Modelling streamflow and sediment yield using Soil and Water Assessment Tool: A case study of Lidder watershed in Kashmir Himalayas, India (original) (raw)
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Journal of Hydroinformatics, 2022
In this study, the Soil and Water Assessment Tool (SWAT) model was used to examine the spatial variability of sediment yield, quantify runoff, and soil loss at the sub-basin level and prioritize sub-basins in the Sindh watershed due to its computational efficiency in complex watersheds. The Sequential Uncertainty Fitting-2 approach was used to determine the sensitivity and uncertainty of model parameters. The parameter sensitivity analysis showed that Soil Conservation Services Curve Number II is the most sensitive model parameter for streamflow simulation, whereas linear parameters for sediment re-entrainment is the most significant parameter for sediment yield simulation. This study used daily runoff and sediment event data from 2003 to 2013; data from 2003 to 2008 were utilized for calibration and data from 2009 to 2013 were used for validation. In general, the model performance statistics showed good agreement between observed and simulated values of streamflow and sediment yiel...
Engineering, 2018
The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool (SWAT) modeling in the Ganga catchment, over a region of 15 621.612 km 2 in the southern part of Uttar Pradesh. The primary goals of this study are: ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting (SUFI-2), the generalized likelihood uncertainty Estimation (GLUE), and parallel solution (ParaSol). The input data used in the SWAT were the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover (LULC) map and soil map were used to create hydrological response units (HRUs). Models utilizing SUFI-2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five categories: their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algorithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity (CH_K2), the universal soil-loss equation (USLE) support parameter (USLE_P), Manning's n value for the main channel (CH_N2), the surface runoff lag time (SURLAG), and the available water capacity of the soil layer (SOL_AWC) were observed to be the most sensitive parameters for modeling the present watershed. It was also found that the maximum runoff occurred in sub-watershed number 40 (SW#40), while the maximum sediment yield was 50 t•a −1 for SW#36, which comprised barren land. The average evapotranspiration for the basin was 411.55 mm•a −1. The calibrated model can be utilized in future to facilitate investigation of the impacts of LULC, climate change, and soil erosion.
High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha −1 yr −1 ) with higher values in the upper mountainous region (92 ± 15.2 t ha −1 yr −1 ) compared to the lower alluvial plains (19.3 ± 4 t ha −1 yr −1 ). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin -Nanak Sagar Dam (NSD) for the period 1962-2008 and Husepur gauging station (HGS) for [1987][1988][1989][1990][1991][1992][1993][1994][1995][1996][1997][1998][1999][2000][2001][2002]. The SY at NSD and HGS are estimated to be 6.9 ± 1.2 × 10 5 t yr −1 and 6.7 ± 1.4 × 10 6 t yr −1 , respectively, and the estimated 90 % interval contains the observed values of 6.4 × 10 5 t yr −1 and 7.2 × 10 6 t yr −1 , respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.
Hydrology and Earth System Sciences Discussions, 2017
High soil erosion and excessive sediment load are serious problems in several Himalayan River basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties of SE over two distinct morpho-climatic regimes of the Garra River basin, namely, upper mountainous region & lower alluvial plains. T...
World Environmental and Water Resources Congress 2013, 2013
Upper Sind River basin is one of the important river basins for agricultural dominant activities in India. Due to the impacts of anthropogenic activities and climate change Upper Sind river basin facing water scarcity. A Semi-distributed model SWAT was selected for effectively manages the water resources. Model calibration and uncertainty analysis were performed with Sequential Uncertainty Fitting of SWAT Calibration and Uncertainty Programme. Results showed that pfactor was 0.73 and r-factor was 0.42 in calibration period (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000) while pfactor was 0.42 and r-factor was 0.36 in validation period (2001)(2002)(2003)(2004)(2005). When values of p-factor and r-factor are accepted, further goodness of fit quantified by the coefficient of determination and Nash-Sutcliffe coefficient between observed and final best simulated data. Results indicated that R 2 was 0.82 and NS was 0.80 in calibration period, while R 2 was 0.96 and NS was 0.93 in validation period. Outcomes of calibration and uncertainty analysis were satisfactory.
Environmental Earth Sciences, 2018
A semi-distributed, physically based, basin-scale Soil and Water Assessment Tool (SWAT) model was developed to determine the key factors that influence streamflow and sediment concentration in Purna river basin in India and to determine the potential impacts of future climate and land use changes on these factors. A SWAT domain with a Geographical Information System (GIS) was utilized for simulating and determining monthly streamflow and sediment concentration for the period 1980-2005 with a calibration period of 1980-1994 and validation period of 1995 to 2005. Additionally, a sequential uncertainty fitting (SUFI-2) method within SWAT-CUP was used for calibration and validation purpose. The overall performance of the SWAT model was assessed using the coefficient of determination (R 2) and Nash-Sutcliffe efficiency parameter (E NS) for both calibration and validation. For the calibration period, the R 2 and E NS values were determined to be 0.91 and 0.91, respectively. For the validation period, the R 2 and E NS were determined to be 0.83 and 0.82, respectively. The model performed equally well with observed sediment data in the basin, with the R 2 and E NS determined to be 0.80 and 0.75 for the calibration period and 0.75 and 0.65 for the validation, respectively. The projected precipitation and temperature show an increasing trend compared to the baseline condition. The study indicates that SWAT is capable of simulating long-term hydrological processes in the Purna river basin.
