Multi-site calibration and validation of SWAT with satellite-based evapotranspiration in a data-sparse catchment in southwestern Nigeria

Abstract. The main objective of this study was to calibrate and validate the eco-hydrological model Soil and Water Assessment Tool (SWAT) with satellite-based actual evapotranspiration (AET) data from the Global Land Evaporation Amsterdam Model (GLEAM_v3.0a) and from the Moderate Resolution Imaging Spectroradiometer Global Evaporation (MOD16) for the Ogun River Basin (20 292 km2) located in southwestern Nigeria. Three potential evapotranspiration (PET) equations (Hargreaves, Priestley–Taylor and Penman–Monteith) were used for the SWAT simulation of AET. The reference simulations were the three AET variables simulated with SWAT before model calibration took place. The sequential uncertainty fitting technique (SUFI-2) was used for the SWAT model sensitivity analysis, calibration, validation and uncertainty analysis. The GLEAM_v3.0a and MOD16 products were subsequently used to calibrate the three SWAT-simulated AET variables, thereby obtaining six calibrations–validations at a monthly timescale. The model performance for the three SWAT model runs was evaluated for each of the 53 subbasins against the GLEAM_v3.0a and MOD16 products, which enabled the best model run with the highest-performing satellite-based AET product to be chosen. A verification of the simulated AET variable was carried out by (i) comparing the simulated AET of the calibrated model to GLEAM_v3.0b AET, which is a product that has different forcing data than the version of GLEAM used for the calibration, and (ii) assessing the long-term average annual and average monthly water balances at the outlet of the watershed. Overall, the SWAT model, composed of the Hargreaves PET equation and calibrated using the GLEAM_v3.0a data (GS1), performed well for the simulation of AET and provided a good level of confidence for using the SWAT model as a decision support tool. The 95 % uncertainty of the SWAT-simulated variable bracketed most of the satellite-based AET data in each subbasin. A validation of the simulated soil moisture dynamics for GS1 was carried out using satellite-retrieved soil moisture data, which revealed good agreement. The SWAT model (GS1) also captured the seasonal variability of the water balance components at the outlet of the watershed. This study demonstrated the potential to use remotely sensed evapotranspiration data for hydrological model calibration and validation in a sparsely gauged large river basin with reasonable accuracy. The novelty of the study is the use of these freely available satellite-derived AET datasets to effectively calibrate and validate an eco-hydrological model for a data-scarce catchment.

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Multi-site calibration and validation of SWAT with satellite-based evapotranspiration in a data sparse catchment in southwestern Nigeria

10.5194/hess-2018-170 ◽

2018 ◽

Author(s):

Abolanle E. Odusanya ◽

Bano Mehdi ◽

Christoph Schürz ◽

Adebayo O. Oke ◽

Olufiropo S. Awokola ◽

...

Keyword(s):

