Search

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.

Climate variability and farmers’ desire to improve the crop yield have resulted in an increase in irrigated agriculture in the mid-Atlantic region. However, the huge initial capital cost associated with the installation and operation of irrigation systems is generally prohibitive, with most farmers finding difficulty in justifying the expenditure, and uncertainty of the overall return on their investment. The objective of this study was to develop a decision tool for farmers in temperate regions to evaluate the cost-benefit of irrigation installations. The developed irrigation economic model involved the development of an economic component that balances the expected economic return, based on anticipated crop yield increases due to supplemental irrigation, versus the water, maintenance, and capital costs associated with the irrigation system. Model development included the input of relevant data and required local calibration. Soil and Water Assessment Tool (SWAT) output files were used as the basis for data input into the irrigation economic model. An irrigation-scheduling component was incorporated into the model to prescribe irrigation volumes for each agricultural field defined within the area of interest. The economic component of the model identifies and prioritizes those fields in which supplemental irrigation will result in the greatest economic return in terms of increased agricultural production and revenue. The study is conducted on the Pocomoke river basin in the Coastal Plain of Maryland’s eastern shore. Results showed that irrigation system selection was mainly influenced by cost of water and irrigation installation costs, and to a lesser extent by physical characteristics of the terrain and the associated properties.

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.

Hennig Brandt's discovery of phosphorus (P) occurred during the early European colonization of the Chesapeake Bay region. Today, P, an essential nutrient on land and water alike, is one of the principal threats to the health of the bay. Despite widespread implementation of best management practices across the Chesapeake Bay watershed following the implementation in 2010 of a total maximum daily load (TMDL) to improve the health of the bay, P load reductions across the bay's 166,000-km(2) watershed have been uneven, and dissolved P loads have increased in a number of the bay's tributaries. As the midpoint of the 15-yr TMDL process has now passed, some of the more stubborn sources of P must now be tackled. For nonpoint agricultural sources, strategies that not only address particulate P but also mitigate dissolved P losses are essential. Lingering concerns include legacy P stored in soils and reservoir sediments, mitigation of P in artificial drainage and stormwater from hotspots and converted farmland, manure management and animal heavy use areas, and critical source areas of P in agricultural landscapes. While opportunities exist to curtail transport of all forms of P, greater attention is required toward adapting P management to new hydrologic regimes and transport pathways imposed by climate change.

Hennig Brandt's discovery of phosphorus (P) occurred during the early European colonization of the Chesapeake Bay region. Today, P, an essential nutrient on land and water alike, is one of the principal threats to the health of the bay. Despite widespread implementation of best management practices across the Chesapeake Bay watershed following the implementation in 2010 of a total maximum daily load (TMDL) to improve the health of the bay, P load reductions across the bay's 166,000-km(2) watershed have been uneven, and dissolved P loads have increased in a number of the bay's tributaries. As the midpoint of the 15-yr TMDL process has now passed, some of the more stubborn sources of P must now be tackled. For nonpoint agricultural sources, strategies that not only address particulate P but also mitigate dissolved P losses are essential. Lingering concerns include legacy P stored in soils and reservoir sediments, mitigation of P in artificial drainage and stormwater from hotspots and converted farmland, manure management and animal heavy use areas, and critical source areas of P in agricultural landscapes. While opportunities exist to curtail transport of all forms of P, greater attention is required toward adapting P management to new hydrologic regimes and transport pathways imposed by climate change.

To reduce nutrient pollution in urban watersheds, residents need to voluntarily practice a range of stormwater Best Management Practices (BMPs). However, little is known about the underlying social factors that may act as barriers to BMP implementation. The overall goal of this study was to better understand barriers to BMP implementation by exploring the links among resident demographics, knowledge, and behaviors so that appropriate education can be more effectively developed and targeted. In 2014-2015, a detailed questionnaire was administered door-to-door to 299 randomly selected households in two sub-watersheds of the Chesapeake Bay basin to test relationships among resident demographics, knowledge and attitudes towards water resources and BMPs, and BMP implementation. Multifactor regression models showed that respondents who had greater knowledge of water resources and BMPs lived in households that implemented greater numbers of BMPs. In turn, resident BMP knowledge, or familiarity with BMPs, strongly varied with race and ownership status, with respondents who identified as Caucasian or within a collection of `Other' races, and who were home owners, having greater BMP knowledge than respondents who identified as African American and who were home renters, respectively. Renters and members of homeowner's associations were also less likely to implement BMPs independent of knowledge, possibly reflecting perceived or real bureaucratic or procedural barriers to good stormwater management. Overall, respondents preferred to receive educational materials on stormwater via pamphlets and YouTube videos. These results suggest that resident ownership status knowledge is important to determining the number of household BMPs, and that education outreach should probably target African American and renting households that have lower BMP knowledge and landlords and administrators of homeowner's associations using well-planned print and video educational media.

Biological mass transport processes determine the behavior and function of cells, regulate interactions between synthetic agents and recipient targets, and are key elements in the design and use of biosensors. Accurately predicting the outcomes of such processes is crucial to both enhancing our understanding of how these systems function, enabling the design of effective strategies to control their function, and verifying that engineered solutions perform according to plan. A Galerkin-based finite element model was developed and implemented to solve a system of two coupled partial differential equations governing biomolecule transport and reaction in live cells. The simulator was coupled, in the framework of an inverse modeling strategy, with an optimization algorithm and an experimental time series, obtained by the Fluorescence Recovery after Photobleaching (FRAP) technique, to estimate biomolecule mass transport and reaction rate parameters. In the inverse algorithm, an adaptive method was implemented to calculate sensitivity matrix. A multi-criteria termination rule was developed to stop the inverse code at the solution. The applicability of the model was illustrated by simulating the mobility and binding of GFP-tagged glucocorticoid receptor in the nucleoplasm of mouse adenocarcinoma. The numerical simulator shows excellent agreement with the analytic solutions and experimental FRAP data. Detailed residual analysis indicates that residuals have zero mean and constant variance and are normally distributed and uncorrelated. Therefore, the necessary and sufficient criteria for least square parameter optimization, which was used in this study, were met.The developed strategy is an efficient approach to extract as much physiochemical information from the FRAP protocol as possible. Well-posedness analysis of the inverse problem, however, indicates that the FRAP protocol provides insufficient information for unique simultaneous estimation of diffusion coefficient and b