Evaluation of extreme rainfall distribution in spatial

2021 Fiscal Year Final Research Report

• Project/Area Number: 19K21982
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 22:Civil engineering and related fields
• Research Institution: Tohoku University
• Principal Investigator: Kazama So 東北大学, 工学研究科, 教授 (50272018)
• Co-Investigator(Kenkyū-buntansha): 井上 亮 東北大学, 情報科学研究科, 准教授 (60401303) ; 峠 嘉哉 東北大学, 工学研究科, 助教 (90761536)
• Project Period (FY): 2019-06-28 – 2022-03-31
• Keywords: 極端現象 / レーダー・アメダス / GEV / d4pdf / 再現期間 / ARFs

Outline of Final Research Achievements

The spatial return period is defined as "the period until the extreme precipitation occurs again in the target area". We used d4PDF with spatial resolution of 20 km to analyze the large ensemble data of thousands of years. The use of d4PDF improves the accuracy of extreme precipitation estimation and also enables spatial analysis of extreme precipitation due to its spatial data. The spatial return period (RP) of the 100-year extreme precipitation over Japan is 1.61 years in the historical simulation and 1.14 years in the +4-K future simulation. We clarified the relationship between the annual area of occurrence of RP100-year extreme precipitation and its probability. In addition, Japan is divided into four areas according to latitude, and the spatial return period is compared for each region. It is found that the spatial return period of high latitude area such as Hokkaido region is about 1.7 times longer than that of low latitude regions such as Kyushu and Shikoku region.

Free Research Field

水文学

Academic Significance and Societal Importance of the Research Achievements

地方自治体管理の中小河川の氾濫確率は，流域が小さいため降雨の確率と同規模の洪水が発生する．本研究によって空間スケールと降雨の再現確率が理解され，流域内の洪水被害の発生頻度をおおよそ理解できた．特に温暖化によるリスクの上昇の地域性が明確になった．より効果的な備え，特に水防施設や配置や治水の投資効果を知ることができ，豪雨災害対策に有効である．確率降雨への正しい認識によって，一般市民への豪雨災害の啓発として利用できるとともに，学問上も新しい空間再現確率を示すことができたと考えている．