Hydrological model of Ukraine: setup, calibration, and web interface

The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service. SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool, as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency's BASINS (Better Assessment Science Integrating Point & Nonpoint Sources) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project. At present, over 250 peer-reviewed, published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are provided.

Jeneberang watershed management plays an important role to the function of Bili-Bili Dam as a multipurpose dam in maintaining year-round water availability (quantity and distribution), agricultural irrigation, water supply for the local freshwater provider (PDAM), demand on drinking water, and hydroelectric power plants in Gowa, Takalar, and Makassar. The study tried to answer the emerging problem of how to predict the hydrological state and water availability in the Jeneberang watershed throughout the year. This study applied the SWAT (Soil and Water Assessment Tool) model, a distributed model connected to the Geographic Information System (GIS) developed by Jeff Arnold for the USDA ARS (US Department of Agriculture - Agriculture Research Service). The hydrological model would be applied to evaluate a scenario of the climate change effects on the hydrology state. Understanding the watershed hydrological response to the changes in physics (land use) and climate (rainfall and air temperature) is an important component of water resource planning and management (Vorosmarty et al., 2000). One of the performance indicators for the watershed water balance is river discharge fluctuation (Surahman, 2016). The river regime coefficient demonstrates fluctuation in river discharge, a number showing the ratio between maximum discharge (Qmax) and minimum discharge (Qmin). SWAT model analysis showed the highest discharge (Qmax) of 30,805 m³/sec and lowest discharge (Qmin) of 994 m³/sec. The analysis employed the data of 2006 and 2009, resulted in the Nash-Sutcliffe (NS) Efficiency values of 0.65 (satisfied) and R2 of 0.88 that in line with a study of Yusuf (2010) at the Cirasea watershed (0.74) and Junaidi (2011) at the Cisadane watershed (0.70). This value indicates that the SWAT method can predict the hydrological state of watersheds in Indonesia, including the Jeneberang watershed.

In Honduras, as well as in many other developing countries, less than 60% of the population inHonduras has reasonable access to safe drinking water and its quality is decreasing at anaccelerated rate. This study consists of assessing the stream flow patterns after land use changesin the 4,200-ha Rio Calan Watershed of Central Honduras. Streamflow modelling was conductedusing SWAT (Soil and Water Assessment Tool), a computer-based program developed byUniversity of Texas to predict the impact of land management practices on discharge and waterquality at the watershed scale. This constitutes the first attempt to use SWAT under tropicalconditions in Honduras.<br><br>To study the land use dynamics, three temporal land use covers: 1993, 1998 and 2000, weredeveloped from Landsat images. Additionally, three hypothetical land use covers were alsomodelled: pine trees, grass land and agriculture. As a first step, the model was calibrated withdata collected for 1 year in the field. Latter, the data bases containing: land use, soils, and climatedata were adapted with field data and information collected from local agencies.<br><br>As a result, we obtained a 10-year hydrograph for each real and hypothetical land use covers.Around 600 ha of tropical broad leaf and pine forests (15% of the watershed area) wereconverted to subsistence agriculture from 1993 to 2000. SWAT simulations, showed that land useconversion caused a slight increase in streamflow values in the 10-year-hydrographs. Theagricultural cover, a hypothetical scenario, showed the highest value on streamflow during thepredicted time. The predicted stream values (SWAT outcomes) and one-year field measurementswere compared and a small disparity was observed. SWAT proved to be a powerful tool formodelling streamflow patterns. Work is still in progress to improve SWATs data bases toHonduran-tropical conditions.

This paper introduces a Special Issue of Hydrological Sciences Journal containing 10 research papers which present current applications of the Soil and Water Assessment Tool (SWAT) for water resources assessment. First, an overview of selected, recently published papers with application of SWAT is given. The papers address the following topics: nutrients and related best management practices (BMPs); sediments and related BMPs; impoundment and wetlands; irrigation; bioenergy crops; climate change impact; and land-use change impacts. Then, papers from this Special Issue are briefly described, covering the themes: surface runoff and sediments; nonpoint-source pollution; surface water and groundwater; impacts of climate and land-use change; and large-scale SWAT applications. The presented model applications of SWAT were conducted across a variety of spatial scales, physiographic regions and climatic zones. This collection of papers demonstrates that applications of SWAT for water resources assessment are growing in number and cover drainage basins in many regions worldwide.Editor M. Acreman; Associate editor Xi Chen

A web-based GIS Decision Support System for managing and planning USDA's Conservation Reserve Program (CRP)

