环境科学
降水
气象学
气候学
数值天气预报
洪水(心理学)
地表径流
水文模型
气候模式
气候变化
地质学
地理
心理学
生态学
海洋学
心理治疗师
生物
出处
期刊:Atmosphere
[Multidisciplinary Digital Publishing Institute]
日期:2022-08-24
卷期号:13 (9): 1348-1348
被引量:7
标识
DOI:10.3390/atmos13091348
摘要
As the world is changing, mainly due to climate change, extreme events such as floods and droughts are becoming more frequent and severe. Considering this, the predictive modeling of flow in small mountain catchments that are particularly vulnerable to flooding is critical. Rainfall data sources such as rain gauges, meteorological radars, and satellites provide data to the hydrological model with a lag. Only numerical weather predictions can achieve this in advance, but their estimates are often subject to considerable uncertainty. This article aims to verify whether Global Environmental Multiscale numerical precipitation prediction can be successfully applied for event-based rainfall–runoff hydrological modeling. These data were verified for use in two aspects: the flow modeling and determination of antecedent moisture conditions. The results indicate that GEM data can be satisfactorily used for hydrological modeling, and particularly good simulation results are obtained when significant rainfall occurs. In addition, these data can be used to correctly estimate the AMC groups for each sub-catchment in advance, which is one of the key elements flowing into the amount of projected outflow in the catchment. It is worth noting that, according to the literature review conducted by the article’s author, this is the first published attempt to use GEM data directly in applied hydrological applications.
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