Assessment of the SWAT model in simulating watersheds in arid regions: Case study of the Yarmouk River Basin (Jordan)

Abstract The Soil and Water Assessment Tool (SWAT) was used to simulate monthly runoff in the Yarmouk River Basin (YRB). The objectives were to assess the performance of this model in simulating the hydrological responses in arid watersheds then utilized to study the impact of YRB agricultural development project on transport of sediments in the YRB. Nine and three years of input data, namely from 2005 to 2013, were used to calibrate the model, whereas data from 2014 to 2015 were used for model validation. Time series plots as well as statistical measures, including the coefficient of determination (R 2) and the Nash–Sutcliffe coefficient of efficiency (NSE) that range between 0 to 1 and −∞ to 1, respectively, between observed and simulated monthly runoff values were used to verify the SWAT simulation capability for the YRB. The SWAT model satisfactorily predicted mean monthly runoff values in the calibration and validation periods, as indicated by R 2 = 0.95 and NSE = 0.96 and R 2 = 0.91 and NSE = 0.63, respectively. The study confirmed the positive impact of soil conservation measures implemented in the YRB development project and confirmed that contouring can reduce soil loss from 15 to 44% during the study period. This study showed that the SWAT model was capable of simulating hydrologic components in the drylands of Jordan.

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Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽

10.3390/w13111548 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1548

Author(s):

Suresh Marahatta ◽

Deepak Aryal ◽

Laxmi Prasad Devkota ◽

Utsav Bhattarai ◽

Dibesh Shrestha

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Models ◽

Assessment Tool ◽

Swat Model ◽

Global Climate Models ◽

Climate Data ◽

The Future ◽

The Impact ◽

Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

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Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran

Water ◽

10.3390/w11030594 ◽

2019 ◽

Vol 11 (3) ◽

pp. 594 ◽

Cited By ~ 9

Author(s):

Majid Fereidoon ◽

Manfred Koch ◽

Luca Brocca

Keyword(s):

Soil Moisture ◽

Hydrological Model ◽

Assessment Tool ◽

Swat Model ◽

Rainfall Data ◽

Coefficient Of Determination ◽

Hydrological Models ◽

Streamflow Prediction ◽

Soil Moisture Data ◽

Monthly Runoff

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.

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Impact of landscape pattern change on runoff processes in catchment area of the Ulungur River Basin

Water Science & Technology Water Supply ◽

10.2166/ws.2020.027 ◽

2020 ◽

Vol 20 (3) ◽

pp. 1046-1058

Author(s):

Fan Gao ◽

Bing He ◽

Songsong Xue ◽

Yizhen Li

Keyword(s):

Land Use ◽

River Basin ◽

Landscape Pattern ◽

Water Conservation ◽

Catchment Area ◽

Positive Impact ◽

Swat Model ◽

Land Use Types ◽

Monthly Runoff ◽

Better Than

Abstract Based on the Soil and Water Assessment Tool (SWAT) model, the monthly runoff processes of two land-use types in 2000 and 2015 were simulated in this paper. The relationship between runoff and landscape pattern was analyzed, and the spatial correlation between runoff and landscape pattern analyzed using the geographic weighted regression model combined with the change of landscape pattern in the study area from 2000 to 2015. The results show the following. (1) The SWAT model can simulate the monthly runoff processes in the catchment area of the Ulungur River Basin (URB) under different land-use types for 2000 and 2015, but the simulation effect in 2000 was found to be better than that in 2015. (2) From 2000 to 2015, the area of woodland and grassland decreased. Runoff was positively correlated with woodland, grassland, largest patch index, mean patch area (AREA_MN), and contagion index, and negatively correlated with others. This indicates that the landscape fragmentation of URB was aggravated in 2000–2015, the landscape balance was destroyed, and the ability of rainfall interception and water conservation was weakened. (3) Landscape pattern indicators of grassland had a negative spatial impact on URB runoff, and the northern region of URB was more severely affected in 2015 than in 2000. AREA_MN landscape pattern index had a positive impact on runoff in the northern part of URB, and the positive impact in northern URB in 2000 was better than that in 2015.

