About

Dr. Adel Shirmohammadi is a Professor in the Department of Environmental Science & Technology at the University of Maryland. His research focuses on watershed scale modeling, examining the relationship between incidences of human cancer and drinking water quality using GIS in Super Fund sites, storm water management in urban and suburban ecosystems, and the sustainable management of agro-ecosystems. He is also involved in creating Diagnostic Decision Support Systems (DDSS) for sustainable landscape management through community empowerment. His work emphasizes environmental health, water quality, and sustainable ecosystem practices, contributing to the understanding and management of water-related environmental challenges.

Research topics

• Geography
• Environmental science
• Water resource management
• Political Science
• Computer Science
• Environmental resource management
• Engineering
• Business
• Ecology
• Environmental planning
• Civil engineering
• Agronomy
• Operations research
• Public relations
• Economics
• Environmental engineering
• Remote sensing

Selected publications

• Quantifying water-deficit and heat stress dynamics for corn and soybean in the Mid-Atlantic region of U.S. across historical and projected climates

  Journal of Water and Climate Change · 2026-05-06

  articleOpen access

  ABSTRACT Understanding water deficit and water stress is crucial, as these factors directly influence irrigation needs, crop productivity, and long-term agricultural sustainability in regions prone to drought and uneven precipitation. This study quantifies historical and future water-deficit and heat-stress dynamics for corn and soybean in the Mid-Atlantic region of the U.S. under three emission scenarios (SSP126, SSP245, and SSP585). Water deficits were assessed using a multi-temporal cumulative deficit framework that captures the effects of precipitation timing and short-term soil moisture carryover on crop water availability. Heat stress was evaluated using crop-specific temperature thresholds during sensitive growth stages, with metrics including total heat-stress days, maximum consecutive hot days, and cumulative thermal excess. Results show consistent increases in ET0 and ETc across all scenarios, with the greatest rises under SSP585, particularly in southern and central Maryland. Water deficits intensify over time, and although multi-day precipitation accumulation reduces apparent deficits, even the lowest-emission scenario projects water-deficit values above historical baselines. Heat-stress exposure also increases, with higher-emission scenarios producing more frequent, prolonged, and intense hot periods, especially in the late century. The combined trends in water deficit and heat stress indicate that, without adaptation, climate change will significantly increase irrigation demand and crop stress risk.

  PublisherDOI

• Watershed-Scale Benefits of Using Reclaimed Water for Agricultural Irrigation

  Water · 2026-03-04

  articleOpen accessSenior author

  Agricultural irrigation is increasing due to climate stress and yield benefits on crops in the Mid-Atlantic region. To lessen groundwater demand, reclaimed water has grown as a popular freshwater alternative for irrigation. While reclaimed water (treated wastewater from wastewater treatment plants (WWTPs)) provides many benefits, additional costs deter farmers from its adoption. This study assesses the economic feasibility of reclaimed water for agricultural irrigation in two Mid-Atlantic watersheds: the Zekiah watershed in southern Maryland and the Greensboro watershed in eastern Maryland and southwestern Delaware. We identified areas most feasible for reclaimed water irrigation based on WWTP capacity, unit prices for water, and yield benefits of irrigation under diverse precipitation scenarios for both watersheds. Under dry precipitation conditions and a unit cost of $0.10 per cubic meter of reclaimed water (m3), 29.77% of cropland in the Zekiah watershed and 34.32% of cropland in the Greensboro watershed are feasible for reclaimed water irrigation, conserving a potential 1,505,154.72 m3 and 12,381,703.45 m3 of freshwater, respectively. However, when reclaimed water pricing and precipitation increase, significantly fewer farms experience sufficient yield benefits to cover reclaimed water costs. Further adoption of reclaimed water irrigation could be enhanced by a cost-share program that covers costs when yield benefits cannot.

  PublisherOA PDFDOI

• Agricultural water management in a changing Maryland: stakeholder experiences and attitudes towards weather variability, alternative water sources, and related factors

