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Eutrophication in the Lobo watershed remains a major problem. The work carried out has focused on chemical and biological analyses in the lake or in its immediate environment: they did not sufficiently take into account the diffuse transfer of nutrients over the entire watershed. This study aims to assess the nutrient (N and P) loads in the Lobo watershed, an agricultural area, to understand the spatio-temporal impacts of land management practices on eutrophication. The methodology uses two steps: streamflow calibration and nutrient (N and P) estimation using the Soil and Water Assessment Tool (SWAT) watershed model. Thus, the nutrient inputs were estimated based on the levels of N and P in every kilogram of Nitrogen-phosphorus-Potassium (NPK) type fertilizers applied by farmers. The average quantities of N and P applied to the crops were 47.24 kg ha−1 and 21.25 kg ha−1. Results show a good performance on flow calibration as evidenced using evaluation criteria R2, Nash–Sutcliffe Efficiency (NSE), and Percent Bias (PBIAS) of 0.63, 0.62, and −8.1, respectively. The yields of inorganic N and soluble P varied from 0 to 0.049 kg ha−1 and from 0 to 0.31 kg ha−1. These results show that the crops' inorganic nitrogen requirements were higher than the demands for soluble phosphorus. Simulations relating to the organic N transfer revealed values ranging from 0.2 to 5 kg ha−1, while the transport of organic phosphorus was estimated to vary from 0.3 to 1.3 kg ha−1. [ABSTRACT FROM AUTHOR]

Climate-induced changes in precipitation and temperature can have a profound impact on watershed hydrological regimes, ultimately affecting agricultural yields and the quantity and quality of surface water systems. In India, the majority of the watersheds are facing water quality and quantity issues due to changes in the precipitation and temperature, which requires assessment and adaptive measures. This study seeks to evaluate the effects of climate change on the water quality and quantity at a regional scale in the Nagavali and Vamsadhara watersheds of eastern India. The impact rainfall variations in the study watersheds were modeled using the Soil and Water Assessment Tool (SWAT) with bias-corrected, statistically downscaled models from Coupled Model Intercomparison Project-6 (CMIP-6) data for historical (1975–2014), near future (2022–2060), and far future (2061–2100) timeframes using three Shared Socioeconomic Pathways (SSP) scenarios. The range of projected changes in percentage of mean annual precipitation and mean temperature varies from 0 to 41.7% and 0.7 °C to 2.7 °C in the future climate, which indicates a warmer and wetter climate in the Nagavali and Vamsadhara watersheds. Under SSP245, the average monthly changes in precipitation range from a decrease of 4.6% to an increase of 25.5%, while the corresponding changes in streamflow and sediment yield range from −11.2% to 41.2% and −15.6% to 44.9%, respectively. Similarly, under SSP370, the average monthly change in precipitation ranges from −3.6% to 36.4%, while the corresponding changes in streamflow and sediment yield range from −21.53% to 77.71% and −28.6% to 129.8%. Under SSP585, the average monthly change in precipitation ranges from −2.5% to 60.5%, while the corresponding changes in streamflow and sediment yield range from −15.8% to 134.4% and −21% to 166.5%. In the Nagavali and Vamsadhara watersheds, historical simulations indicate that 2438 and 5120 sq. km of basin areas, respectively, were subjected to high soil erosion. In contrast, under the far future Cold-Wet SSP585 scenario, 7468 and 9426 sq. km of basin areas in the Nagavali and Vamsadhara watersheds, respectively, are projected to experience high soil erosion. These results indicate that increased rainfall in the future (compared to the present) will lead to higher streamflow and sediment yield in both watersheds. This could have negative impacts on soil properties, agricultural lands, and reservoir capacity. Therefore, it is important to implement soil and water management practices in these river basins to reduce sediment loadings and mitigate these negative impacts. [ABSTRACT FROM AUTHOR]

Mekong River Basin (MRB) experiences extreme droughts and floods frequently, due to the precipitation deficit across the basin. The meteorological droughts will have a profound impact on the distribution of soil moisture and hence agricultural productivity, which will lead to the reduction of surface water resources. It is therefore important to evaluate the deficits in hydrometeorological extremes, that is, precipitation, soil moisture, and streamflow to help decipher how one drought results in the other. In this study, a streamflow deficit index (SDI) has been proposed and applied to understand the changes in hydrology due to the fluctuations in precipitation and soil moisture in the Mekong River Basin (MRB). The study used percent normal (PN), a precipitation deficit index, and soil moisture deficit index (SMDI) to identify the initiation and sustenance of hydrological drought using SDI. The SMDI was obtained from soil moisture simulated using the soil and water assessment tool (SWAT) for the periods of 1980–2008. The study results suggested that the proposed index was able to represent the historical river flow deficit that persisted in the basin in the year 1992. Increasing variation in the streamflow deficit in parts of Thailand, Lao PDR, Vietnam, and Cambodia from the year 1992 was also captured by SDI. The flooding year 2000, which resulted in an economic loss of over 200 million USD, was also effectively captured by the proposed index. The lengthening of the streamflow drought, a metric used to represent drought propagation, was shorter by at least 2 months in forested catchments compared with that of agricultural catchments, which implies that any deficit in precipitation and soil moisture, will have a severe impact on agricultural basins. Similarly, the attenuation of both agricultural and hydrological drought was found to be smaller in forested subbasins than those in agricultural subbasins. The findings of the study will be useful for the timely identification of extreme hydrological events and for planning mitigation measures. [ABSTRACT FROM AUTHOR]

