Pulse Brain · Growing Health Evidence Index
Peer-reviewed

Flood Simulations Using a Sensor Network and Support Vector Machine Model

Jakub Langhammer

Water · 2023

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Summary

This study aims to couple the support vector machine (SVM) model with a hydrometeorological wireless sensor network to simulate different types of flood events in a montane basin. The model was tested in the mid-latitude montane basin of Vydra in the Šumava Mountains, Central Europe, featuring complex physiography, high dynamics of hydrometeorological processes, and the occurrence of different types of floods. The basin is equipped with a sensor network operating in headwaters along with the conventional long-term monitoring in the outlet. The model was trained and validated using hydrological observations from 2011 to 2021, and performance was assessed using metrics such as R2, NSE, KGE, and RMSE. The model was run using both hourly and daily timesteps to evaluate the effect of timestep a

Source type
Peer-reviewed study
DOI
10.3390/w15112004
Catalogue ID
SNmokyl7if-om2x61
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