  Frontiers in Environmental Science · 2026-02-05 · 1 citations

  articleOpen accessSenior author

  The state of Maryland has experienced significant but commonly overlooked impacts on water quality and quantity. Future climate change is predicted to further reduce water availability, with nontraditional water sources such as treated recycled wastewater (TRW) as one potential way to mitigate impacts. We conducted semi-structured interviews with 17 Maryland stakeholders—including farmers, extension agents, state agency personnel, and academics—to explore their perceptions and experiences with 1) past, existing and future weather variability; 2) freshwater and reusable water use and management in agriculture; and 3) related factors impacting agricultural water management. Qualitative coding of interview transcripts produced 27 categories containing 291 unique codes and 121 sub-codes. Analysis revealed 24% of interviewees were hesitant to confirm climate change as a human-caused phenomenon, yet all interviewees described changes to the weather over recent decades, including drought, high rainfall events, extreme and unpredictable weather, and changes in temperature. Over half of interviewees had some knowledge of TRW in agriculture, and a majority thought it would be valuable; however, none had direct experience with its application. Many identified implementation barriers, with Distance, Infrastructure/Transport, Cost, and Contamination Concern as the most common codes. Many interviewees did not believe that water provisioning for agriculture was a problem because the region receives enough or more than enough precipitation. Related factors mentioned by interviewees included tension between residential and agricultural water use, land ownership, and concerns over existing or potential regulations. These findings inform our research exploring the use of TRW to support Maryland water sustainability under projected climate scenarios.

  PublisherOA PDFDOI

• Watershed-Scale Investigation of the Net-Benefit of Irrigation with Reclaimed Water

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Fine-scale assessment of projected future changes in weather and climate extremes in the Chesapeake Bay watershed of the Mid-Atlantic United States

  Theoretical and Applied Climatology · 2025-05-24 · 4 citations

  articleSenior author
  PublisherDOI

• Climate change effects on the spatial and temporal distribution of extreme precipitation in the Mid-Atlantic region

  Urban Climate · 2025-03-15 · 12 citations

  articleOpen access

  Global environmental stability is significantly impacted by climate change, with an increasing frequency and intensity of extreme weather events posing substantial risks to infrastructure, ecosystems, and communities. In this study, a comprehensive analysis of extreme precipitation events in Maryland is provided, utilizing the latest CMIP6 models to assess historical (1951–2022) trends and project future scenarios from 2022 to 2100 under three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585). Extreme precipitation events were analyzed by fitting a Generalized Logistic (GLO) distribution to daily observational precipitation data, with events above the 95th percentile identified as extreme. The frequency and magnitude of these events were determined by counting annual occurrences, calculating mean magnitudes, and assessing their probability across different climate scenarios. Additionally, Depth-Duration-Frequency (DDF) curves were developed to estimate expected precipitation amounts for various durations and return periods, with a focus on the associated uncertainties. The findings indicate that the probability of extreme precipitation events has slightly increased over the past seven decades, with notable variability between years, while the magnitude of these events has remained relatively stable. Future projections suggest a considerable rise in both the frequency and magnitude of extreme events, particularly under the SSP585 scenario, with the most severe impacts expected in certain regions of Maryland (Anne Arundel County and Dorchester County) and on the global level. This highlights the varying degrees of vulnerability across the state and underscores the need for targeted adaptation strategies. These results emphasize the critical importance of emissions mitigation to limit the severity of future extreme weather events and suggest that robust, region-specific adaptation measures will be essential in managing the increasing risks associated with climate change. • Extreme precipitation events were obtained using probability trend for diverse SSPs. • GLO distributions are powerful to identify extreme events and compute DDF curves. • Rising Extreme events pose high risks under historical and future climate scenarios. • Some Maryland counties need climate adaptation due to high risks of extreme events. • Mitigation strategies are urged to manage future risks of extreme events.

  PublisherDOI

• Evaluating the potential of recycled water use for irrigation in southern Maryland: impact on groundwater conservation and crop yield

  Water Science & Technology Water Supply · 2024-06-10 · 6 citations

  articleOpen access

  ABSTRACT Climate change and rainfall variability are driving many farmers to adopt irrigation, who were historically within rain-dependent regions, to sustain crop productivity. In the Mid-Atlantic region, irrigation in agriculture has grown since the 1980s due to rising temperatures and changes in precipitation patterns. Dry summers and uneven seasonal rainfall have necessitated a shift toward irrigation, particularly in Maryland's Coastal Plain. However, high dependence on confined groundwater for irrigation around this area has strained aquifers. To mitigate this strain, exploring alternative water sources is now important. This study investigates the viability of utilizing treated wastewater from plants as an irrigation substitute in Maryland's Coastal Plain. Using the Soil and Water Assessment Tool, the research evaluates crop productivity and irrigation needs under various climate scenarios. Results indicate that recycled water from nearby treatment plants can meet crop water requirements during wet years and partially during moderate and dry years, reducing aquifer reliance by 56 and 30%, respectively. This framework aims to boost yields while conserving freshwater resources. By serving as a decision support tool, stakeholders can assess the feasibility of recycled water for irrigation, thereby potentially reducing strain on confined aquifers.

