Environmental Science & Technology Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2748
Browse
14 results
Search Results
Item MODELING GROUNDWATER FLUCTUATIONS IN THE COASTAL PLAIN OF MARYLAND: AN ANN POWERED STRATEGY(2024) Steeple, Jennifer Lynne; Negahban-Azar, Masoud; Shirmohammadi, Adel; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Groundwater management in the face of climate change presents a critical challenge with far-reaching implications for water resource sustainability. This study evaluates the effectiveness of Artificial Neural Networks (ANNs) as predictive tools for estimating current groundwater levels and forecasting future groundwater levels in the Aquia aquifer in the Coastal Plain ofMaryland. The groundwater levels of the Aquia aquifer have declined under the pressures of land use change, increases in agricultural irrigation, and population growth. We tested, trained, and employed eight county-level artificial neural network (ANNs) models to predict and project Aquia aquifer groundwater levels for the near (2030-2050) and far (2050-2100) future under two socio-economic pathways (SSP245 and SSP585). The models exhibited significant predictive performance during testing (R²= 0.82-0.99). Minimum temperature and population were the most influential variables across all county-based models. When used to forecast groundwater level under two climate scenarios, the models predicted declining groundwater levels over time in Calvert, Caroline, Queen Anne’s, and Kent counties, aligning with regional trends in the Aquia aquifer. Conversely, Anne Arundel, Charles, St. Mary’s, and Talbot counties exhibited projected increases in groundwater levels, likely influenced by correlations with the variable irrigated farm acreage, underscoring the importance of considering nonlinear relationships and interactions among variables in groundwater modeling. The study highlights the ability of ANNs to accurately predict county-scale groundwater levels, even with limited data, indicating their potential utility for informing decision-making processes regarding water resource management and climate change adaptation strategies. This study also assessed the usability of multiple methods to fill in the missing data and concluded that using the repeated groundwater level data still resulted in powerful ANN models capable of both predicting and forecasting ground water levels in the Coastal Plain of Maryland.Item SUSTAINABLE WATER RESOURCES MANAGEMENT THROUGH AGRICULTURAL WATER REUSE: APPLICATION OF A DECISION SUPPORT SYSTEM(2022) SHOUSHTARIAN, FARSHID; NEGAHBAN-AZAR, MASOUD; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The water crisis caused by climate change, population growth, high urbanization rate, lifestyle changes, and industrialization has decreased global access to safe freshwater resources. As the primary food-producing and the largest water-consuming sector, agriculture heavily depends on water availability. Incorporating alternative water supplies (e.g., water reuse) can reduce freshwater demands, addressing water crisis consequences. Water reuse generally includes recycling treated effluent (known as recycled water) from wastewater treatment plants for different applications (e.g., agricultural irrigation). This alternative water resource can reliably and sustainably increase the resiliency of agriculture to water shortage. However, the complexities inherent in water resources management and the challenges associated with water reuse make planning and managing agricultural water reuse practices demanding. Agricultural water reuse projects include many interrelated/ interconnected components, including the human (e.g., farmers) and technical (e.g., engineering and natural infrastructures) components. The abilities of existing models are limited in simulating these components’ complex and adaptive behaviors. It is necessary to utilize tools capable of capturing these complexities and adaptations to plan and manage agricultural water reuse practices sustainably.The main research question of this dissertation was: How to capture the complex and adaptive dynamics of socio-hydrological systems inherent in sustainable water resources management when alternative water sources are introduced in the water supply system? The primary focus of the dissertation was to develop a dynamic decision support system that can successfully simulate the complexities and adaptations inherent in agricultural water reuse practices. It aims at increasing the existing knowledge regarding agricultural water reuse planning and management and help water resource decision-makers make sustainable and better-informed decisions in agricultural water reuse practices. To accomplish this goal, first, the literature was thoroughly reviewed to identify, collect, and analyze the data related to agricultural water reuse (e.g., current agricultural water reuse regulations and guidelines). Second, two models were developed using a “bottom-up” approach to study two agricultural water reuse practices in the Southwest (CA) and Mid-Atlantic (MD-DE) regions. These two models were used to further study the dynamics of agricultural water reuse adoption by farmers and their impacts on local water resources. The results showed that the regulations and guidelines were mainly human health centered, insufficient regarding some potentially dangerous pollutants such as emerging constituents, and with large discrepancies when compared with each other. In addition, some important water quality parameters, such as pathogens, heavy metals, and salinity, were only included in a few of the regulations and guidelines investigated in this study. Finally, specific treatment processes were only mentioned in some of the regulations and guidelines, with high levels of discrepancy. Moreover, results showed that agricultural water reuse adoption by farmers