The Kabul River Basin (KRB) in Afghanistan is densely inhabited and heterogenic. The basin’s water resources are limited, and climate change is anticipated to worsen this problem. Unfortunately, there is a scarcity of data to measure the impacts of climate change on the KRB’s current water resources. The objective of the current study is to introduce a methodology that couples remote sensing and the Soil and Water Assessment Tool (SWAT) for simulating the impact of climate change on the existing water resources of the KRB. Most of the biophysical parameters required for the SWAT model were derived from remote sensing-based algorithms. The SUFI-2 technique was used for calibrating and validating the SWAT model with streamflow data. The stream-gauge stations for monitoring the streamflow are not only sparse, but the streamflow data are also scarce and limited. Therefore, we selected only the stations that are properly being monitored. During the calibration period, the coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) were 0.75–0.86 and 0.62–0.81, respectively. During the validation period (2011–2013), the NSE and R2 values were 0.52–0.73 and 0.65–0.86, respectively. The validated SWAT model was then used to evaluate the potential impacts of climate change on streamflow. Regional Climate Model (RegCM4-4) was used to extract the data for the climate change scenarios (RCP 4.5 and 8.5) from the CORDEX domain. The results show that streamflow in most tributaries of the KRB would decrease by a maximum of 5% and 8.5% under the RCP 4.5 and 8.5 scenarios, respectively. However, streamflow for the Nawabad tributary would increase by 2.4% and 3.3% under the RCP 4.5 and 8.5 scenarios, respectively. To mitigate the impact of climate change on reduced/increased surface water availability, the SWAT model, when combined with remote sensing data, can be an effective tool to support the sustainable management and strategic planning of water resources. Furthermore, the methodological approach used in this study can be applied in any of the data-scarce regions around the world.

The spatial and temporal dimensions of environmental impacts of climate and land cover changes are two significant factors altering hydrological processes. Studying the effects of these factors on water quality, provides important insight for water resource management and optimizing land planning given increasing water scarcity and water pollution. The impact of land cover and climate changes on surface water quality was assessed for the Neka River basin in Northern Iran. The widely used Soil and Water Assessment Tool (SWAT) was applied for pollutant modeling, and was calibrated using the Sequential Uncertainty Fitting (SUFI-2) algorithm. An ensemble of 17 CMIP5 climate models under two IPCC greenhouse gas emission scenarios were selected, and future land cover change (LCC) was modeled based on the evolution that occurred in the last decades. We simulated the impacts of climate change (CC) and LCC on sediment, nitrate, and phosphate for the 2035-2065 time slice. The annual loads of sediment, phosphate, and nitrate are projected to decrease under both CC scenarios based on the inter-model average, and generally follow a pattern similar to the change in river discharge. Nitrate concentrations show an increase across all seasons, while the sediment and phosphate concentrations increase in winter and autumn under CC conditions. Results indicate that pollutants are expected to increase under LCC alone, mainly due to the expansion of the cultivated areas. Overall, it seems CC has a greater impact than LCC on the variation of water quality variables in the Neka River basin. With a combined change in climate and land cover, the annual nitrate concentrations are expected to increase by + 19.7% and + 17.9%, under RCP 4.5 and RCP 8.5, respectively. The combined impacts of the CC and LCC caused a decline in the annual sediment and phosphate concentrations by -10.1% and -2.2% under RCP 4.5 and -9%, and -3.2% under RCP 8.5, respectively.

The present study proposes a framework to mitigate impact of climate change on the rice production by maximizing the yield while the energy use and ecological impacts on the river ecosystem as the irrigation source are mitigated. Coupled general circulation model- soil and water assessment tool (SWAT) was utilized to project the impact of climate change on the stream flow. Fuzzy physical habitat simulation was applied to develop the ecological impact function of the river. Moreover, a data-driven model was developed to predict the rice yield through changing water and energy consumption. Finally, all the simulations were utilized in the structure of the optimization model in which minimizing loss of the production, greenhouse gas emission by reducing energy use and physical habitat loss were considered as the objectives. Based on the results, the Nash–Sutcliffe model efficiency coefficient of the SWAT is 0.7 that demonstrates its reliability for simulating the impact of climate change on river flow. The optimization model is able to reduce the impact of climate change on yield of production by balancing water and energy use. In the most pessimistic scenario, water use should approximately be reduced 25% for protecting river ecosystem. However, the optimization model approximately increased energy use 16% for preserving the yield of the rice. Conversely, model decreased the energy use 40% compared with the current condition due to increasing water supply. Moreover, physical habitat loss is less than 50% that means the combined optimization model is able to protect river habitats properly.

