Devi Dayal

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

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling 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 non-parametric 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 with 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 non-parametric 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 with 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 modeling 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.

Spatial modelling of rainfall trends using satellite datasets and geographic information system

ABSTRACT This study developed a standard methodology for identifying spatial trends using satellite-based raster datasets. It involves the novelty of exploring the capabilities of a geographic information system in implementing the procedures of three trend tests, the Spearman rank order correlation (SROC) test, the Kendall rank correlation (KRC) test and the Mann-Kendall (MK) test, on raster datasets of the Tropical Rainfall Measuring Mission at 0.25° × 0.25° resolution. Comparative evaluation of the three tests revealed fair agreement of a major part of the test results for pre-, post- and non-monsoon and one-day maximum rainfall. Also, similar results from KRC and MK tests were obtained over a considerable area for annual, monsoon and monthly maximum rainfall. These findings suggest the importance of selecting the appropriate test depending on rainfall magnitudes at the chosen time scale and emphasize the robustness of the KRC and MK tests.

Long-term rainfall trends and change points in hot and cold arid regions of India

ABSTRACT This study examined trends and change points in 100-year annual and seasonal rainfall over hot and cold arid regions of India. Using k-means clustering, 32 stations were classified into two clusters: the coefficient of variation for annual and seasonal rainfall was relatively high for Cluster-II compared to Cluster-I. Short-term and long-term persistence was more dominant in Cluster-II (entirely arid) and Cluster-I (partly arid), respectively. Trend tests revealed prominent increasing trends in annual and wet season rainfall of Cluster-II. Dry season rainfall increased by 1.09 mm year−1 in the cold arid region. The significant change points in annual and wet season rainfall mostly occurred in the period 1941–1955 (hot and cold), and in the dry season in the period 1973–1975 (hot arid) and in 1949 (cold arid). The findings are useful for managing a surplus or deficiency of rainwater in the Indian arid region. EDITOR A. Castellarin; ASSOCIATE EDITOR S. Kanae