Characterizing rainfall of hot arid region by using time series modeling and sustainability approaches: a case study from Gujarat, India

Abstract

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time series modelling techniques and sustainability approach. Five characteristics, i.e. normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and nonparametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series, and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability (Ry), resilience (Re) and vulnerability (Vy) approach. Box-whisker plots, normal probability plots and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively-skewed and non-normal compared to that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t-tests and the nonparametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically-significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag) and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations (Ry=0.50 and 0.44; Re=0.47 and 0.47; Vy=0.49 and 0.46, respectively) are the most sustainable and dependable compared to that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of Ry-Re-Vy approach. In general, annual rainfall of the study area is less reliable, less resilient and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time series modelling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.