River Basin ◽

Model Calibration ◽

Hydrological Model ◽

Assessment Tool ◽

Potential Evapotranspiration ◽

Swat Model ◽

Model Structure ◽

Analysis Model ◽

Southwestern Nigeria ◽

Calibration And Validation

Abstract. The main objective of this study was to calibrate and validate the eco-hydrological model Soil and Water Assessment Tool (SWAT) with satellite based actual evapotranspiration (AET) data (Global Land Evaporation Amsterdam Model (GLEAM_v3.0a) and Moderate Resolution Imaging Spectroradiometer Global Evaporation (MOD16) for the Ogun River Basin (20 292 km2) located in southwestern Nigeria. The novelty of the study is the use of freely available satellite derived AET data for calibration/validation of each of the SWAT delineated subbasins, thereby obtaining a better performing model at the local scale as well as at the whole watershed level. The Sequential Uncertainty Fitting technique (SUFI-2) in the SWAT-Calibration and Uncertainty Program was used for the sensitivity analysis, model calibration, validation, and uncertainty analysis. Three different structures of the SWAT model were used in which each model structure was a set-up of SWAT with a different potential evapotranspiration (PET) equation. The two global AET products (GLEAM_v3.0a and MOD16) were subsequently used to calibrate the SWAT simulated AET outputs from each model structure resulting in six calibration/validation procedures at a monthly time scale. The model performance for the three SWAT model structures was evaluated for each of the 53 subbasins through the six calibrations/validations, which enabled the best model structure with the highest performing AET product to be chosen. A verification of the simulated AET variable was carried out by: (i) comparing the simulated AET of the calibrated model to GLEAM_v3.0b AET, this is a product that has a different forcing data to version of GLEAM used for the calibration, and (ii) assessing the long-term average annual and average monthly water balances at the outlet of the watershed. Overall, the SWAT model structure composed of Hargreaves PET equation and calibrated using the GLEAM_v3.0a data performed well for the simulation of AET and provided a good level of confidence for using the SWAT model as a decision support tool. The 95% uncertainty of the SWAT simulated variable bracketed most of the satellite based AET data in each subbasin. The SWAT model also proved efficient in capturing the seasonal variability of the water balance components at the outlet of the watershed. This study demonstrated the potential to use remotely sensed evapotranspiration data for hydrological model calibration and validation in a sparsely gauged large river basin with reasonable accuracy.

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Estimation of Water Balance Components of Watersheds in the Manjira River Basin using SWAT Model and GIS

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.c6431.029320 ◽

2020 ◽

Vol 9 (3) ◽

pp. 3898-3907

Keyword(s):

Water Balance ◽

River Basin ◽

Assessment Tool ◽

Potential Evapotranspiration ◽

Swat Model ◽

Geographical Information ◽

Weather Data ◽

Water Yield ◽

Water Balance Components ◽

Rain Data

This study mainly focus on hydrological behavior of watersheds in The Manjira River basin using soil and water assessment tool (SWAT) and Geographical information system (GIS). The water balance components for watersheds in the Manjira River were determined by using SWAT model and GIS. Determination of these water balance components helps to study direct and indirect factors affecting characteristics of selected watersheds. Manjira River contains total 28 watersheds among them 2 were selected having watershed code as MNJR008 and MNJR011 specified by the Central Ground Water Board. The SWAT input data such as Digital elevation model (DEM), land use and land cover (LU/LC), Soil classification, slope and weather data was collected. Using these inputs in SWAT the different water balancing components such as rainfall, baseflow, surface runoff, evapotranspiration (ET), potential evapotranspiration (PET) and water yield for each watershed were determined. The evaluated data is then validated by Regression analysis, in which two datasets were compared. Simulated rain data from SWAT simulation and observed rain data from Global Weather Data for SWAT was selected for comparison for each watershed.

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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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Calibração hidrológica do modelo SWAT em bacia hidrográfica caracterizada pela expansão do cultivo da cana-de-açúcar

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v13.2.p576-594 ◽

2020 ◽

Vol 13 (2) ◽

pp. 576

Author(s):

Letícia Lopes Martins ◽

Wander Araújo Martins ◽

Jener Fernando Leite De Moraes ◽

Mário José Pedro Júnior ◽

Isabella Clerici De Maria

Keyword(s):

