Soil And Water Assessment Tool Calibration Research Articles

Enhanced SWAT calibration through intelligent range-based parameter optimization

Hydrological models are vital tools in environmental management. Weaknesses in model robustness for hydrological parameters transfer uncertainties to the model outputs. For streamflow, the optimized parameters are the primary source of uncertainty. A reliable calibration approach that reduces prediction uncertainty in model simulations is crucial for enhancing model robustness and reliability. The optimization of parameter ranges is a key aspect of parameter calibration, yet there is a lack of literature addressing the optimization of parameter ranges in hydrological models. In this paper, we introduce a parameter calibration strategy that applies a clustering technique, specifically the Self-Organizing Map (SM), to intelligently navigate the parameter space during the calibration of the Soil and Water Assessment Tool (SWAT) model for monthly streamflow simulation in the Baishan Basin, Jilin Province, China. We selected the representative algorithm, the Sequential Uncertainty Fitting version 2 (SUFI-2), from the commonly used SWAT Calibration and Uncertainty Programs for comparison. We developed three schemes: SUFI-2, SUFI-2-Narrowing Down (SUFI-2-ND), and SM. Multiple diagnostic error metrics were used to compare simulation accuracy and prediction uncertainty. Among all schemes, SM outperformed the others in describing watershed streamflow, particularly excelling in the simulation of spring snowmelt runoff (baseflow period). Additionally, the prediction uncertainty was effectively controlled, demonstrating the SM's adaptability and reliability in the interval optimization process. This provides managers with more credible prediction results, highlighting its potential as a valuable calibration tool in hydrological modeling.

Effects of input data accuracy, catchment threshold areas and calibration algorithms on model uncertainty reduction

AbstractLow resolution of input data and equifinality in model calibration can lead to inaccuracy and insufficient reflection of spatial differences, thereby increasing model errors. However, the impact of input data accuracy, catchment threshold area, and calibration algorithm on model uncertainty reduction has not yet been well understood. The sequential uncertainty fitting version 2 (SUFI‐2) that is linked with the Soil and Water Assessment Tool (SWAT) in the package called SWAT Calibration Uncertainty Programs (SWAT‐CUP) was introduced to quantify the effects of different input data resolutions on parameter sensitivity and model uncertainty in the Jinghe River watershed, and the effects of different sub‐basin delineations and other two calibration algorithms on model uncertainty were also comparatively analysed. (i) USLE_C, EPCO, ALPHA_BNK, and CN2 are the most sensitive parameters among all SWAT projects. When the change of digital elevation model (DEM) resolution is small, the sensitivity of parameters does not change obviously. When the DEM resolution changes significantly, BIOMIX, LAT_SED, USLE_K, and CH_N1 become highly sensitive parameters by replacing OV_N, SMTMP, SURLAG, and USLE_P. However, the change in land use resolution has little impact on parameter sensitivity, with only a slight change in the sensitivity ranking of specific parameters. (ii) Model uncertainty responded to changes in the resolution of DEM more than land use. Most of the runoff simulations had smaller uncertainties (P factor, R factor, percentage of bias [PBIAS]) than sediment. High resolution DEM data reduced model uncertainty, but the models with 2000 m DEM resolution also achieved small uncertainty. Small catchment threshold area leads to high uncertainty of the model, and large catchment threshold areas decrease the model uncertainty. The model has relatively good simulation effects in runoff and sediment when the catchment threshold area was 2000 km2. (iii) The SWAT model has different simulation deviations and uncertainties in different calibration algorithms, the SUFI‐2 and generalized likelihood uncertainty estimation (GLUE) algorithms show better applicability than particle swarm optimization (PSO). The NSE indicators of the three algorithms are in the following order: SUFI‐2 > GLUE > PSO for runoff, and GLUE > SUFI‐2 > PSO for sediment. This study helps us understand the cause, knowledge of which moves from the particular to the general by the comprehension of essence, power, and nature in reducing model uncertainty.

