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The potential of a quasi-2D model for rapid flood modelling as a planning tool for nature-based solutions

急速な洪水モデリングのための準2次元モデルの可能性：自然に基づく解決策の計画ツールとして (AI 翻訳)

Leng-Hsuan Tseng, Zoran Vojinović, Meng-Hsuan Wu, Yared Abayneh Abebe, Dong-Jiing Doong, Wei‐Cheng Lo, Laddaporn Ruangpan, Slobodan Djordjević

Blue-Green Systems📚 査読済 / ジャーナル2026-07-04#気候リスクOrigin: Global
DOI: 10.2166/bgs.2026.139
原典: https://doi.org/10.2166/bgs.2026.139

🤖 gxceed AI 要約

日本語

この論文は、準2次元洪水モデル（PHDモデル）が、自然に基づく解決策（NBS）の評価のための計画ツールとして有効であることを示している。MIKE FLOODとの比較で、精度は高く（水深誤差0.12m）、計算時間は約3分の1である。

English

This paper demonstrates the potential of a quasi-2D flood model (PHD) as a planning tool for nature-based solutions (NBS) assessment, achieving comparable accuracy to MIKE FLOOD with about three times less computational time.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本では洪水頻発とNBS導入が進んでおり、本モデルは低コストで流域スケールのリスク評価を可能にする点で有用である。

In the global GX context

Globally, nature-based solutions are increasingly recognized for flood risk reduction; this model offers a computationally efficient tool for large-scale NBS planning.

👥 読者別の含意

🔬研究者:This paper provides a validation of a quasi-2D model for NBS assessment, useful for further methodological development.

🏢実務担当者:Planners can use the PHD model for rapid catchment-scale flood modeling to evaluate nature-based solutions with limited computational resources.

🏛政策担当者:The model supports integration of NBS into flood risk management by enabling scenario analysis without heavy computational demands.

📄 Abstract（原文）

ABSTRACT Flooding causes increasing social, economic, and environmental losses, driving demand for flood risk assessment tools that can handle catchment-scale modelling with limited computational resources, a key requirement for evaluating nature-based solutions (NBS) across multiple scenarios. This paper examines the potential of the PHysiographic drainage-inundation (PHD) model, a quasi-2D flood model using physically-based flow formulas (Manning's equation and weir flow) with irregular computational cells, as a practical planning tool for catchment-scale flood modelling and large-scale NBS assessment. The PHD model is benchmarked against the 1D–2D hydrodynamic model MIKE FLOOD on the Sint Maarten case study using 100-year and 20-year design rainfall events, comparing flood extent, water depth, discharge hydrographs, flood risk, and computational time. The PHD model produces results comparable to MIKE FLOOD, a critical success index of 77% and root mean square error in water depth of 0.12 m, while requiring approximately three times less computational time. These findings confirm the PHD model's strong potential as a rapid, accurate planning tool suitable for NBS assessment and real-time operations.

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