Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model : case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019

• 資料種別: 記事
• タイトル: Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model : case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019
• 著者・編者: Takahiro Sayama; Masafumi Yamada; Yoshito Sugawara
• 出版事項: 日本 : Springer Nature
• 出版年月日等: 2020-12-10
• 出版年（W3CDTF）: 2020-12-10
• タイトル（掲載誌）: Progress in earth and planetary science
• 巻号年月日等（掲載誌）: 7(75)
• 掲載巻: 7(75)
• ISSN（掲載誌）: 2197-4284
• ISSN-L（掲載誌）: 2197-4284
• 本文の言語コード: eng
• DOI: 10.1186/s40645-020-00391-7; https://doi.org/10.1186/s40645-020-00391-7
• 国立国会図書館永続的識別子: info:ndljp/pid/11616317; https://dl.ndl.go.jp/pid/11616317
• コレクション（共通）: 障害者向け資料
• コレクション（障害者向け資料：レベル1）: テキストデータ
• コレクション（個別）: 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他; https://dl.ndl.go.jp/collections/B00035
• 収集根拠: オンライン資料収集制度
• 受理日（W3CDTF）: 2021-01-13T14:13:05+09:00
• 保存日（W3CDTF）: 2021-01-13
• 記録形式（IMT）: application/pdf
• オンライン閲覧公開範囲: 国立国会図書館内限定公開
• デジタル化資料送信: 図書館・個人送信対象外
• 遠隔複写可否（NDL）: 可
• 掲載誌（URI）: https://progearthplanetsci.springeropen.com/articles
• 掲載誌（国立国会図書館永続的識別子）: info:ndljp/pid/11467724; https://dl.ndl.go.jp/pid/11467724
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• 要約等: コレクション : 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他
• DOI: 10.1186/s40645-020-00391-7; https://doi.org/10.1186/s40645-020-00391-7; 10.21203/rs.3.rs-40714/v1; https://doi.org/10.21203/rs.3.rs-40714/v1; 10.21203/rs.3.rs-40714/v2; https://doi.org/10.21203/rs.3.rs-40714/v2
• オンライン閲覧公開範囲: インターネット公開
• 関連情報（URI）: http://id.ndl.go.jp/digimeta/11616317; https://dl.ndl.go.jp/pid/11616317; https://www.researchsquare.com/article/rs-40714/v1; https://www.researchsquare.com/article/rs-40714/v1.html; https://www.researchsquare.com/article/rs-40714/v2; https://www.researchsquare.com/article/rs-40714/v2.html; http://link.springer.com/content/pdf/10.1186/s40645-020-00391-7.pdf; http://link.springer.com/article/10.1186/s40645-020-00391-7/fulltext.html
• 参照: Identification of the spatio-temporal and fluvial-pluvial sources of flood inundation in the Lower Mekong Basin; https://cir.nii.ac.jp/crid/1050293246444066048; A new kinematic wave model that describes lateral subsurface flow and percolation in hillslopes; https://cir.nii.ac.jp/crid/1050302172855280768; Assimilating water level observations with the ensemble optimal interpolation scheme into a rainfall‐runoff‐inundation model: A repository‐based dynamic covariance matrix generation approach; https://cir.nii.ac.jp/crid/1050302315064416384; Ensemble rainfall–runof and inundation simulations using 100 and 1000 member rainfalls by 4D LETKF on the Kumagawa River fooding 2020; https://cir.nii.ac.jp/crid/1050576811655720320; Parameter regionalization of large-scale distributed rainfall-runoff models using a conditional probability method; https://cir.nii.ac.jp/crid/1050585407782333952; Assessment of Climate Change Impacts on River Flooding due to Typhoon Hagibis in 2019 Using Non‐Global Warming Experiments; https://cir.nii.ac.jp/crid/1050866882754465792; Specifications and Accuracy of Rainfall Forecast Required for Pre-Release at Multi-Purpose Reservoirs in Japan; https://cir.nii.ac.jp/crid/1360298757208041856; Evaluating