Land use/land cover (LULC) is a key influencer for runoff generation and the estimation of evapotranspiration in the hydrology of watersheds. Therefore, it is essential to use accurate and reliable LULC data in hydrological modelling. Ground-based data deficiencies are a big challenge in most parts of developing countries and remote areas around the globe. The main objective of this research was to evaluate the accuracy of LULC data from two different sources in hydrological modelling using the soil and water assessment tool (SWAT). The first LULC data was prepared by the classification of Landsat 8 satellite imagery, and the second LULC data was extracted from the ESRI 2020 global LULC dataset. The study was conducted on the Kokcha Watershed, a mountainous basin partly covered by permanent snow and glaciers. The accuracy assessment was done based on a comparison between observed river discharge and simulated river flow, utilizing each LULC dataset separately. After calibration and validation of the models, the acquired result was approximately similar and slightly (5.5%) different. However, due to the higher resolution and easily accessible ESRI 2020 dataset, it is recommended to use ESRI 2020 in hydrological modelling using the SWAT model.
Two land use/land cover (LULC) datasets were evaluated to analyse their accuracy.
The ESRI LULC dataset represents a more accurate result than LULC data, which was prepared by the classification of Landsat 8 satellite images.
The utilized remote sensing data in this study can be used in hydrological modelling for similar studies in the region.