation program if you don’t already have one. Develop a manage­ ment strategy to retain snags in various stages and in a variety of habitats. Monitor snags for safety and develop­ ment of undesirable pest problems. Provide additional nesting sites for birds by leaving snags as a source of shelter and food. Reduce the number of trees and limbs you have to dispose of by leaving them standing to help all of the cavity-nesting forms of wildlife that are looking for homes. And, most important, educate your golfers about the economic and envi­ ronmental benefits of leaving dead trees to enhance habitat and provide nature’s resources for the living. Write a short article for your newsletter, post a sign on a snag explaining its natural resources, take slides and post photos to demonstrate the integration of nature’s way as part of the golf course — a contribution to the environ­ ment as well as to the aesthetic unique­ ness of the course. RON DODSON is president of Audubon International, based in Selkirk, New York. He coordinates the “On Course With Nature” feature for the USGA Green Section Record. ALL THINGS CONSIDERED BUYER... BEWARE Products without active ingredients may not be active! by STANLEY J. ZONTEK CONSIDER THIS STORY. You’re sitting in your office and you don’t feel well. You go to your local drugstore to find something that you hope will make you feel better. You stand at the shelf and pick up a product called “Makes You Feel Good.” Next to it is another product called “Makes You Feel Very Good.” What is your first impulse? You read each label to check their active ingredients. You base your purchase decision on what is contained in the product. This is being a smart consumer, and it makes good common sense. Consider this story. You’re sitting in your office and your turfgrass is under stress. It does not feel well. In walks a salesman with a product or series of products that, according to the sales­ man, will solve your problem and make your grass perform better. You ask the salesman, “What’s in your product?” The answer could in­ clude any number of materials that sound interesting or even logical. You look at the label. Sometimes there is a list of items or benefits like “complex carbohydrates, bio-stimulants, all­ natural ingredients, stimulates bene­ ficial microbes,” etc. Sounds good, but does it work? While there may be a list of ingredients, are active ingredients and nutrient percentages clearly stated or defined on the label? There is a difference. Think about this for a second. If no active ingredients are claimed on the label of a product, there may not be anything active in the product! You ask, “Who else has used this material?” The salesman responds with a long list of turf managers (usually at the best courses in the area) who have purchased the product and who are, according to the salesman, raving about how well it performs. Your next question may be, “Has your product been tested by a univer­ sity?” This is where it can get interest­ ing. Normally, some sort of diplomatic answer is given like, “Well, no, but,” or “We are trying to interest a few univer­ sities in doing some research.” (Believe me, almost any university, for a fee, will test any material.) You are concerned about the health of your grass, so why not give it a try? You reason that it won’t hurt anything; after all, it is natural and just maybe it will help your grass. All too often, a decision to use a product is based upon testimonials, claims by the salesman, and/or a list of interesting ingredients without clearly knowing how the product actually functions. This may not be wise. It can also be expensive. I am seeing a trend in our industry to use more and more “feel good” products, many of which claim no active ingredients. Yet, these products have a long list of claims on the product label — claims, by the way, that do not have to be proven because there are no active ingredients. Let me repeat this point. There seems to be a prolifera­ tion of materials available to the turf manager that claim any number of benefits on the label, but actually con­ tain no active ingredients! Think about it. One respected plant pathologist calls these products muck and magic materials. In the past, these materials were simply referred to as snake oils. The purpose of my opinion article is simple. I want to remind you, the turf