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- Title
- A stochastic multi-scale model of stream-groundwater interaction in strongly heterogeneous porous medium and its application in southern Branch County, Michigan
- Creator
- Xinyu, Ye
- Date
- 2014
- Collection
- Electronic Theses & Dissertations
- Description
-
In this paper, stream depletion is assessed by the approach of multi-scale geostatistics in stressed watershed, South Branch County, Michigan. The watershed is currently under large water demand and representative of the general failure to pass the online Water Withdrawal Assessment Tool. Due to the heterogeneity of porous medium and the high variability of hydrogeological parameters and scale, there is a deviation between field observations and simulated groundwater flow in those areas. The...
Show moreIn this paper, stream depletion is assessed by the approach of multi-scale geostatistics in stressed watershed, South Branch County, Michigan. The watershed is currently under large water demand and representative of the general failure to pass the online Water Withdrawal Assessment Tool. Due to the heterogeneity of porous medium and the high variability of hydrogeological parameters and scale, there is a deviation between field observations and simulated groundwater flow in those areas. The approach of multi-scale geostatistics model based on detailed lithological data and its application in numerical groundwater simulation can be used in stream depletion assessment. Specifically, the multi-scale transition probability geostatistics approach, supplemented with a 10m Digital Elevation Model, allows for a more realistic integration of heterogeneous medium into the development of correlated spatial variability of hydrogeological parameters at each spatial scale. This approach enables accurate simulation of complex hydrogeology, including vertical shift structural variation and aquifer thickness variations. Systematic hydrology models at the regional, local and site scale allows for simulations of integrated water budget analysis. These simulations are necessary to evaluate the water depletions of targeted streams and the surrounded protected area. The hydrology system is calibrated with the steady state water levels from 732 monitoring wells.The stability of transition probability geostatistics model depends on the distributions, the heterogeneity of simulated area and other factors. The results show that transition probability geostatistics model provides a reasonable distribution of materials in aquifer medium, improving numerical groundwater modeling in assessing water depletion in streams and venerable area.
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- Title
- Can a credit-insurance package increase the adoption of a modern variety package? : an application to Honduran dry bean farmers
- Creator
- Pejuan Ucles, Wolfgang Baudino
- Date
- 2015
- Collection
- Electronic Theses & Dissertations
- Description
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ABSTRACTCAN A CREDIT-INSURANCE PACKAGE INCREASE THE ADOPTION OF A MODERN VARIETY PACKAGE?: AN APPLICATION TO HONDURAN DRY BEAN FARMERSByWolfgang Baudino Pejuan UclesAs farmers face an expected income-risk tradeoff, they can only obtain a higher expected income by increasing their exposure to risk. Many farmers choose low-yielding technologies (e.g., traditional varieties) with lower yield variability over high-yielding technologies (e.g., modern varieties) with higher yield variability....
Show moreABSTRACTCAN A CREDIT-INSURANCE PACKAGE INCREASE THE ADOPTION OF A MODERN VARIETY PACKAGE?: AN APPLICATION TO HONDURAN DRY BEAN FARMERSByWolfgang Baudino Pejuan UclesAs farmers face an expected income-risk tradeoff, they can only obtain a higher expected income by increasing their exposure to risk. Many farmers choose low-yielding technologies (e.g., traditional varieties) with lower yield variability over high-yielding technologies (e.g., modern varieties) with higher yield variability. Farmers' lack of liquidity at planting time exacerbates the income-risk tradeoff by raising the cost of investing in modern varieties--hence, making yield uncertainty even more daunting. The objective of this study is to assess the potential of a credit-insurance package to increase farmer adoption of modern bean varieties and complementary inputs (e.g., fertilizer) and thereby increase bean farmers' gross income in Honduras. The specific objectives are to: 1) assess if the change from a traditional variety to a modern variety is profitable, and if the change from a traditional variety package to a modern variety package is profitable, 2) assess farmers' exposure to price risk, perceived yield risk, and consumption risk, 3) identify how farmers currently cope with shocks, 4) evaluate the existing insurance policies for bean farms adopting modern varieties to observe the extent of risk transfer and load in excess of the actuarial fair rate, and propose alternative policies that improve risk transfer, and 5) assess the benefits of a credit-insurance package for bean farmers in Honduras.The change from a traditional variety package to a modern variety package is profitable as it is shown with partial budgets together with the marginal income from fertilizer compared to its marginal cost. However, farmers face price risk at a level of approximately 20% coefficient of variation (CV) for both beans and corn, and a yield risk at a range of approximately 32%-34% CV for beans depending on the bean technology, and 32% CV for corn. Currently farmers in Honduras are offered catastrophic crop insurance policies (i.e., coverages of 45%) with high loads to the premium (i.e., 3-5) that do not provide high levels of risk transfer, although it provides the means to grow another crop in case of a peril striking. Thus, farmers decide to mainly cope with shocks by working in another job besides their crop enterprise (50%), selling their assets (24%), and asking for a loan from friends, family or other person (14%). Simulations, using a multiperiod stochastic model where households maximize expected consumption utility, were used to evaluate farmers' decisions on obtaining credit and purchasing crop insurance. Farmers' elicited probability distributions together with secondary data and expert opinion were used for specifying the stochastic element in the simulation.Farmers under general conditions would be benefited by a subsidized credit-insurance package (i.e., load of 1.0) that enables them to change from a traditional variety package (i.e., low fertilizer and traditional seed) to a modern variety package (i.e., high fertilizer level and modern seed). The specific conditions in which insurance would benefit are when farmers are highly risk averse and do not need credit for crop production and living in villages with relatively high prices, or, moderately risk averse farmers that need credit in villages with relatively high prices. It is advisable to revisit the approach of estimating the yield probability distributions due to the problems encountered.
