A coupled SWATPlus and BiLSTM tuning model for improved daily scale hydroclimate simulation in typical loess hilly areas of China

Xianqi Zhang (), Jiawen Liu (), He Ren (), Yang Yang () and Jie Zhu ()
Additional contact information
Xianqi Zhang: North China University of Water Resources and Electric Power
Jiawen Liu: North China University of Water Resources and Electric Power
He Ren: North China University of Water Resources and Electric Power
Yang Yang: North China University of Water Resources and Electric Power
Jie Zhu: North China University of Water Resources and Electric Power

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 1, No 3, 81 pages

Abstract: Abstract Global climate change and land use alterations are contributing to more frequent and severe extreme events globally. This trend is especially pronounced in the Loess Plateau's hilly regions of China. In order to more accurately simulate runoff, especially peak flows, to enhance the planning and management of water resources in China's loess hilly areas, as well as to mitigate the impacts of global climate change, we propose a novel hydrologic model. The model employs an integrated approach by combining the Soil and Water Assessment Tool (SWATPlus), a process-based conceptual hydrological model, with a deep learning model known as the Bi-Directional Long Short-Term Memory (BiLSTM). Our primary objective is to enhance runoff simulation performance in the Zuli River Basin (ZRB), a key tributary of the upper Yellow River. We designed two coupled models, SWATPlus-BiLSTM-D and SWATPlus-BiLSTM-T. In SWATPlus-BiLSTM-D, all influential parameters of SWATPlus were kept at their default values; while in SWATPlus-BiLSTM-T, we calibrated multiple SWATPlus parameters. By comparing the daily runoff simulation results, we find that SWATPlus-BiLSTM-T consistently outperforms SWATPlus-BiLSTM-D, the stand-alone SWATPlus, and the BiLSTM model throughout the simulation period. Of particular note, SWATPlus-BiLSTM-T significantly outperforms the other three models in the simulation of daily peak flows. In the testing process, the error values of SWATPlus-BiLSTM-T reached relatively excellent levels, with an NSE of 0.88, an R2 of about 0.9, and an RMSE of 2.63 m3/s. The assessment and management of hydrological and environmental conditions in river basins can be significantly optimized through the development of such model tuning methods.

Keywords: Coupled modeling; SWATPlus; BiLSTM; Hydroclimatic simulation; ZRB (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-024-06840-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:121:y:2025:i:1:d:10.1007_s11069-024-06840-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-024-06840-6

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().