Parametric and Non-parametric Analysis of Annual Precipitation for Amaravati: A Spatial and Temporal Analysis

Abstract

Abstract Analysis of the trends, homogeneity and stationarity of yearly rainfall series at gauged stations located in and around Amaravati, the research is centered on the new declared capital of Andhra Pradesh, India. Thirty years (1985-2014) of annual precipitation data from 17 gauged stations were available for the study. The study is conducted using both parametric linear regression and non-parametric approaches, namely the Sen’s slope method and Mann-Kendall trend test. The homogeneity of the precipitation series is assessed using the Standard Normal Homogeneity Test (SNHT), von Neumann’s test, and Pettitt’s test and von Neumann’s test. Stationarity and non-stationarity of precipitation time series are determined using Dickey-Fuller (ADF), Kwiatkowski–Phillips–Schmidt–Shin (KPSS) and Phillips-Perron (PP) methods. For most of the stations, the parametric linear regression analysis of annual precipitation indicated a positive trend. Out of all the stations analysed in the non-parametric test for the average yearly precipitation series, 47 percent exhibited a positive trend. Specifically, a significant trend was seen at the Vijayawada urban station. Sen’s slope values varied from -1.233 mm/year (at Kanchikacherala) to 1.744 mm/year (in Vijayawada Urban). With the exception of Amaravati and Vijayawada urban stations, the remaining stations demonstrated more stationarity and homogeneity in the conducted tests. With the exception of Amaravati and Vijayawada urban stations, the remaining stations demonstrated more stationarity and homogeneity in the conducted tests. The findings of this study will assist in making informed choices on the organising, management, as well as growth of the water supply within the Amaravati region, in response to climate change.