Theses and Dissertations from UMD
Permanent URI for this communityhttp://hdl.handle.net/1903/2
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item APPLICATION OF RECLAIMED WASTEWATER FOR AGRICULTURAL IRRIGATION: DEVELOPING A DECISION SUPPORT TOOL USING SPATIAL MULTI-CRITERIA DECISION ANALYSIS(2020) Paul, Manashi; Negahban-Azar, Masoud; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Intensified climate variability, depleting groundwater, and escalating water demand create severe stress on high-quality freshwater sources used for agricultural irrigation. These challenges necessitate the exploration of alternative water sources such as reclaimed water to reduce the pressure on freshwater sources. To do so, it is key to investigate the spatial pattern of areas that are more suitable for water reuse to determine the potential of reclaimed wastewater use for irrigation. This study provides a systematic decision-analysis framework for the decision-makers using an integrated process-based hydrologic model for sustainable agricultural water management. The outcomes of this study provide evidence of the feasibility of reclaimed wastewater use in the agricultural sector. The two objectives of this study were to: 1) identify the locations that are most suitable for the reclaimed wastewater use in agriculture (hotspots); and 2) develop the watershed-scale models to assess the agricultural water budget and crop production using different water conservation scenarios including reclaimed wastewater use. To achieve the first objective, a decision-making framework was developed by using the Geographic Information System and Multi-Criteria Decision Analysis (GIS-MCDA). This framework was then tested in the Southwest (California), and the Mid-Atlantic (Maryland) regions. Based on WWTPs’ proximity, sufficient water availability, and appropriate treatment process of the treated wastewater, the “Most Suitable” and “Moderately Suitable” agricultural areas were found to be approximately 145.5 km2, and 276 km2 for California and, 26.4 km2 and 798.8 km2 for Maryland, respectively. These results were then used to develop the hydrologic models to examine water conservation and water reuse scenarios under real-world conditions, using the Soil and Water Assessment Tool (SWAT). In California, the combination of auto irrigation (AI) and regulated deficit irrigation (RDI) resulted in higher WP for both almond and grape (> 0.50 kg/m3). Results also suggested that the wastewater reuse in almond and grape irrigation could reduce groundwater consumption more than 74% and 90% under RDI and AI scenarios, respectively. For Maryland, model simulations suggested that the green water productivity (only rainfall) can be improved up to 0.713 kg/m3 for corn and 0.37 kg/m3 for soybean under the reclaimed wastewater use scenario.Item INTEGRATED ECONOMIC DECISION SUPPORT SYSTEM MODEL FOR DETERMINING IRRIGATION APPLICATION AND PROJECTED AGRICULTURAL WATER DEMAND ON A WATERSHED SCALE(2006-11-27) Hanna, Kalim; Shirmohammadi, Adel; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study involves the development of an irrigation economic model used to determine the estimated net benefit of various irrigation systems when used in temperate zones. The model processes SWAT (Soil and Water Assessment Tool) output data together with user supplied economic data as a basis for identifying agricultural fields likely to result in the greatest economic return for irrigation installations, based on irrigation installation costs, water costs, and the expected revenue from increased yields due to applied water. The model is capable of not only identifying those agricultural fields within the area of interest likely to result in the greatest net benefit, but is able to prescribe the most profitable irrigation system from an array of possible systems, based on user supplied economic and performance data. The model can also be used to determine the optimal average monthly irrigation volume to be applied to a given field, by balancing the expected revenue due to the estimated yield increase as a result of irrigation application verses the cost of water. The model is applied in this study to a range of water cost levels and crop types from which general conclusions about the use of irrigation in temperate zones are made. The primary product of this study is an irrigation economic tool capable of determining the profitability of irrigation installations verses non-irrigated systems for a wide range of hydrological and environmental conditions. The project included the collection and compilation of required data on land-use, topography, and soil properties, into a GIS project, used as a data input basis for the SWAT model. For demonstration purposes the model is applied to the Pocomoke River basin located in the Coastal Plain of Maryland's Eastern Shore. Input data for the model is taken from multiple SWAT simulations for various crops, modeled with a statistically generated artificial weather pattern typical of the region. Further analysis is conducted on the environmental impact of irrigation, using SWAT model simulations over a range of irrigation application levels. General conclusions are drawn on the effects of irrigation on water quality parameters and the nutrient/sediment transport processes involved.