Computer simulation models are a useful tool in planning, enabling reliable yet affordable what-if scenario analysis. Many simulation models have been proposed and used for urban planning and management. Still, there are a few modeling options available for the purpose of evaluating the effects of various stormwater control measures (SCM), including LID (low-impact development) controls (green roof, rain garden, porous pavement, rainwater harvesting), upland off-line controls (sedimentation, filtration, retention–irrigation) and online controls (detention, wet pond). We explored the utility and potential of the Soil and Water Assessment Tool (SWAT) as a modeling tool for urban stormwater planning and management. This study demonstrates how the hydrologic modeling strategies of SWAT and recent enhancements could help to develop efficient measures for solving urban stormwater issues. The case studies presented in this paper focus on urban watersheds in the City of Austin (COA), TX, where rapid urbanization and population growth have put pressure on the urban stormwater system. Using the enhanced SWAT, COA developed a framework to assess the impacts on erosion, flooding, and aquatic life due to changes in runoff characteristics associated with land use changes. Five catchments in Austin were modeled to test the validity of the SWAT enhancements and the analytical framework. These case studies demonstrate the efficacy of using SWAT and the COA framework to evaluate the impacts of changes in hydrology and the effects of different regulatory schemes. [ABSTRACT FROM AUTHOR]

This study is to establish a new approach to estimate river salinity of semi‐arid agricultural watershed and identify drivers by using hydrologic modeling and machine learning. We augmented the limitations of the Soil and Water Assessment Tool (SWAT) to model salinity by coupling with eXtreme Gradient Boosting (XGBoost), a decision‐tree‐based ensemble machine learning algorithm. Streamflow, precipitation, elevation, main reach length, and dominant soil texture of the top two layers were used along with NO3, NO2, and total phosphorus (TP) output from a calibrated SWAT model are used as predictors to Total Dissolved Solids (TDS) in the XGBoost algorithm. Then, the SWAT model simulations of streamflow, NO3+NO2, and TP from 2000 to 2015 are used as inputs of the XGBoost model to predict monthly water TDS distribution along the river. The predicted river water TDS showed a higher concentration as going downstream from El Paso (inlet) through the Hudspeth canal to Fort Quitman (outlet). Finally, this study carried out cause analysis focusing on soil physical characteristics. The soil salinity level is directly affected by the soil permeability and irrigation water. As a result, the highest TDS is shown in sites with silt loam, whereas the lowest TDS was shown in sites with very cobbly soil. Silt soils can hold more water and are slower to drain than soils of a sand type. These analyses can be used to better understand the mitigation of water salinity. [ABSTRACT FROM AUTHOR]

With increased demand for water and soil in this Anthropocene era, it is necessary to understand the water balance components and critical source areas of land degradation that lead to soil erosion in agricultural dominant river basins. Two medium-sized east-flowing rivers in India, namely Nagavali and Vamsadhara, play a significant role in supporting water supply and agriculture demands in parts of the Odisha districts of Kalahandi, Koraput and Rayagada, as well as the Andhra Pradesh districts of Srikakulam and Vizianagaram. Floods are more likely in these basins as a result of cyclones and low-pressure depressions in the Bay of Bengal. The water balance components and sediment yield of the Nagavali and Vamsadhara river basins were assessed using a semi-distributed soil and water assessment tool (SWAT) model in this study. The calibrated model performance revealed a high degree of consistency between observed and predicted monthly streamflow and sediment load. The water balance analysis of Nagavali and Vamsadhara river basins showed the evapotranspiration accounted for 63% of the average annual rainfall. SWAT simulated evapotranspiration showed a correlation of 0.78 with FLDAS data. The calibrated SWAT model showed that 26.5% and 49% of watershed area falling under high soil erosion class over Nagavali and Vamsadhara river basins, respectively. These sub watersheds require immediate attention to management practices to improve the soil and water conservation measures. [ABSTRACT FROM AUTHOR]

The Soil and Water Assessment Tool (SWAT) is a watershed-scale hydrologic model that integrates water quantity and quality modules. Despite the large amount of knowledge on the SWAT model, specific understanding of sub-daily applications remains limited. In this review, we identify the shortcomings and possible ways forward in simulating sub-daily processes with the model. A literature review was conducted, along with a participatory method based on a questionnaire. We reviewed 28 scientific articles and categorized them into: (i) model development, (ii) streamflow methods comparison, (iii) water quality, and (iv) other applications. We found that using sub-daily data improves hydrograph peak simulation, while for medium flows use of daily data was better. From all the reviewed studies, a 1-hour time step was the most suitable time scale for the sub-daily model application. The participatory questionnaire confirmed the hypothesis that the main challenge for using the sub-daily routine was the lack of high-resolution data. [ABSTRACT FROM AUTHOR]

Water is vital for human survival and ecosystem health. In arid and semi-arid areas like the Limpopo River Basin (LRB) in Southern Africa, water is a precious commodity. The study of spatial and temporal distribution of freshwater components is an important step toward sustainable planning and management of water resources. This case study applied the Soil and Water Assessment Tool (SWAT) to characterize freshwater availability and scarcity in the LRB. SWAT predictions of hydrologic fluxes in the basin are generally satisfactory when compared to measured streamflow records, although uncertainties persist in model estimates. Estimates of streamflow, herein referred to as blue water, varied from 0.2 to 570 mm/year between 1984 and 2013 over the basin. The analysis revealed alternating cycles of one to two years of water surplus periods and three to five years of dry periods during the study period. The results also indicated that, considering the natural water yield, 20% of the basin (mostly east) has enough water, while the remaining 80% continues to experience dryness and water stress. [ABSTRACT FROM AUTHOR]

