Flood Forecasting via the Ensemble Kalman Filter Method Using Merged Satellite and Measured Soil Moisture Data

Flood Forecasting via the Ensemble Kalman Filter Method Using Merged Satellite and Measured Soil Moisture Data

Flood monitoring in the Chaohe River Basin is crucial for the timely and accurate forecasting of flood flow. Hydrological models used for the simulation of hydrological processes are affected by soil moisture (SM) data and uncertain model parameters. Hence, in this study, measured satellite-based SM...

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Bibliographic Details
Main Authors: Chen Zhang, Siyu Cai, Juxiu Tong, Weihong Liao, Pingping Zhang
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Water
Subjects:
ensemble Kalman filter
merged soil moisture
multi-source data assimilation
flood forecast
Online Access:https://www.mdpi.com/2073-4441/14/10/1555

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