Impacts of Land Use and Climate Changes on Hydrological Processes in South Dakota Watersheds

This study aims to evaluate the impacts of climate and land use change on the hydrology of South Dakota’s watersheds using the Soil and Water Assessment Tool (SWAT). The study analyzed the hydrologic impacts of climate and land use changes in two ways. The first aspect consists of characterizing hydrological changes between two recent decades in three representative watersheds – Bad River watershed, Skunk Creek watershed and Upper Big Sioux River watershed. Two historical land use maps (NLCD 1992 and 2011) were used to represent land use change on these watersheds, and two historical climate datasets (1981-1990 and 2005-2014) were used to create SWAT models for each watershed. Results showed that due to historical land use and climate variations the annual water balance components mostly increased in the 2000s compared to 1980s. Between the 1980s and 2000s, seasonal variation in hydrology mostly increased during the wet season (i.e., May to October) in all three watersheds. Spatial analysis revealed that the hydrological components increased with a decrease in grassland in the watersheds, except in Skunk Creek watershed. The second aspect was to quantify the influence of future climate and land use changes on hydrological processes in the James River Watershed located in South and North Dakotas. A set of 42 scenarios of future projected land use and climate changes were developed under three emission scenarios (A1B, A2 and B1) to represent mid (2046-2065) and end (2080-2099) of the 21st century. Corresponding land use maps (2055 and 2090) were derived from the FOREcasting SCEnarios (FORE-SCE) model to represent land use conditions for mid and end of the century. Projected climate data were used from three general circulation models (CGCM3.1, GFDL-CM2.1, and HADCM3) for the mid-century (2046-2065) and end of the century (2080-2099). The scenarios were designed in a way that (1) land use was changed while climate conditions remained constant, (2) land use remained constant under a changing climate, and (3) both land use and climate were changed simultaneously. Results showed that future climate change will likely have more influence on hydrology compared to future land use change. The combined effects of land use and climate changes would intensify changes in hydrological processes of the region in the near future

APPLICATION OF RECLAIMED WASTEWATER FOR AGRICULTURAL IRRIGATION: DEVELOPING A DECISION SUPPORT TOOL USING SPATIAL MULTI-CRITERIA DECISION ANALYSIS

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

Assessing Crop Water Productivity under Different Irrigation Scenarios in the Mid–Atlantic Region

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

Developing a Multicriteria Decision Analysis Framework to Evaluate Reclaimed Wastewater Use for Agricultural Irrigation: The Case Study of Maryland

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.https://doi.org/10.3390/hydrology801000

Developing a Decision Support System for Economic Analysis of Irrigation Applications in Temperate Zones

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

Streamflow response to potential land use and climate changes in the James River watershed, Upper Midwest United States

Study region: North and South Dakotas, United States Study focus: Changes in watershed hydrology are mainly driven by changes in land use and climate. This study evaluated the impacts of climate and land use changes on streamflow in an agricultural watershed in the Upper Midwest. Three projected climate change scenarios (A1B, A2 and B1) of three general circulation models (CGCM3.1, GFDL-CM2.1, and HADCM3) were developed for mid (2046â2065) and end (2080â2099) of the 21st century. Corresponding land use maps for years 2055 and 2090 were obtained from the FOREcasting SCEnarios of Land-Cover (FORE-SCE) model. The scenarios were designed in a way that land use was changed while climate conditions remain constant, land use was then held constant under a changing climate, and finally both land use and climate were changed simultaneously to reflect possible future land use and climate conditions. New hydrological insights for the region: Potential land use and climate changes would result in 12â18% % and 17â41% increases in annual streamflow, respectively, by end of the century. The combined effects of land use and climate changes would intensify future streamflow responses with 13â60% increases in the region. This study provides a broad perspective on plausible hydrologic alterations in the region, prompting individual and collective opportunities to engage with this topic for sustainable planning and management of watersheds. Keywords: Watershed modeling, Precipitation, Agricultural land, Grassland, Dakota, SWA

Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

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.https://doi.org/10.3390/cli812013

Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

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

Persistent Spatial Patterns of Listeria monocytogenes and Salmonella enterica Concentrations in Surface Waters: Empirical Orthogonal Function Analysis of Data from Maryland

High spatiotemporal variability of pathogen concentrations in surface waters complicates the design and interpretation of microbial water quality monitoring. Empirical orthogonal function (EOF) analysis can provide spatial patterns (EOFs) of variability in deviations of concentrations in specific locations from the average concentration across the study area. These patterns can be interpreted to assess the effect of environmental factors on pathogen levels in the water. The first and the second EOFs for Listeria monocytogenes explained 84.4% and 9.7% of the total variance of deviations from average, respectively. That percentage was 50.8% and 45.0% for Salmonella enterica. The precipitation also had a strong explanatory capability (79%) of the first EOF. The first EOFs of Listeria and precipitation were similar at pond sites but were opposite to the precipitation at the stream sites. The first EOF of S. enterica and precipitation demonstrated opposite trends, whereas the second S. enterica EOF pattern had similar signs with the precipitation EOF at pond sites, indicating a relationship between rainfall and Salmonella at these sites. Overall, the rainfall data could inform on persistent spatial patterns in concentrations of the two pathogens at the pond sites in farm settings but not at stream sites located in forested areas

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-