Change analysis of All India and regional rainfall data series at annual and monsoon scales

Author:

Jain Sharad K.1ORCID,Xu Chong-Yu2,Zhou Yanlai3

Affiliation:

1. a Civil Engineering Department, IIT Roorkee, 247667 Roorkee, India

2. b Department of Geosciences, University of Oslo, N-0316, Oslo, Norway

3. c State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China

Abstract

AbstractRainfall characteristics are changing due to several reasons and change/trend detection is required. Literature survey reveals many relevant studies whose outcomes are divergent, possibly because different data series and different methodologies have been applied. This paper presents a critical appraisal of past studies and methodologies for trend analysis. Results of trend analysis of Indian rainfall data are presented. Data for all of India and for five homogenous regions (North-West, Central North-East, North-East, West Central, and Peninsular India) for 1871–2016 were used. The Pettitt change point test, regression, Mann-Kendall (MK), and Wavelet Decomposition were used to study different aspects of changes. Results of the change point test showed that most rainfall series had change points around 1957–65, possibly due to large-scale land use, cultivation, irrigation, and industrial changes in this period. Generally, rainfall for most homogenous regions and sub-divisions show falling trends; some are statistically significant. Series was also decomposed by the wavelet method. Approximate and detailed components of some decomposed series showed a significant declining trend. This work has focused on the magnitude of rainfalls; trends in rainfall intensities are also important. It is necessary to establish denser observation networks to collect short-term data and analyze.

Publisher

IWA Publishing

Subject

Water Science and Technology

Reference70 articles.

1. Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data;Atmospheric Research,2015

2. Technical Summary;Masson-Delmotte,2021

3. To prewhiten and not to prewhiten in trend analysis?;Hydrological Sciences Journal,2007

4. Detection and Attribution of Climate Change: from Global to Regional;Stocker,2013

5. Analysis of rainfall trend using non-parametric methods and innovative trend analysis during 1901–2020 in seven states of north east India;Current Science,2022

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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