Natural gas development using hydraulic fracturing has many potential environmental impacts, but among the most certain is the land disturbance required to build the well pads and other infrastructure required to drill and extract the gas. We used the Soil and Water Assessment Tool ( SWAT) model to investigate how natural gas development could impact streamflow and sediment, total nitrogen (TN), and total phosphorous (TP) loadings in the upper Delaware River Basin ( DRB), a relatively undeveloped watershed of 7,950 km2 that lies above the Marcellus Shale formation. If gas development was permitted, our projections show the DRB could experience development of over 600 well pads to extract natural gas at build out, which, with supporting infrastructure (roads, gathering pipelines), could convert over 5,000 ha from existing land uses in the study area. In subbasins with development activity we found sediment, TN, and TP yields could increase by an average of 15, 0.08, and 0.03 kg/ha/yr, respectively (an increase of 2, 3, and 15%, respectively) for each one percent of subbasin land area converted into natural gas infrastructure. At the study area outlet on the Delaware River at Port Jervis, New York, we found increases in the annual average streamflow and sediment, nitrogen, and phosphorus loads of up to 0.01, 0.2, 0.2, and 1%, respectively, for a rapid development year, and 0.08, 1.3, 2.0, and 11%, respectively, for the full development scenario. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series. [ABSTRACT FROM AUTHOR]

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool ( SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case-dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series. [ABSTRACT FROM AUTHOR]

In the semi-arid Texas High Plains, the underlying Ogallala Aquifer is experiencing continuing decline due to long-term pumping for irrigation with limited recharge. Accurate simulation of irrigation and other associated water balance components are critical for meaningful evaluation of the effects of irrigation management strategies. Modelers often employ auto-irrigation functions within models such as the Soil and Water Assessment Tool (SWAT). However, some studies have raised concerns as to whether the function is able to adequately simulate representative irrigation practices. In this study, observations of climate, irrigation, evapotranspiration (ET), leaf area index (LAI), and crop yield derived from an irrigated lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used to evaluate the efficacy of the SWAT auto-irrigation functions. Results indicated good agreement between simulated and observed daily ET during both model calibration (2001–2005) and validation (2006–2010) periods for the baseline scenario (Nash-Sutcliffe efficiency; NSE ≥ 0.80). The auto-irrigation scenarios resulted in reasonable ET simulations under all the thresholds of soil water deficit (SWD) triggers as indicated by NSE values > 0.5. However, the auto-irrigation function did not adequately represent field practices, due to the continuation of irrigation after crop maturity and excessive irrigation when SWD triggers were less than the static irrigation amount. [ABSTRACT FROM AUTHOR]

Modification of the hydrological cycle and, subsequently, of other global cycles is expected in Arctic watersheds owing to global change. Future climate scenarios imply widespread permafrost degradation caused by an increase in air temperature, and the expected effect on permafrost hydrology is immense. This study aims at analyzing, and quantifying the daily water transfer in the largest Arctic river system, the Yenisei River in central Siberia, Russia, partially underlain by permafrost. The semi-distributed SWAT (Soil and Water Assessment Tool) hydrological model has been calibrated and validated at a daily time step in historical discharge simulations for the 2003-2014 period. The model parameters have been adjusted to embrace the hydrological features of permafrost. SWAT is shown capable to estimate water fluxes at a daily time step, especially during unfrozen periods, once are considered specific climatic and soils conditions adapted to a permafrost watershed. The model simulates average annual contribution to runoff of 263 millimeters per year (mm yr-1) distributed as 152 mm yr-1 (58%) of surface runoff, 103 mm yr-1 (39%) of lateral flow and 8 mm yr-1 (3%) of return flow from the aquifer. These results are integrated on a reduced basin area downstream from large dams and are closer to observations than previous modeling exercises. [ABSTRACT FROM AUTHOR]

Application of a temperature-index melt model incorporated into the Soil and Water Assessment Tool (SWAT) is presented to simulate mass balance (MB) and equilibrium line altitude (ELA) of three glaciers. The snow accumulation/melt parameters were adjusted to glacierized and free glacier areas, respectively. The SWAT snow algorithm enabled us to consider spatial variation of snow parameters by elevation bands across the sub-basins, while in the previous studies using SWAT, the related parameters were constant for an entire basin. The results show slight improvement in runoff simulation and significant improvement in simulated MB when considering ELA in model calibration. The results showed that SWAT can be applied to simulate MB, vertical MB distribution and annual ELA, with light calibration efforts for data-scarce catchments. The accuracy of the results depends on the modelled area of ablation zone from which most of the meltwater is released. [ABSTRACT FROM PUBLISHER]

The effects of Low Impact Development (LID) practices on urban runoff and pollutants have proven to be positive in many studies. However, the effectiveness of LID practices can vary depending on different urban patterns. In the present study, the performance of LID practices was explored under three land uses with different urban forms: (1) a compact high-density urban form; (2) a conventional medium-density urban form; and (3) a conservational medium-density urban form. The Soil and Water Assessment Tool (SWAT) was used and model development was performed to reflect hydrologic behavior by the application of LID practices. Rain gardens, permeable pavements, and rainwater harvesting tanks were considered for simulations, and a modeling procedure for the representation of LID practices in SWAT was specifically illustrated in this context. Simulations were done for each land use, and the results were compared and evaluated. The application of LID practices demonstrated a decrease in surface runoff and pollutant loadings for all land uses, and different reductions were represented in response to the land uses with different urban forms on a watershed scale. In addition, the results among post-LIDs scenarios generally showed lower values for surface runoff and nitrate in the compact high-density urban land use and for total phosphorus in the conventional medium-density urban land use compared to the other land uses. We suggest effective strategies for implementing LID practices. [ABSTRACT FROM AUTHOR]

