Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs

Taking full advantage of 'low-quality' datasets in watershed modeling and management: From a perspective of parameter calibration

The quality of calibration datasets is critical for establishing well-calibrated models for reliable decision-making support. However, the analysis of the influence of calibration dataset quality and the discussion on how to use flawed and/or incomplete datasets are still far from sufficient. An evaluation framework for the impact of model calibration data on parameter identifiability, sensitivity, and uncertainty (ISU) was established. Three quantitative and normalized indicators were designed to describe the magnitude of ISU. With the case study of the upper Daqing River watershed, China and the model SWAT (Soil and Water Assessment Tool), one ideal dataset without quality flaws and 79 datasets with different types of flaws including observation error, low monitoring frequency, short data duration and low data resolution were evaluated. The result showed that 4 of 13 parameters that control canopy, groundwater and channel processes have higher ISU values, indicating the high identifiability, high sensitivity, and low uncertainty. The largest gap of parameter ISU between dataset with quality flaw and ideal dataset was 0.61 due to short data duration, while the smallest gap was -0.28 due to low monitoring data frequency. Although some defective datasets caused unacceptable calibration results and model output, some defective datasets can still be valuable for model calibration which depends on the hydrological processes of interest when applying the model. Equivalent calibration results were yielded by the datasets with similar statistical properties. When using datasets with traditional defective issues for calibration, a new step checking the consistency among decision goal, representative system process, determinative parameters and calibration datasets is suggested. Practices including process-related data selection, dataset regrouping and risk self-reporting when using low-quality datasets are encouraged to increase the reliability of model-based watershed management.

Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model

The Soil and Water Assessment Tool (SWAT) is a computational hydrological model extensively utilised for developing sustainable strategies and viable approaches for prudent management of water resources. The central emphasis of this study is on the utilisation of SWAT model along with SWAT-CUP (SWAT calibration toolbox) to simulate streamflow in the upper Jhelum basin, the North West Himalayas, for a period of 20 years from 2000 to 2019. The global sensitivity analysis algorithm, Sequential Uncertainty Fitting 2 (SUFI-2) of SWAT-CUP, is used for sensitivity and uncertainty analysis. The optimised parameter set estimated by SUFI-2 constitutes 11 parameters that are found to be sensitive with soil conservation service (SCS) curve number (CN) being the most influential parameter followed by snowmelt base temperature. Autocorrelation analysis using the autocorrelation function was conducted on the temperature and precipitation time series data, followed by a pre-whitening procedure to remove any autocorrelation effects. Subsequently, the modified Mann-Kendall (MMK) test was applied to examine trends in the annual temperature and precipitation data. The results indicated statistically significant positive trends in both datasets on an annual scale. The results for the calibration period (2003-2014) for monthly simulation displayed good model performance at three gauging stations, Rambiara, Sangam and Ram Munshi Bagh with R2 values of 0.83, 0.847, 0.829, P factor values of 0.73, 0.76, 0.75 and R factor values of 0.61, 0.58, 0.63, respectively. The validation results for monthly simulation for the 2015-2019 period showed good model agreement with R2 values of 0.817, 0.853, and 0.836, P factor values of 0.76, 0.8, and 0.75 and R factor values of 0.62, 0.53, and 0.65, respectively. The study concludes that the SWAT hydrological model can perform satisfactorily in high mountainous catchments and can be employed to analyse the impact of land use-land cover changes and the effect of climate variation on streamflow dynamics.

Calibration and Validation of SWAT Model by Using Hydrological Remote Sensing Observables in the Lake Chad Basin

Model calibration and validation are challenging in poorly gauged basins. We developed and applied a new approach to calibrate hydrological models using distributed geospatial remote sensing data. The Soil and Water Assessment Tool (SWAT) model was calibrated using only twelve months of remote sensing data on actual evapotranspiration (ETa) geospatially distributed in the 37 sub-basins of the Lake Chad Basin in Africa. Global sensitivity analysis was conducted to identify influential model parameters by applying the Sequential Uncertainty Fitting Algorithm–version 2 (SUFI-2), included in the SWAT-Calibration and Uncertainty Program (SWAT-CUP). This procedure is designed to deal with spatially variable parameters and estimates either multiplicative or additive corrections applicable to the entire model domain, which limits the number of unknowns while preserving spatial variability. The sensitivity analysis led us to identify fifteen influential parameters, which were selected for calibration. The optimized parameters gave the best model performance on the basis of the high Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and determination coefficient (R2). Four sets of remote sensing ETa data products were applied in model calibration, i.e., ETMonitor, GLEAM, SSEBop, and WaPOR. Overall, the new approach of using remote sensing ETa for a limited period of time was robust and gave a very good performance, with R2 > 0.9, NSE > 0.8, and KGE > 0.75 applying to the SWAT ETa vs. the ETMonitor ETa and GLEAM ETa. The ETMonitor ETa was finally adopted for further model applications. The calibrated SWAT model was then validated during 2010–2015 against remote sensing data on total water storage change (TWSC) with acceptable performance, i.e., R2 = 0.57 and NSE = 0.55, and remote sensing soil moisture data with R2 and NSE greater than 0.85.

