Updated on 2025/04/15

写真a

 
TANOUCHI Hiroto
 
Name of department
Faculty of Systems Engineering, Environmental Science
Job title
Associate Professor
Mail Address
E-mail address
Homepage
External link

Education

  • 2014
    -
    2015

    Swedish Meteorological and Hydrological Institute  

  • 2013
    -
    2016

    Tokyo Metropolitan University   Graduate School of Urban Environmental Sciences   都市基盤環境学域  

  • 2011
    -
    2013

    Tokyo Metropolitan University   Graduate School of Urban Environmental Sciences  

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    Master

  • 2009
    -
    2011

    Hokkaido University   Faculty of Environmental Earth Science   Division of Earth System Science  

  • 2004
    -
    2008

    Shinshu University   Faculty of Engineering   社会開発工学科  

Degree

  • Ph.D. in Engineering   2016

Academic & Professional Experience

  • 2022.04
    -
    Now

    Wakayama University   Faculty of Systems Engineering   Lecturer

  • 2016.04
    -
    2022.03

    Wakayama University   Faculty of Systems Engineering   Assistant professor

Association Memberships

  • 2023.09
    -
    Now

    日本自然災害学会

  • 2018.09
    -
    2023.04

    人工知能学会

  • 2017.04
    -
    Now

    廃棄物資源循環学会

  • 2016.04
    -
    Now

    地盤工学会

  • 2016.04
    -
    Now

    日本水環境学会

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Research Areas

  • Social infrastructure (civil Engineering, architecture, disaster prevention) / Hydroengineering

  • Social infrastructure (civil Engineering, architecture, disaster prevention) / Civil engineering (environmental systems)

  • Social infrastructure (civil Engineering, architecture, disaster prevention) / Disaster prevention engineering

Classes (including Experimental Classes, Seminars, Graduation Thesis Guidance, Graduation Research, and Topical Research)

  • 2023   Information Processing ⅡB   Liberal Arts and Sciences Subjects

  • 2023   Information Processing ⅡB   Liberal Arts and Sciences Subjects

  • 2023   Information Processing ⅡA   Liberal Arts and Sciences Subjects

  • 2023   Information Processing ⅡA   Liberal Arts and Sciences Subjects

  • 2023   Introductory Seminar in Systems Engineering   Specialized Subjects

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Satellite Courses

  • 2023   Regional Disaster Prevention in southern Osaka Prefecture   Cooperative Development Subjects

  • 2020   Heavy rain disaster and its preparation   Cooperative Development Subjects

Classes

  • 2023   Systems Engineering SeminarⅠA   Master's Course

  • 2023   Systems Engineering SeminarⅠB   Master's Course

  • 2023   Systems Engineering SeminarⅡA   Master's Course

  • 2023   Systems Engineering SeminarⅡB   Master's Course

  • 2023   Systems Engineering Project SeminarⅠA   Master's Course

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Research Interests

  • Inundation Analysis

  • Simulation

  • GIS

  • Tsunami

  • Runoff Analysis

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Published Papers

  • Urban Flood Runoff Modeling in Japan: Recent Developments and Future Prospects

    Akira Kawamura, Hideo Amaguchi, Jonas Olsson, Hiroto Tanouchi

    Water ( MDPI AG )  15 ( 15 ) 2733 - 2733   2023.07  [Refereed]

     View Summary

    Since the 20th century, Japan has experienced a period of very rapid urbanization. Cities have experienced substantial densification and expansion, resulting in gradually elevated flood risk. Urban flooding has also occurred in most large cities in Japan, particularly in Tokyo. In response to this growing problem, much effort and resources have been spent on research and development aimed at understanding, simulating, and managing urban flood risk in Japan. The objective of this review is to summarize, discuss, and share key outputs from some of the main research directions in this field, significant parts of which have been uniquely developed in Japan and only published in Japanese. After a general introduction to urban runoff modeling, in the next section, key historical works in Japan are summarized, followed by a description of the situation in Japan with respect to observations of precipitation and water level. Then, the storage function model approach is reviewed, including an extension to urban basins, as well as recent experiments with AI-based emulation in Japanese basins. Subsequently, we review the prospects of detailed hydrodynamic modeling involving high-resolution, vector-based Geographical Information System (GIS) data for the optimal description of the urban environment with applications in Tokyo. We conclude the paper with some future prospects related to urban flood risk modeling and assessment in Japan.

