Investigating the impact of surface soil moisture assimilation on state and parameter estimation in SWAT model based on the ensemble Kalman filter in upper Huai River basin

Title:

Investigating the impact of surface soil moisture assimilation on state and parameter estimation in SWAT model based on the ensemble Kalman filter in upper Huai River basin

Creator:

Liu, Yongwei, Wang, Wen, and Hu, Yiming

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:1efe44b6-f1bb-4b72-9079-58f5f701b942
uuid:1efe44b6-f1bb-4b72-9079-58f5f701b942
doi:10.1515/johh-2017-0011

Subject:

soil moisture, EnKF, SWAT, and ESA CCI SM

Type:

article, model:article, and TEXT

Description:

This paper investigates the impact of surface soil moisture assimilation on the estimation of both parameters and states in the Soil and Water Assessment Tool (SWAT) model using the ensemble Kalman filter (EnKF) method in upper Huai River basin. The investigation is carried out through a series of synthetic experiments and real world tests using a merged soil moisture product (ESA CCI SM) developed by the European Space Agency, and considers both the joint state-parameter updating and only state updating schemes. The synthetic experiments show that with joint stateparameter update, the estimation of model parameter SOL_AWC (the available soil water capacity) and model states (the soil moisture in different depths) can be significantly improved by assimilating the surface soil moisture. Meanwhile, the runoff modeling for the whole catchment is also improved. With only state update, the improvement on runoff modeling shows less significance and robustness. Consistent with the synthetic experiments, the assimilation of the ESA CCI SM with joint state-parameter update shows considerable capability in the estimation of SOL_AWC. Both the joint stateparameter update and the only state update scheme could improve the streamflow modeling although the optimal model and observation error parameters for them are quite different. However, due to the high vegetation coverage of the study basin, and the strong spatial mismatch between the satellite and the model simulated soil moisture, it is still challenging to significantly benefit the runoff estimates by assimilating the ESA CCI SM.

Language:

Slovak

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Journal of hydrology and hydromechanics | 2017 Volume:65 | Number:2

Harvested from:

CDK

Metadata only:

false