Staged SWAT calibration with bias-corrected precipitation product for enhancing flow data continuity in tributaries of the Mekong River

Accurate and continuous flow data are crucial for effective water management in large river basins worldwide. However, these catchments often face challenges regarding data continuity in the mainstream and their tributaries. This study proposes a methodological framework for enhancing flow data continuity that uses a staged calibration scheme of Soil and Water Assessment Tool (SWAT) modeling with an appropriate satellite precipitation product (SPP) for each watershed. This framework is successfully applied in the Mun-Chi River Basin, the largest tributary of the Lower Mekong River, over a 20-year period at 34 stations. The staged calibration involves partitioning the catchment into smaller sub-catchments, guided by the flow monitoring stations and flow discontinuity structures such as dams. The sequential calibration from upstream to downstream partitions the overall model calibration challenge into smaller problems and contributes to a more efficient and accurate calibration and validation. Alternative SPPs were considered to overcome monitoring gaps. Their bias was corrected using quantile mapping, and their performance was evaluated with flow simulations using the SWAT model. The assessment indicates that the CMORPH-CRT product, with a spatial resolution of 0.25°, demonstrates good suitability for hydrological modeling of the Mun-Chi River Basin. The proposed methodological framework provides a continuous time series of flow discharge at multiple stations within the watershed, offering valuable insights for sustainable water resource management strategies in river systems under changing climate and land use conditions, and supporting future studies on environmental issues.

Groundwater Recharge and Surface Runoff Modeling Response to Land Use and Land Cover Dynamics in a Mae Wong Watershed of Thailand

This study aims to develop efficient management strategies and assess the spatiotemporal dynamics of land use and land cover (LULC) on surface runoff modeling response dynamics for the long-term sustainability of watersheds. The soil and water assessment tool (SWAT) model was used to evaluate the LULC dynamics on GRSR in the Mae Wong Watershed (MWW) of Thailand. Using Landsat images, three different LULC maps (2011, 2021, and 2031) were created using the cellular automata markov chain (CA-Markov) model, and TerrSet 2020 geospatial monitoring and modeling software. In the overall MWW, the forestland has undergone deforestation and decreased by 2.10% of the total area and 2.72% of the total area has been transformed into agricultural lands due to human activity and population growth. The soil, LULC, weather, and the digital elevation model (DEM) were all used in the SWAT simulation procedure. To understand the groundwater recharge and surface runoff (GRSR) responses of each hydrologic response units (HRUs), the SWAT model was calibrated and verified using streamflow and the sequential uncertainty fitting (SUFI-2) technique from the SWAT calibration and uncertainty program (SWAT-CUP). The results indicate that there is a good agreement for both the calibration and validation phases of all LULC simulations. The study indicated that groundwater recharge has decreased over the last two decades while surface runoff has increased due to the forest area being converted to agricultural land. Thus, the study can support maximizing water management and strategies for systematically attaining sustainability.

Efficiency analysis of best management practices under climate change conditions in the So-okcheon watershed, South Korea

Best management practices (BMPs) are widely applied to address water quality degradation issues attributed to non-point source pollutants. The objective of this study was to assess the efficiency of two types of BMPs, vegetation filter strips (VFS) and wetlands, in reducing total nitrogen (TN) and total phosphorus (TP) in a watershed, and to investigate whether the efficiency of the two BMPs is maintained under future climate scenarios by employing the Soil and Water Assessment Tool (SWAT). A set of parameters was calibrated using the SWAT Calibration and Uncertainty Program (SWAT-CUP) to ensure acceptable simulation results. Three BMP scenarios were developed by applying VFS and wetlands individually and in combination. Projected climate data from 18 global circulation models under Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were used to depict climate change conditions. VFS demonstrated 18.2% and 22.9% greater reduction efficiency for TN and TP, respectively, relative to wetlands. When the two BMPs were simultaneously applied, the reduction efficiency was even greater than that of single-BMP implementation (by 7.4% for TN and 6.8% for TP compared to VFS alone and by 25.5% for TN and 29.7% for TP compared to wetlands alone). To assess the effect of climate change, the model simulated results for the period of 2021–2,100. The differences in efficiency between the combined BMP scenario and the individual BMPs increased with greater intensity of climate change, especially in the distant future. Therefore, this study supports the effectiveness of nutrient pollution control by applying multiple BMPs rather than by applying individual BMPs. Furthermore, this research underscores the adaptability and reliability of natural-based solutions in mitigating non-point source pollution in a changing climate, which is essential for effective ecological restoration in complex urban-agricultural landscapes. The study provides valuable insights for watershed managers and policymakers seeking effective strategies to combat nutrient pollution in the face of a changing climate within the unique landscape of South Korea.