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Assessing the Impact of Best Management Practices in a Highly Anthropogenic and Ungauged Watershed Using the SWAT Model: A Case Study in the El Beal Watershed (Southeast Spain)

Agronomy ◽

10.3390/agronomy9100576 ◽

2019 ◽

Vol 9 (10) ◽

pp. 576 ◽

Cited By ~ 3

Author(s):

Adrián López-Ballesteros ◽

Javier Senent-Aparicio ◽

Raghavan Srinivasan ◽

Julio Pérez-Sánchez

Keyword(s):

Coastal Lagoon ◽

Best Management Practices ◽

Management Practices ◽

Assessment Tool ◽

Swat Model ◽

Fertilizer Application ◽

Coefficient Of Determination ◽

Check Dam ◽

Best Management ◽

The Impact

Best management practices (BMPs) provide a feasible solution for non-point source pollution problems. High sediment and nutrient yields without retention control result in environmental deterioration of surrounding areas. In the present study, the soil and water assessment tool (SWAT) model was developed for El Beal watershed, an anthropogenic and ungauged basin located in the southeast of Spain that drains into a coastal lagoon of high environmental value. The effectiveness of five BMPs (contour planting, filter strips, reforestation, fertilizer application and check dam restoration) was quantified, both individually and in combination, to test their impact on sediment and nutrient reduction. For calibration and validation processes, actual evapotranspiration (AET) data obtained from a remote sensing dataset called Global Land Evaporation Amsterdam Model (GLEAM) were used. The SWAT model achieved good performance in the calibration period, with statistical values of 0.78 for Kling–Gupta efficiency (KGE), 0.81 for coefficient of determination (R2), 0.58 for Nash–Sutcliffe efficiency (NSE) and 3.9% for percent bias (PBIAS), as well as in the validation period (KGE = 0.67, R2 = 0.83, NS = 0.53 and PBIAS = −25.3%). The results show that check dam restoration is the most effective BMP with a reduction of 90% in sediment yield (S), 15% in total nitrogen (TN) and 22% in total phosphorus (TP) at the watershed scale, followed by reforestation (S = 27%, TN = 16% and TP = 20%). All effectiveness values improved when BMPs were assessed in combination. The outcome of this study could provide guidance for decision makers in developing possible solutions for environmental problems in a coastal lagoon.

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Application of SWAT (Soil and Water Assessment Tool) to the Abay River Basin of Ethiopia: The Case of Didessa Sub Basin

10.20944/preprints201805.0147.v1 ◽

2018 ◽

Author(s):

Timketa Adula Duguma

Keyword(s):

River Basin ◽

Time Scale ◽

Assessment Tool ◽

Peak Flow ◽

Swat Model ◽

Distributed Model ◽

Statistical Measures ◽

Sensitive Parameters ◽

Water Assessment ◽

Soil And Water

Abstract: In this study the semi-distributed model SWAT (Soil and Water Assessment Tool), were applied to evaluate stream flow of Didessa sub basin, which is one of the major sub basins in Abay river basin of Ethiopia. The study evaluated the quality of observed meteorological and hydrological data, established SWAT hydrological model, identified the most sensitive parameters, evaluated the best distribution for flow and developed peak flow for major tributary in the sub basin. The result indicated that the SWAT model developed for the sub basin evaluated at multi hydro-gauging stations and its performance certain with the statistical measures, coefficient about determination (R2) and also Nash coefficient (NS) with values ranging 0.62 to 0.8 and 0.6 to 0.8 respectively at daily time scale. The values of R2 and NS increases at monthly time scale and found ranging 0.75 to 0.92 and 0.71 to 0.91 respectively. Sensitivity analysis is performed to identify parameters those were most sensitive for the sub basin. CN2, GWQMN, CH_K, ALPHA_BNK and LAT_TIME are the most sensitive parameters in the sub basin. Finally, the peak flow for 2-10000 returns periods were determined after the best probability distribution is identified in EasyFit computer program.