is a gradual and time-consuming process. In addition, results also showed that agricultural water reuse could significantly decrease the water shortage (by 57.7%) and groundwater withdrawal (by 74.1%) in CA. The results also showed that climate change and recycled water storage capacity and unit price were among the top factors with significant influence on agricultural water reuse practice studied in this dissertation. This study demonstrated the importance of conducting time-varying sensitivity analysis for complex simulation models. Furthermore, results demonstrated that implementing agricultural water reuse could decrease farmers' water shortage, groundwater consumption, and surface water consumption (by almost 19.5 %) in MD. This dissertation’s results can help decision-makers effectively take advantage of agricultural water reuse projects and other alternative water resources to plan and manage water resources sustainably.Item DYNAMICS OF PHYTOPLANKTON POPULATIONS IN IRRIGATION PONDS(2022) Smith, Jaclyn Elizabeth; Hill, Robert L; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The dynamics of phytoplankton community structure in two agricultural irrigation ponds located in Maryland, USA were evaluated. Stable spatiotemporal patterns and zones of consistently higher and consistently lower phytoplankton functional group concentrations were established for both ponds. Moderate and strong correlations were found between the spatial patterns of several water quality parameters and phytoplankton concentrations. Additionally, zones of consistently higher and lower concentrations were found for the cyanobacteria pigment, phycocyanin. Chlorophyll, colored dissolved organic matter, and turbidity were the most influential predictors for phycocyanin concentrations. The prediction of phytoplankton community structure from water quality measurements with the random forest machine learning algorithm was possible and easily measured physicochemical parameter models offered the best model performance. Results of this work indicate that in-situ water quality measurements may be a cost-effective and faster alternative to time-intensive microscopy analysis of phytoplankton, allowing for more efficient water quality monitoring.Item Monitoring and Predicting the Microbial Water Quality in Irrigation Ponds(2022) Stocker, Matthew Daniel; Hill, Robert L; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Small- to medium-sized farm ponds are a popular source of irrigation water and provide a substantial volume of water for crop growth in the United States. The microbial quality of irrigation waters is assessed by measuring concentrations of the fecal indicator bacteria Escherichia coli (E. coli). Minimal guidance currently exists on the use of surface irrigation waters to minimize consumer health risks. The overall objective of this work was to provide science-based guidance for microbial water quality monitoring of irrigation ponds. Spatial and temporal patterns of E. coli were evaluated in two Maryland irrigation ponds over three years of observations. Patterns of E. coli were stable over the three years and found to be significantly correlated to patterns of water parameters such as temperature, dissolved oxygen, turbidity, and pH. The EPA Environmental Fluid Dynamics Code model was used to evaluate the spatial 3D heterogeneity of E. coli concentrations within the ponds. Significant differences in E. coli concentrations by sampling depth were found. Spatial heterogeneity of E. coli within the pond also resulted in substantial temporal variation at the irrigation pump, which was dependent on the intake location. Diurnal variation of E. coli concentrations was assessed for three farm ponds. E. coli concentrations declined from 9:00 to 15:00 for each pond, but statistically significant declines were only observed in two of the three ponds. Dissolved oxygen, pH, and electrical conductance were found to be the most influential environmental variables affecting E. coli concentrations. To better describe the relationships between E. coli and the environmental variables, four machine learning algorithms were used to estimate E. coli concentrations using water quality parameters as predictors. The random forest algorithm provided the highest predictive accuracy with R2 = 0.750 and R2 = 0.745 for Ponds 1 and 2, respectively, in the multi-year dataset containing 12 predictors. Temperature, electrical conductance, and organic matter content were identified as the most influential predictors. It is anticipated that the recommendations contained in this dissertation will be used to improve microbial monitoring strategies and protect public health.Item Extending the Cover Crop Growing Season to Reduce Nitrogen Pollution(2021) Sedghi, Nathan; Weil, Ray R; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Maryland currently has the highest rate of cover crop use in the United States. The Cover Crop Program, started as an initiative to clean nutrients from the Chesapeake Bay, has made it a common practice to plant a cereal cover crop after cash crop harvest in fall, and kill it several weeks before cash crop planting in spring. In Maryland, this practice does not allow enough growing time with warm conditions for optimal cover crop growth. Planting earlier in fall and killing a cover crop later in spring could improve soil N cycling. We hypothesized that interseeding into a cash crop in early fall, and delaying spring cover crop termination could increase cover crop biomass, carbon accumulation, and nitrogen uptake and decrease nitrate leached. We tested these hypotheses over four years with five field experiments, consistently using a brassica-legume-cereal cover crop mix. We evaluated the relationships between cover crop planting date and fall cover crop N uptake and reduction in nitrate leaching. In spring, we tested termination