Future climate change is projected to have significant impact on water resources availability and quality in many parts of the world. The objective of this paper is to assess the effect of projected climate change on water quantity and quality in two lowland catchments (the Upper Narew and the Barycz) in Poland in two future periods (near future: 2021-2050, and far future: 2071-2100). The hydrological model SWAT was driven by climate forcing data from an ensemble of nine bias-corrected General Circulation Models-Regional Climate Models (GCM-RCM) runs based on the Coordinated Downscaling Experiment-European Domain (EURO-CORDEX). Hydrological response to climate warming and wetter conditions (particularly in winter and spring) in both catchments includes: lower snowmelt, increased percolation and baseflow and higher runoff. Seasonal differences in the response between catchments can be explained by their properties (e.g., different thermal conditions and soil permeability). Projections suggest only moderate increases in sediment loss, occurring mainly in summer and winter. A sharper increase is projected in both catchments for TN losses, especially in the Barycz catchment characterized by a more intensive agriculture. The signal of change in annual TP losses is blurred by climate model uncertainty in the Barycz catchment, whereas a weak and uncertain increase is projected in the Upper Narew catchment. [ABSTRACT FROM AUTHOR]

The Hawizeh marsh, a unique wetland which is part of the Mesopotamian marshes, is recognized as a wetland of international importance. The marsh has been shrinking and there has been little research into its degradation. This study aims to reconstruct historical water regimes in the contributing basins (Tigris and Karkheh river Basins, TKRB) to investigate factors that have affected the wellbeing of the marsh. The Soil and Water Assessment Tool (SWAT) was used for this study. The model was calibrated and validated using nine river gauging stations. Results indicated that inflows to the marsh decreased by 65% and 80% in the '90s and 2000s, respectively, compared to the '80s. The reductions in streamflow were caused by decrease in precipitation and water abstraction. The annual precipitation decreased by 14% and 38% in the '90s and 2000s, respectively, compared to the '80s. Highest water abstraction was seen in Karkheh dam which caused a reduction of 45% in the annual streamflows. Average annual evaporative losses from Tharthar lake (2700 km 2 ) were very high (2260 hm 3 [cubic hectometer]). Although the Hawizeh marsh has been shrinking for the last three decades, recent satellite images (2013) have shown that the marsh has been reviving, mainly due to increased precipitation from 2011 to 2013. The revival of the marsh is promising; however, if the planned dams on TKRB are implemented, the future of the marsh remains uncertain. The sustainability of the Hawizeh marsh will require integrated water resources management among the riparian countries to rehabilitate and maintain this unique wetland. [ABSTRACT FROM AUTHOR]

The Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile), with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snowmelt/accumulation by elevation band across each subbasin. In previous studies, melt rates varied as a function of elevation because of an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is the separation of the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from the glaciered watersheds: (1) the snow parameters are lumped (constant throughout the entire basin) and (2) the snow parameters are spatially variable based on elevation bands of a subbasin (modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulations of monthly runoff from the basins with a monsoon runoff regime. [ABSTRACT FROM AUTHOR]

Soil erosion threatens both soil and water resources and has increased globally because of the removal of natural vegetation and the intensification of existing agriculture. Brazil is privileged by a large proportion of natural vegetation and abundant freshwater. Recently, modifications of the Brazilian Forest Act (BFA) have been approved, which offer landowners that had committed illegal riparian deforestation in the past amnesty from reforestation, and further reductions of riparian protected areas are currently discussed. Here, we used the Soil and Water Assessment Tool to simulate river discharge and sediment exports in a typical human-impacted Brazilian catchment, the Rio das Mortes catchment. By restoring the riparian vegetation according to the BFA and ignoring amnesties to land owners, the current annual sediment export of the catchment of 0·830 t ha−1 was reduced by 29·4% according to our model. Further, simulated reforestation twice the size demanded by the BFA resulted in a 31·4% reduction of the current sediment export. However, reforestation of a 5-m homogeneous riparian corridor only, as currently discussed in the Federal Brazilian State of São Paulo, reduced sediment exports by only 23·8%, not considering expected additional erosion due to deforestation outside the simulated reforested 5-m corridor. Our study is the first catchment-wide assessment of the role of riparian vegetation in preventing soil erosion in Brazil. Its results support intensive reforestation efforts of the riparian zone and point to substantial negative effects of further reductions of the protected riparian corridor width and amnesties from reforestation to land owners. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study tests the applicability of the curve number ( CN) method within the Soil and Water Assessment Tool ( SWAT) to estimate surface runoff at the watershed scale in tropical regions. To do this, surface runoff simulated using the CN method was compared with observed runoff in numerous rainfall-runoff events in three small tropical watersheds located in the Upper Blue Nile basin, Ethiopia. The CN method generally performed well in simulating surface runoff in the studied watersheds (Nash-Sutcliff efficiency [NSE] > 0.7; percent bias [ PBIAS] < 32%). Moreover, there was no difference in the performance of the CN method in simulating surface runoff under low and high antecedent rainfall ( PBIAS for both antecedent conditions: ~30%; modified NSE: ~0.4). It was also found that the method accurately estimated surface runoff at high rainfall intensity (e.g., PBIAS < 15%); however, at low rainfall intensity, the CN method repeatedly underestimated surface runoff (e.g., PBIAS > 60%). This was possibly due to low infiltrability and valley bottom saturated areas typical of many tropical soils, indicating that there is scope for further improvements in the parameterization/representation of tropical soils in the CN method for runoff estimation, to capture low rainfall-intensity events. In this study the retention parameter was linked to the soil moisture content, which seems to be an appropriate approach to account for antecedent wetness conditions in the tropics. [ABSTRACT FROM AUTHOR]