Assessing the Effect of Land-Use and Land-Cover Changes on Discharge and Sediment Yield in a Rural Coal-Mine Dominated Watershed in Kentucky, USA

The Appalachian Mountain region of eastern Kentucky is unique and contains high proportions of forestland along with coal and natural gas depositaries. Landscape changes due to extreme mining activities can eventually threaten the downstream ecosystems, including soil and water quality, resulting in excessive runoff and sedimentation. The purpose of this study is to assess the impacts of land-use and land-cover (LULC) changes in streamflow and sediment yield in Yellow Creek Watershed, Kentucky, USA, between 1992 and 2016. LULC, digital elevation model, soil, and weather data were inputted into the Soil and Water Assessment Tool (SWAT) to simulate discharge and sediment yield. The model output was evaluated on several statistical parameters, such as the Nash-Sutcliffe efficiency coefficient (NSE), RMSE-observations standard deviation ratio (RSR), percent bias (PBIAS), and the coefficient of determination (R2). In addition, two indices, P-factor and R-factor, were used to measure the prediction uncertainty. The calibrated model showed an increase in surface runoff and sediment yield due to changes in LULC in the Yellow Creek Watershed. The results provided important insights for studying water management strategies to make more informed land management decisions and adaptive practices.

Significance of using dynamic land-use data and its threshold in hydrology and water quality simulation models

Land-use changes have a significant impact on the hydrological cycle and non-point source (NPS) pollution discharge and transport. Thus, using dynamic land-use inputs in the simulation models is important. However, there is currently no clear standard for which situation the land-use data should be updated in the models. In this study, we quantified the impacts of land-use change on hydrological and NPS pollution simulation outputs, and analyzed the thresholds for land-use change level and time nodes. The results indicated that the error caused by land-use change had a linear relationship with the land-use change level. The total nitrogen (TN) output error was the most sensitive to land-use change, with a gradient of 0.73. The impact of land-use change on the model outputs was different at different temporal scales. Flow and TN had the highest output errors at a daily scale, while sediment had the highest output error at an annual scale. The threshold analysis results revealed that the land-use change thresholds for the flow, sediment, and TN simulations were 40%, 30%, and 10%, respectively. When the land-use change level exceeded the threshold, the model simulation error increased dramatically. The land-use change time node would also affect the simulation performance, especially for TN. This study initially explored the quantified standard for land-use data updates in the SWAT model. The results could be useful for improving the simulation accuracy of the SWAT model and may provide ideas for follow-up studies.

Simulating internal watershed processes using multiple SWAT models

The need for effective water quality models to help guide management and policy, and extend monitoring information, is at the forefront of recent discussions related to watershed management. These models are often calibrated and validated at the basin outlet, which ensures that models are capable of evaluating basin scale hydrology and water quality. However, there is a need to understand where these models succeed or fail with respect to internal process representation, as these watershed-scale models are used to inform management practices and mitigation strategies upstream. We evaluated an ensemble of models-each calibrated to in-stream observations at the basin outlet-against discharge and nutrient observations at the farm field scale to determine the extent to which these models capture field-scale dynamics. While all models performed well at the watershed outlet, upstream performance varied. Models tended to over-predict discharge through surface runoff and subsurface drainage, while under-predicting phosphorus loading through subsurface drainage and nitrogen loading through surface runoff. Our study suggests that while models may be applied to predict impacts of management at the basin scale, care should be taken in applying the models to evaluate field-scale management and processes in the absence of data that can be incorporated at that scale, even with the use of multiple models.