Assessing Hydropower Potential in Nepal's Sunkoshi River Basin: An Integrated GIS and SWAT Hydrological Modeling Approach.

This study assessed the hydropower potential of a mountain watershed within the Sunkoshi River basin in Sindhupalchok, Nepal, utilizing geographic information systems (GIS) and the soil and water assessment tool (SWAT) hydrological model. Topographical, soil, land use, meteorological, and discharge data were employed to assess the study area for the appropriateness of hydropower generation. SWAT was utilized to delineate the Sunkoshi basin into 23 distinct subbasins and involved the creation of a detailed river network, incorporating various hydrological attributes including stream links, stream order, stream length, and slope gradient. After that, it was employed to simulate river discharges within these subbasins. The Sequential Uncertainty Fitting Version 2 (SUFI-2) algorithm, integrated within the SWAT Calibration and Uncertainty Program (SWAT-CUP), was employed to calibrate and validate the model. This step involved the adjustment of 25 selected parameters to enhance the model's accuracy and reliability in representing the hydrological processes of the Sunkoshi basin. Model performance was assessed utilizing three well-established efficiency criteria: coefficient of determination (R2 = 0.79), Nash-Sutcliffe efficiency (NSE = 0.73), and percent bias (PBIAS = 17.59). The study identified 36 sites across streams of order 3, 4, and 5 as having potential for hydropower generation. The hydropower potential at each identified site was evaluated using estimated stream flow and topographical head at various probability of exceedance (PoE) levels (40%, 45%, 50%, and 60%). The aggregate hydropower potential of the basin was quantified, yielding a potential of 371.30 MW at a 40% PoE. The findings suggest that an integrated approach combining SWAT-based hydrological modeling within a GIS can accurately assess a river basin's hydropower potential and provide insights into further evaluation of the comprehensive environmental assessment of the fragile Himalayan watersheds.

Modeling the Potential Influence of Subsurface Tile Drainage Systems on Downstream Flooding in a Midwestern Agricultural Watershed

Highlights Tile flow was simulated to study the impacts of tile drainage on watershed hydrology and downstream flood days. Three tile drainage scenarios with varied extents of drained land were compared with a baseline scenario. The depth of tile flow contributing to streamflow was found to increase as the area of drained land increased. Results suggest that drainage systems decrease flood days when compared to the baseline scenario. Abstract. Subsurface tile drainage systems are common in agricultural regions of the Midwestern United States. Drainage systems remove excess water from the surface and soil profile of agricultural fields, allowing crop production in previously unsuitable locations. However, these systems impact watershed hydrology and could influence flooding events. Therefore, this study aimed to determine whether tile drainage systems influence downstream flood days in a Midwestern agricultural watershed, specifically the Skunk Creek watershed. The Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrologic processes of the Skunk Creek Watershed for an 18-year period (2004–2021). The model was calibrated and validated using observed daily streamflow data with the SWAT Calibration and Uncertainty Program (SWAT-CUP) software and through the manual modification of missed precipitation data. Three tile drainage scenarios—ranging from 15% to 75% tile-drained agricultural land—were individually incorporated into the model. Results indicated that with increased tile drainage, surface runoff, groundwater flow, deep aquifer recharge, and percolation decreased, whereas lateral soil flow, tile flow, evapotranspiration, and water yield increased. A comparison of tile drainage scenarios suggests that increasing the area of tile-drained agricultural land decreases total flood days. However, the impact of tile drainage systems on downstream peak flood flows varied by event, with large precipitation events initiating flood days across all scenarios. While tile flow decreased flood days on a daily time step, flash floods might have occurred on a sub-daily time step but were not captured in this study. Future studies can replicate the approach with a sub-daily time step for simulating hourly flood events with various tile drainage scenarios. Keywords: Midwestern United States, Streamflow, SWAT, Tile drainage, Watershed hydrology.

