ABSTRACT Monitoring of snow cover variability is crucial because it is closely linked with mountain water resources, ecosystems, and climate change. For this, moderate-resolution imaging spectroradiometer (MODIS) daily snow cover products (SCPs, version 6) were used over the Chenab river basin (CRB) during 2001–2017. In these data, cloud cover is a significant problem that produces a discontinuity in spatial and temporal scale for long-term snow cover monitoring. Therefore, a sequential non-spectral composite methodology (with five successive steps) was applied to reduce cloud obscuration. Further, the cloud gap-filled SCPs were validated with the indirect method as well as high-resolution satellite data (Landsat-8). Results indicate that the cloud-removed SCPs show an overall efficiency of 92.8 1.6% with an indirect approach, while an overestimation (9.3%) was observed between Landsat and MODIS snow cover area (SCA) along with higher correlation (R = 0.99, p < 0.001). The result shows an increasing trend (0.25% ) of mean annual SCA during 2001–2017, while it is slightly decreasing since 2009 and was statistically insignificant. Moreover, the Snow Cover Day and nine indexes (from snow depletion curves) were derived for snow cover characterization, indicating that a shift or change in the snow accumulation period in terms of the seasonal snow cover in the recent decade. Furthermore, the linear relationships between SCA and climatic variables were established to identify the influence of snow cover distribution and its related snowmelt onset. The analysis demonstrated that the precipitation and net shortwave radiation (SWN) were increasing in the north-eastern region of the basin. However, the air temperature ( ) and wind speed showed a declining trend. Furthermore, associated uncertainty and sensitivity analyzes were performed, suggesting that the SCA is more sensitive to . However, it may be less susceptible to precipitation during the melt season. Overall, this finding indicates the potential importance of climatic variables on the snow cover distribution that is essential for proper management of the hydrological system.

中文翻译：

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喜马拉雅西部 Chenab 河流域积雪的时空特征及其与气候变化的联系

摘要 雪盖变化的监测至关重要，因为它与山区水资源、生态系统和气候变化密切相关。为此，2001 年至 2017 年期间，在 Chenab 河流域 (CRB) 上使用了中等分辨率成像光谱仪 (MODIS) 每日积雪产品（SCP，第 6 版）。在这些数据中，云覆盖是一个重要的问题，它会导致长期积雪监测的空间和时间尺度不连续。因此，采用顺序非光谱复合方法（具有五个连续步骤）来减少云遮挡。此外，用间接方法以及高分辨率卫星数据 (Landsat-8) 验证了云隙填充的 SCP。结果表明，通过间接方法去除云的 SCP 的整体效率为 92.8 1.6%，而在 Landsat 和 MODIS 积雪面积 (SCA) 之间观察到高估 (9.3%) 以及更高的相关性 (R = 0.99, p < 0.001)。结果表明，2001-2017 年平均年 SCA 呈上升趋势（0.25%），而自 2009 年以来略有下降，在统计上不显着。此外，积雪日和九个指数（来自积雪消耗曲线）用于积雪特征，表明积雪期在最近十年季节性积雪方面的转移或变化。此外，建立了 SCA 与气候变量之间的线性关系，以识别积雪分布及其相关融雪开始的影响。分析表明，盆地东北部地区的降水和净短波辐射（SWN）正在增加。但气温（ ）和风速呈下降趋势。此外，还进行了相关的不确定性和敏感性分析，表明 SCA 对 . 然而，在融化季节，它可能不太容易受到降水的影响。总体而言，这一发现表明气候变量对积雪分布的潜在重要性，这对于适当管理水文系统至关重要。在融化季节，它可能不太容易受到降水的影响。总体而言，这一发现表明气候变量对积雪分布的潜在重要性，这对于适当管理水文系统至关重要。在融化季节，它可能不太容易受到降水的影响。总体而言，这一发现表明气候变量对积雪分布的潜在重要性，这对于适当管理水文系统至关重要。