the Influence of Topographic and Process Representation on Runoff and River Flow in Small‐Valley Scenarios Using a Coupled Rainfall–Runoff–Inundation and River‐Flow Model; https://cir.nii.ac.jp/crid/1360306904393667968; Contribution of Geography and Geospatial Technology to Cope with Hazards and Risks: Implications of GIS Development in Japan; https://cir.nii.ac.jp/crid/1360306906066583552; Developing Flood Risk Zones during an Extreme Rain Event from the Perspective of Social Insurance Management; https://cir.nii.ac.jp/crid/1360580232192477824; Applicability of a nationwide flood forecasting system for Typhoon Hagibis 2019; https://cir.nii.ac.jp/crid/1361981468853606656; 水系毎の警戒レベル4相当雨量を指標とした氾濫危険確率予測手法の提案; https://cir.nii.ac.jp/crid/1390009640053673088; 水害に強いまちづくりのための洪水ハザード予測とリスク評価; https://cir.nii.ac.jp/crid/1390015122299865856; SYNTHETIC EXPERIMENTS OF WATER LEVEL OBSERVATION ASSIMILATION INTO THE RRI MODEL WITH THE ENSEMBLE OPTIMAL INTERPOLATION SCHEME; https://cir.nii.ac.jp/crid/1390017843874914688; 「山地流出過程と地形発達過程の整合性を考える研究会」最終報告; https://cir.nii.ac.jp/crid/1390020984105886080; 琵琶湖水位と連動した統合水理モデルによる「地先の安全度」評価; https://cir.nii.ac.jp/crid/1390021846533961344; 日和佐川月輪地点における洪水予測の不確実性に関する研究; https://cir.nii.ac.jp/crid/1390021846533982208; Advances in Urban Stormwater Management in Japan: A Review; https://cir.nii.ac.jp/crid/1390287540630336256; 全国多目的ダムにおける気象庁MSM・GSMの事前放流への利用可能性; https://cir.nii.ac.jp/crid/1390291115021932288; 日本全域分布型水文モデルへの河道測量横断面反映手法の開発と水位再現性の検証; https://cir.nii.ac.jp/crid/1390291767694781184; 山地流出過程と地形発達過程の整合性を考える研究会 第1回・第2回オンライン研究会報告; https://cir.nii.ac.jp/crid/1390293568073487616; 流域治水対策評価に向けた谷津における流出解析精度に及ぼす格子解像度の影響分析 ～千葉県一宮川流域を例に～; https://cir.nii.ac.jp/crid/1390294883125332352; Grid-based parameter regionalization of distributed hydrologic models based on geospatial dataset for flash flood predictions in heterogeneous catchments in Japan; https://cir.nii.ac.jp/crid/1390301919372374400; 平面二次元氾濫解析に基づく車中死発生時の洪水氾濫・車両流失状況の検討; https://cir.nii.ac.jp/crid/1390572590015161856; 令和元年東日本台風荒川上流域の洪水氾濫状況への気候変動影響評価; https://cir.nii.ac.jp/crid/1390572590023269888; アンサンブル洪水予測情報の活用におけるユーザーとの双方向コミュニケーションの重要性; https://cir.nii.ac.jp/crid/1390573242522061056; 多段階浸水想定に向けたd4PDFに基づく流量表現手法の検討; https://cir.nii.ac.jp/crid/1390576358102084224; 気象災害の潜在性を示す情報の基礎的分析 ～情報の特徴分類と意識調査を通じて～; https://cir.nii.ac.jp/crid/1390576502655653248; 大アンサンブル気候予測情報を用いた水害リスク評価への超解像活用可能性; https://cir.nii.ac.jp/crid/1390588767007093376; 保険データを活用した全国版RRIモデルの検証と浸水推定精度の向上; https://cir.nii.ac.jp/crid/1390588767007101568; 水分保持曲線を反映する流量流積関係式の導出と分布型流出モデルへの適用; https://cir.nii.ac.jp/crid/1390853423037051136; グローバル河川氾濫モデル出力の日本国内ハザードマップとしての利用可能性の検証; https://cir.nii.ac.jp/crid/1390855656045353728; REGIONALIZATION OF A HIGH-RESOLUTION DISTRIBUTED RAINFALL-RUNOFF MODEL TO FORECAST FLASH FLOOD IN UNGAUGED URBAN CATCHMENTS; https://cir.nii.ac.jp/crid/1390857833078760576; 広域降雨流出氾濫モデルによる浸水分布の推定 - 地形補正の効果検証 -; https://cir.nii.ac.jp/crid/1390857833078803456; Advanced Impact-Based Forecast for a Severe Flood Event Using a 1000-member Ensemble Weather Prediction at Convective-Scale; https://cir.nii.ac.jp/crid/1390868527321921408