Modeling projected impacts of climate and land use/land cover changes on streamflow in Gelana Catchment, Southern Ethiopia

Effective watershed management is extremely critical because changes in the global and local distribution of climate have a direct impact on ecosystems. The primary goal of the current study was to evaluate current and projected climate and land use land cover (LULC) change on streamflow in Gelana catchment. LULC prepared via supervised classification algorithm by using ERDAS (Earth Resources and Development Systems) software, ArcGIS 10.4 (for satellite image processing and map preparation), and the Cellular Automata (CA)-Markov model revealed significant gains in agricultural and built-up over forest and pasture land classes. A coordinated regional climate downscaling experiment under the Africa domain for three regional climate data for two future scenarios (RCP 4.5 and RCP 8.5) showed a significant reduction in rainfall from 48.64 % to 4.6 %, while minimum and maximum temperatures increased from 0.58 to 3.35 °C and 0.5 to 2.93 °C, respectively. The Soil and Water Assessment Tool (SWAT) model was applied to analyze the impact of LULC and climate change on streamflow. The model calibration and validation were carried out by using monthly observed streamflow for the most sensitive parameters by using Sequential Uncertainty Fitting (SUFI-2) within the SWAT Calibration of Uncertainty Program (SWAT-CUP). The model performed well between observed and simulated streamflow, with R2, NSE, PBIAS, P, and r-factors of 0.84, 0.77, −15.9, 0.68, and 0.56 for calibration and 0.88, 0.8, −14, 0.63, and 0.65 for validation, respectively. The results of the study implied the simulated mean annual streamflow increased from 3.22 % to 23.82 % in the case of LULC change alone, while it decreased from 38.2 % to 23.27 % for climate change alone for the near-term of RCP 4.5 and from 45.3 % to 24.6 % for RCP 8.5. Further substantial decline was observed in the combined simulation, from 55.38 % to 42.45 % and 62.15 % to 59.36 % for the near and far future of RCP 4.5 and RCP 8.5, respectively. In order to address the constraints, current findings are valuable to scale up sustainable natural resource management.

Water Quality Assessment and Nutrient Management by SWAT from Sanitation and Agricultural Sources in Warana River Basin, MH, India

The Warana river watershed in Western Maharashtra, India has been recognized for exporting some of the highest nitrate-nitrogen loadings in western Maharashtra and is also a major source of sediment and other nutrient loadings. An integrated modeling framework has been constructed with Soil and Water Assessment Tool (SWAT) model and the interactive SWAT CUP. The simulation framework includes a detailed land use and management data such as different crop rotations and an array of nutrient and tillage management schemes, derived from the various source including the state department of Agriculture. This paper presents the calibration and validation of SWAT for the streamflow, sediment losses, and nutrient loadings in the watershed. Streamflow, sediment yield, and nitrate loadings were calibrated for the 1979-1984 period and validated for the 1984-2014 period. Secondary field data on organic nitrogen, organic phosphorus, and mineral phosphorus is used in model to validate for the 2007-2014 period. Model predictions generally performed very well on both an annual and monthly basis during the calibration and validation periods, as indicated by coefficient of determination (R2) and Nash-Sutcliffe simulation efficiency (E) values that exceeded 0.7 in most cases. The first scenario set with application of fertilizer and no sanitation practices and set of land use change scenarios based on taking cropland out of production indicated a significant benefit in reducing sediment yield at the watershed outlet. A second scenario set found that relatively small reductions in nutrient applications resulted in significant reductions in nitrate loadings at the watershed outlet, without affecting crop yields significantly.