Modeling Stream Flow Using SWAT Model in the Bina River Basin, India
Journal of Water Resource and Protection, 2020
Understanding watershed runoff processes is critical for planning effective soil and water management practices and efficiently utilize available water resources. The main objective of this study was to investigate the performance of the Soil and Water Assessment Tool (SWAT) to simulate streamflow from the Bina basin in the Madhya Pradesh state of India. The SWAT model was calibrated and validated on a daily and monthly basis using historical streamflow and weather data from the Bina basin. The Sequential Uncertainty Fitting (SUFI-2) technique in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) program was used to assess model uncertainties. The SWAT model performed "satisfactory" and "very good" in simulating streamflow at daily and monthly time steps, respectively. Model calibration results showed that coefficients of determination (R 2) values were 0.66 and 0.96; while Nash-Sutcliffe (NSE) values were 0.65 and 0.94 for daily and monthly simulations, respectively. The R 2 values of daily and monthly simulations during model validation were 0.65 and 0.72, respectively while the respective NSE values were 0.58 and 0.72. This study demonstrated that the SWAT model could be effectively used to simulate streamflow in the Bina river basin.
The Soil and Water Assessment Tool (SWAT) was implemented in a small forested watershed of the Soan River Basin in northern Pakistan through application of the sequential uncertainty fitting (SUFI-2) method to investigate the associated uncertainty in runoff and sediment load estimation. The model was calibrated for a 10-year period (1991–2000) with an initial 4-year warm-up period (1987–1990), and was validated for the subsequent 10-year period (2001–2010). The model evaluation indices R 2 (the coefficient of determination), NS (the Nash-Sutcliffe efficiency), and PBIAS (percent bias) for stream flows simulation indicated that there was a good agreement between the measured and simulated flows. To assess the uncertainty in the model outputs, p-factor (a 95% prediction uncertainty, 95PPU) and r-factors (average wideness width of the 95PPU band divided by the standard deviation of the observed values) were taken into account. The 95PPU band bracketed 72% of the observed data during the calibration and 67% during the validation. The r-factor was 0.81 during the calibration and 0.68 during the validation. For monthly sediment yield, the model evaluation coefficients (R 2 and NS) for the calibration were computed as 0.81 and 0.79, respectively; for validation, they were 0.78 and 0.74, respectively. Meanwhile, the 95PPU covered more than 60% of the observed sediment data during calibration and validation. Moreover, improved model prediction and parameter estimation were observed with the increased number of iterations. However, the model performance became worse after the fourth iterations due to an unreasonable parameter estimation. Overall results indicated the applicability of the SWAT model with moderate levels of uncertainty during the calibration and high levels during the validation. Thus, this calibrated SWAT model can be used for assessment of water balance components, climate change studies, and land use management practices.
Tons river basin has a great significance to states Madhya Pradesh and Uttar Pradesh in India, concerning water resources aspects and the ecological balances. A hydrological modeling approach was used to identify the sensitive hydrological parameters of the basin through Sequential Uncertainty Fitting (SUFI-2) technique. SUFI-2 was used for the calibration of SOIL WATER ASSESSMENT TOOL (SWAT) model. It was calibrated for period (1979–2000) including 3 years as warm up (1979–1982), subsequently model was validated on 11 years of datasets (2001–2011). The percentage of observation covered by the 95PPU (p-factor) and the average thickness of the 95PPU band divided by the standard deviation of the measured data (r-factor), were taken into an account for performance evaluation of model. In calibration and validation the p-factor and the r-factor was obtained as 0.54, 0.76 and 0.68, 0.56 respectively. The coefficient of determination (R2 ), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS) and RMSE-observations standard deviation ratio (RSR) have been used for goodness of fit between observation and final best simulation. The R2 , NSE, PBIAS and RSR are 0.74, 0.73, −3.55 and 0.54 respectively during the calibration whereas in validation period values are 0.75, 0.69, 18.55 and 0.56 respectively
International Journal of Hydrology Science and Technology, 2022
Model calibration and validation are necessary before applying it for scenario assessment and watershed management. This study presented the methodology of evaluating Soil and Water Assessment Tool (SWAT) and tested the feasibility of SWAT on runoff and sediment load simulation in the Zhifanggou watershed located in hilly-gullied region of China. Daily runoff and sediment event data from 1998-2008 were used in this study; data from 1998-2003 were used for calibration and 2004-2008 for validation. The evaluation statistics for the daily runoff simulation showed that the model results were acceptable, but the model underestimated the runoff for high-flow events. For sediment load simulation, the SWAT performed well in capturing the trend of sediment load, while the model tended to underestimate sediment load during both the calibration and validation periods. The disparity between observed and simulated data most likely resulted from limitations of the existing SCS-CN and MUSLE methods in the model. This study indicated that the modification of SWAT components is needed to take rainfall intensity and its duration into account to enhance the model performance on peak flow and sediment load simulation during heavy rainfall season.