Evaluation of the predictive reliability of a new watershed health assessment method using the SWAT model

The purpose of watershed assessments is to give information about conditions of water quality, stream morphology, and biological integrity to identify the sources of stressors and their impacts. In recent decades, different watershed assessment methods have been developed to evaluate the cumulative impacts of human activities on watershed health and the condition of aquatic systems. In the current research, we propose a new approach for assessing watershed vulnerability to contamination based on spatial analysis by using geographic information systems (GIS) and the analytic hierarchy process (AHP) technique. This new procedure, designed to identify vulnerable zones, depends on six basic factors that represent watershed characteristics: land use/land cover, soil type, average annual precipitation, slope, depth to groundwater, and bedrock type. The general assumptions for assessing watershed vulnerability are based on the response of watersheds to different contamination impacts and how the six selected factors interact to affect watershed health. The new watershed vulnerability assessment technique was used to create maps showing the relative vulnerabilities of specific sub-watersheds in the Eagle Creek Watershed in central Indiana. The results showed a remarkable difference in watershed susceptibility between the sub-watersheds in their vulnerability to pollution. To test the reliability of the proposed vulnerability assessment technique, the SWAT (Soil and Water Assessment Tool) model was applied to predict the water quality in each sub-watershed. Using the SWAT model, some parameters (e.g., total suspended solids [TSS] and nitrate) were tested based on the availability of the data needed for comparison. Both the SWAT and the newly proposed method produced good results in predicting water quality loads, which validated the proposed method. Hence, the results of the evaluation of the predictive reliability of the watershed vulnerability assessment method revealed that the proposed approach is suitable as a decision-making tool to predict watershed health.

Impacts of Climate Change and Land-Use Change on Hydrological Extremes in the Jinsha River Basin

Hydrological extremes are closely related to extreme hydrological events, which have been and continue to be one of the most important natural hazards causing great damage to lives and properties. As two of the main factors affecting the hydrological cycle, land-use change and climate change have attracted the attention of many researchers in recent years. However, there are few studies that comprehensively consider the impacts of land-use change and climate change on hydrological extremes, and few researchers have made a quantitative distinction between them. Regarding this problem, this study aims to quantitatively distinguish the effects of land-use change and climate change on hydrological extremes during the past half century using the method of scenarios simulation with the soil and water assessment tool (SWAT). Furthermore, the variations of hydrological extremes are forecast under future scenarios by incorporating the downscaled climate simulations from several representative general circulation models (GCMs). Results show that: (1) respectively rising and declining risks of floods and droughts are detected during 1960–2017. The land use changed little during 1980–2015, except for the water body and building land. (2) The SWAT model possesses better simulation effects on high flows compared with low flows. Besides, the downscaled GCM data can simulate the mean values of runoff well, and acceptable simulation effects are achieved for the extreme runoff indicators, with the exception of frequency and durations of floods and extreme low flows. (3) During the period 1970–2017, the land-use change exerts little impact on runoff extremes, while climate change is one of the main factors leading to changes in extreme hydrological situation. (4) In the context of global climate change, the indicators of 3-day max and 3-day min runoff will probably increase in the near future (2021–2050) compared with the historical period (1970–2005). This research helps us to better meet the challenge of probably increased flood risks by providing references to the decision making of prevention and mitigation measures, and thus possesses significant social and economic value.

Progress in pectin based hydrogels for water purification: Trends and challenges

Pectin is one of the finest natural polymer which has drawn great attention because of its applications in different fields. Due to the quintessential structure of pectin, it can be transformed into variety of useful products. It can be utilized as a blend in many polymers to make a mixture or a composite material. Owing to considerable collection in chemical conformation and cross-linking mechanism, different pectin based hydrogels have been prepared for different characteristics in pharmaceutical and bio-medical sites. Inventive properties of hydrogels like volubility, swellability, solvability and hydrophilicity make them better alternative for wastewater treatment. Recently, pectin based hydrogels have demonstrated excellent performance to eliminate various metal ions and dyes from the polluted water. The adsorption characteristics of pectin based hydrogels can be upgraded by using nanoparticles, which prompts to the development of hydrogel nano-composites. In this review article, we have summarized a comprehensive assessment in the direction of using pectin based hydrogels to remove toxic pollutants from aqueous solution. Sodium acrylate-co-N-isopropylacrylamide based pectin hydrogel has demonstrated the maximum adsorption capacities of 265.49, 137.43, 54.86, 53.86, 51.72 and 50.01 mg g^-1 for the adsorption of methyl violet, methylene blue, Pb(II), Cu(II), Co(II) and Zn(II) respectively. We have also discussed the pectin structure, properties and applications in this article.