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 20years 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.

Spatial-Temporal Response of Sediment Loads to Climate Change and Soil Conservation Practices in the Northern Aegean Watershed, Türkiye

Climate change and agricultural activities are significant sources of stress to the natural environment and water resources. These also affect erosion and the associated estimation of sediment yields, which is also a crucial task in the hydrological models. The presented study is significant for the development of sustainable watershed management practices. It also aims to determine the effects of climate change and different agricultural best management practices (BMPs) on the sediment loads of the North Aegean Basin in Türkiye by using the Soil and Water Assessment Tool (SWAT) model. While sediment calibration was performed for 2014, streamflow calibration and verification were performed using the SWAT Calibration and Uncertainty Program (SWAT-CUP) for the period 2012–2013 and 2014–2015, respectively. The obtained results showed that the climate change scenarios reduce the surface waters of the basin and sediment yield in accordance with the hydrological transport processes. During the 2012–2030 time period, runoff in the basin for the RCP4.5 and RCP8.5 climate change scenarios decreased by 38.5% and 31.8%, respectively, and the basin sediment yield decreased by 55.7% and 50.7%, respectively. The sediment yields to water resources had distinctive reductions due to BMPs such as zero tillage, vertical tillage, cover crop, and terracing. Considering the RCP4.5 and RCP8.5 scenarios, BMPs reduced the sediment yield in the range of 0.93–4.03% and 0.89–3.85%, respectively. Determining the sediment transport by using hydrological modeling and the effects of climate change for different agricultural practices on erosion will be useful for decision-makers.

Assimilation versus optimization for SWAT calibration: accuracy, uncertainty, and computational burden analysis

Abstract The accurate estimation of runoff by hydrological models depends on proper model calibration. Sequential Data Assimilation (DA), as an online method, is used to estimate complex hydrological models' states and parameters simultaneously. Although DA was applied for estimating the Soil and Water Assessment Tool (SWAT) model's state and/or parameter, the previous research did not pay attention to the model calibration by DA or the comparison between DA and popular SWAT calibration methods. This paper compares Ensemble Kalman Filter (EnKF), a well-known DA method, with Sequential Uncertainty Fitting (SUFI2), a popular SWAT calibration method, to calibrate the model. We test the impact of the selected objective function in the SUFI2 application. We evaluate the results based on the multiple deterministic and uncertainty-based Goodness of Fit (GOF) measures and compare all scenarios based on the simulation accuracy, computational burden, uncertainty assessment, and parameter ranges. Results show that under the SUFI2 application, some GOFs might be located in unsatisfactory ranges while the algorithm obtains (very) good results concerning the objective functions. On the other hand, EnKF simultaneously locates most GOFs in (very) good ratings. Moreover, we found that the selection of SUFI2's objective function and the specification of uncertainty's error in EnKF have significant effects on the results.

Comparison of Flood Frequency at Different Climatic Scenarios in Forested Coastal Watersheds

Climate change-induced extreme precipitation causes coastal flooding. A streamflow simulation in coastal watersheds, Wolf River Watershed (WRW) and Jourdan River Watershed (JRW), was conducted using the Soil and Water Assessment Tool (SWAT) to compare variation in flow at different climates and to analyze the flood frequency. Baseline models were auto-calibrated with SWAT calibration and uncertainty programs (SWAT-CUP). Kling–Gupta efficiency (KGE), defined as the objective function in SWAT-CUP, ranged from 0.8 to 0.7 in WRW and from 0.55 to 0.68 in JRW during the calibration–validation process. Results indicated reliability of the model performances. Monthly averaged baseline flow was 1% greater than historical and 8.9% lower than future climate in WRW. In JRW, monthly averaged baseline flow was 11% greater than historical and 5.7% lower than future climate. Flood frequency analysis showed the highest 1% exceedance probability in annual maximum series (AMS) of baseline model in WRW, whereas AMS of projected model was estimated the highest in JRW. This study aids in preparing for future flood management.