manager, that: A. One of the most common sales techniques is to use testimonials, not science. It is easy to claim that a product improves turf quality or solves a problem. However, independent uni­ versity testing under varied conditions is needed to verify these claims. B. Active ingredients are just that; they are chemicals that do a job. Don’t confuse a simple list of ingredients with a list of active ingredients. I am con­ stantly amazed, when reading labels, how many claims are made without a list of active ingredients! I once heard a fellow say, “But will it do any harm?” The answer is, “Probably not.” The real question is, however, “Does it do any good?” C. When looking at a list of ingredi­ ents, it is important to know how much material is actually contained in that product. This is especially important for nutrients. When the need exists, is it more cost effective to spray calcium, for example, onto grass at a rate of only several pounds per acre, or apply lime or gypsum at several hundred to several thousand pounds per acre? It may be a lot cheaper and more effective, in the long term, to use tried-and-true bulk materials versus products that contain only a few pounds of material on a per- acre basis. Are we losing sight of the basics? D. The final purpose of this opinion article is to remind the turf manager to always remember the basics. Never try to do with a feel good chemical what aeration, topdressing, balanced fertility, good water management, and reason­ able mowing heights can accomplish. The late Professor Lawrence S. Dickinson, from the University of Massachusetts, said it best: “Let grass grow, don’t make it grow.” Those are good words to live by. You cannot find this wisdom in a bottle, especially one without any active ingredients! STANLEY J. ZONTEK is the director of the Green Section’s Mid-Atlantic Region. JANUARY/FEBRUARY1997 17 United States Golf Association Green Section Education Conference Tuesday, February 11,1997,1:00 - 3:45 p.m. Las Vegas Convention Center, Room N250 Las Vegas, Nevada Teaching Young Dogs Old Tricks Moderator: James T. Snow, National Director, USGA Green Section 1:00 p.m. Welcome Joe England, USGA Executive Committee 1:15 p.m. Dedman Curves Robert Dedman, CEO, Club Corporation As head of one of the largest golf course management companies, Mr. Dedman successfully applies many principles for achieving success in the golf course industry He will discuss his techniques for working with and motivating people. 1:45 p.m. The Best Turf Tips from the Green Section Staff Patrick O’Brien, Director, Southeastern Region Matt Nelson, Agronomist, Northeastern Region John Foy, Director, Florida Region 2:00 p.m. Sage Advice from a Young Pup Bill Bengeyfield, National Director, USGA Green Section, 1982-1990 In his 34 years with the Green Section, and many other activities in the golf industry, Mr. Bengeyfield has espoused sound golf course management practices worldwide. He will share recurring ideas from his many experiences that are still important today. 2:30 p.m. More of the Best Turf Tips Paul Vermeulen, Director, Mid-Continent Region Bob Vavrek, Agronomist, North-Central Region Mike Huck, Agronomist, Western Region Stanley Zontek, Director, Mid-Atlantic Region 2:50 p.m. That’s Why They Call Them SUPERintendents Judy Bell, President, United States Golf Association The president of the USGA talks about how golf course conditions have changed from her early playing days, and about how she sees golf evolving in the years ahead. 3:20 p.m. The Best Turf Tips Just Keep on Coming David Oatis, Director, Northeastern Region Bob Brame, Director, North-Central Region Larry Gilhuly, Director, Western Region 3:35 p.m. Closing Remarks 18 USGA GREEN SECTION RECORD 1997 GREEN SECTION NATIONAL & REGIONAL CONFERENCES NATIONAL CONFERENCE February 11 Las Vegas Convention Center Las Vegas, Nevada FLORIDA REGION April 14 April 17 Orlando Airport Marriott Palm Beach Gardens Marriott Orlando, Florida Orlando, Florida MID-ATLANTIC REGION March 20 Woodholme Country Club Baltimore, Maryland MID-CONTINENT REGION March 6 March 11 March 12 April 1 Dallas Athletic Club Old Warson Country Club GCSAA Headquarters Des Moines Golf & Country Club Dallas, Texas Ladue, Missouri Lawrence, Kansas Des Moines, Iowa NORTH-CENTRAL REGION March 25 March 27 The American Club Meridian Hills Country Club Kohler, Wisconsin