Evaluating rainfall trend in four key stations of the Northwestern Himalayan region, Uttarakhand: utilizing innovative graphical approaches for trend assessment

Abstract

Comprehending rainfall patterns is a multifaceted endeavor, both in terms of spatial and temporal dimensions. Gaining insight into these patterns necessitates a close examination of trends within rainfall time series data. The main focus of this research is to evaluate the variations in annual and seasonal precipitation characteristics within the Kosi River Basin (KRB) of Uttarakhand using globally recommended method such as., Innovative Trend Analysis (ITA), Mann-Kendall (MK) test and linear regression (LR) analysis. Through ITA, both monotonic and non-monotonic trends were discerned, irrespective of serial correlation, dataset size, or distribution characteristics. This technique proves valuable in identifying diverse trends in rainfall data. In contrast to MK tests, ITA exhibited greater efficacy in trend detection, yielding distinct results across various seasons. For instance, during the monsoon season, MK tests failed to detect trends, while ITA successfully identified them. Conversely, post-monsoon season trends were identified using all three techniques. In sum, ITA emerged as a more dependable method for trend identification in rainfall data. This insight can be instrumental in formulating strategies for sustainable water resource management and addressing potential challenges posed by climate change on water availability. The findings of this study hold significant relevance for ongoing climate change policies, particularly in the context of hill agriculture in Uttarakhand and other parts of the globe.