Preprints
https://doi.org/10.5194/egusphere-2022-452
https://doi.org/10.5194/egusphere-2022-452
 
04 Jul 2022
04 Jul 2022

Technical note: Improving the Initial Conditions of Hydrological Model with Reanalysis Soil Moisture Data

Lingxue Liu1,, Tianqi Ao1,2,, and Li Zhou2 Lingxue Liu et al.
  • 1Institute for Disaster Management and Reconstruction, Sichuan University-Hong Kong Polytechnic University, Chengdu 610065, China
  • 2State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, No.24 South Section 1, Yihuan Road, Chengdu 610065, China
  • These authors contributed equally to this work.

Abstract. The initial conditions (e.g., soil moisture content) of the hydrological model, which is usually obtained from the warm-up of the hydrological modeling, significantly impact the simulation efficiency. However, spending the valuable data in warm-up instead of calibration and validation is luxurious. In order to improve hydrological simulation efficiency in the case of no warm-up phase, this paper proposes a methodology to fill the gap via improving the initial conditions of the hydrological model using an alternative global soil moisture dataset. Specifically, three soil moisture (SM) variables of the initial conditions from the Block-wise use of the TOPMODEL (BTOP) model and ERA5-Land reanalysis data were adopted and conducted correlation analysis. Several traditional curve-fitting functions and the state-of-art technical, long-short term memory (LSTM), were applied to develop the relationship between BTOP and ERA5-Land SM variables in the Fuji and Shinano River Basin, Japan. Furthermore, four configured hydrological simulations evaluated the benefits of the proposed methodology for improving the initial conditions. As a result, LSTM outperforms the traditional curve-fitting method in constructing the relationship between variables in time and space. Moreover, the hydrological simulation cases using the initial conditions related to the SM from the ERA5-land performs better than the case without the warm-up phase, and the simulated discharge process approaches the "optimal" case with the warm-up phase. It is confirmed that the proposed methodology helps improve the initial conditions of the hydrological model using reanalysis soil moisture data.

Lingxue Liu et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-452', Anonymous Referee #1, 13 Sep 2022
  • RC2: 'Comment on egusphere-2022-452', Anonymous Referee #2, 11 Oct 2022
  • RC3: 'Comment on egusphere-2022-452', Anonymous Referee #3, 27 Oct 2022

Lingxue Liu et al.

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Short summary
Soil moisture (SM) initial conditions of the hydrological model, usually obtained from the model warm-up, significantly impact the simulation efficiency. In the case of no warm-up phase, this paper proposes a methodology to fill the gap via obtaining the SM initial conditions using an alternative global dataset. It validates that warm-up is necessary for the model calibration with default initial conditions, and well-utilization of the processed ERA5-Land could skip warm-up effectively.