Investigation of Climate Extremes in Jabalpur District of Madhya Pradesh: Trends and Future Implications

Author:

Thakur Pankaj Kumar1,Gururani Dheeraj Mohan2,Agrawal Abhishek3,Varade Divyesh2,Dubey Snehil4,Kumari Pushpanjali5

Affiliation:

1. Indian Institute of Technology Roorkee

2. Indian Institute of Technology Jammu

3. Maharana Pratap University of Agriculture and Technology

4. Indian Institute of Technology Hyderabad

5. Central University of Jharkhand

Abstract

Abstract

Climate change is a long-term change in hydro-meteorological conditions in a particular geographical region. In the present study, spatio-temporal long-term change in rainfall during 1961–2020 was analyzed using IMD 0.25°×0.25° resolution gridded dataset in the Jabalpur district. The non-parametric Mann–Kendall trend test and Sen’s slope estimator was applied to determine the trend and its magnitude, respectively in the precipitation time series. Extreme indices were employed to understand the risks and vulnerabilities associated with extreme weather events in the district. Mann-Kendall trend test showed an insignificant trend at 95% confidence interval with Sen’s slope value of -2.98 to 0.73 mm/year. CLIMPACT tool was used to study extreme indices and it revealed that, in the district, CDD, CWD, R10, R20, and RX5 were decreasing, whereas RX1 and SDII were found increasing. The study’s outcomes provide valuable inferences for future water resource planning and management in central India, particularly in Jabalpur district.

Publisher

Springer Science and Business Media LLC

Reference67 articles.

1. Trends analysis of groundwater: using non-parametric methods in Terengganu Malaysia;Abdullahi MG;Journal of Earth Science and Climatic Change,2015

2. A homogeneity test applied to precipitation data;Alexandersson H;J Climatol,1986

3. Homogenization of Swedish temperature data. Part I: a homogeneity test for linear trends;Alexandersson H;Int J Climatol,1997

4. Trend analysis of temperature in Gombe state using Mann Kendall trend test;Alhaji UU;Journal of Scientific Research and Reports,2018

5. Spatiotemporal clustering: a review;Ansari MY;Artificial Intelligence Review,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3