• 参照: Hydrologic sensitivity of flood runoff and inundation: 2011 Thailand floods in the Chao Phraya River basin; https://cir.nii.ac.jp/crid/1050001335818767232; Meteorological overview and mesoscale characteristics of the Heavy Rain Event of July 2018 in Japan; https://cir.nii.ac.jp/crid/1360004231312899840; Ensemble flood forecasting considering dominant runoff processes – Part 1: Set-up and application to nested basins (Emme, Switzerland); https://cir.nii.ac.jp/crid/1360011143631394304; A review of advances in flash flood forecasting; https://cir.nii.ac.jp/crid/1360011144234654464; The Science of NOAA's Operational Hydrologic Ensemble Forecast Service; https://cir.nii.ac.jp/crid/1360011145698472832; Analytical results for operational flash flood guidance; https://cir.nii.ac.jp/crid/1360011146326734464; Evaluation of two hydrometeorological ensemble strategies for flash-flood forecasting over a catchment of the eastern Pyrenees; https://cir.nii.ac.jp/crid/1360292618762479616; The role of subsurface runoff through bedrock on storm flow generation; https://cir.nii.ac.jp/crid/1360292620521338112; Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin; https://cir.nii.ac.jp/crid/1360565167189429888; Evaluation of ensemble streamflow predictions in Europe; https://cir.nii.ac.jp/crid/1360574093651535232; Assessing the impact of resolution and soil datasets on flash-flood modelling; https://cir.nii.ac.jp/crid/1360574094770057088; Coevolution of volcanic catchments in Japan; https://cir.nii.ac.jp/crid/1360574095263060480; Numerical Simulation of 2010 Pakistan Flood in the Kabul River Basin by Using Lagged Ensemble Rainfall Forecasting; https://cir.nii.ac.jp/crid/1360848661489512960; Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States; https://cir.nii.ac.jp/crid/1360855568960344192; Runoff generation mechanisms in high-relief mountainous watersheds with different underlying geology; https://cir.nii.ac.jp/crid/1360855569002964608; Evaluating flash-flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system; https://cir.nii.ac.jp/crid/1361137044202408704; Operational use of a grid-based model for flood forecasting; https://cir.nii.ac.jp/crid/1361137045443161600; The European Flood Alert System – Part 1: Concept and development; https://cir.nii.ac.jp/crid/1361418519590083968; Toward Probabilistic Prediction of Flash Flood Human Impacts; https://cir.nii.ac.jp/crid/1361418519873133312; CONUS-Wide Evaluation of National Weather Service Flash Flood Guidance Products; https://cir.nii.ac.jp/crid/1361418520562370304; A European precipitation index for extreme rain‐storm and flash flood early warning; https://cir.nii.ac.jp/crid/1361699994599759104; Continental and global scale flood forecasting systems; https://cir.nii.ac.jp/crid/1361699994986547200; Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling; https://cir.nii.ac.jp/crid/1362262945014461184; The FLASH Project: Improving the Tools for Flash Flood Monitoring and Prediction across the United States; https://cir.nii.ac.jp/crid/1362544418913888512; Ensemble forecasting of typhoon rainfall and floods over a mountainous watershed in Taiwan; https://cir.nii.ac.jp/crid/1362544419652022400; The european flood alert system EFAS – Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts; https://cir.nii.ac.jp/crid/1362544420497496576; Modeling flash