Abstract

<p>Reliability of hydrological model simulation plays an important role in better understanding of hydrological processes, eco-hydrologic and eco-hydraulic condition of a data scarce catchment with limited baseline data. Due to the lack of baseline hydrological dataset, precise simulation of hydrological output from a hydrological model becomes essential. There has been several studies carried out to calibrate a data scarce catchment using river discharge solely on remote sensing data but they have been limited to the rivers with large width. The current study was carried out in Manipur River basin where the widths of the streams are narrow due to which direct application of remotely sensed data possesses serious challenge. This study attempts to calibrate and validate a comprehensive physically semi-distributed Soil and Water Assessment Tool (SWAT) model in Manipur River basin. The SWAT hydrological model was set-up using elevation, soil, weather, and land use land cover (LULC) dataset. For the calibration and validation of model two different approaches has been applied. In the first approach, river streamflow was generated by using stage data based on stage-discharge curve through the technique of spatial proximity, whereas in the second approach, Moderate Resolution Imaging Spectroradiometer (MODIS) evapotranspiration dataset was used at sub-basin scale to calibrate and validate the SWAT model. In the calibration period, the model returned R<sup>2</sup> and Kling-Gupta Efficiency (KGE) of 0.78 and 0.73, whereas in the validation period R<sup>2</sup>, KGE was found to be 0.75, 0.71 while using the stage-discharge curve approach. The model performance of R<sup>2</sup>, KGE equals 0.67, 0.41, respectively during calibration and R<sup>2</sup>, KGE equals 0.79, 0.53 respectively was obtained during validation when MODIS evapotranspiration dataset was used. From the modelling result it was observed that the model performance was found to be better when streamflow dataset derived from stage-discharge curve used as compared to the MODIS evapotranspiration dataset. The main reason behind the under performance of the model while using MODIS evapotranspiration dataset was due to the underestimation of evapotranspiration by the SWAT model in the cold-dry season from December to February.</p><p><strong> </strong></p>

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