Abstract Understanding the spatiotemporal variability of rainfall is vital for water resources planning and management, flood and drought mitigation, and erosion control, among others. Despite the progress in this direction, through proposal of many different approaches and their applications to rainfall data at various regions around the world, our knowledge of the spatiotemporal variability of rainfall remains limited. Studies in this direction have largely focused on the amount of rainfall and its spatial patterns, and investigations of spatiotemporal variability at multiscale are limited. In this study, we introduce a novel measure, Standardized Variability Index (SVI), based on the concept of entropy to investigate the spatiotemporal variability of gridded rainfall in the Indian subcontinent at different timescales. The results show distinct spatial patterns in the inter-annual rainfall variability at all timescales. Also, the intra-annual variability of rainfall amount, as well as rainy days, is found to increase from east to west of India. The Mann-Kendall trend test at different timescales reveals significant increase in rainfall variability. In addition, coupling the mean annual rainfall with SVI enables a relative assessment of the water resources availability.

中文翻译：

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使用多尺度熵的印度降雨时空变化

摘要 了解降雨的时空变异性对于水资源规划和管理、减轻洪水和干旱以及控制侵蚀等至关重要。尽管在这个方向上取得了进展，但通过提出许多不同的方法及其在世界各地的降雨数据中的应用，我们对降雨时空变异性的了解仍然有限。该方向的研究主要集中在降雨量及其空间格局上，对多尺度时空变异性的研究是有限的。在这项研究中，我们基于熵的概念引入了一种新的衡量标准，即标准化变异指数 (SVI)，以研究不同时间尺度下印度次大陆网格降雨的时空变异性。结果显示了所有时间尺度上年际降雨变化的不​​同空间模式。此外，发现降雨量的年内变化以及雨天，从印度东到西增加。不同时间尺度的 Mann-Kendall 趋势检验显示降雨变异性显着增加。此外，将年平均降雨量与 SVI 相结合，可以对水资源可用性进行相对评估。