floods in southern France for road management purposes; https://cir.nii.ac.jp/crid/1362544421002156928; Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 2. Streamflow verification; https://cir.nii.ac.jp/crid/1362825894747118592; Flood mapping in ungauged basins using fully continuous hydrologic–hydraulic modeling; https://cir.nii.ac.jp/crid/1362825895079525376; A distributed hydrologic model and threshold frequency-based method for flash flood forecasting at ungauged locations; https://cir.nii.ac.jp/crid/1363107368791673728; Setting up a French national flash flood warning system for ungauged catchments based on the AIGA method; https://cir.nii.ac.jp/crid/1363107369294395520; An emergency response‐type rainfall‐runoff‐inundation simulation for 2011 Thailand floods; https://cir.nii.ac.jp/crid/1363670318923883264; Towards operational joint river flow and precipitation ensemble verification: considerations and strategies given limited ensemble records; https://cir.nii.ac.jp/crid/1363670318947608064; A dynamic runoff co-efficient to improve flash flood early warning in Europe: evaluation on the 2013 central European floods in Germany; https://cir.nii.ac.jp/crid/1363670320259858304; Integrated high-resolution dataset of high-intensity European and Mediterranean flash floods; https://cir.nii.ac.jp/crid/1363670321146352640; On the Design of National, Real-Time Warning Systems with Capability for Site-Specific, Flash-Flood Forecasts; https://cir.nii.ac.jp/crid/1363951793668734464; Flash flood forecasting: What are the limits of predictability?; https://cir.nii.ac.jp/crid/1363951796055909760; Ensemble hydro-meteorological simulation for flash flood early detection in southern Switzerland; https://cir.nii.ac.jp/crid/1364233268585437184; Ensemble flood forecasting: A review; https://cir.nii.ac.jp/crid/1364233271194618752; 分布型流出モデルと時空間起源追跡法による鬼怒川洪水の流出解析; https://cir.nii.ac.jp/crid/1390001204440633856; 格子状擬河道網のスケール変換に関する新しい方法; https://cir.nii.ac.jp/crid/1390001204440791552; Influence of the Track Forecast of Typhoon Prapiroon on the Heavy Rainfall in Western Japan in July 2018; https://cir.nii.ac.jp/crid/1390001277398025600; Environmental Factors for the Development of Heavy Rainfall in the Eastern Part of Japan during Typhoon Hagibis (2019); https://cir.nii.ac.jp/crid/1390002184876872704; 日本全域高解像度の表面流向データ整備; https://cir.nii.ac.jp/crid/1390003825206799872; 日本の山地河川の流況に及ぼす流域の地質の効果; https://cir.nii.ac.jp/crid/1390282679972972800; Toward flood risk prediction: a statistical approach using a 29-year river 37 discharge simulation over Japan; https://cir.nii.ac.jp/crid/1390282680265972480; Predictability of Record-Breaking Rainfall in Japan in July 2018: Ensemble Forecast Experiments with the Near-Real-Time Global Atmospheric Data Assimilation System NEXRA; https://cir.nii.ac.jp/crid/1390282763094830080; Assessing the Predictability of Heavy Rainfall Events in Japan in Early July 2018 on Medium-Range Timescales; https://cir.nii.ac.jp/crid/1390282763125923840
• 連携機関・データベース: 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• 提供元機関・データベース: 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org; 科学研究費助成事業データベース; https://kaken.nii.ac.jp/ja
• 書誌ID（NDLBibID）: 11616317; http://id.ndl.go.jp/bib/11616317