Indianapolis, Indiana NORTHEASTERN REGION March 11 March 18 Country Club of Rochester Marriott Windwatch Hotel Rochester, New York Hauppauge, New York SOUTHEASTERN REGION March 25 April 22 Carmel Country Club Springhouse Golf Club at the Opryland Hotel WESTERN REGION Charlotte, North Carolina Nashville, Tennessee March 5 March 20 March 25 March 31 April 1 April 2 April 3 April 7 Sheridan Holiday Inn Indian Summer Golf & Country Club Lakewood Country Club Industry Hills Golf Course TPC Summerlin Castlewood Country Club Moon Valley Country Club Waialae Country Club Sheridan, Wyoming Lacey, Washington Lakewood, Colorado City of Industry, California Las Vegas, Nevada Pleasanton, California Phoenix, Arizona Honolulu, Hawaii JANUARY/FEBRUARY1997 19 The Proof of a Golfer by EDGAR GUEST The proof of the pudding is the eating they say, But the proof of a golfer is not The number of strokes he takes in a day Or the skill he puts into a shot. There is more to the game than the score which you make Here’s a truth which all golfers endorse: You don’t prove your worth by the shots which you make; But the care which you take of the course. A golfer is more than a ball-driving brute He is more than a mug-hunting czar. To be known as a golfer, you don’t have to shoot, The course of your home club in par. But you do have to love every blade of the grass, Every inch of the fairway and greens. If you don’t take care of the course as you pass, You’re not what “a good golfer” means. Just watch a good golfer some day when you’re out, And note what he does as he plays, He never goes on leaving divots about, Till the grass is put back, there he stays. Observe him in traps as he stands for his shot, Then note when the ball has been played, He never unthinkingly turns from the spot, Till he’s covered the footprints he made. You may brag of your scores and may boast of your skill, You may think as a golfer you’re good; But if footprints you make, in traps you don’t fill, You don’t love the game as you should. For your attitude unto the sport you enjoy, Isn’t proven by brilliance or force; The proof of a golfer — now get this my boy, Is the care that you take of the course. 20 USGA GREEN SECTION RECORD USGA PRESIDENT Judy Bell GREEN SECTION COMMITTEE CHAIRMAN C. McD. England III P.O. Box 58 Huntington, WV 25706 EXECUTIVE DIRECTOR David B. Fay EDITOR James T. Snow ASSOCIATE EDITOR Kimberly S. Erusha, Ph.D. DIRECTOR OF COMMUNICATIONS Marty Parkes ©1996 by United States Golf Association® Subscriptions $15 a year, Canada/Mexico $18 a year, and international $30 a year (air mail). Subscriptions, articles, photographs, and corre­ spondence relevant to published material should be addressed to: United States Golf Association Green Section, Golf House, P.O. Box 708, Far Hills, NJ 07931. Permission to reproduce articles or material in the USGA GREEN SECTION RECORD is granted to newspapers, periodicals, and educa­ tional institutions (unless specifically noted otherwise). Credit must be given to the author, the article’s title, USGA GREEN SECTION RECORD, and the issue’s date. Copyright protection must be afforded. To reprint material in other media, written permission must be obtained from the USGA. In any case, neither articles nor other material may be copied or used for any advertising, promotion, or commercial purposes. GREEN SECTION RECORD (ISSN 0041-5502) is published six times a year in January, March, May, July, September, and November by the UNITED STATES GOLF ASSOCIATION®, Golf House, Far Hills, NJ 07931. Postmaster: Send address changes to the USGA Green Section Record, P.O. Box 708, Golf House, Far Hills, NJ 07931-0708. Periodicals postage paid at Far Hills, NJ, and other locations. Office of Publication, Golf House, Far Hills, NJ 07931. Visit the USGA’s Internet site on the World Wide Web. The address is: http://www.usga.org Turfgrass Information File (TGIF): (800) 446-8443 http://www.lib.msu.edu/tgif GREEN SECTION NATIONAL OFFICES: United States Golf Association, Golf House P.O. Box 708, Far Hills, NJ 07931 • (908) 234-2300 • Fax (908) 781-1736 James T. Snow, National Director Kimberly S. Erusha, Ph.D., Director of Education P.O. Box 2227, Stillwater, OK 74076 • (405) 743-3900 • Fax (405) 743-3910 Michael P. Kenna, Ph.D., Director Construction Education Programs: 720 Wooded Crest, Waco, IX 76712 • (817) 776-0765 • Fax (817) 776-0227 James