  PublisherOA PDFDOI

• Transport and retention of pollutants from different production systems

  Työväentutkimus Vuosikirja · 2024-12-12 · 5 citations

  articleOpen accessSenior author

  Transport and retentions of agricultural pollutants both at farm level and catchment scale are key challenges faced by researchers, environmental managers, and regulatory agencies. Researchers have responded to this challenge by either monitoring or modelling strategies. Models, both empirical and theoretical, have been developed and used at different scales trying to evaluate the dynamics of the pollutants as they move from upland agricultural areas to water bodies. Monitoring studies at different scales (plot, field, catchment) have tried to represent the natural system and provide data-base for calibrating and testing mathematical models. Scientists have also used both modelling and monitoring strategies to evaluate the impact of different management practices such as contour cropping, vegetated buffer strips, riparian zones, and constructed wetlands on reduction of pollutant loads to water bodies. Manuscripts presented in this special issue provide results of both modelling and monitoring at different scales as they relate to transport and retention of nutrients in different landscapes. For example, it covers application of SWAT model in Finland to meet the environmental goals of European Water Framework Directive, and application of the same model in the US to meet the Total Maximum Daily Load mandated by US's 1972 Clean Water Act. Also covered are results on nutrient and sediment reduction due to different management practices including vegetated buffer strips, riparian zones, and constructed wetlands. Overall results of monitoring indicate effectiveness of such practices in attenuating sediment and nutrients, thus reducing their entry into the water bodies.

  PublisherDOI

• Modeling at catchment scale and associated uncertainties

  Työväentutkimus Vuosikirja · 2024-12-12 · 10 citations

  articleOpen access1st authorCorresponding

  This study describes application of a catchment scale model, SWAT (Soil Water Assessment Tool), to a small scale agricultural watershed in northern Maryland. It covers the steps involved in model application and associated model uncertainty as affected by variability in input parameters using Latin Hyper Cube Sampling (LHS) with Constrained Monte Carlo Simulation (MCS). SWAT model predictions of the impact of environmentally friendly practices are discussed within the context of input variability. Results indicate that SWAT is a reasonable monthly predictor of hydrology, but does not provide strong association between measured and simulated nitrate loss at that time scale. SWAT was found to perform very well when used for annual nitrate loss predictions. Results also show that using average input parameter values without considering their variability due to media heterogeneity produces simulation outputs that can be misleading and should not be given 100% confidence. It was concluded that in developing TMDL (Total Maximum Daily Load) plans for a given watershed one has to assert associated uncertainty levels in model's inputs and simulation results for proper resource management.

  PublisherDOI

• Utilizing Data-Driven Approaches to Forecast Fluctuations in Groundwater Table

  Water · 2024-05-24 · 2 citations

  articleOpen accessSenior authorCorresponding

  Accurate forecasting of fluctuations in groundwater table is crucial for the effective management of regional water resources. This study explores the potential of utilizing remotely sensed satellite data to predict and forecast water table variations. Specifically, two Artificial Neural Network (ANN) models were developed to simulate water table fluctuations at two distinct well sites, namely BA Ea 18 and FR Df 35 in Maryland. One model leveraged the relationship between variations in brightness temperature and water table depth, while the other model was founded on the association between changes in soil moisture and water table depth. These models were trained and validated using recorded water table depths from the aforementioned wells, brightness temperature data acquired from the Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E), and soil moisture information generated using the Land Data Assimilation System (LDAS). All models exhibited strong performance in predicting and forecasting water table fluctuations, with root mean square errors ranging from 0.043 m to 0.047 m for a 12-month forecasting horizon. Sensitivity tests revealed that the models displayed greater sensitivity to uncertainties in water table depth compared to uncertainties in both brightness temperature and soil moisture content. This underscores the feasibility of constructing an ANN-based water table prediction model, even in cases where high-resolution remotely sensed data is unavailable. In such situations, the model’s efficacy is contingent on the compatibility of the time series trends in data, such as brightness temperature or soil moisture, with those observed at the study site.

  PublisherOA PDFDOI

Frequent coauthors

• Hubert J. Montas

  University of Maryland, College Park

  103 shared

• J. M. Sheridan

  Southeast Watershed Research Laboratory

  48 shared

• A. Pouyan Nejadhashemi

  Michigan State University

  44 shared

• David D. Bosch

  24 shared

• Ali M. Sadeghi

  23 shared

• W. L. Magette

  University College Dublin

  23 shared

• Amanda Rockler

  Maryland Sea Grant

  20 shared

• Lars Bergström

  Swedish University of Agricultural Sciences

  16 shared