A Runoff-On-Grid Approach to Embed Hydrological Processes in Shallow Water Models

IF 4.6 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Pasquale Perrini, Luis Cea, Francesco Chiaravalloti, Salvatore Gabriele, Salvatore Manfreda, Mauro Fiorentino, Andrea Gioia, Vito Iacobellis
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引用次数: 0

Abstract

Catchment-scale hydrological models encountered dichotomies with the numerical hydrodynamic models when describing surface routing process. We propose a new modeling framework, the so-called “Runoff-On-Grid” approach, for embedding distributed process-based hydrological modeling into shallow water models, as an alternative to the traditional Fully Hydrodynamic Approach (also known as Rain-On-Grid). Antecedent Soil Moisture, subsurface dynamics, and other topsoil hydrological processes are implicitly integrated in the governing hydrodynamic equations via the proposed methodology. The resulting hydrological-hydrodynamic coupling, based on the DREAM distributed hydrological model and the Iber+ shallow water model, enhances the capabilities of both reference models. Through introducing non-negligible runoff generation sources, the Runoff-On-Grid approach extends the surface hydrodynamic modeling to medium-sized vegetated and/or (semi)humid catchments, bypassing the limitations of the widespread hydrological losses' empirical formulations. Employed in an event-based analysis within a High-Performance Computing framework, the DREAM-Iber model provides an efficient and reliable reconstruction of the November 2020 flood that occurred in Crotone (Italy), envisaging consequences of similar future scenarios. We show that the proposed modeling technique, nested within emerging environmental technologies and robust on-site data, details the flood hazard inducing processes merging physical hydrology with advanced hydrodynamics.
将水文过程嵌入浅水模型的网格径流法
在描述地表溃决过程时,流域尺度水文模型与数值水动力模型之间存在对立。我们提出了一种新的建模框架,即所谓的 "Runoff-On-Grid "方法,用于将基于过程的分布式水文模型嵌入浅水模型,以替代传统的完全水动力方法(也称为 "Rain-On-Grid")。通过所提出的方法,前兆土壤水分、地下动力学和其他表土水文过程被隐含地集成到水动力方程中。基于 DREAM 分布式水文模型和 Iber+ 浅水模型的水文-水动力耦合增强了这两个参考模型的能力。通过引入不可忽略的径流产生源,Runoff-On-Grid 方法将地表水动力模型扩展到中型植被和/或(半)湿润集水区,绕过了广泛的水文损失经验公式的限制。在高性能计算框架内进行的基于事件的分析中,DREAM-Iber 模型对 2020 年 11 月发生在意大利克罗托内的洪水进行了高效可靠的重建,并设想了未来类似情况的后果。我们的研究表明,所提议的建模技术嵌套于新兴环境技术和可靠的现场数据中,详细描述了物理水文学与先进流体力学相结合的洪水灾害诱发过程。
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来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
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