*2.2. Datasets Used*

The current study utilized an arrangemen<sup>t</sup> of hydro-meteorological and geospatial information of the LRB in order to establish the desired results. The datasets included the following.

#### 2.2.1. Geospatial Data of LRB

To extract the topographical features of the LRB, a 90 m resolution Advanced Thermal Emission and Reflection Radiometer, Global Digital Elevation Model (ASTER, GDEM) was developed for the study area (Figure 1). The land use features of the LRB were established using Landsat-8 Operational Land Imager (OLI) imagery with a 30 m resolution. The best cloud free images, with (137, 39) and (138, 39) path and row respectively, were used to delineate the land use map for the study area using maximum likelihood classification of the land features. The soil profile of the LRB was described using FAO-UNESCO (Food and Agricultural Organization-United Nations Educational, Scientific, and Cultural Organization) Harmonized World Soil Database version 1.2 (HWSD v1.2), a 30 arc-second raster database with over 15,000 different soil mapping units within the 1:5,000,000 scale FAO-UNESCO Soil Map of the World. All the datasets were projected to Universal Transverse Mercator 45N projection. All these datasets were mandatory input for SWAT model to simulate the LR streamflow.

**Figure 1.** Location map of the Lhasa River Basin extracted from the Advanced Thermal Emission and Reflection Radiometer, Global Digital Elevation Model (ASTER GDEM) dataset showing hydrological and meteorological stations, hydropower plants, and some other features of the study area.

#### 2.2.2. Hydro-Meteorological Data of LRB

The long-term continuous records for Lhasa River streamflow were obtained from the Lhasa hydrological station located in Lhasa city, 120 km below the Zhikong Dam near the basin outlet. The hydrological data records are maintained at three hydrometric stations, but the current study utilized the data records of the Lhasa station because they represented the total river discharge contributed from the entire catchment from 1956 to 2016. For data on the required climatic variables in the current study, the long-term data from three meteorological stations—Damxung, Maizhokunggar, and Lhasa—were used. The meteorological dataset includes records of daily precipitation, maximum and minimum temperature, relative humidity, wind speed, and sunshine hours. Data on these climate variables were fed into the SWAT model to simulate LR streamflow.