    DOI

  • EARLY PREDICTION SYSTEM FOR THE AMOUNT, COMPOSITION AND SPATIAL DISTRIBUTION OF DISASTER WASTE GENERATED BY ACTIVE FAULT EARTHQUAKES

    Yukiya MARUYAMA, Hiroto TANOUCHI, Nobuyuki EGUSA (Part: Corresponding author )

    Japanese Journal of JSCE ( Japan Society of Civil Engineers )  81 ( 22 ) 1 - 12   2025.02  [Refereed]

    DOI

  • AN IMMEDIATE PREDICTION SYSTEM OF DISASTER WASTE QUANTITY, QUANTITY AND SPATIAL DISTRIBUTION GENERATED BY INUNDATION

    Hiroto TANOUCHI, Takayuki SAKAI, Yoshikazu OTSUKA, Masaki NAKANO (Part: Lead author, Corresponding author )

    Japanese Journal of JSCE ( Japan Society of Civil Engineers )  80 ( 22 ) 1 - 11   2024.03  [Refereed]

    DOI

  • A Transfer Learning Approach Based on Radar Rainfall for River Water-Level Prediction

    Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa, Takuya Yoshihiro

    Water ( MDPI AG )  16 ( 4 ) 607 - 607   2024.02  [Refereed]

     View Summary

    River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological stations. A prediction model incorporating a two-dimensional convolutional neural network (2D-CNN) and long short-term memory (LSTM) is constructed to exploit geographical and temporal features of radar rainfall data, and a transfer learning method using a newly defined flow–distance matrix is presented. The results of our evaluation of the Oyodo River basin in Japan show that the presented transfer learning model using radar rainfall instead of upstream measurements has a good prediction accuracy in the case of torrential rain, with a Nash–Sutcliffe efficiency (NSE) value of 0.86 and a Kling–Gupta efficiency (KGE) of 0.83 for 6-h-ahead forecast for the top-four peak water-level height cases, which is comparable to the conventional model using upstream measurements (NSE = 0.84 and KGE = 0.83). It is also confirmed that the transfer learning model maintains its performance even when the amount of training data for the prediction site is reduced; values of NSE = 0.82 and KGE = 0.82 were achieved when reducing the training torrential-rain-period data from 12 to 3 periods (with 105 periods of data from other rivers for transfer learning). The results demonstrate that radar rainfall data and a few torrential rain measurements at the prediction location potentially enable us to predict river water levels even if hydrological stations have not been installed at the prediction location.

    DOI

  • A NUMERICAL SIMULATION OF DISASTER WASTE DISPOSAL IN WAKAYAMA CITY BY USING DHT MODEL

    Soichiro ASAI, Tatsuya AKIYAMA, Hiroto TANOUCHI, Nobuyuki EGUSA (Part: Corresponding author )

    International Journal of GEOMATE   20 ( 80 ) 23 - 28   2021.02  [Refereed]

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Misc

  • A spontaneously disaster evacuation drill for Tsunami by imitating a game of tag

    Hiroto Tanouchi, Tomomi Nakano, Nobuyuki Egusa (Part: Lead author )

    GEOMATE2023 Mie Fullpaper     2023.11  [Refereed]

  • 災害廃棄物処理の初動支援を目的とした発生量・空間分布・組成の推定システム

    田内裕人, 酒井崇之, 大塚義一, 中野正樹 (Part: Lead author )

    第48回土木情報学シンポジウム講演集     2023.09

  • River Water Level Prediction Using Radar Rainfall with Deep Learning

    Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa, Takuya Yoshihiro

    17th International Workshop on Informatics (IWIN 2023)     2023.09  [Refereed]

  • 災害廃棄物処理プロセスの最適化を導入した災害廃棄物処理実行計画作成支援システムの開発

    中野正樹, 田内裕人, 酒井崇之, 大塚義一, 加藤雅彦, 高井敦史, 佐々木秀幸

    第15回環境地盤工学シンポジウム論文集     2023.06  [Refereed]

  • 和歌山県日高川町弥谷地区において昭和の紀伊半島大水害時に発生した土砂災害とその伝承

    秋山 晋二, 谷垣 勝久, 田内 裕人, 後 誠介

    日本応用地質学会研究発表会     2022.10

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Awards & Honors

  • Best Paper Award

    Winner: Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa, and Takuya Yoshihiro

