Application of Global Environmental Multiscale (GEM) Numerical Weather Prediction (NWP) Model for Hydrological Modeling in Mountainous Environment

• Published in: Atmosphere Vol. 13; no. 9; p. 1348
• Main Author: Gilewski, Paweł
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2022
• Subjects: Antecedent moisture; Atmospheric chemistry; Catchments; Climate change; Climatic extremes; Drought; Environment models; Flooding; Floods; Gauges; Global Environmental Multiscale model; HEC-HMS; Hydrologic data; Hydrologic models; Hydrology; Investigations; Literature reviews; Mathematical models; Modelling; Moisture effects; mountainous catchment; Numerical prediction; Numerical weather forecasting; numerical weather prediction; Outflow; Precipitation; Prediction models; Predictions; Rain; Rain gauges; Rainfall; Rainfall data; Rainfall runoff; Rainfall-runoff modeling; Rainfall-runoff relationships; Response time; Runoff; Watersheds; Weather forecasting; Poland; Europe
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos13091348

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.