Addressing data challenges in riverine nutrient load modeling of an intensively managed agro‐industrial watershed

AbstractData limitations often challenge the reliability of water quality models, especially in intensively managed watersheds. While numerous studies report successful hydrological model setup and calibration, few have addressed in detail the data challenges for multisite and multivariable model calibration to an intensively managed watershed. In this study, we address some of these challenges based on our reflective experience calibrating the Soil and Water Assessment Tool (SWAT) to the Upper Sangamon River Watershed in central Illinois based on daily flow, annual crop yield, and monthly sediment, nitrate, and total phosphorus loads. We highlight some challenges in SWAT calibration processes due to data errors and inconsistencies, and insufficient precipitation and water quality observations. Following, we demonstrate the merits of additional weather and water quality observations that could help reduce input uncertainties, and we provide suggestions for selecting appropriate observations for the model calibration. After dealing with the data issues, we show that the SWAT model could be calibrated with acceptable results for the case study watershed.

SWAT_DA: Sequential Multivariate Data Assimilation‐Oriented Modification of SWAT

AbstractMultivariate data assimilation (DA), a novel way to couple big data with land surface models, was extensively employed in forecasting‐reanalyzing systems (FRSs), for example, ECMWF and GLDAS. Meanwhile, most (distributed) hydrological models, like soil and water assessment tool (SWAT), have not been equipped with straightforward ways to link to DA algorithms. Therefore, it is one of the main barriers to utilizing such hydrological models in FRSs. This paper deals with multivariate DA into SWAT (DA‐SWAT), which is complicated since the original model does not provide full access to the models' initial conditions (ICs) at the hydrologic response unit (HRU) scale. The preceding DA‐SWAT works commonly used an integrated approach in which the DA and SWAT codes were implemented in the same programming environment. We discuss how this approach complicates and prevents the application of DA‐SWAT in multivariate, multimodel, and multisensor systems. Accordingly, we proposed a new approach for DA‐SWAT by which SWAT can be perfectly linked with any DA algorithm of interest coded in any desired programming environment. Our framework utilizes input/output text files to access ICs and to link DA with SWAT. Moreover, we designed some univariate and multivariate scenarios for assimilating in situ streamflow measurement and MODIS's snow cover fraction (SCF) data, which has not yet been focused on in the SWAT calibration context. Results show that compared to the univariate assimilation of streamflow (SCF), the multivariate assimilation mitigates the equifinality problem and more accurately estimates SCF (streamflow) by improving NS and PBIAS measures with the differences of 0.4 (0.86), 12% (64%), respectively.

Ecohydrologic modeling using nitrate, ammonium, phosphorus, and macroinvertebrates as aquatic ecosystem health indicators of Albaida Valley (Spain)

Study regionAlbaida Valley, Spain. Study focusRivers are experiencing a rapid biodiversity loss largely due to water quality degradation imposed by anthropogenic activities. To show the capability of modeling to inform water management at watershed scales, this research develops an eco-hydrological model of the Albaida Valley (Spain). SWAT (Soil and Water Assessment Tool) is used for modeling of discharge and nutrients after calibration with SWAT-CUP (SWAT Calibration and Uncertainty Program). Results from SWAT are coupled to regressions between nutrients concentrations and macroinvertebrate-based metrics obtained from field monitoring. The spatio-temporal assessment of ecological status of streams is then carried out using simulated chemical and biological quality indicators (nitrate, ammonium, phosphorus, and macroinvertebrates). New hydrological insights for the regionManagement measures (e.g., improving treatment of wastewater and/or adopting policies for reducing fertilizer use) are needed as the ecological status of Albaida Valley rivers is mostly classified as poor because of nutrients pollution. The reasonably low uncertainty in the model prediction (expressed by R-factor: discharge (0.2–0.61), nitrate (0.79–1.27) and total phosphorus (0.8–1.68)) demonstrates the potential of the presented model for future applications (i.e., for investigating possible responses of the Albaida Valley ecosystem to changes in climate, land-use, and local management policies). The modeling approach provided in this study could be generally used as a complementary technique to field monitoring in assessing and managing ecological conditions of rivers.

