EGU23-15276
https://doi.org/10.5194/egusphere-egu23-15276
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Developing an operational model to support groundwater management decision-making in the UK

Doris Wendt1, Gemma Coxon2, and Francesca Pianosi1
Doris Wendt et al.
  • 1University of Bristol, Department of Civil Engineering, Bristol, United Kingdom of Great Britain – England, Scotland, Wales
  • 2University of Bristol, Geographical Sciences, Bristol, United Kingdom of Great Britain – England, Scotland, Wales

Decision-making in groundwater management could benefit from a robust modelling approach that considers the complexity and uncertainty in water availability, dynamic impact of management and modelling setups available. Modelling groundwater is a complex matter on its own given the heterogeneous aquifers, delayed climate signal in groundwater recharge and dynamic influence of water abstractions. Due to this complexity, decision-making models are often simplified to address only the main impacts on the hydrological cycle. Whilst this simplification is necessary, it is important to examine model process controls and uncertainty in parameters of a simplified model setup. 

In this study, we have converted a lumped conceptual socio-hydrological model to an operational tool for supporting decision-making by (1) evaluating and (2) calibrating the model. First, we applied global sensitivity to examine the “consistency” and “leverage” of the model. A model is considered consistent when modelled process controls match our system understanding. Leverage is observed when modelled strategies have adequate influence on modelling output regardless of parameter uncertainty. Results show that even with large uncertainty in parameter values, consistency is achieved for all hydrological variables. Input parameters defining management strategies are found to have significant leverage, as varying them induce noticeable changes in simulation outputs regardless of the physical conditions or uncertainty in parameters. When looking at hydrological extremes, this impact was amplified. 

Second, the model was calibrated for a range of catchments in the UK. The eleven model parameters were constrained using statistical criteria to identify an optimum parameter range. Model outputs were compared to observations (discharge and groundwater level time series using both similarity and signature-based evaluation criteria. Additionally, we sourced open access UK datasets to validate our data-based parameter ranges with local information. In general, calibrated model outputs represent surface water and groundwater features well and in particular, baseflow generation is well-represented. This encourages model applications for examining regional/national policies aiming to protect groundwater-fed streams. Exploratory model runs can also be used to facilitate discussions on new/altered management strategies and may spark further detailed modelling once a suitable strategy is identified. 

How to cite: Wendt, D., Coxon, G., and Pianosi, F.: Developing an operational model to support groundwater management decision-making in the UK, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15276, https://doi.org/10.5194/egusphere-egu23-15276, 2023.