Understanding the impact of climate change on water resources is important for developing regional adaptive water management strategies. This study investigated the impact of climate change on water resources in the Yarmouk River Basin (YRB) of Jordan by analyzing the historical trends and future projections of temperature, precipitation, and streamflow. Simple linear regression was used to analyze temperature and precipitation trends from 1989 to 2017 at Irbid, Mafraq, and Samar stations. The Statistical Downscaling Model (SDSM) was applied to predict changes in temperature and precipitation from 2018 to 2100 under three Representative Concentration Pathway (RCP) scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5), and the Soil and Water Assessment Tool (SWAT) was utilized to estimate their potential impact on streamflow at Addasiyia station. Analysis of data from 1989 to 2017 revealed that mean maximum and minimum temperatures increased at all stations, with average rises of 1.62°C and 1.39°C, respectively. The precipitation trends varied across all stations, showing a significant increase at Mafraq station, an insignificant increase at Irbid station, and an insignificant decrease at Samar station. Historical analysis of streamflow data revealed a decreasing trend with a slope of −0.168. Significant increases in both mean minimum and mean maximum temperatures across all stations suggested that evaporation is the dominant process within the basin, leading to reduced streamflow. Under the RCP scenarios, projections indicated that mean maximum temperatures will increase by 0.32°C to 1.52°C, while precipitation will decrease by 8.5% to 43.0% throughout the 21st century. Future streamflow projections indicated reductions in streamflow ranging from 8.7% to 84.8% over the same period. The mathematical model results showed a 39.4% reduction in streamflow by 2050, nearly double the SWAT model’s estimate under RCP8.5 scenario. This research provides novel insights into the regional impact of climate change on water resources, emphasizing the urgent need to address these environmental challenges to ensure a sustainable water supply in Jordan.

Jin, Xin and Venkataramana Sridhar, 2012. Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins. Journal of the American Water Resources Association (JAWRA) 48(2): 197‐220. DOI: 10.1111/j.1752‐1688.2011.00605.xAbstract: In the Pacific Northwest, warming climate has resulted in a lengthened growing season, declining snowpack, and earlier timing of spring runoff. This study characterizes the impact of climate change in two basins in Idaho, the Spokane River and the Boise River basins. We simulated the basin‐scale hydrology by coupling the downscaled precipitation and temperature outputs from a suite of global climate models and the Soil and Water Assessment Tool (SWAT), between 2010 and 2060 and assess the impacts of climate change on water resources in the region. For the Boise River basin, changes in precipitation ranged from −3.8 to 36%. Changes in temperature were expected to be between 0.02 and 3.9°C. In the Spokane River region, changes in precipitation were expected to be between −6.7 and 17.9%. Changes in temperature appeared between 0.1 and 3.5°C over a period of the next five decades between 2010 and 2060. Without bias‐correcting the simulated streamflow, in the Boise River basin, change in peak flows (March through June) was projected to range from −58 to +106 m3/s and, for the Spokane River basin, the range was expected to be from −198 to +88 m3/s. Both the basins exhibited substantial variability in precipitation, evapotranspiration, and recharge estimates, and this knowledge of possible hydrologic impacts at the watershed scale can help the stakeholders with possible options in their decision‐making process.

Evaluating the impact of interbasin water transfer on water quality in the recipient river basin with SWAT

<abstract><title><italic>Abstract. </italic></title> The land use and land cover (LULC) map of a watershed is a critical input to the Soil and Water Assessment Tool (SWAT) model. LULC is a categorical geospatial data layer that is typically developed based on models that establish relationships between pixel-based spectral reflectance and corresponding ground-truth information. Hence, LULC maps, like other classified remote-sensing datasets, are subject to error, which varies for each LULC category. The purpose of this study was to evaluate the effect of published LULC categorical errors on SWAT model uncertainty. A new algorithm was developed within the SWAT2009_LUC tool framework [see Transactions of the ASABE 54(5): 1649-1658] to produce multiple realizations of the LULC layer based on LULC categorical errors and integrate them dynamically within SWAT simulations. The enhanced SWAT2009_LUC tool and algorithm were tested for the SWAT model of the Illinois River Drainage Area in Arkansas (IRDAA) watershed. Tool evaluation results showed that the algorithm successfully integrated the LULC realizations within SWAT runs. Uncertainty evaluation showed that LULC categorical errors produced deviations in water yield output ranging from 0% to 8% at an annual scale and 0% to 19.9% at a monthly scale for the IRDAA subwatersheds. Results from this research highlight the importance of LULC categorical accuracy in the SWAT model and provide a generic tool for examining this uncertainty in any other watershed.

Evaluation of the impacts of BMPs and tailwater recovery system on surface and groundwater using satellite imagery and SWAT reservoir function

Assessment of land use and climate change effects on land subsidence using a hydrological model and radar technique

Adding bioenergy to the U.S. energy portfolio requires long-term profitability for bioenergy producers and long-term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a regional scale. To quantify feedstock production, we compared lowland switchgrass yields simulated by SWAT with estimates from a model based on empirical data for the eastern U.S. The two produced similar geographic patterns. Average yields reported in field trials tended to be higher than average SWAT-predicted yields, which may nevertheless be more representative of production-scale yields. As a preliminary step toward quantifying bioenergy-related changes in water quality, we evaluated flow predictions by the SWAT model for the Arkansas-White-Red river basin. We compared monthly SWAT flow predictions to USGS measurements from 86 subbasins across the region. Although agreement was good, we conducted an analysis of residuals (functional validation) seeking patterns to guide future model improvements. The analysis indicated that differences between SWAT flow predictions and field data increased in downstream subbasins and in subbasins with higher percentage of water. Together, these analyses have moved us closer to our ultimate goal of identifying areas with high economic and environmental potential for sustainable feedstock production.