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ABSTRACT The Upper Indus Basin (UIB) has experienced gradual changes in water supply due to variations in the Snow Cover Area (SCA) in recent decades. This study examined daily snow cover changes using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua (2002–2022) and Terra (2001–2022) via Google Earth Engine. An Auto‐regressive Integrated Moving Average (ARIMA) model was developed using time series data to predict SCA. Model accuracy was assessed using Stationarity, ACF, and PACF plots, as well as performance metrics, including AIC, BIC, RMSE, and MSE. The most appropriate iteration (0, 1, 1) (3, 1, 1) of the best‐performing model showed strong agreement between observed and simulated SCA, with R 2 values of 0. 72 for calibration (2017–2020) and 0. 84 for validation (2021–2023). Predicted SCA was further correlated with climate change variables (precipitation, maximum and minimum temperature) from NASA Earth Exchange (NEX) Global Daily Downscaled Projections under SSP1‐2. 6 and SSP5‐8. 5 scenarios. Results showed a significant decline in SCA, with moderate negative correlations (r = −0. 82 to −0. 72) under SSP1‐2. 6 and stronger correlations (r = −0. 99 to −0. 81) under SSP5‐8. 5. Precipitation showed a non‐significant correlation with SCA (r = 0. 14 ± 0. 41under SSP1‐2. 6; r = 0. 11 ± 0. 52 under SSP5‐8. 5) with decreasing snow cover %. Regionally, Astore, Zanskar, Shigar, and Shingo exhibited significant SCA reductions (tau = −0. 585 ± −0. 002; p = 0. 036 ± < 0. 0001), while Shyok, Gilgit, and Hunza showed significant increases (tau = 0. 45 ± 0. 67; p ≤ 0. 0001). The IndusDownstream subbasin showed a non‐significant decreasing trend (tau = −0. 002; p = 0. 961). These findings highlight the challenges in maintaining runoff, hydropower generation, and freshwater storage, particularly in high‐altitude regions, due to uncertainties in SCA predictions under climate scenarios.
Muzammal et al. (2025) studied this question.