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Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin

机译:评估捕获亚马逊盆地峰河流的全球水文模型的表现

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摘要

Extreme flooding impacts millions of people that live within the Amazon floodplain. Global hydrological models (GHMs) are frequently used to assess and inform the management of flood risk, but knowledge on the skill of available models is required to inform their use and development. This paper presents an intercomparison of eight different GHMs freely available from collaborators of the Global Flood Partnership (GFP) for simulating floods in the Amazon basin. To gain insight into the strengths and shortcomings of each model, we assess their ability to reproduce daily and annual peak river flows against gauged observations at 75 hydrological stations over a 19-year period (1997-2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) ground-water and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems.
机译:极端洪水影响着数百万人住在亚马逊洪泛区。全球水文模型(GHM)经常用于评估和告知洪水风险的管理,但需要了解可用模型技能的知识,以告知其使用和开发。本文从全球洪水合作伙伴关系(GFP)的合作者自由地提供了八种不同的GHM,用于模拟亚马逊盆地的洪水。要深入了解每个模型的优势和缺点,我们评估了他们在19年期间的75个水文站(1997-2015)的75个水文站中繁殖每日和年峰河流流量的能力。除了突出显示模拟流流的准确性的区域可变性,这些结果表明,(a)气象投入是对日常和年度最大河流的准确性的主导控制,(B)地下水和路由校准基于日常河流流动的Lisflood对所选河流盆地模拟洪水峰的能力没有影响。这些调查结果对大规模水文模型的应用具有重要相关性,包括分析气候变异性的影响,对土地利用和人为气候变化等长期变化的影响,对洪水可能性的评估以及洪水可能性的影响洪水预测系统。

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