Response of runoff and nitrogen loadings to climate and land use changes in the middle Fenhe River basin in Northern China

Abstract Investigating and understanding the responses of runoff and nitrogen loading to climate and land use change is particularly important for future water resources management. In this article, the Soil and Water Assessment Tool (SWAT) was used to simulate runoff and nitrogen loading in the middle reaches of the Fenhe River. The model was calibrated by the SWAT calibration and uncertainty procedure (SWAT-CUP) to achieve the accuracy of simulating runoff and nitrogen loadings. Furthermore, 20 climate change scenarios and seven extreme land use change scenarios were set up and run on the calibrated model. The results showed that runoff and nitrogen loading decreased when temperature increased and increased with increasing precipitation. Runoff was more sensitive to changes in precipitation (±10%) than temperature (±2 °C), while nitrogen loading showed the opposite pattern. When the two climatic factors changed in the same direction, the combined effect was larger than either factor alone, whereas the change in the opposite direction produced a weaker effect. The changes produced by different extreme land use scenarios on runoff and nitrogen loading were significantly different and were more obvious during the flood season than in the non-flood season. The results of this study provide a useful guide for water resource managers.

Identification of soil erosion hot-spot areas for prioritization of conservation measures using the SWAT model in Ribb watershed, Ethiopia

Soil erosion is one of the pressing environmental problem in Ethiopia Thus, identifying soil erosion hot-spot areas of a watershed/basin and isolating best management practices (BMPs) for soil erosion-prone sub-watersheds is imperative for effective soil loss reduction and lessening its on-site and off-site effects. The present study aimed to identify erosion hot-spot areas for prioritization of conservation measures and evaluate BMPs for reducing soil erosion using the Soil and Water Assessment Tool (SWAT) model in Ribb watershed, Ethiopia. The SWAT model was calibrated (1995–2002) and validated (2003–2008) using flow and sediment data in the SWAT Calibration and Uncertainty Program (SWAT-CUP). The NSE (Nash–Sutcliffe efficiency), R 2 (Coefficient of determination), PBIAS (Percent bias) and RSR (Root Mean Square Error — observations standard deviation ratio) values during flow and sediment calibration and validation periods ranged from 0.7 to 0.9, 0.71 to 0.92, -0.4% to 15.2% and 0.32 to 0.55, respectively, indicating that SWAT is able to simulate streamflow and sediment with sufficient accuracy. The calibrated and validated SWAT model was used to evaluate the effectiveness of three BMPs against the baseline conditions for reducing soil erosion, such as filter strips Scenario (Scenario F), stone/soil bunds Scenario (Scenario S) and reforestation Scenario (Scenario R). The result indicated that about 95% of the watershed are indentified as soil erosion hot-spot areas, which experienced sediment yield > 11 t ha − 1 yr − 1 . The mean annual sediment yield (1995–2008) of the watershed at the baseline conditions was nearly 29 t ha − 1 yr − 1 . The implementation of Scenario F, Scenario S and Scenario R reduced the baseline sediment yield by 28%, 76% and 62% at the watershed scale, respectively. At the sub-watershed levels, Scenario S and Scenario R reduced the mean annual sediment yield from 45%–90% and 0%–90%, respectively. Therefore, the study suggests implementations of Scenario S and Scenario R for effective soil erosion reduction in the study watershed in particular and to other watersheds in Ethiopia in general which have similar environmental settings. • SWAT was applied to identify soil erosion hot-spot areas and evaluate BMPs. • Filter strips, stone/soil bunds and reforestation Scenarios were evaluated. • About 95% of the watershed are identified as soil erosion hot-spot areas. • Stone/soil bunds (76%) and reforestation (62%) Scenarios reduced maximum sediment. • Implementations of stone/soil bunds and reforestation Scenarios are suggested.

