利用综合建模方法估算未经测量的小型集水区的极端暴雨径流量

Ziyong Zhao , Mohamad Reza Salehi Sadaghiani , Wenyu Yang , Pei Hua , Jin Zhang , Peter Krebs
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引用次数: 0

摘要

水文建模通常需要长期稳定的径流数据。由于水文站的限制,小尺度流域的水文建模面临着数据匮乏的挑战。为了克服水文数据不完整的挑战,我们在德国莱乌特拉河上游伊瑟施泰特的一个小规模集水区采用了一种综合建模方法,其中包括半分布式水文模型和水动力数值模型。结果表明,这种综合建模方法有效地利用了每个模型的优势,合理地预测了峰值流量。作为区域径流管理的一项措施,龙骨法有助于获得更稳定的水文图和更低的峰值流量,并在蓄水和调节当地气候方面发挥作用。本研究提出的框架对暴雨极端径流中的关键暴雨、水文图和洪水范围提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Estimating storm runoff extreme in small ungauged catchments using an integrated modeling approach

Estimating storm runoff extreme in small ungauged catchments using an integrated modeling approach

Hydrological modeling often requires long-term and stable runoff data. Due to limitations in hydrological stations, hydrological modeling in small-scale catchments faces the challenge of data scarcity. To overcome the challenge of incomplete hydrological data, an integrated modeling approach that includes a semi-distributed hydrological and a hydrodynamic numerical model was employed in a small-scale catchment located in Isserstedt, upstream of the Leutra River, Germany. The results indicated that this integrated modeling approach effectively leverages the strengths of each model and reasonably predicted peak flows. As a measure for regional runoff management, keyline method contributed to more stable hydrographs and lower peak flows, and played a role in water storage and local climate regulation. The framework proposed in this study provided valuable insights into critical storms, hydrographs, and flood extent in storm runoff extremes.

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