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Nonpoint source (NPS) pollution is a pressing issue worldwide, especially in the Chesapeake Bay, where sediment, nitrogen (N), and phosphorus (P) are the most critical water quality concerns. Despite significant efforts by federal, state, and local governments, the improvement in water quality has been limited. Investigating the spatial distribution of NPS hotspots can help understand NPS pollutant output and guide control measures. We hypothesize that as land cover changes from natural (e.g., forestland) and agricultural to suburban and ultra-urban, the distribution of NPS pollution source areas becomes increasingly spatially uniform. To test this hypothesis, we analyzed three real watersheds with varying land cover (Greensboro watershed for agriculture, Watts Branch watershed for suburban, and Watershed 263 for ultra-urban) and three synthetic watersheds developed based on the Watts Branch watershed, which ranged from forested and agricultural to ultra-urban but had the same soil, slope, and weather conditions. The Soil and Water Assessment Tool (SWAT) was selected as a phenomenological model for the analysis, and SWAT-CUP was used for model calibration and validation. The hydrologic responses of the three real and synthetic watersheds were simulated over ten years (1993–2002 or 2002–2011), and calibration and validation results indicated that SWAT could properly predict the export of runoff and three target NPS pollution constituents (sediment, total nitrogen, and total phosphorus). The results showed that the distribution of NPS pollutant outputs becomes increasingly uniform as land cover changes from agriculture to ultra-urban across watersheds. This research suggests that the spatial distribution of NPS pollution source areas is a function of the major land cover category of study watersheds, and control strategies should be adapted accordingly. If NPS pollution is distributed unevenly across a watershed, hotspot areas output a disproportionate amount of pollution and require more targeted and intensive control measures. Conversely, if the distribution of NPS pollution is more uniform across a watershed, the control strategies need to be more widespread and encompass a larger area. 

Groundwater is the main source of irrigation and residential use in the Eastern Shore Maryland, which is experiencing challenges regarding overuse, saltwater intrusion, and diminishing productivity. The Chesapeake Bay is also facing the problem of water pollution due to pollutant loading from agricultural fields and wastewater treatment plants (WWTPs). Using recycled water for irrigation has the potential to alleviate the pressure on groundwater and reduce pollutant loading. The objective of this study was to develop a decision tool to explore the use of recycled water for agricultural irrigation in Maryland using Multicriteria Decision Analysis (MCDA) integrated with Geographical Information Systems (GIS). Four main evaluation criteria were included in the GIS-MCDA framework: agricultural land cover, climate, groundwater vulnerability, and characteristics of the WWTPs as sources of recycled water. Groundwater vulnerability zones were developed using the groundwater well density, water extraction data, and the aquifer information. Then, the most suitable areas for irrigation using recycled water were identified. About 13.5% and 32.9% of agricultural land was, respectively, found to be “highly” and “moderately” suitable for irrigation with recycled water when WWTPs were categorized based on their treatment process information. The results provide a useful decision tool to promote the use of recycled water for agricultural irrigation. 

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.