This study simulated crop and water yields in the Missouri River Basin (MRB; 1,371,000 km2), one of the largest river basins in the United States, using the Soil and Water Assessment Tool (SWAT) at a fine resolution of 12-digit Hydrological Unit Codes (HUCs) using the regionalization calibration approach. Very few studies have simulated the entire MRB, and those that have developed were at a coarser resolution of 8-digit HUCs and were minimally calibrated. The MRB was first divided into three subbasins and was further divided into eleven regions. A 'head watershed' was selected in each region and was calibrated for crop and water yields. The parameters from the calibrated head watershed were extrapolated to other subwatersheds in the region to complete comprehensive spatial calibration. The simulated crop yields at the head watersheds were in close agreement with observed crop yields. Spatial validation of the aggregated crop yields resulted in reasonable predictions for all crops except dryland corn in a few regions. Simulated and observed water yields in head watersheds and also in the validation locations were in close agreement in naturalized streams and poor agreement in streams with high groundwater-surface water interactions and/or reservoirs found upstream of the gauges. Overall, the SWAT model was able to reasonably capture the hydrological and crop growth dynamics occurring in the basin despite some limitations. [ABSTRACT FROM AUTHOR]

In recent years, large-scale watershed modeling has been implemented broadly in the field of water resources planning and management. Complex hydrological, sediment, and nutrient processes can be simulated by sophisticated watershed simulation models for important issues such as water resources allocation, sediment transport, and pollution control. Among commonly adopted models, the Soil and Water Assessment Tool (SWAT) has been demonstrated to provide superior performance with a large amount of referencing databases. However, it is cumbersome to perform tedious initialization steps such as preparing inputs and developing a model with each changing targeted study area. In this study, the Hydrologic and Water Quality System (HAWQS) is introduced to serve as a national-scale Decision Support System (DSS) to conduct challenging watershed modeling tasks. HAWQS is a web-based DSS developed and maintained by Texas A & M University, and supported by the U.S. Environmental Protection Agency. Three different spatial resolutions of Hydrologic Unit Code (HUC8, HUC10, and HUC12) and three temporal scales (time steps in daily/monthly/annual) are available as alternatives for general users. In addition, users can specify preferred values of model parameters instead of using the pre-defined sets. With the aid of HAWQS, users can generate a preliminarily calibrated SWAT project within a few minutes by only providing the ending HUC number of the targeted watershed and the simulation period. In the case study, HAWQS was implemented on the Illinois River Basin, USA, with graphical demonstrations and associated analytical results. Scientists and/or decision-makers can take advantage of the HAWQS framework while conducting relevant topics or policies in the future. [ABSTRACT FROM AUTHOR]

Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence the ability of the model to represent real world conditions. Understanding how these decisions influence model performance is crucial, especially when making science-based policy decisions. This study used the Soil and Water Assessment Tool (SWAT) model in West Lake Erie Basin (WLEB) to examine the influence of several of these decisions on hydrological processes and streamflow simulations. Specifically, this study addressed the following objectives (1) demonstrate the importance of considering intra-watershed processes during model development, (2) compare and evaluated spatial calibration versus calibration at outlet and (3) evaluate parameter transfers across temporal and spatial scales. A coarser resolution (HUC-12) model and a finer resolution model (NHDPlus model) were used to support the objectives. Results showed that knowledge of watershed characteristics and intra-watershed processes are critical to produced accurate and realistic hydrologic simulations. The spatial calibration strategy produced better results compared to outlet calibration strategy and provided more confidence. Transferring parameter values across spatial scales (i.e. from coarser resolution model to finer resolution model) needs additional fine tuning to produce realistic results. Transferring parameters across temporal scales (i.e. from monthly to yearly and daily time-steps) performed well with a similar spatial resolution model. Furthermore, this study shows that relying solely on quantitative statistics without considering additional information can produce good but unrealistic simulations. [ABSTRACT FROM AUTHOR]

Failure to setup a large-scale hydrological model correctly may not allow proper calibration and uncertainty analyses, leading to inaccurate model prediction. To build a model with accurate accounting of hydrological processes, a data discrimination procedure was applied in this study. The framework uses a hydrological model of Alberta built with the Soil and Water Assessment Tool (SWAT) program. The model was used to quantify the causes and extents of biases in predictions due to different types of input data. Data types represented different sources of errors, including input data (e.g., climate), conceptual model (e.g., potholes, glaciers), and control structure (e.g., reservoirs, dams). The results showed that accounting for these measures leads to a better physical accounting of hydrological processes, significantly improving the overall model performance. The procedure used in this study helps to avoid unnecessary and arbitrary adjustment of parameters to compensate for the errors in the model structure. [ABSTRACT FROM AUTHOR]

