Spatio-temporal trend analysis of rainfall using parametric and non-parametric tests: case study in Uttarakhand, India

Abstract

This study investigates the spatial and temporal patterns of trends and magnitude of rainfall on monthly, seasonal and annual time scales of 13 districts of Uttarakhand State located in Central Himalayan region of India. The temporal trend was analyzed using Mann-Kendall (MK), Modified Mann-Kendall (MMK), and Kendall Rank Correlation (KRC) tests at 10%, 5%, and 1% significance levels. The magnitude (slope) of rainfall trend (mm/year) was determined using Theil-Sen’s Slope (TSS) and Simple Linear Regression (SLR) tests. The autocorrelation coefficient (ACC) of three different time series was calculated at one-time lag and were tested at 10%, 5%, and 1% levels of significance for the application of MMK test. The results of analysis revealed significant positive and negative trends were observed in monthly, seasonal, and annual rainfall time series in all 13 districts of Uttarakhand state. The spatial variation of the trends based on monthly, seasonal, and annual rainfall time series data was interpolated using the Thiessen polygon (TP) method in ArcGIS 10.2 environment. The maps of spatial variability of rainfall trends were developed to help local stakeholders and water resource managers to understand the risk and vulnerability related to climate change in the region.