Drought characterization over India under projected climate scenario

Abstract

The study evaluates the drought characteristics in India over projected climatic scenarios in different time frames, that is, near‐future (2010–2039), mid‐future (2040–2069), and far‐future (2070–2099) in comparison with reference period (1976–2005). Standardized Precipitation Evapotranspiration Index (SPEI), a multi‐scalar drought index was used owing to its robustness in capturing drought conditions while accounting the temperature. Gridded rainfall and temperature data provided by India Meteorological Department (IMD) was used to perform bias correction of nine Global Climate Models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5) project. Quantile mapping was used to correct the daily rainfall data at seasonal scale whereas daily temperature data was corrected at monthly scale. Multi‐Model Ensemble (MME) was prepared for different homogeneous monsoon regions of India, namely Hilly Regions (HR), Central Northeast (CNE), Northeast (NE), Northwest (NW), West Central (WC), and Peninsula (PS). Taylor diagram statistics were used for the preparation of MME. The regional climate cycle obtained from MME was found to be in good agreement with observed cycle derived from IMD data. The Mann–Kendal trend test was employed to detect the trend in drought severity and magnitude whereas L‐moments based frequency analysis was used to assess the magnitude of extreme drought severity under different time frames. The study reveals an increasing trend in drought severity, duration, occurrences, and the average length of drought under warming climate scenarios. Furthermore, the area under “above moderate drought” (i.e., severe and extreme drought combined) condition was also found to be increasing in projected climate.

Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India

“…More precisely, the increase in both the duration and the areal spread is more significant in the severe drought compared to the historical period, as shown in Figure 14. Bisht et al [68] also exhibited an increase in Indian regions in terms of drought occurrences and the drought durations in the near future. The future drought situation can be attributed to increasing water stress under warming scenarios, which can further be related to higher evaporative demand.…”

Long-Term Homogeneity, Trend, and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

“…In the next stage, lag−1 serial correlation coefficient ρ 1 of the detrended series y t is calculated as mentioned in Equation (9). If ρ 1 is not significant, the trend detection is performed on the detrended series.…”

“…India is quite vulnerable to climate change and its impact on various sectors such as water resources, agriculture, forestry, and the health sector, etc. are well documented by several researchers [3][4][5][6][7][8][9][10]. 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].…”

Long Term Homogeneity, Trend and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

“…In the next stage, lag 1 serial correlation coefficient ρ 1 of the detrended series is calculated as mentioned in equation (9). If ρ 1 is not significant, the trend detection is performed on the detrended series.…”

“…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 GDP [2]. India is quite vulnerable to climate change and its impacts on various sectors like water resources, agriculture, forestry, and health sector etc., are well documented by several researchers [3][4][5][6][7][8][9][10]. Detailed analysis of rainfall trend is useful in 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].…”