Merging Real-Time Channel Sensor Networks with Continental-Scale Hydrologic Models: A Data Assimilation Approach for Improving Accuracy in Flood Depth Predictions

Merging Real-Time Channel Sensor Networks with Continental-Scale Hydrologic Models: A Data Assimilation Approach for Improving Accuracy in Flood Depth Predictions

This study proposes a framework that (i) uses data assimilation as a post processing technique to increase the accuracy of water depth prediction, (ii) updates streamflow generated by the National Water Model (NWM), and (iii) proposes a scope for updating the initial condition of continental-scale h...

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Bibliographic Details
Main Authors: Amir Javaheri, Mohammad Nabatian, Ehsan Omranian, Meghna Babbar-Sebens, Seong Jin Noh
Format: Article
Language:English
Published: MDPI AG 2018-01-01
Series:Hydrology
Subjects:
data assimilation
ensemble Kalman filter
flood inundation maps
National Water Model (NWM)
Online Access:http://www.mdpi.com/2306-5338/5/1/9

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