Meghalaya is known to receive the most torrential rainfall in the world, but the region suffers from water shortage as soon as the rain recedes, and the dry season starts. Changes in rainfall patterns and distribution can have a profound impact on water availability in a watershed, and therefore, examining spatial and temporal variations in rainfall is essential. However, the long-term rainfall variations in Meghalaya are not well explored. In this study, we take up two important watersheds in Meghalaya, i.e. Umiam and Umtru watersheds, to study the spatial and temporal rainfall variations. Using the gridded rainfall data from the Indian Meteorological Department from 1901 to 2018, we show that annual, winter, pre-monsoon, and monsoon rainfall is decreasing, whereas the post-monsoon rainfall is increasing. We use the innovative trend analysis (ITA) method to identify the trends in low-, medium-, and high-intensity rainfall. We find that low- and medium-intensity rainfall is in decreasing trend while high-intensity rainfall is increasing across annual and seasonal time scales. Lastly, we cross-check the trends detected using the innovative trend analysis method with a widely accepted Mann-Kendall (MK) test. We find that the results obtained by using the two methods generally concur; however, the ITA can detect non-monotonic trends in different rainfall intensities and is more sensitive to hidden patterns than the MK test.

梅加拉亚邦（Meghalaya）是世界上降雨最多的地区，但该地区一旦雨水消退，便开始缺水，旱季开始。降雨模式和分布的变化可能对流域的水供应产生深远影响，因此，检查降雨的时空变化至关重要。然而，梅加拉亚邦的长期降雨变化没有得到很好的探索。在这项研究中，我们研究了梅加拉亚邦的两个重要流域，即Umiam流域和Umtru流域，以研究时空降雨的变化。使用印度气象局1901年至2018年的栅格化降雨数据，我们发现年，冬季，季风前和季风降水在减少，而季风后降水在增加。我们使用创新的趋势分析（ITA）方法来确定低，中和高强度降雨的趋势。我们发现，中低强度降雨呈下降趋势，而高强度降雨在年度和季节尺度上呈上升趋势。最后，我们使用广泛接受的Mann-Kendall（MK）测试来交叉检查使用创新趋势分析方法检测到的趋势。我们发现，使用两种方法获得的结果通常是一致的。但是，ITA可以检测到不同降雨强度下的非单调趋势，并且比MK测试对隐藏模式更为敏感。最后，我们使用创新的趋势分析方法和广泛接受的Mann-Kendall（MK）检验来交叉检查检测到的趋势。我们发现，使用两种方法获得的结果通常是一致的。但是，ITA可以检测到不同降雨强度下的非单调趋势，并且比MK测试对隐藏模式更为敏感。最后，我们使用创新的趋势分析方法和广泛接受的Mann-Kendall（MK）检验来交叉检查检测到的趋势。我们发现，使用两种方法获得的结果通常是一致的。但是，ITA可以检测到不同降雨强度下的非单调趋势，并且比MK测试对隐藏模式更为敏感。