The Upper Trinity River Basin (TRB) is the most populated river basin and one of the largest water suppliers in Texas. However, sediment and nutrient loads are reducing the capacity of reservoirs and degrading water quality. The objectives of this study are to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for ten study watersheds within the Upper TRB in order to assess nutrient loads into major reservoirs in the basin and to predict the effects of point source elimination and urbanization on nutrient loads through scenario analyses. SWAT performed reasonably well for the current condition except for two out of five tributaries in the Eagle Mountain watershed and total phosphorous in Richland-Chambers. The impacts of simulated scenarios varied within watersheds. Point-source elimination achieved reductions ranging from 0.3% to 24% in total phosphorus and 1% to 56% in total nitrogen received by the reservoirs. Population and development projections were used to examine the impacts of urbanization on each watershed. Projected urbanization in 2030 had large effects on simulated total phosphorus loads in some watersheds, ranging from a reduction of 1% to an increase of 111%. Projected urbanization also affected simulated total nitrogen loads, from a reduction of 3% to an increase of 24%. One limitation of this study is the lack of long-term, up-to-date water quality data due to discontinued water-quality monitoring stations. Although careful considerations were given to the adjustment of parameter values reflecting various aspects of the nutrient processes, further data collection will enhance modeling study for assessment of these watersheds' water resources and environmental problem. [ABSTRACT FROM AUTHOR]

Data scarcity has been a huge problem in modeling the water resources of the Upper Blue Nile basin, Ethiopia. Satellite data and different statistical methods have been used to improve the quality of conventional meteorological data. This study assesses the applicability of the National Centers for Environmental Prediction's Climate Forecast System Reanalysis ( CFSR) climate data in modeling the hydrology of the region. The Soil and Water Assessment Tool was set up to compare the performance of CFSR weather with that of conventional weather in simulating observed streamflow at four river gauging stations in the Lake Tana basin - the upper part of the Upper Blue Nile basin. The conventional weather simulation performed satisfactorily (e.g., NSE ≥ 0.5) for three gauging stations, while the CFSR weather simulation performed satisfactorily for two. The simulations with CFSR and conventional weather yielded minor differences in the water balance components in all but one watershed, where the CFSR weather simulation gave much higher average annual rainfall, resulting in higher water balance components. Both weather simulations gave similar annual crop yields in the four administrative zones. Overall the simulation with the conventional weather performed better than the CFSR weather. However, in data-scarce regions such as remote parts of the Upper Blue Nile basin, CFSR weather could be a valuable option for hydrological predictions where conventional gauges are not available. [ABSTRACT FROM AUTHOR]

Accurate analysis of water flow pathways from rainfall to streams is critical for simulating water use, climate change impact, and contaminants transport. In this study, we developed a new scheme to simultaneously calibrate surface flow (SF) and baseflow (BF) simulations of soil and water assessment tool (SWAT) by combing evolutionary multi-objective optimization (EMO) and BF separation techniques. The application of this scheme demonstrated pronounced trade-off of SWAT's performance on SF and BF simulations. The simulated major water fluxes and storages variables (e.g. soil moisture, evapotranspiration, and groundwater) using the multiple parameters from EMO span wide ranges. Uncertainty analysis was conducted by Bayesian model averaging of the Pareto optimal solutions. The 90% confidence interval (CI) estimated using all streamflows substantially overestimate the uncertainty of low flows on BF days while underestimating the uncertainty of high flows on SF days. Despite using statistical criteria calculated based on streamflow for model selection, it is important to conduct diagnostic analysis of the agreement of SWAT behaviour and actual watershed dynamics. The new calibration technique can serve as a useful tool to explore the tradeoff between SF and BF simulations and provide candidates for further diagnostic assessment and model identification. [ABSTRACT FROM AUTHOR]

Climate change has the potential to reduce water resource availability in the Nile Basin countries in the forthcoming decades. We investigated the sensitivity of water resources to climate change in the Lake Tana Basin, Ethiopia, using outputs from global climate models (GCMs). First, we compiled projected changes in monthly precipitation and temperature in the basin from 15 GCMs. Although the GCMs uniformly suggest increases in temperature, the rainfall projections are not consistent. Second, we investigated how changes in daily temperature and precipitation might translate into changes in streamflow and other hydrological components. For this, we generated daily climate projections by modifying the historical data sets to represent the changes in the GCM climatologies and calculated hydrological changes using the Soil and Water Assessment Tool (SWAT). The SWAT model itself was calibrated and validated using the flows from four tributaries of Lake Tana. For the Special Report on Emissions Scenarios A2 scenario, four of the nine GCMs investigated showed statistically significant declines in annual streamflow for the 2080-2100 period. We interpret our results to mean that anthropogenic climate changes may indeed alter the water balance in the Lake Tana Basin during the next century but that the direction of change cannot be determined with confidence using the current generation of GCMs. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) were used to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this combined method, several SWAT models with different structures are first selected; next GA is used to calibrate each model using observed streamflow data; finally, BMA is applied to combine the ensemble predictions and provide uncertainty interval estimation. This method was tested in two contrasting basins, the Little River Experimental Basin in Georgia, USA, and the Yellow River Headwater Basin in China. The results obtained in the two case studies show that this combined method can provide deterministic predictions better than or comparable to the best calibrated model using GA. The 66.7% and 90% uncertainty intervals estimated by this method were analyzed. The differences between the percentage of coverage of observations and the corresponding expected coverage percentage are within 10% for both calibration and validation periods in these two test basins. This combined methodology provides a practical and flexible tool to attain reliable deterministic simulation and uncertainty analysis of SWAT. [Copyright &y& Elsevier]

The article presents the findings from a study that addressed the efficacy of five optimization algorithms for parameter calibration of the hydrologic model, Soil and Water Assessment Tool (SWAT), as applied to four watersheds in the U.S. It discusses the performance of each optimization algorithm, which includes genetic algorithm (GA), shufflex complex evolution (SCE), particle swarm optimization (PSO), differential evolution (DE) and artificial immune system (AIS). It notes that PSO algorithm is opted when given a limited computational time, while GA is preferred when there is more time for such process.

