Spatio-temporal trend analysis and future projections of precipitation at regional scale: a case study of Haryana, India

Abstract

In this study, we investigated the spatio-temporal distribution and performance of seasonal precipitation in all districts of Haryana, India. We analysed the gridded precipitation dataset of the India Meteorological Department (IMD) for a period of 120 years (1901–2020) using different statistical methods. We found that Haryana received a mean precipitation of 37.0, 37.7, 468.3, and 24.8 mm during the winter, pre-monsoon, monsoon, and post-monsoon seasons, respectively. During each season, the eastern districts of Haryana received more precipitation than its western counterparts. Sen's slope results obtained after trend-free pre-whitening (TFPW) showed a statistically significant increasing trend of 0.12 mm (p-value; 0.04) during the pre-monsoon period, whereas decreasing but non-significant trends were observed during the winter, monsoon and post-monsoon seasons at the rate of −0.04 mm (p-value; 0.49), −0.26 mm (p-value; 0.52), −0.05 mm (p-value; 0.33) per year, respectively, for the entire Haryana state. The winter precipitation is expected to increase under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, whereas pre-monsoon precipitation is expected to decrease under the RCP8.5 scenario by the end of the 21st century. The monsoon precipitation is expected to decrease under all RCP scenarios, whereas post-monsoon precipitation is expected to gradually increase under the RCP8.5 scenario by the end of the 21st century.

Efficacy of Machine Learning in Simulating Precipitation and Its Extremes Over the Capital Cities in North Indian States

“…For India, a few literatures are available for extreme precipitation analysis 30,[42][43][44] , however relatively fewer for extreme precipitation modelling using machine learning 37,45,46 . The limited availability of highquality and comprehensive meteorological data in India and complexity of the regional topography and climate are also prominent contributing factor for limited number of research.…”

Fate of Rainfall Over the North Indian States in the 1.5 and 2°C Warming Scenarios

“…Many other studies were done by the authors in which rainfall pattern, distribution, frequency, etc. of different North Indian states were studied, that is, Haryana (Chauhan et al., 2022; Nain & Hooda, 2019), Himachal Pradesh (Jaswal et al., 2015), Punjab (Kaur et al., 2021), Rajasthan (Mundetia & Sharma, 2014; Pingale et al., 2013), Uttarakhand (Malik & Kumar, 2020) and Uttar Pradesh (Guhathakurta et al., 2020). Mondal et al.…”

“…Increasing trends in precipitation during autumn and winter, whereas decreasing trends during monsoon and spring were reported by Pal and Al-Tabbaa (2011) based on the analysis for the period of 1954-2003. Many other studies were done by the authors in which rainfall pattern, distribution, frequency, etc. of different North Indian states were studied, that is, Haryana (Chauhan et al, 2022;Nain & Hooda, 2019), Himachal Pradesh (Jaswal et al, 2015), Punjab (Kaur et al, 2021), Rajasthan (Mundetia & Sharma, 2014;Pingale et al, 2013), Uttarakhand (Malik & Kumar, 2020) and Uttar Pradesh (Guhathakurta et al, 2020). Mondal et al (2022) showed that the extreme precipitation events across South Asia may increase up to 3.5%-6.6% due to increase in warming from 1.5 to 2.0°C.…”