Inter-comparison of water balance components of river basins draining into selected delta districts of Eastern India

Quantification of hydrological components in-terms of surface runoff, stream flow and evapotranspiration is important and useful in planning and management of water resources across the river basin, including downstream delta regions. River deltas water availability; management and related disaster risk are largely influenced by the hydrological state of upstream river basins. The paper presents the results of hydrological modelling (SWAT) based long-term water balance components in river basins draining into selected delta Districts of Eastern India. Mahanadi, Brahmani-Baitarani river basins and Hooghly river and adjacent small river basins are considered. The long-term water balance components of Mahanadi and Brahmani-Baitarani river basins are similar and significantly different in Hooghly river and adjacent small river basins. The runoff coefficient is significantly higher in Hooghly river and adjacent small river basins at 0.39 compared to other two river basins (0.247 & 0.256). The evapotranspiration component is relatively low in Hooghly river and adjacent small river basins with smaller range of long-term variation. The time-series model outputs brought out the basin-specific hydrological response variations in low and high rainfall years such as changes in fraction of evapotranspiration and surface runoff. Mahanadi and Brahmani-Baitarani river basins exhibit large inter-annual variation in evapotranspiration, surface runoff fractions. The developed hydrological modelling framework is capable of incorporating future climate data and to predict the basin-scale future water availability, demand, use and to bring out resulting water scenarios that would impact river deltas in-terms of their exposure towards water related adversities, such as drought and flood.

Effects of Different Spatial Configuration Units for the Spatial Optimization of Watershed Best Management Practice Scenarios

Different spatial configurations (or scenarios) of multiple best management practices (BMPs) at the watershed scale may have significantly different environmental effectiveness, economic efficiency, and practicality for integrated watershed management. Several types of spatial configuration units, which have resulted from the spatial discretization of a watershed at different levels and used to allocate BMPs spatially to form an individual BMP scenario, have been proposed for BMP scenarios optimization, such as the hydrologic response unit (HRU) etc. However, a comparison among the main types of spatial configuration units for BMP scenarios optimization based on the same one watershed model for an area is still lacking. This paper investigated and compared the effects of four main types of spatial configuration units for BMP scenarios optimization, i.e., HRUs, spatially explicit HRUs, hydrologically connected fields, and slope position units (i.e., landform positions at hillslope scale). The BMP scenarios optimization was conducted based on a fully distributed watershed modeling framework named the Spatially Explicit Integrated Modeling System (SEIMS) and an intelligent optimization algorithm (i.e., NSGA-II, short for Non-dominated Sorting Genetic Algorithm II). Different kinds of expert knowledge were considered during the BMP scenarios optimization, including without any knowledge used, using knowledge on suitable landuse types/slope positions of individual BMPs, knowledge of upstream–downstream relationships, and knowledge on the spatial relationships between BMPs and spatial positions along the hillslope. The results showed that the more expert knowledge considered, the better the comprehensive cost-effectiveness and practicality of the optimized BMP scenarios, and the better the optimizing efficiency. Thus, the spatial configuration units that support the representation of expert knowledge on the spatial relationships between BMPs and spatial positions (i.e., hydrologically connected fields and slope position units) are considered to be the most effective spatial configuration units for BMP scenarios optimization, especially when slope position units are adopted together with knowledge on the spatial relationships between BMPs and slope positions along a hillslope.

Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds

Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km² , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization approach provide a capable method for predicting the aquatic exposure required to support pesticide regulatory decision making. Integr Environ Assess Manag 2018;14:358-368. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Calibration of a Field-Scale Soil and Water Assessment Tool (SWAT) Model with Field Placement of Best Management Practices in Alger Creek, Michigan

Subwatersheds within the Great Lakes “Priority Watersheds” were targeted by the Great Lakes Restoration Initiative (GLRI) to determine the effectiveness of the various best management practices (BMPs) from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) Database. A Soil and Water Assessment Tool (SWAT) model is created for Alger Creek, a 50 km2 tributary watershed to the Saginaw River in Michigan. Monthly calibration yielded very good Nash–Sutcliffe efficiency (NSE) ratings for flow, sediment, total phosphorus (TP), dissolved reactive phosphorus (DRP), and total nitrogen (TN) (0.90, 0.79, 0.87, 0.88, and 0.77, respectively), and satisfactory NSE rating for nitrate (0.51). Two-year validation results in at least satisfactory NSE ratings for flow, sediment, TP, DRP, and TN (0.83, 0.54, 0.73, 0.53, and 0.60, respectively), and unsatisfactory NSE rating for nitrate (0.28). The model estimates the effect of BMPs at the field and watershed scales. At the field-scale, the most effective single practice at reducing sediment, TP, and DRP is no-tillage followed by cover crops (CC); CC are the most effective single practice at reducing nitrate. The most effective BMP combinations include filter strips, which can have a sizable effect on reducing sediment and phosphorus loads. At the watershed scale, model results indicate current NCP BMPs result in minimal sediment and nutrient reductions (<10%).