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- Title
- Stochastic modeling of routing protocols for cognitive radio networks
- Creator
- Soltani, Soroor
- Date
- 2013
- Collection
- Electronic Theses & Dissertations
- Description
-
Cognitive radios are expected torevolutionize wireless networking because of their ability tosense, manage and share the mobile available spectrum.Efficient utilization of the available spectrum could be significantly improved by incorporating different cognitive radio based networks. Challenges are involved in utilizing the cognitive radios in a network, most of which rise from the dynamic nature of available spectrum that is not present in traditional wireless networks. The set of available...
Show moreCognitive radios are expected torevolutionize wireless networking because of their ability tosense, manage and share the mobile available spectrum.Efficient utilization of the available spectrum could be significantly improved by incorporating different cognitive radio based networks. Challenges are involved in utilizing the cognitive radios in a network, most of which rise from the dynamic nature of available spectrum that is not present in traditional wireless networks. The set of available spectrum blocks(channels) changes randomly with the arrival and departure of the users licensed to a specific spectrum band. These users are known as primary users. If a band is used by aprimary user, the cognitive radio alters its transmission power level ormodulation scheme to change its transmission range and switches to another channel.In traditional wireless networks, a link is stable if it is less prone to interference. In cognitive radio networks, however, a link that is interference free might break due to the arrival of its primary user. Therefore, links' stability forms a stochastic process with OFF and ON states; ON, if the primary user is absent. Evidently, traditional network protocols fail in this environment. New sets of protocols are needed in each layer to cope with the stochastic dynamics of cognitive radio networks.In this dissertation we present a comprehensive stochastic framework and a decision theory based model for the problem of routing packets from a source to a destination in a cognitive radio network. We begin by introducing two probability distributions called ArgMax and ArgMin for probabilistic channel selection mechanisms, routing, and MAC protocols. The ArgMax probability distribution locates the most stable link from a set of available links. Conversely, ArgMin identifies the least stable link. ArgMax and ArgMin together provide valuable information on the diversity of the stability of available links in a spectrum band. Next, considering the stochastic arrival of primary users, we model the transition of packets from one hop to the other by a Semi-Markov process and develop a Primary Spread Aware Routing Protocol (PSARP) that learns the dynamics of the environment and adapts its routing decision accordingly. Further, we use a decision theory framework. A utility function is designed to capture the effect of spectrum measurement, fluctuation of bandwidth availability and path quality. A node cognitively decides its best candidate among its neighbors by utilizing a decision tree. Each branch of the tree is quantified by the utility function and a posterior probability distribution, constructed using ArgMax probability distribution, which predicts the suitability of available neighbors. In DTCR (Decision Tree Cognitive Routing), nodes learn their operational environment and adapt their decision making accordingly. We extend the Decision tree modeling to translate video routing in a dynamic cognitive radio network into a decision theory problem. Then terminal analysis backward induction is used to produce our routing scheme that improves the peak signal-to-noise ratio of the received video.We show through this dissertation that by acknowledging the stochastic property of the cognitive radio networks' environment and constructing strategies using the statistical and mathematical tools that deal with such uncertainties, the utilization of these networks will greatly improve.
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