Abstract
The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the subdistrict level and aggregated to monthly, annual, seasonal rainfall totals, and the number of rainy days. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. NonParametric Mann–Kendall test and Spearman’s rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen’s slope method. For the data influenced by serial correlation, various modified versions of Mann–Kendall tests (pre-whitening, trend-free pre-whitening, bias-corrected pre-whitening, and two variants of variance correction approaches) were applied. A significant increasing summer rainfall trend is observed in six out of 27 stations. Significant decreasing trends are observed at two stations during the southwest monsoon season and at two stations during the northeast monsoon season. To identify the trend change points in the time series, distribution−free cumulative sum test, and sequential Mann–Kendall tests were applied. Two open−source library packages were developed in R language namely, ”modifiedmk” and ”trendchange” to implement the statistical tests mentioned in this paper. The study results benefit water resource management, drought mitigation, socio−economic development, and sustainable agricultural planning in the region.
Highlights
Hydrological regime is under a lot of stress due to climate change and is gaining a lot of attention in the scientific community due to its potential adverse effects on the environment [1]
Each station contains 17 series (12 monthly, one annual and four seasonal series), and a total of 459 time series generated from 27 rain gauge locations (27 × 17) were subjected to statistical tests and the analysis is provided
Trend change points are reported when there is any significant positive or negative trend observed in the time series
Summary
Hydrological regime is under a lot of stress due to climate change and is gaining a lot of attention in the scientific community due to its potential adverse effects on the environment [1]. Rainfall variability plays a major role in the Indian economy and extreme rainfall events resulting in drought and floods impact the nation’s food security and Gross Domestic Product (GDP) [2]. India is quite vulnerable to climate change and its impact on various sectors such as water resources, agriculture, forestry, and the health sector, etc. Detailed analysis of rainfall trend is useful to rainfall forecasting, planning water resources development and management, designing water storage structures, irrigation practices and crop choices, drinking water supply, industrial development, and disaster management for current and future climatic conditions [11,12,13,14,15]. The evaluation of past trends of meteorological parameters at various spatial and temporal scales plays a crucial role in understanding climate change and its impact on food security, energy security, natural resource management, and sustainable development [16,17].
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