Updated on 2025/01/21

写真a

 
CHIKAMORI Hidetaka
 
Organization
Faculty of Environmental, Life, Natural Science and Technology Professor
Position
Professor
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Degree

  • Doctor of Engineering ( Kyoto University )

  • Master of Engineering ( Kyoto University )

Research Interests

  • 排水システムの最適化

  • 洪水予測

  • Optimal Design of Drainage System

  • 水文統計

Research Areas

  • Environmental Science/Agriculture Science / Rural environmental engineering and planning

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Hydroengineering

Professional Memberships

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Committee Memberships

  • Japan Society of Hydrology and Water Resources   Member of editing and publishing commitee  

       

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    Committee type:Academic society

    Japan Society of Hydrology and Water Resources

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  • 土壌物理学会   編集委員  

       

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    Committee type:Academic society

    土壌物理学会

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  • 水文・水資源学会   編集・出版委員  

       

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    Committee type:Academic society

    水文・水資源学会

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  • 土木学会   水工学委員会水文部会委員  

       

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    Committee type:Academic society

    土木学会

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  • Japanese Society of Soil Physics   Member of Editing commitee  

       

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    Committee type:Academic society

    Japanese Society of Soil Physics

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Papers

  • Estimation of Secular Change in Return Level of Daily Rainfall Using Metastatistical Extreme Value Distribution

    近森秀高, 工藤亮治, 丸尾啓太

    農業農村工学会論文集   91 ( 2 )   2023

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    J-GLOBAL

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  • わが国の農業分野における水文・水資源研究の動向

    近森秀高

    水文・水資源学会誌   31 ( 6 )   500 - 508   2018.11

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    Authorship:Lead author   Language:Japanese  

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  • Comparison of efficiency between differential evolution and evolution strategy: application of the LST model to the Be River catchment in Vietnam

    Nguyen Thi Thuy Hang, Hidetaka Chikamori

    PADDY AND WATER ENVIRONMENT   15 ( 4 )   797 - 808   2017.9

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    Authorship:Last author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:SPRINGER HEIDELBERG  

    Parameter calibration is an important step in the development of rainfall-runoff models. Recently, there has been a significant focus on automatic calibration. In this paper, two evolutionary optimization algorithms were applied to calibration of the long-and short-term runoff model (LST model) to simulate the daily rainfall-runoff process in the Be River catchment located in southern Vietnam. The differential evolution (DE) and evolution strategy (ES) algorithms were employed to optimize three objective functions: the Nash-Sutcliffe efficiency coefficient, root mean square error, and mean absolute error, which are indices for evaluating the simulation accuracy of the LST model. Hydrometeorological data for the periods 1985-1989 and 1990-1991 were used for calibration and validation, respectively. The LST model was calibrated for each objective function using five different parent and offspring population conditions. The results show that both the DE and ES algorithms are efficient methods for automatic calibration of the LST model. After 1000 generations, the best values of the fitness indices found by the DE technique were slightly better and more stable than those found by the ES technique in both calibration and validation. The average computation time for each generation using the DE algorithm was approximately two-thirds as long as that using the ES algorithm.

    DOI: 10.1007/s10333-017-0593-z

    Web of Science

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  • 確率分布の適合度評価 Invited

    近森秀高, 永井明博

    土地改良の測量と設計   83   1 - 8   2016

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    Authorship:Lead author   Language:Japanese  

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  • Regional Frequency Analysis of Daily Rainfall Observed at Meteorological Observatories in Japan

    CHIKAMORI Hidetaka, NAGAI Akihiro

    Journal of the Agricultural Engineering Society, Japan   81 ( 5 )   439 - 451   2013

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    Language:Japanese   Publisher:The Japanese Society of Irrigation, Drainage and Rural Engineering  

    Regional frequency analysis (RFA) has an advantage in size of usable data over the conventional at-site frequency analysis (SFA). Thus, the RFA is a potential approach for reliable estimation of design rainfall for drainage planning and flood control planning especially in the case that usable data is limited when available record length is short, which is because, for example, observing period is short or length of a climatologically homogeneous period is limited due to long-term climate change. This paper deals with a case study of RFA of daily rainfall observed at 155 hydrometeorological observatories in Japan. In advance to RFA, the observatories were categorized into eight regions by adjusting a result of cluster analysis based on similarity in statistics of daily rainfall and geographical closeness, and validity of the classification was assessed by checking discordancy of each rain gauge in each classified region and homogeneity of each region. The eight regions were similar to region classification for applying flood envelope curve in Japan. The results show that RFA estimates are close to SFA estimates, and bootstrap confidence intervals of RFA estimates were narrower than those of SFA estimates at almost all observatories, which suggests higher confidence of RFA estimates than those of SFA estimates.

    DOI: 10.11408/jsidre.81.439

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Books

  • 地域環境水文学

    田中丸, 治哉, 大槻, 恭一, 近森, 秀高, 諸泉, 利嗣(第5章 極端現象の水文統計解析;付録D 「大雨」が増えてきている?)