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Assessment of the Impact of Land Cover Type on the Water Quality in Lake Tondano Using a SWAT Model

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.56.1.25 ◽

2021 ◽

Vol 56 (1) ◽

Author(s):

Moh Sholichin ◽

Tri Budi Prayogo

Keyword(s):

Water Quality ◽

Land Cover ◽

Agricultural Land ◽

Assessment Tool ◽

Swat Model ◽

Coefficient Of Determination ◽

Organic N ◽

Lake Water Quality ◽

Total N ◽

The Impact

Lake Tondano is the largest natural lake in North Sulawesi, Indonesia, which functions as a provider of clean water, hydroelectric power, rice field irrigation, inland fisheries, and tourism. This research aims to determine the effect of land cover types from the Tondano watershed on the lake water quality. The Soil and Water Assessment Tool (SWAT) model was used to evaluate the rate of soil erosion and the pollutant load of various land types in the watershed during the last ten years. Rainfall data is obtained from two rainfall stations, namely Paleloan Station and Noonan Station. The model is calibrated and validated before being used for analysis. We use climatological data from 2014 to 2019. The process of the SWAT model calibration and validation was carried out with the statistical formulas of the coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE). The results show that the potential for pollution load from the Tondao watershed is organic N of 0.039 kg/ha and organic P of 0.006 kg/ha coming from the agricultural land. The results of this study conclude that the fertility conditions of Lake Tondano are at the eutrophic level, where the pollutant inflow is collected in the lake waters, especially for the parameters of total N (1503697.44kg/year) and total P (144831.36kg/year). The SWAT simulation results show deviation between the modeling and field data collected with the value of R2 = 0.9303, and the significant level ≤ 10.

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Estimating Runoff and Environment Protection in Tao River Basin based on Swat Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.340.942 ◽

2013 ◽

Vol 340 ◽

pp. 942-946 ◽

Cited By ~ 1

Author(s):

Kai Xu ◽

Hui Qing Peng

Keyword(s):

River Basin ◽

Assessment Tool ◽

Swat Model ◽

Environment Protection ◽

Validation Period ◽

Calibration And Validation ◽

Monthly Runoff ◽

Arcview Gis ◽

Water Assessment ◽

Soil And Water

The Soil and Water Assessment Tool (SWAT) was used to simulate runoff yield in Tao River Basin on ArcView GIS platform. The main objective was to validate the performance of SWAT and the feasibility of this model as a simulator of runoff in a catchment. The investigation was conducted using a 6-year historical runoff record from 2001 to 2008 (2001-2004 for calibration and 2005-2008 for validation). The simulated monthly runoff matched the observed values satisfactorily, with Re was less than 20%, R2 > 0.78 and Nash-suttclife (Ens)>0.8 for both calibration and validation period at 4 hydrological stations. These indicated that the simulation of runoff was reasonable, reflecting the validity of SWAT model in Tao River Basin.

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Evaluating the impact of spatial variability of precipitation on streamflow simulation using a SWAT model

Water Policy ◽

10.2166/wp.2018.118 ◽

2018 ◽

Vol 21 (1) ◽

pp. 178-196 ◽

Cited By ~ 2

Author(s):

Feng Xue ◽

Peng Shi ◽

Simin Qu ◽

Jianjin Wang ◽

Yanming Zhou

Keyword(s):

Spatial Variability ◽

Assessment Tool ◽

Swat Model ◽

Model Performance ◽

Coefficient Of Determination ◽

Interpolation Methods ◽

Monthly Streamflow ◽

Areal Precipitation ◽

The Difference ◽

The Impact

Abstract The spatial variability of precipitation is often considered to be a major source of uncertainty for hydrological models. The widely used Soil and Water Assessment Tool (SWAT) is insufficient to calculate a sub-basin's mean areal precipitation (MAP) since it only uses data from the rainfall station nearest to the centroid of each sub-basin. Therefore, Inverse Distance Weighting (IDW), Thiessen Polygons (TP) and Ordinary Kriging (OK) were applied as alternative interpolation methods in this study to calculate sub-basin MAP. The MAP results from the four methods used for the Xixian Basin were quite different in terms of amount and spatial distribution. The SWAT model performance was then assessed at monthly and daily timescales, based on Nash–Sutcliffe efficiency (NSE), the Coefficient of Determination (R2) as well as Percentage Bias (PBIAS) at the basin outlet. The results under different network densities and spatial distributions of gauge stations indicated that the modified MAP models did not have an advantage over the default Nearest Neighbour (NN) method in simulating monthly streamflow. However, the modified areal precipitation obtained through IDW and TP showed relatively high accuracy in simulating daily flows as the applied rainfall stations changed. The difference in terms of estimated rainfall and streamflow in this study confirmed that evaluation of interpolation methods is necessary before building a SWAT model.