Despite the general awareness that in Africa many people and large areas are suffering from insufficient water supply, spatially and temporally detailed information on freshwater availability and water scarcity is so far rather limited. By applying a semidistributed hydrological model SWAT (Soil and Water Assessment Tool), the freshwater components blue water flow (i.e., water yield plus deep aquifer recharge), green water flow (i.e., actual evapotranspiration), and green water storage (i.e., soil water) were estimated at a subbasin level with monthly resolution for the whole of Africa. Using the program SUFI-2 (Sequential Uncertainty Fitting Algorithm), the model was calibrated and validated at 207 discharge stations, and prediction uncertainties were quantified. The presented model and its results could be used in various advanced studies on climate change, water and food security, and virtual water trade, among others. The model results are generally good albeit with large prediction uncertainties in some cases. These uncertainties, however, disclose the actual knowledge about the modeled processes. The effect of considering these model-based uncertainties in advanced studies is shown for the computation of water scarcity indicators. [ABSTRACT FROM AUTHOR]

The Soil and Water Assessment Tool (SWAT) model combined with different snowmelt algorithms was evaluated for runoff simulation of an 114,345 km2 mountainous river basin (the headwaters of the Yellow River), where snowmelt is a significant process. The three snowmelt algorithms incorporated into SWAT were as follows: (1) the temperature-index, (2) the temperature-index plus elevation band, and (3) the energy budget based SNOW17. The SNOW17 is more complex than the temperature-based snowmelt algorithms, and requires more detailed meteorological and topographical inputs. In order to apply the SNOW17 in the SWAT framework, SWAT was modified to operate at the pixel scale rather than the normal Hydrologic Response Unit scale. The three snowmelt algorithms were evaluated under two parameter scenarios, the default and the calibrated parameters scenarios. Under the default parameters scenario, the parameter values were determined based on a review of the current literature. The purpose of this type of evaluation was to assess the applicability of SWAT in ungauged basins, where there is little observed data available for calibration. Under the calibrated parameters scenario, the parameters were calibrated using an automatic calibration program, the Shuffled Complex Evolution (SCE-UA). The purpose of this type of evaluation was to assess the applicability of SWAT in gauged basins. Two time periods (1975-1985 and 1986-1990) of monthly runoff data were used in this study to evaluate the performance of SWAT with different snowmelt algorithms. Under the default parameters scenario, the SWAT model with complex energy budget based SNOW17 performed the best for both time periods. Under the calibrated parameters scenario, the parameters were calibrated using monthly runoff from 1975-1985 and validated using monthly runoff from 1986-1990. After parameter calibration, the performance of SWAT with the three snowmelt algorithms was improved from the default parameters scenario. Further, the SWAT model with temperature-index plus elevation band performed as well as the SWAT model with SNOW17. The SWAT model with temperature-index algorithm performed the poorest for both time periods under both scenarios. Therefore, it is suggested that the SNOW17 model be used for modeling ungauged basins; however, for gauged basins, the SNOW17 and simple temperature-index plus elevation band models could provide almost equally good runoff simulation results. [ABSTRACT FROM AUTHOR]

Departures in precipitation from the normal are the cause of the onset of agricultural drought. In this study, we aim to identify extreme precipitation deficits using an index called Percent Normal (PN). We applied the proposed PN index to the agriculturally productive Mekong River Basin (MRB) to evaluate the propagation of precipitation deficits into agricultural drought based on the change in slope and mean of the precipitation, soil moisture and evapotranspiration anomalies. The results of the study showed the proposed PN index identified historical droughts in the years 1992, 1997–1998 and 2000–2006 in MRB; of these, 1992 was shown to be the longest drought, which lasted from the 43rd week (October) of 1991 to the 49th week (December) of 1994. The short-term but extreme drought was identified to occur in 2005 with below-normal precipitation that lasted for more than a year. An immediate effect of precipitation deficit was observed in evapotranspiration (ET) and soil water for agricultural (Thailand) and forested regions (Parts of Cambodia) of the basin with <5 weeks lag. We conclude that the drought indices adopted in this study are suitable to identify the small and long-term drought events, which will facilitate the development of a drought-resilient agricultural production system. [ABSTRACT FROM AUTHOR]