    朝倉書店  2016.3  ( ISBN:9784254445015

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    Total pages:vii, 210p   Language:Japanese

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  • 水理公式集 例題プログラム集 平成13年版

    土木学会  2002 

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  • 新編 土壌物理用語事典

    養賢堂  2002 

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  • 防災事典

    築地書店  2002 

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MISC

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Presentations

  • 気候シナリオのサンプル数の違いが極端現象の気候変動評価に与える影響岡山大(院

    工藤亮治, 近森秀高

    2023年度 農業農村工学会大会講演会  2023.8.31 

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    Event date: 2023.8.29 - 2023.8.31

    Language:Japanese   Presentation type:Oral presentation (general)  

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  • メタ統計的極値分布による気候予測情報のバイアス補正

    﨑川和起, 近森秀高, 工藤亮治, 丸尾啓太

    2023年度 農業農村工学会大会講演会  2023.8.31 

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    Event date: 2023.8.29 - 2023.8.31

    Language:Japanese   Presentation type:Oral presentation (general)  

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  • 時空間統計モデルを用いた線状降水帯のシミュレーション

    丸尾啓太, 近森秀高, 工藤亮治

    令和5年度 農業農村工学会大会講演会  2023.8.30 

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    Event date: 2023.8.29 - 2023.8.31

    Language:Japanese   Presentation type:Oral presentation (general)  

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  • Study on Uncertainty in Climate Change Impact due to Natural Variability of Extreme Events using Large Ensemble Climate Scenario

    KUDO Ryoji, CHIKAMORI Hidetaka

    2022.8.30 

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    Event date: 2022.8.30 - 2022.9.2

    Language:Japanese   Presentation type:Oral presentation (general)  

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  • Criteria for Selecting Probability Distribution in the Metastatistical Approach

    MARUO Keita, CHIKAMORI Hidetaka, KUDO Ryoji

    2022.9.1 

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    Event date: 2022.8.30 - 2022.9.1

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Awards

  • 農業農村工学会沢田賞

    2013  

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    Country:Japan

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  • 岡山市文化奨励賞

    2006  

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    Country:Japan

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  • Japan Society of Irrigation, Drainage and Reclamation Engineering (JSIDRE) Award, Science Ecouragement Award

    1999  

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  • 農業土木学会学術賞研究奨励賞

    1999   農業土木学会  

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    Country:Japan

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  • Japan Society of Irrigation, Drainage and Reclamation Engineering (JSIDRE) Award, Science Ecouragement Award

    1999  

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    Country:Japan

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Research Projects

  • 大規模アンサンブルデータを用いた事前放流における治水効果と利水運用リスクの定量化

    Grant number:23H02329  2023.04 - 2027.03

    日本学術振興会  科学研究費助成事業  基盤研究(B)

    工藤 亮治, 近森 秀高, 相原 星哉, 吉田 武郎

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    Grant amount:\8190000 ( Direct expense: \6300000 、 Indirect expense:\1890000 )

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  • Study on estimation accuracy of return level of hydrological values by applying Metastatistical Extreme Value Distribution and its

    Grant number:21K05831  2021.04 - 2024.03

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)  Grant-in-Aid for Scientific Research (C)

    近森 秀高, 工藤 亮治

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    Grant amount:\4160000 ( Direct expense: \3200000 、 Indirect expense:\960000 )

    本研究は,2021年度を最終年度とする基盤研究(C)(課題番号18K05879)の「ベイズ統計の理論を用いた既往最大規模豪雨および洪水の統計的評価に関する研究」の後継に位置付けており,メタ統計的極値分布の手法を,地域頻度解析に適用する手法の開発を研究目的の一つとしている。
    これまで,地域頻度解析では,雨量データの統計値であるL積率比や緯度・経度を用いて地域分類をおこなってきたが,気候の経年変動を考慮すると,豪雨などの極端現象を代表とする年最大値の経年変化パターンの類似性に着目して地域頻度分析を行うことも考えられる。
    ここでは,MEV分布についての検討の前段階として,年最大値時系列を対象とした下記の地域分類法について,(1) 各観測地点におけるL積率比と緯度・経度を用いたクラスター分析,(2) 各観測地点における年最大値時系列を平均値で除した基準化データを用いたクラスター分析,とを行った。
    岡山県内の雨量観測点を対象として検討した結果,岡山県全体を1地域として解析を行うと,地点頻度解析による結果との差が大きくなり過大または過小推定と思われる結果が多いこと,地域分類を,年最大値時系列を用いた方法で行い,従来のL積率比による地域分類の結果と比べると,年最大値時系列を用いた地域分類の方が,地点頻度解析に近い結果が得られることが分かった。
    以上の結果から,本研究で検討しているMEV法を用いて地域頻度解析を行うための地域分類について有用な知見が得られた。MEV法への地域頻度解析の適用では,地域を構成する全ての雨量観測点における雨量時系列データによる分類法を検討する必要があるが,そのためには年最大値を対象とした地域頻度解析について検討した結果に基づき,日雨量または時間雨量データを用いた適切な地域分類法を検討する必要がある。