    2023.10   IWIN 2023   River Water Level Prediction Using Radar Rainfall with Deep Learning

  • 関西支部 社会貢献賞

    Winner: 矢野晴彦, 辻野裕之, 谷垣勝久, 石田優子, 田内裕人, 本塚智貴, 江種伸之

    2018.02   地盤工学会   平成 23 年台風 12 号に伴う熊野那智退社裏山の斜面崩壊・土石流に関する 調査研究

  • 優秀ポスター賞

    Winner: 田内裕人, 天口英雄, 河村明

    2015.03   水文・水資源学会   個別建物を考慮した浸水解析格子の自動構築に関する一考察

Conference Activities & Talks

  • Possibility of Introducing Renewable Energy to in-situ Remediation Technology

    江種伸之, 田内裕人, 丸山裕嗣, 平田健正

    第26回水環境学会シンポジウム 土壌地下水汚染研究委員会企画セッション  2023.09  

  • レーダ雨量を用いた深層学習による増水時の河川水位予測の試み

    上田風斗, 田内裕人, 江種伸之, 吉廣卓哉

    第106回モバイルコンピューティングと新社会システム研究会 (MBL)  2023.02  

  • 災害廃棄物の収集運搬・処理連動モデルの基礎的性能の検証

    田内 裕人, 黒木 秀和, 岩下 将也, 大塚 義一, 中野 正樹

    第46回土木情報学シンポジウム  2021.09.25  

  • Pythonによる災害廃棄物の収集運搬・処理連動モデルのプロトタイプの開発

    田内裕人, 浅井惣一郎, 江種 伸之

    第45回土木情報学シンポジウム  2020.09.24  

  • 揮発性有機化合物に対する原位置浄化技術の環境負荷

    江種伸之, 田内裕人, 丸山裕嗣, 平田健正

    第23回日本水環境学会シンポジウム  2020.09  

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KAKENHI

  • 新旧歴史災害情報に基づく土砂災害の再現性に注目した素因・誘因分析

    2018.04
    -
    2021.03
     

    Grant-in-Aid for Scientific Research(C)  Co-investigator

Competitive funding, donations, etc. from foundation, company, etc.

  • システム工学部寄附金(株式会社奥村組技術本部)

    2024.08
     

    Contribution  Principal investigator

  • システム工学部寄附金(株式会社奥村組技術本部)

    2023.07
     

    Contribution  Principal investigator

Joint or Subcontracted Research with foundation, company, etc.

  • AI等の活用による災害廃棄物処理プロセスの最適化と処理計画・処理実行計画の作成支援システムの構築

    2020.04
    -
    2023.03
     

    Contracted research  Co-investigator

Instructor for open lecture, peer review for academic journal, media appearances, etc.

  • 浸水対策に関する有識者

    2024.09.02
    -
    2024.09.13

    和歌山市

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    内水氾濫、防災

    浸水対策事業における意見聴取

  • 非常勤講師

    2024.08.06

    太地町立太地小学校

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    防災、津波、避難訓練、防災教育

    太地町教育研究会(太地小・中・こども園)の会員による防災学習を実施するにあたり、田内准教授には、「津波を鬼に見立てて逃げ切れ」プロジェクトとして、津波避難アプリを使った避難訓練の支援、指導・助言をしていただく。

  • 浸水対策に関する有識者

    2023.09.25
    -
    2023.10.31

    和歌山市

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    防災

    浸水対策事業における意見聴取

  • 水工学講演会 座長

    2022.11

    土木学会水工学委員会

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    座長

    地下水セッションにおける座長

  • 和歌山県警の防災ジオツアー

    2022.10.07

    和歌山県警察

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    防災、豪雨災害、土砂災害、洪水

    職員の防災研修の一環として、上記日時、場所において、防災ジオツアー研修を依頼するもので、ツアー講師役をお願いします。

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Committee member history in academic associations, government agencies, municipalities, etc.

  • プログラムワーキンググループ リーダー

    2022.05
    -
    Now
     

    地盤工学会 地下水・土壌汚染とその防止対策に関する研究集会

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    学協会、政府、自治体等の公的委員

    研究集会の運営業務,任期:1年(自動的に毎年継続される)
    〇2022年度は、プログラムの募集、要綱作成、チェック、編集および公開のすべてを担うワーキングリーダーに着任し、業務を行った。

  • 査読者

    2022.04
     

    土木学会(水工学委員会、地球環境委員会)

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    査読

    2編の査読業務

  • 橋本市環境保全審議会

    2021.11.01
    -
    2023.10.30
     

    橋本市

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    環境保護、環境改善

    橋本市環境保全審議会は、橋本市環境保全条例第29条の規定に基づき設置されている市長の附属機関で、
    ①環境の保全に関する施策を総合的かつ計画的に実施するために橋本市環境基本計画を策定するとき
    ②県等から産業廃棄物処理施設の設置における意見照会があった場合
    に意見を求められ、健全で快適な環境の確保に関する基本的事項や重要事項を審議する委員のおひとりとしてお願いします。

  • 意見聴取

    2020.01
    -
    Now
     

    和歌山市企業局 浸水対策事業における意見聴取

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    国や地方自治体、他大学・研究機関等での委員

    意見聴取,任期:2020年1月~

  • 水文・水資源学会 査読編集委員

    2018.04
    -
    Now
     

    水文・水資源学会

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    水文・水資源学会 査読編集委員

    学会誌の査読編集委員を行った。