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Climate change impact assessment on water security in South Africa: A case study in a semi-arid river basin

E3S Web of Conferences ◽

10.1051/e3sconf/20199806014 ◽

2019 ◽

Vol 98 ◽

pp. 06014

Author(s):

Yali Woyessa

Keyword(s):

Climate Change ◽

South Africa ◽

River Basin ◽

Historical Data ◽

Assessment Tool ◽

Greenhouse Gas Emission ◽

Swat Model ◽

Climate Change Scenarios ◽

The Impact ◽

Semi Arid

The main aim of this paper is to assess the impact of regional climate change scenarios on the availability of water resources in a semi-arid river basin in South Africa using a hydrological model called Soil and Water Assessment Tool (SWAT). In this paper, climate change data was derived from two downscaling approaches, namely statistical downscaling experiment (SDE) and dynamic downscaling (CORDEX). These were derived from the GCM simulations of the Coupled Model Inter-comparison Project Phase-5 (CMIP5) and across two greenhouse gas emission scenarios known as Representative Concentration Pathways (RCP) 4.5 and 8.5. The spatial resolution of the dataset for the SDE method is 25 km × 25 km and 50 km × 50 km for the CORDEX method. Six GCM models were used for SDE set of data and four for the CORDEX set of data. SWAT model was run using these data for a period of up to mid-century (2020 – 2050) for SDE and for a period of up to the end of this century (2020 – 2100) for CORDEX data. The results were then compared with long-term historical data (1975-2005). Comparison of measured data with simulated historical data showed strong correlation (R2 = 0.95 for SDE data and R2 = 0.92 for CORDEX data), which is indicative of the reliability of projected future climate.

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ANÁLISE DE SENSIBILIDADE DE PARÂMETROS HIDROLÓGICOS NA BACIA DO RIO DAS PEDRAS - GUARAPUAVA-PR

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v12.5.p1746-1756 ◽

2019 ◽

Vol 12 (5) ◽

pp. 1746

Author(s):

Rafael Adriano de Castro Adriano de Castro ◽

Elias Machado

Keyword(s):

Sensitivity Analysis ◽

Input Data ◽

Assessment Tool ◽

Swat Model ◽

Coefficient Of Determination ◽

Land Use And Management ◽

The Impact ◽

Water Assessment ◽

Soil And Water

O modelo Soil and Water Assessment Tool (SWAT) é amplamente utilizado para predizer o impacto das alterações no uso e no manejo do solo, entre outros, é extremamente sensível à qualidade dos dados de entrada. Assim, antes da simulação é necessário que se realize uma análise de sensibilidade de tal forma que se possa dar ênfase maior à aquisição e refinamento de determinados dados, diminuir as incertezas e aumentar a confiança nos resultados gerados. Os resultados simulados na bacia do Rio das Pedras – Guarapuava, foram realizadas a análise de sensibilidade e a calibração do modelo SWAT. Após a calibração do modelo os resultados do Índice de Nash & Sutcliffe alterado (COE), do percentual de tendência (PBIAS), e o coeficiente de determinação (R²) foram, respectivamente, 0,69, -0,5 e 0,7, indicando bom ajuste entre a vazão média mensal da bacia Rio das Pedras simulada pelo modelo SWAT em relação aos dados observados. Sensitivity analysis of hydrological parameters in the Rio das Pedras basin - Guarapuava-PR A B S T R A C TThe SWAT model is widely used to predict the impact of changes in land use and management, among others, is extremely sensitive to the quality of input data. Thus, prior to the simulation, it is necessary to perform a sensitivity analysis in such a way that greater emphasis can be placed on the acquisition and refinement of certain data, decrease uncertainties and increase confidence in the results generated. The simulated results in the Rio das Pedras - Guarapuava basin, were performed the sensitivity analysis and calibration of the SWAT model. After the calibration of the model, the results of the modified Nash & Sutcliffe Index (COE), percentage of trend (PBIAS), and coefficient of determination (R²) were, respectively, 0.69, -0.5 and 0.7, Indicating a good fit between the average monthly flow of the Rio das Pedras basin simulated by the SWAT model in relation to the observed data.

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