A framework for modelling groundwater floods and its applications for forecasting and assessing the impact of climate change in groundwater systems: examples from Ireland

Climate change will have a major impact on Ireland’s water resources. It will pose significant risks to water management and exacerbate existing pressures in terms of water supply, quality, flooding and drought. Early detection of these pressures in hydrological regimes is key to informing adaptation strategies and minimizing adverse environmental and societal impacts. In response to this risk, a framework was developed to enable short-term forecasting of groundwater levels, and to quantify and analyse the impact that climate change will have on Irish groundwater systems.

A key element of the framework is the use of robust hydrological models to simulate groundwater levels. The framework was developed in Python, with a particular focus on groundwater flooding, and incorporates two modelling approaches: 1) mathematical transfer functions (combination of exponential decay, gamma distribution, and linear decay functions), and 2) a physically based lumped model (reservoir model). For both modelling approaches, precipitation data is converted to effective rainfall based on soil moisture deficit and evapotranspiration data, and the model parameters are calibrated using a Bayesian Markov Chain Monte Carlo algorithm.

The framework was tested and implemented with synthetically generated groundwater level time series, and with a selection of 12 groundwater dependent wetlands covering a wide range of hydrological behaviours. The tested approaches have proof successful to: 1) produce viable numerical models for those systems, with Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) values between 0.85 and 0.98 for most of the sites calibration and validation datasets, and 2) inform on how the groundwater systems operate (i.e. multiple outflows, changes in catchment area). The models are now used for forecasting groundwater levels and assessing the potential impact of climate change in ecologically important wetlands.

The outputs of this project will improve the national ability to understand how groundwater resources respond to climatic stresses and improve the reliability of adaptation planning and predictions in the groundwater sector.