Land Use ◽

Water Resources ◽

Model Calibration ◽

Assessment Tool ◽

Swat Model ◽

Sao Paulo ◽

São Paulo ◽

Calibration And Validation ◽

Water Assessment ◽

Soil And Water

A dificuldade na gestão de recursos hídricos aliada à dinâmica do uso e ocupação do solo em bacias hidrográficas agrícolas são fatores relevantes para a conservação da água e solo. A gestão de bacias hidrográficas, bem como o monitoramento de cenários de expansão agrícola e mudança no uso do solo, podem se beneficiar de ferramentas de modelagem hidrossedimentológica, como o SWAT (Soil and Water Assessment Tool). Entretanto, para que os resultados obtidos sejam confiáveis, os modelos precisam ser calibrados. Objetivou-se, neste trabalho, calibrar e validar o modelo SWAT, para a variável vazão, tendo como base a bacia hidrográfica do Ribeirão do Pinhal, Limeira -São Paulo, que se caracteriza pela expansão da cana-de-açúcar sobre áreas citrícolas. Dados de vazão de um posto fluviométrico localizado no exutório da bacia foram utilizados para a calibração e validação, a partir de séries temporais diferentes. Utilizou-se o software QSWAT para a simulação hidrológica e o SWAT-CUP para a calibração e validação do modelo. O modelo foi calibrado e validado resultando nos seguintes índices estatísticos NSE=0,64; PBIAS=15,2 e RSR=0,60 para calibração e NSE=0,68 PBIAS=-2,8 e RSR=0,56 para a validação. O ajuste de parâmetros do SWAT (USLE_P, USLE_C, CN2) e do calendário de operações da cana-de-açúcar em acordo com a situação real da bacia foi necessário para a calibração do modelo. Os resultados indicam que o modelo SWAT subestima as vazões extremas, no entanto, dentro de faixa aceitável. O SWAT, após a calibração, pode ser utilizado na gestão de recursos hídricos na bacia do Ribeirão do Pinhal.Hydrological calibration of the SWAT model in a watershed characterized by the expansion of sugarcane cultivationA B S T R A C TThe difficulty in water resources management combined with the dynamics of land use and occupation in agricultural watersheds are relevant factors for water and soil conservation. River basin management, as well as monitoring scenarios of agricultural expansion and land-use change, can benefit from hydrossedimentological modeling tools such as the SWAT (Soil and Water Assessment Tool). However, for the results to be reliable, the models must be calibrated. The objective of this study was to calibrate and validate the SWAT model for the flow variable, based on the Ribeirão do Pinhal watershed, Limeira-São Paulo, which is characterized by the expansion of sugarcane over citrus areas. Flow data from a fluviometric station located in the basin's outfall were used for calibration and validation from different time series. QSWAT software was used for hydrological simulation and SWAT-CUP for model calibration and validation. The model was calibrated and validated resulting in the following statistical indices NSE = 0.64; PBIAS = 15.2 and RSR = 0.60 for calibration and NSE = 0.68 PBIAS = -2.8 and RSR = 0.56 for validation. Adjustment of SWAT parameters (USLE_P, USLE_C, and CN2) and the sugarcane operation schedule according to the actual basin situation was necessary for model calibration. The results indicate that the SWAT model underestimates the extreme flow rates, however, within an acceptable range. After calibration, the SWAT can be used to manage water resources in the Ribeirão do Pinhal basin.Keywords: Hydrologic simulation; land use; flow rate.

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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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Exploring the application of flood scaling property in hydrological model calibration

Journal of Hydrometeorology ◽

10.1175/jhm-d-21-0123.1 ◽

2021 ◽

Author(s):

Yanchen Zheng ◽

Jianzhu Li ◽

Ting Zhang ◽

Youtong Rong ◽

Ping Feng

Keyword(s):

