College of Agriculture & Natural Resources

Permanent URI for this communityhttp://hdl.handle.net/1903/1598

The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

Browse

Subject: search.filters.subject.SWAT

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Assessing Crop Water Productivity under Different Irrigation Scenarios in the Mid–Atlantic Region
    (MDPI, 2021-06-30) Paul, Manashi; Negahban-Azar, Masoud; Shirmohammadi, Adel
    The continuous growth of irrigated agricultural has resulted in decline of groundwater levels in many regions of Maryland and the Mid–Atlantic. The main objective of this study was to use crop water productivity as an index to evaluate different irrigation strategies including rainfed, groundwater, and recycled water use. The Soil and Water Assessment Tool (SWAT) was used to simulate the watershed hydrology and crop yield. It was used to estimate corn and soybean water productivity using different irrigation sources, including treated wastewater from adjacent wastewater treatment plants (WWTPs). The SWAT model was able to estimate crop water productivity at both subbasin and hydrologic response unit (HRU) levels. Results suggest that using treated wastewater as supplemental irrigation can provide opportunities for improving water productivity and save fresh groundwater sources. The total water productivity (irrigation and rainfall) values for corn and soybean were found to be 0.617 kg/m3 and 0.173 kg/m3, respectively, while the water productivity values for rainfall plus treated wastewater use were found to be 0.713 kg/m3 and 0.37 kg/m3 for corn and soybean, respectively. The outcomes of this study provide information regarding enhancing water management in similar physiographic regions, especially in areas where crop productivity is low due to limited freshwater availability.
  • Thumbnail Image
    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.
  • Thumbnail Image
    Item
    Evaluation of SWAT Model Applicability for Waterbody Impairment Identification and TMDL Analysis
    (2007-10-30) Sexton, Aisha M; Shirmohammadi, Adel; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The U.S. EPA's Total Maximum Daily Load (TMDL) program has encountered hindrances in its implementation partly because of its strong dependence on mathematical models to set limitations on the release of impairing substances. The uncertainty associated with predictions of such models is often not formally quantified and typically assigned as an arbitrary safety factor to the margin of safety (MOS) portion of TMDL allocations. AVSWAT-X, a semi-distributed, watershed-scale model, was evaluated to determine its applicability to identify the impairment status and tabulate a nutrient TMDL for a waterbody located in the Piedmont physiographic region of Maryland. The methodology for tabulating the nutrient TMDL is an enhancement over current methods used in Maryland. The mean-value first-order reliability method (MFORM) was used to calculate variance in output variables with respect to input parameter variance and the MOS value was derived based on the level confidence in meeting the water quality standard. A calibration, validation and an uncertainty analysis was conducted on the AVSWAT-X model. Monthly results indicated that AVSWAT-X is a good predictor of streamflow, a moderate (at best) predictor of nutrient loading and a poor predictor of sediment loading. Improved performance was observed on an annual basis for nitrate and sediment loadings, indicating the most appropriate use of SWAT for long-term simulations. The most pronounced reason for discrepancies in model performance was the use of the SCS curve number method to tabulate surface runoff. Uncertainty results indicated that input parameters that are highly sensitive may not necessarily contribute the largest amount of uncertainty to model output. The largest amount of variance in output variables occurred during wet periods. Predicted sediment output had the largest amount of variability around its mean, followed by nitrate, phosphate, and streamflow as indicated by average annual coefficients of variation of 28%, 19%, 17%, and 15%, respectively. The methodology used in this study to quantify the nitrate TMDL and the MOS associated with it, was a useful tool and an improvement over current methods of nutrient TMDL analysis in Maryland. Overall, AVSWAT-X is a moderate to good model for estimating waterbody impairment and conducting TMDL analysis of waterbodies impaired by nutrients.