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  • 事前放流支援に向けた中長期気象予報による河川流況アンサンブル予測システムの構築

    Grant number:20K06298  2020.04 - 2023.03

    日本学術振興会  科学研究費助成事業 基盤研究(C)  基盤研究(C)

    工藤 亮治, 近森 秀高

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    Grant amount:\4160000 ( Direct expense: \3200000 、 Indirect expense:\960000 )

    課題1について, アンサンブル流況予測システムのコアとなる水文モデルとしてタンクモデルを選定し,寒河江ダム流域に適用した.その結果,降雪量を補正して水収支をバランスさせることで実測のダム流入量が精度よく再現できることを示した.
    課題 2について,レーダーアメダスを用いて流域平均降水量を保持しながら降雨の空間的な集中度のみを変えた模擬降雨を複数パターン作成し,集中型流出モデルをグリッドに展開した分布型モデルに入力することで,降雨の空間的集中度が洪水ピーク流量に与える影響を吟味した.その結果,流域平均降水量が同値でも降雨の空間的集中度が高いほどに,洪水のピーク流量が大きくなることがわかった.
    次に,上記の流出計算で得られた計算流量を模擬洪水イベントとして,これを対象として集中型モデルのパラメータを同定し,降雨の空間分布の違いがモデルパラメータに与える影響を検討した.その結果,降雨の集中度の違いにより異なる性質のパラメータが同定されることがわかり,降雨の空間的な集中度が集中型モデルのパラメータの不確実性の要因となることがわかった.
    課題3について,寒河江ダム流域を対象として,パターン認識法の一種であるNearest Neighbor法を適用して5日先までのダム流入量予測を行った.その結果,1日先までは精度よく予測できるものの,3日先以降では出水を過小推定するなど予測精度が大きく低下した.そこで,気象予測値としてバイアス補正済みの週間アンサンブル予報をNearest Neighbor法によるダム流入量予測システムに導入したところ,予測精度が大幅に向上し3日先の出水もある程度の精度で予測が可能となった.ただし,リードタイムが長くなるほど高水部の過小推定軽奥が大きくなった.この点は今後の課題である.

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  • Study on Statistical Evaluation of Record Maximum Rainfall and Flood Discharge by Bayes' theorem

    Grant number:18K05879  2018.04 - 2022.03

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)  Grant-in-Aid for Scientific Research (C)

    Chikamori Hidetaka

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    Grant amount:\4420000 ( Direct expense: \3400000 、 Indirect expense:\1020000 )

    The purpose of this study was to examine a method for more accurate estimation of extreme values from limited data at the beginning, and initially used the Markov chain Monte Carlo method based on Bayesian statistical ideas that have been widely used in recent years. Firstly, extreme statistical analysis using the conventional annual maximum value method and threshold excess method were applied and evaluated, but as we proceeded with the research, we found a meta-statistical extreme value (MEV) distribution that uses all rainfall time series data. Comparison between the application results of the MEV method and those of the annual maximum method showed that the return level of rainfall can be estimated by suppressing the influence of a small number of extremely large peculiar data by the MEV method.

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  • Impact assessment of climate change on drought risk and quantification of its uncertainty by using large ensemble climate data set

    Grant number:17K08004  2017.04 - 2020.03

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)  Grant-in-Aid for Scientific Research (C)

    Kudo Ryoji

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    Grant amount:\4680000 ( Direct expense: \3600000 、 Indirect expense:\1080000 )

    This study addressed the uncertainty in climate change impact on drought risk caused by the natural variability which hydrological indices naturally have, using d4PDF, large-ensemble climate dataset. We used three indices for the assessment: 10-year drought discharges during puddling and heading periods for drought risk, and 10-year daily discharge for flood risk. To detect influence of the natural variability, we calculated 9,000 pattern change ratio of each index using 100 ensemble members for present climate and 90 ensemble members for future climate.
    The results show the large distribution of the change ratio for each index except 10-year drought discharge during puddling period in heavy snow region; this means that in the assessment on extreme events such as flood and drought, the assessment results may include both increasing and decreasing trends due to the natural variability, the uncertainty in climate change impact caused by natural variability are inevitable.

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Class subject in charge

  • SDGs:Meteorology and Hydrology (2024academic year) Third semester  - 月7~8

  • Career Education (2024academic year) 1st semester  - 水3~4

  • Meteorology and Hydrology (2024academic year) Third semester  - 月7~8

  • Water Use Design (2024academic year) Second semester  - 月5~6,水3~4

  • Flood disaster prevention (2024academic year) Prophase  - 月3~4

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Media Coverage

  • 田んぼダム 普及推進 水害防止 河川への流入抑制 倉敷市、面積22 年度7倍に 広域化が課題 Newspaper, magazine

    山陽新聞社  山陽新聞  2022.1.18

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    Author:Other 

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