Simulation of targeted pollutant-mitigation-strategies to reduce nitrate and sediment hotspots in agricultural watershed

About 50% of U.S. water pollution problems are caused by non-point source (NPS) pollution, primarily sediment and nutrients from agricultural areas, despite the widespread implementation of agricultural Best Management Practices (BMPs). However, the effectiveness of implementation strategies and type of BMPs at watershed scale are still not well understood. In this study, the Soil and Water Assessment Tool (SWAT) ecohydrological model was used to assess the effectiveness of pollutant mitigation strategies in the Raccoon River watershed (RRW) in west-central Iowa, USA. We analyzed fourteen management scenarios based on systematic combinations of five strategies: fertilizer/manure management, changing row-crop land to perennial grass, vegetative filter strips, cover crops and shallower tile drainage systems, specifically aimed at reducing nitrate and total suspended sediment yields from hotspot areas in the RRW. Moreover, we assessed implications of climate change on management practices, and the impacts of management practices on water availability, row crop yield, and total agricultural production. Our results indicate that sufficient reduction of nitrate load may require either implementation of multiple management practices (38.5% with current setup) or conversion of extensive areas into perennial grass (up to 49.7%) to meet and maintain the drinking water standard. However, climate change may undermine the effectiveness of management practices, especially late in the 21st century, cutting the reduction by up to 65% for nitrate and more for sediment loads. Further, though our approach is targeted, it resulted in a slight decrease (~5%) in watershed average crop yield and hence an overall reduction in total crop production, mainly due to the conversion of row-crop lands to perennial grass. Such yield reductions could be quite spatially heterogeneously distributed (0 to 40%).

Agricultural Conservation Planning Framework: 3. Land Use and Field Boundary Database Development and Structure

Conservation planning information is important for identifying options for watershed water quality improvement and can be developed for use at field, farm, and watershed scales. Translation across scales is a key issue impeding progress at watershed scales because watershed improvement goals must be connected with implementation of farm- and field-level conservation practices to demonstrate success. This is particularly true when examining alternatives for "trap and treat" practices implemented at agricultural-field edges to control (or influence) water flows through fields, landscapes, and riparian corridors within agricultural watersheds. We propose that database structures used in developing conservation planning information can achieve translation across conservation-planning scales, and we developed the Agricultural Conservation Planning Framework (ACPF) to enable practical planning applications. The ACPF comprises a planning concept, a database to facilitate field-level and watershed-scale analyses, and an ArcGIS toolbox with Python scripts to identify specific options for placement of conservation practices. This paper appends two prior publications and describes the structure of the ACPF database, which contains land use, crop history, and soils information and is available for download for 6091 HUC12 watersheds located across Iowa, Illinois, Minnesota, and parts of Kansas, Missouri, Nebraska, and Wisconsin and comprises information on 2.74 × 10 agricultural fields (available through /). Sample results examining land use trends across Iowa and Illinois are presented here to demonstrate potential uses of the database. While designed for use with the ACPF toolbox, users are welcome to use the ACPF watershed data in a variety of planning and modeling approaches.

An Analysis of the Climate Change Mitigation Potential through Soil Organic Carbon Sequestration in a Corn Belt Watershed

Land-based carbon sequestration constitutes a major low cost and immediately viable option in climate change mitigation. Using downscaled data from eight atmosphere-ocean general circulation models for a simulation period between 2015 and 2099, we examine the carbon sequestration potential of alternative agricultural land uses in an intensively farmed Corn Belt watershed and the impact of climate change on crop yields. Our results show that switching from conventional tillage continuous corn to no-till corn-soybean can sequester the equivalent of 192.1 MtCO2 eq of soil organic carbon per hectare with a sequestration rate of 2.26 MtCO2 eq ha-1 yr-1. Our results also indicate that switchgrass can sequester the equivalent of 310.7 MtCO2 eq of soil organic carbon per hectare with a sequestration rate of 3.65 MtCO2 eq ha-1 yr-1. Our findings suggest that, unlike for corn and soybean yields, climate change does not have a significant effect on switchgrass yields, possibly due to the carbon fertilization effect.