Model Calibration ◽

Hydrological Model ◽

Assessment Tool ◽

Swat Model ◽

Flood Frequency ◽

Efficiency Coefficient ◽

Distributed Hydrological Model ◽

Flood Peak ◽

Scaling Property ◽

Streamflow Data

Abstract Model calibration has always been one major challenge in hydrological community. Flood scaling property (FS) is often used to estimate the flood quantiles for data-scarce catchments based on the statistical relationship between flood peak and contributing areas. This paper investigates the potential of applying FS and multivariate flood scaling property (MLR) as constraints in model calibration. Based on the assumption that the scaling property of flood exists in four study catchments in Northern China, eight calibration scenarios are designed with adopting different combination of traditional indicators and FS or MLR as objective functions. The performance of the proposed method is verified by employing a distributed hydrological model, namely Soil and Water Assessment Tool (SWAT) model. The results indicate that reasonable performance could be obtained in FS with less requirements of observed streamflow data, exhibiting better simulation on flood peak than Nash-Sutcliffe efficiency coefficient calibration scenario. The observed streamflow data or regional flood information are required in MLR calibration scenario to identify the dominant catchment descriptors, and MLR achieve better performance on catchment interior points, especially for the events with uneven distribution of rainfall. On account of the improved performance on hydrographs and flood frequency curve at watershed outlet, adopting the statistical indicators and flood scaling property simultaneously as model constraints is suggested. The proposed methodology enhances the physical connection of flood peak among sub-basins and considers watershed actual conditions and climatic characteristics for each flood event, facilitating a new calibration approach for both gauged catchments and data-scarce catchments.

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Application of Meteorological and Hydrological Drought Indices to Establish Drought Classification Maps of the Ba River Basin in Vietnam

Hydrology ◽

10.3390/hydrology6020049 ◽

2019 ◽

Vol 6 (2) ◽

pp. 49 ◽

Cited By ~ 4

Author(s):

Doan Quang Tri ◽

Tran Tho Dat ◽

Dinh Duc Truong

Keyword(s):

River Basin ◽

Drought Index ◽

Assessment Tool ◽

Swat Model ◽

Standardized Precipitation Index ◽

Aridity Index ◽

Meteorological Drought ◽

Hydrological Drought ◽

Drought Indices ◽

Calibration And Validation

The objective of this study was to establish drought classification maps to simulate and calculate the lack of discharge in the Ba River basin in Vietnam. The maps were established using three meteorological drought indices (the Standardized Precipitation Index (SPI), the Drought Index (J), and the Ped Index (Ped)), the Soil and Water Assessment Tool (SWAT) model, and the hydrological drought index (KDrought). The results from the calculation of the SPI, Aridity Index (AI), and Ped at three stations (An Khe, Ayunpa, and MDrak) showed that the J index was suitable for the study area. Based on the J index, an extreme drought was predicted to occur at the Ayunpa, An Khe, and MDrak stations. During the calibration process, the SWAT Calibration Uncertainties Program (SWAT-CUP) model, with automatic algorithms, was used to select the parameters to optimize the SWAT model. For the calibration and validation, the observed discharge at two hydrology stations, An Khe and Cung Son, from the periods 1981–1991 and 1992–2002, respectively, were used. The simulated discharge was found to be acceptable, with the Nash–Sutcliffe efficiency (NSE), Percent bias (PBIAS), and R2 reaching good levels in both calibration and validation. The results from the calculation of the drought index (KDrought), and the established drought classification maps in 2016, showed that the most affected areas were the communes of the Gia Lai and Dak Lak provinces. The results from the simulation and calculations were found to be consistent with the situation that occurred in practice. The application of meteorological and hydrological drought indices, as well as the hydrological model, to support impact assessments of drought classification in space and time, as well as the establishment of forecasting and warning maps, will help managers to effectively plan policy responses to drought.

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

10.20944/preprints201812.0361.v1 ◽

2018 ◽

Cited By ~ 1

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 have been 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 nowadays 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, firstly 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. Secondly, the SWAT (Soil and Water Assessment Tool) hydrological model is 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 SM2R-AMSRE- SWAT- simulated monthly runoff reproduces well the observations at the 6 gauging stations (with coefficient of determination, R² > 0.72), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation than the SWAT model with ground-based rainfall input. Furthermore, rainfall estimations of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model. The monthly runoff obtained with 3B42- rainfall have 0.39< R2 < 0.70 and are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SM2R-AMSRE- SWAT- simulated runoff above. Therefore, in spite of the afore-mentioned 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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Influence of multisite calibration on streamflow estimation based on the hydrological model with CMADS inputs