In the semi-arid regions of South Asia, tank systems are the major source of irrigation. In India, the Telangana state government has initiated the Mission Kakatiya program to rejuvenate irrigation tank systems. Understanding the hydrological processes that supply water to these systems is critical to the success of these types of programs in India. The current study attempted to comprehend the hydrological processes and flow routing in the Salivagu watershed tank cascade system in Telangana. There are a lot of ungauged tank cascade systems in this region. Soil Water Assessment Tool (SWAT), a physically-based model, was used to simulate flow patterns in the Salivagu watershed with and without tank systems. The geospatially extracted area and volume were used for this study provided by WBIS-Bhuvan-NRSC. Additionally, the Katakshapur Tank Cascade System (KTCS) was chosen to analyze the water availability in each tank using the water balance approach. The Salivagu watershed flow simulation without tanks overestimated streamflow. The volume difference in flow between with and without tank was 606 Mm3, 615.9 Mm3, and 1011 Mm3 in 2017, 2018, and 2019, respectively. The SWAT simulated volumes of the Ramchandrapur and Dharmaraopalle tanks in KTCS were merely satisfied because the tank size was less than 0.7 km2 and the storage capacity was up to 1 Mm3. Due to tank sizes more than 0.8 km2 and capacities greater than 2 Mm3, the Mallampalli and Katakshapur tank simulation findings were in good agreement with WBIS-Bhuvan-NRSC. This research advances our understanding of the hydrological processes in ungauged cascading tank systems in tropical semi-arid regions. [ABSTRACT FROM AUTHOR]

The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from −17% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach. [ABSTRACT FROM AUTHOR]

The quality of input data and the process of watershed delineation can affect the accuracy of runoff predictions in watershed modeling. The Upper Mississippi River Basin was selected to evaluate the effects of subbasin and/or hydrologic response unit (HRU) delineations and the density of climate dataset on the simulated streamflow and water balance components using the Hydrologic and Water Quality System (HAWQS) platform. Five scenarios were examined with the same parameter set, including 8- and 12-digit hydrologic unit codes, two levels of HRU thresholds and two climate data densities. Results showed that statistic evaluations of monthly streamflow from 1983 to 2005 were satisfactory at some gauge sites but were relatively worse at others when shifting from 8-digit to 12-digit subbasins, revealing that the hydrologic response to delineation schemes can vary across a large basin. Average channel slope and drainage density increased significantly from 8-digit to 12-digit subbasins. This resulted in higher lateral flow and groundwater flow estimates, especially for the lateral flow. Moreover, a finer HRU delineation tends to generate more runoff because it captures a refined level of watershed spatial variability. The analysis of climate datasets revealed that denser climate data produced higher predicted runoff, especially for summer months. [ABSTRACT FROM AUTHOR]

The spatial and temporal scale of rainfall datasets is crucial in modeling hydrological processes. Recently, open-access satellite precipitation products with improved resolution have evolved as a potential alternative to sparsely distributed ground-based observations, which sometimes fail to capture the spatial variability of rainfall. However, the reliability and accuracy of the satellite precipitation products in simulating streamflow need to be verified. In this context, the objective of the current study is to assess the performance of three rainfall datasets in the prediction of daily and monthly streamflow using Soil and Water Assessment Tool (SWAT). We used rainfall data from three different sources: Climate Hazards Group InfraRed Rainfall with Station data (CHIRPS), Climate Forecast System Reanalysis (CFSR) and observed rain gauge data. Daily and monthly rainfall measurements from CHIRPS and CFSR were validated using widely accepted statistical measures, namely, correlation coefficient (CC), root mean squared error (RMSE), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The results showed that CHIRPS was in better agreement with ground-based rainfall at daily and monthly scale, with high rainfall detection ability, in comparison with the CFSR product. Streamflow prediction across multiple watersheds was also evaluated using Kling-Gupta Efficiency (KGE), Nash-Sutcliffe Efficiency (NSE) and Percent BIAS (PBIAS). Irrespective of the climatic characteristics, the hydrologic simulations of CHIRPS showed better agreement with the observed at the monthly scale with the majority of the NSE values ranging between 0.40 and 0.78, and KGE values ranging between 0.62 and 0.82. Overall, CHIRPS outperformed the CFSR rainfall product in driving SWAT for streamflow simulations across the multiple watersheds selected for the study. The results from the current study demonstrate the potential of CHIRPS as an alternate open access rainfall input to the hydrologic model. [ABSTRACT FROM AUTHOR]

Gridded precipitation products (GPPs) with wide spatial coverage and easy accessibility are well recognized as a supplement to ground-based observations for various hydrological applications. The error properties of satellite rainfall products vary as a function of rainfall intensity, climate region, altitude, and land surface conditions—all factors that must be addressed prior to any application. Therefore, this study aims to evaluate four commonly used GPPs: the Climate Prediction Center (CPC) Unified Gauge-Based Analysis of Global Daily Precipitation, the Climate Prediction Center Morphing (CMORPH) technique, the Tropical Rainfall Measuring Mission (TRMM) 3B42, and the Global Satellite Mapping of Precipitation (GSMaP), using data collected in the period 1998–2006 at different spatial and temporal scales. Furthermore, this study investigates the hydrological performance of these products against the 175 rain gauges placed across the whole Mekong River Basin (MRB) using a set of statistical indicators, along with the Soil and Water Assessment Tool (SWAT) model. The results from the analysis indicate that TRMM has the best performance at the annual, seasonal, and monthly scales, but at the daily scale, CPC and GSMaP are revealed to be the more accurate option for the Upper MRB. The hydrological evaluation results at the daily scale further suggest that the TRMM is the more accurate option for hydrological performance in the Lower MRB, and CPC shows the best performance in the Upper MRB. Our study is the first attempt to use distinct suggested GPPs for each individual sub-region to evaluate the water balance components in order to provide better references for the assessment and management of basin water resources in data-scarce regions, suggesting strong capabilities for utilizing publicly available GPPs in hydrological applications. [ABSTRACT FROM AUTHOR]

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. [ABSTRACT FROM AUTHOR]