timing effects on cover biomass C and N, soil mineral N concentration, soil moisture, and corn yield. We tested multiple dates for broadcast interseeding cover crops into standing soybean cash crops. We partnered with farmers on Maryland’s Eastern Shore to test if our methods are feasible at a realistic scale. We measured nitrous oxide emissions to test if our recommended cover crop practice has the negative drawback of increasing emissions of nitrous oxide, a powerful greenhouse gas. The nitrate leached under late drilled and early interseeded methods were comparable under conditions which favored late drilling, but interseeding outperformed drilling when there was adequate rainfall for seed germination. The result was lower nitrate porewater concentrations under early planted cover crops. Nitrous oxide emissions increased slightly with cover crops relative to no cover crop, but the increase was negligible when compared to the nitrous oxide produced from applying N fertilizer. Our research showed that extending the cover crop growing season of a brassica-legume-cereal mix has multiple environmental benefits and few drawbacks.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 URBAN WATER SUPPLY PLANNING UNDER CLIMATE AND DEMAND GROWTH UNCERTAINTIES: A FRAMEWORK FOR IMPROVING SYSTEM RESILIENCE(2019) Yhap, Krystal Gayle; Negahban-Azar, Masoud; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Urban areas around the world are facing increased challenges in consistently and reliably providing water services. Rapid urbanization, climate change, and the disjointed management of water distribution systems reveal the need for the creation of holistic management solutions. San Francisco Public Utilities Commission (SFPUC) is considering alternative water supply options to improve the reliability of San Francisco’s water resource, which provided a case study for this research. This research proposes an alternative planning tool used for systematic urban water supply planning and demand management. This approach compares water supply options using the Water Evaluation and Planning tool (WEAP) and a drought resilience matrix. Future implications of modeled climate change, extreme drought, and population increase effects on the natural and urban water system are explored in this study. The effectiveness of water supply portfolios is compared through the creation and use of a drought resilience matrix.Item Identifying Problematic Hydric Soils Derived from Red Parent Materials in the United States(2018) Mack, Sara Christine; Rabenhorst, Martin C; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hydric soils derived from some red parent materials are “problematic” to identify during wetland delineations because they resist redox-induced color changes. These (PRPM) soils can be identified using the F21 – Red Parent Material field indicator, but the distribution and cause of the phenomenon, remains uncertain. The objectives of this study were to identify locations where PRPM occurs for appropriate use of the F21 field indicator throughout the country, and to better understand why PRPM soils resist redox-induced color changes. We found that PRPM is associated with sedimentary, hematite-rich, “red bed” formations and the deposits derived from them. Guidance maps have been developed showing where use of F21 is appropriate to support hydric soil (and therefore wetland) delineations impacted by PRPM. We also demonstrated that the cause of PRPM appears to be related to larger crystallite sizes of hematite in PRPM soils.Item KNOWLEDGE, ATTITUDES, AND IMPLEMENTATION OF BMPS AND MOSQUITO MANAGEMENT ACROSS A SOCIOECONOMIC GRADIENT(2017) Maeda, Potential Kanoko; Leisnham, Paul T.; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)To reduce nutrient pollution in our waterways and restore impaired watersheds, residents are needed to voluntarily practice a range of stormwater best management practices (BMPs). The overall goal of my thesis was to better understand barriers to BMP implementation by exploring the links among resident demographics, knowledge, and behaviors, as well as mosquito management, so that appropriate education can be more effectively developed and targeted. Importantly, this study found respondents who defined themselves as Caucasian or other races, and that were in owned houses, had higher mean BMP knowledge than respondents that identified themselves as African American and who are renters, respectively. This study also found that one barrier to BMP implementation, concern of mosquito breeding in BMPs, was not significant. Estimated abundances for all mosquito abundance metrics were significantly higher in combined other types of wet containers compared to wet disconnected downspouts, a commonly found BMP.Item Stormwater Green Infrastructure Climate Resilience In Chesapeake Bay Urban Watersheds(2017) Giese, Emma; Pavao-Zuckerman, Mitchell A; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Stormwater green infrastructure (GI) practices (e.g. bioretention, green roofs) are implemented to reduce stormwater runoff and pollution in urban watersheds. However, current implementation and design is based on historic and current climate. As a result, current implementation may not be sufficient to meet runoff and water quality goals under future climate conditions. This study conducted 1) a review of previous assessments of stormwater GI climate resilience, and 2) a SWAT modeling study of two case study watersheds (one with stormwater GI and one with traditional stormwater management) in Clarksburg, Maryland. Results from both the literature review and modeling study indicate the stormwater GI can help adapt urban watersheds to climate change. Results from the modeling study indicate that stormwater GI is resilient to changes in climate, but that there may be seasonal increases in fall and winter runoff.