Preprints
https://doi.org/10.5194/gmd-2024-211
https://doi.org/10.5194/gmd-2024-211
Submitted as: model description paper
 | 
19 Nov 2024
Submitted as: model description paper |  | 19 Nov 2024
Status: this preprint is currently under review for the journal GMD.

DECIPHeR-GW v1: A coupled hydrological model with improved representation of surface-groundwater interactions

Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris Wendt

Abstract. Groundwater is a crucial part of the hydrologic cycle and the largest accessible freshwater source for humans and ecosystems. However, most hydrological models lack explicit representation of surface-groundwater interactions, leading to poor prediction performance in groundwater-dominated catchments. This study presents DECIPHeR-GW v1, a new surface-groundwater hydrological model that couples a Hydrological Response Units (HRU)-based hydrological model and a two-dimensional gridded groundwater model. By using a two-way coupling method, the groundwater model component receives recharge from HRUs, simulates surface-groundwater interactions, and returns groundwater levels and groundwater discharges to HRUs, where river routing is then performed. These interactions are happening at each time step in our new surface-groundwater model. Depending on the storage capacity of the surface water model component and the position of the modelled groundwater level, three scenarios are developed to derive recharge and capture surface-groundwater interactions dynamically. Our new coupled model was calibrated and evaluated against daily flow timeseries from 669 catchments and groundwater level data from 1804 wells across England and Wales. The model provides streamflow simulation with a median KGE of 0.83 across various catchment characteristics, with high performance particularly for the drier chalk catchments in southeast England, where the average KGE increased from 0.49 in the benchmark DECIPHeR model to 0.7. Furthermore, our model reproduces temporal patterns of the groundwater level timeseries, with more than half of the wells achieving a Spearman correlation coefficient of 0.6 or higher when comparing simulations to observations. Overall, this new DECIPHeR-GW model demonstrates remarkable accuracy and computational efficiency in reproducing streamflow and groundwater levels, making it a valuable tool for addressing water resources and management issues over large domains.

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Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris Wendt

Status: open (until 14 Jan 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris Wendt

Data sets

DECIPHeR-GW v1: A coupled hydrological model with improved representation of surface-groundwater interactions Yanchen Zheng https://data.bris.ac.uk/data/dataset/wt0r1ec81zti2tww4p64fsqr3

Model code and software

DECIPHeR-GW Yanchen Zheng https://zenodo.org/records/14113870

Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris Wendt

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Short summary
Groundwater is vital for people and ecosystems, but most physical models lack surface-groundwater interactions representation, leading to inaccurate streamflow predictions in groundwater-rich areas. This study presents DECIPHeR-GW v1, which links surface and groundwater systems to improve predictions of streamflow and groundwater levels. Tested across England and Wales, DECIPHeR-GW shows high accuracy, especially in south east England, making it a valuable tool for large-scale water management.