Influence of Localized Rainfall Patterns on Landslide Occurrence—A Case Study of Southern Hiroshima with eXtended Radar Information Network Data during the July 2018 Heavy Rain Disasters

Author:

Rodrigues Neto José Maria dos Santos1,Bhandary Netra Prakash2ORCID

Affiliation:

1. Graduate School of Science and Engineering, Ehime University, Matsuyama 790-8577, Japan

2. Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama 790-8577, Japan

Abstract

In this study, we use GIS and other analytical platforms to analyze the landslide distribution pattern in the July 2018 heavy rain disasters in the southern part of Hiroshima Prefecture in Japan in conjunction with chronological XRAIN (eXtended Radar Information Network) radar-acquired localized rainfall data in order to better understand the relationship between rainfall characteristics and landslide probability. An analysis of event rainfall from the July 2018 disasters determines that landslide-inducing rainfall started from 8:30 AM on 5 July and continued until 7:30 AM on 7 July, accumulating to up to 368 mm in total precipitation, and that there were two intensity peaks, one around 7:30 PM on 6 July, and another one around 4:30 AM on 7 July. These two events are associated with particularly high landslide activity, which indicates that landslide activation is related to peak-intensity rainfall combined with accumulated continuous precipitation. The XRAIN data were also used together with landslide reports to calculate the intensity–duration (i.e., I-D) rainfall threshold for the area. The mean annual precipitation in the whole study area ranged between 2025 mm and 3030 mm, with an average value of about 2300 mm. The spatial distribution of rainfall throughout the sampled years indicates that rainfall is remarkably localized, with higher values concentrated on elevated areas. However, it was also observed that the maximum precipitation volumes are not so closely related to landslide occurrence, and the highest landslide activity was found in intermediate precipitation class zones instead. Correlating the localization patterns of event precipitation and mean annual precipitation using Pearson’s correlation coefficient, we found an r value of 0.55, which is considered a moderate correlation between the two datasets (i.e., event precipitation and mean annual precipitation).

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference45 articles.

1. Geertsema, M., Highland, L., and Vaugeouis, L. (2009). Landslides–Disaster Risk Reduction, Springer.

2. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey);Yilmaz;Comput. Geosci.,2009

3. Global patterns of loss of life from landslides;Petley;Geology,2012

4. (2022, July 27). Centre for Research on the Epidemiology of Disasters. Economic Losses, Poverty & Disasters 1998–2017. United Nations Office for Disaster Risk Reduction. Available online: https://www.preventionweb.net/files/61119_credeconomiclosses.pdf.

5. The Influence of Structural Setting and Lithology on Landslide Type and Pattern;Guzzetti;Environ. Eng. Geosci.,1996

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