F. Moore, Director REGIONAL OFFICES: Northeastern Region: PO. Box 4717, Easton, PA 18043 • (610) 515-1660 • Fax (610) 515-1663 David A. Oatis, Director • Matthew C. Nelson, Agronomist 500 N. Main Street, Palmer, MA 01069 • (413) 283-2237 • Fax (413) 283-7741 James E. Skorulski, Agronomist Mid-Atlantic Region: P.O. Box 2105, West Chester, PA 19380-0086 • (610) 696-4747 • Fax (610) 696-4810 Stanley J. Zontek, Director • Keith A. Happ, Agronomist • Darin S. Bevard, Agronomist Southeastern Region: P.O. Box 95, Griffin, GA 30224-0095 • (770) 229-8125 • Fax (770) 229-5974 Patrick M. O’Brien, Director 4770 Sandpiper Lane, Birmingham, AL 35244 • (205) 444-5079 • Fax (205) 444-9561 Christopher E. Hartwiger, Agronomist Florida Region: P.O. Box 1087, Hobe Sound, FL 33475-1087 • (561) 546-2620 • Fax (561) 546-4653 John H. Foy, Director Mid-Continent Region: P.O. Box 1130, Mahomet, IL 61853 • (217) 586-2490 • Fax (217) 586-2169 Paul H. Vermeulen, Director 4232 Arbor Lane, Carrollton, IX 75010 • (972) 492-3663 • Fax (972) 492-1350 Brian M. Maloy, Agronomist North-Central Region: P.O. Box 15249, Covington, KY 41015-0249 • (606) 356-3272 • Fax (606) 356-1847 Robert A. Brame, Director P.O. Box 5069, Elm Grove, WI 53122 • (414) 797-8743 • Fax (414) 797-8838 Robert C. Vavrek, Jr., Agronomist Western Region: 5610 Old Stump Drive N.W, Gig Harbor, WA 98332 (206) 858-2266 • Fax (206) 857-6698 Larry W. Gilhuly, Director 22792 Centre Drive, Suite 290, Lake Forest, CA 92630 (714) 457-9464 • Fax (714) 457-9364 Patrick J. Gross, Agronomist • Michael T. Huck, Agronomist TOW WHSTO I MEET HIGH EXPECTATIONS Question: The golfers at my course have very high expectations, but they don’t give me the budget I need to achieve the conditions they desire. Is there an objective way to determine what is a realistic level of maintenance based on our budget? (California) Answer: Developing a set of golf course maintenance standards can help reconcile the needs of the golfers with your available resources. The superintendent and course officials should work together to develop the guidelines, which should include such items as recommended mowing frequencies, a range of suitable mowing heights, bunker maintenance, course marking, tree pruning, course cleanup, and all other maintenance activities. It is then possible for the superintendent to determine the number of labor hours and resources needed to meet the desired goals and match this with the current budget. In this way, the course officials can see what it actually takes to maintain the golf course, after which they can set priorities accordingly. BY PROVIDING VIABLE ALTERNATIVES Question: Is overseeding fairways with Poa trivialis a viable alternative to avoid spring transition problems? (Arizona) Answer: Some courses have had fairly good results overseeding fairways with Poa trivialis at the rate of 90 lbs. to 100 lbs. per acre. Although the seed is more expensive per pound, it generally is planted at % to % the rate of perennial ryegrass. Poa trivialis will not produce the same brilliant green color as perennial ryegrass; however, the newer cultivars have acceptable winter color without causing significant spring transition problems. It is important to note that Poa trivialis generally takes longer to germinate and may totally transition in the spring before bermudagrass resumes active growth. If your goal is to avoid transition problems, you may wish to try Poa trivialis. If winter color is the primary concern, you may be better off overseeding with perennial ryegrass at a reduced rate. TO TRAFFIC TROUBLES Question: The daily-fee golf course I manage receives about 50,000 rounds of golf a year. Needless to say, wear injury from cart traffic is a problem. I have tried requiring carts on paths at certain times, but the golfers loudly object and it seems like this policy is more trouble than it is worth. Any suggestions for this problem? (Florida) Answer: A good solution would be to require carts on the path on one hole on the front nine and one hole on the back nine each week. After nine weeks, each hole has received a reduction in traffic of approximately 11 percent. This policy should be started early in the season before cart traffic has caused significant problems. Of course, during extremely wet periods, requiring carts to remain on the path is needed to protect the course from severe damage.