Journal of Water and Climate Change ◽

10.2166/wcc.2021.115 ◽

2021 ◽

Author(s):

Yongyu Song ◽

Jing Zhang ◽

Yuequn Lai

Keyword(s):

Spatial Heterogeneity ◽

Model Calibration ◽

Water Resource Management ◽

Hydrological Model ◽

Assessment Tool ◽

Swat Model ◽

Coupled Model ◽

Model Driven ◽

Streamflow Estimation ◽

Set Up

Abstract Due to the spatial heterogeneity, the hydrological model calibration results only at the total outlet of the basin may not represent the whole basin. To more accurately simulate the historical streamflow process within the Qujiang River Basin, we set up three calibration strategies (single-site, S1; multisite simultaneous, S2; and multisite sequential, S3) for four hydrological stations based on the SWAT (Soil and Water Assessment Tool) model driven by CMADS (China Meteorological Assimilation Driving Datasets for the SWAT model). In addition, the implications of these calibration issues are extended to future streamflow projections using multimodel ensemble data in CMIP6 (Coupled Model Intercomparison Project Phase 6). In the model calibration phase, the SWAT model achieved very satisfactory results in the study area. Compared with S1 and S2, S3 can effectively improve the accuracy of streamflow simulation of stations within the basin and reduce the simulation deviation. Especially at the daily scale, the average NSE values of the four stations with S3 increased by 0.26 and 0.07, and the overall deviation decreased by 0.25 and 6.43%, respectively. Parameter sensitivity analysis also shows that spatial heterogeneity can be more adequately considered when using S3 to calibrate the model. As for the results of future streamflow projection, when using the S3, the average annual streamflow of four stations in the three climate scenarios from 2021 to 2050 is about 44.21, 130.00, 321.55 and 713.24 m3/s, respectively. Correspondingly, the use of S1 and S2 would bring certain risks to future water resource management.

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Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part I: Model Development)

Water ◽

10.3390/w13111546 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1546

Author(s):

Suresh Marahatta ◽

Laxmi Prasad Devkota ◽

Deepak Aryal

Keyword(s):

River Basin ◽

River Flow ◽

Assessment Tool ◽

Swat Model ◽

Rainfall Runoff ◽

Flow Data ◽

Monsoon Period ◽

Hydrological Simulation ◽

Calibration And Validation ◽

Mountainous River

The soil and water assessment tool (SWAT) hydrological model has been used extensively by the scientific community to simulate varying hydro-climatic conditions and geo-physical environment. This study used SWAT to characterize the rainfall-runoff behaviour of a complex mountainous basin, the Budhigandaki River Basin (BRB), in central Nepal. The specific objectives of this research were to: (i) assess the applicability of SWAT model in data scarce and complex mountainous river basin using well-established performance indicators; and (ii) generate spatially distributed flows and evaluate the water balance at the sub-basin level. The BRB was discretised into 16 sub-basins and 344 hydrological response units (HRUs) and calibration and validation was carried out at Arughat using daily flow data of 20 years and 10 years, respectively. Moreover, this study carried out additional validation at three supplementary points at which the study team collected primary river flow data. Four statistical indicators: Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), ratio of the root mean square error to the standard deviation of measured data (RSR) and Kling Gupta efficiency (KGE) have been used for the model evaluation. Calibration and validation results rank the model performance as “very good”. This study estimated the mean annual flow at BRB outlet to be 240 m3/s and annual precipitation 1528 mm with distinct seasonal variability. Snowmelt contributes 20% of the total flow at the basin outlet during the pre-monsoon and 8% in the post monsoon period. The 90%, 40% and 10% exceedance flows were calculated to be 39, 126 and 453 m3/s respectively. This study provides additional evidence to the SWAT diaspora of its applicability to simulate the rainfall-runoff characteristics of such a complex mountainous catchment. The findings will be useful for hydrologists and planners in general to utilize the available water rationally in the times to come and particularly, to harness the hydroelectric potential of the basin.

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