Comparison of classical mann–kendal test and graphical innovative trend analysis for analyzing rainfall changes in India

Abstract

The analysis of rainfall trends is of the utmost importance for sustainable management and planning of agriculture and water resources under changing climate. Therefore, this study aims to detect the long-term rainfall trends of 36 meteorological subdivisions of India for the period 1901–2015. The graphical innovative trend analysis (ITA) technique and the classical statistical Mann–Kendall (MK) or modified Mann–Kendall (mMK) tests are used to detect historical rainfall changes. The nonparametric Sen’s slope (Q) estimator is also applied to measure the magnitude of change. The ITA results show about 61.11% of the subdivisions exhibited decreasing trends in annual rainfall. On the seasonal scale, about 58.33%, 50%, 69.44%, and 88.88% of the subdivisions are experiencing decreasing trends in pre-monsoon (Mar–May), monsoon (Jun–Sep), post-monsoon (Oct–Nov), and winter (Dec–Feb) seasons, respectively. The results of the Z statistic show a good match (about 90%) with the graphical ITA method. However, the ITA method is able to detect subtrends while, MK/mMK shows only the monotonic trend. Such a trend analysis of rainfall can provide significant information that will be useful to build up adaptive capacity and community resilience against climate change. This study can be helpful for regional-scale planning about pre and post-disaster floods, drought mitigation, and agricultural development.