Hydrologic response of arid and semi-arid river basins in Iraq under a changing climate

Abstract An assessment of the total hydrologic response of arid and semi-arid river basins to various scenarios of climate change by considering evapotranspiration, streamflow, and snowmelt is essential for sustainable management of water resources. The Diyala River Basin in Iraq has been chosen as a typical case study of dozens of river basins in arid and semi-arid regions. Here, the Long Ashton Research Station-Weather Generator (LARS-WG), the Soil and Water Assessment Tool (SWAT), and the SWAT Calibration and Uncertainty Program (CUP) were used to evaluate the total response by considering three Representative Concentration Pathways (RCPs); RCPs 2.6, 4.5, and 8.5 over three periods, 2021–2040, 2041–2061, and 2061–2080. The results indicate that by the year 2080, the basin will experience a temperature increase by 6.6, 10.1, and 16.6% for RCP 2.6, RCP 4.5, and RCP 8.5, respectively. The corresponding reduction in precipitation will be 3.2, 6.4, and 8.7%, resulting in 38.8, 47.9, and 52.8% fall in streamflow for RCPs 2.6, 4.5, and 8.5, respectively. Due to the increase in temperature, an earlier and less contribution of snowmelt is expected in the projected streamflow. Our findings provide a useful reference and a guide to decision makers for developing adaption plans to sustainably manage water resources in the Diyala River Basin and other similar basins in arid and semi-arid regions.

Spatial and temporal variability evaluation of sediment yield and sub-basins/hydrologic response units prioritization on Genale Basin, Ethiopia

Erosion of the topsoil is a serious environmental problem worldwide that critically alarms agricultural and upland areas. Most wetlands, rivers, and reservoirs are losing their capacity because of sediment deposition into the water body from the upstream of watersheds, as they were not managed. Soil and Water Assessment Tool (SWAT) model is used to simulate streamflow, sediment load, & identify spatiotemporal variability of the sediment yield and sediment delivery ratio (SDR), point out erosion-prone area, and prioritize sub-basins/hydrologic response units (HRUs) for management. The model is implemented by utilizing a digital elevation model, land use, soil type, and slope of the Genale basin; 464 HRUs were created, spreading over 25 sub-basins within the drainage area 54,942Km2. SUFI 2 algorithm of SWAT calibration & uncertainty programs (SWAT_CUP) is used to calibrate (1990 – 2005) and validated (2006 – 2013) streamflow & sediment on monthly scale, and the resulted statistics are; R2 = 0.87, 0.85 and NSE = 0.81, 0.78 for flow calibration and validation respectively whereas R2 = 0.84, 0.82 and NSE = 0.79, 0.75 for sediment calibration and validation respectively. Significant spatiotemporal variability of sediment yield was observed in the watershed, as the characteristics of the terrain, land use, & soil type in each sub-basin varies. Among the total 25 sub-basins, three sub-basins produced a very high sediment rate (21–31 ton/ha/year), one produced high (16–20 ton/ha/year), one is moderate (11–15 ton/ha/year), three were low (6–10 ton/ha/year), and the rest 16 sub-basins were under very low categories. In the case of SDR, three sub-basins have very high SDR (>0.452), two sub-basins resulted in high SDR (0.326–0.451), which are located at the upland basin. Based on the model results, sub-basins 6, 8, 12, 10, and 7 were identified as sediment-prone areas. Further investigation at the HRUs scale is taken to understand critical erosion areas and minimize the cost of management practice, time & human resources. HRU analysis has revealed the immense scope of minimizing cost by concentrating management measures only in the critical HRUs. For example, Sub-basin-6 has 31 HRUs, of which only seven are assessed to have the high rates of sediment yield and thus prioritized as; HRU-159, HRU-160, HRU-161, HRU-168, HRU-170, and HRU-171, which are located on agricultural and arable lands of steep slopes.