Accounting for groundwater abstraction and its uncertainties in hydrological models

Groundwater sustains human water use globally, as it provides about a quarter and half of the total water withdrawn for irrigation and domestic purposes, respectively. Intense groundwater pumping has an impact both under- and above-ground, by lowering the water table and reducing streamflow in surrounding rivers. However, groundwater abstraction is often neglected in hydrological models because of the large uncertainties involved. These modelling uncertainties arise from the lack of data to constrain natural processes (including groundwater recharge and discharge, intercatchment groundwater flow) and anthropogenic processes (abstraction rates and their spatiotemporal patterns). Therefore, there is a need to represent groundwater abstraction in hydrological models, to consider its uncertainties, and to determine the appropriate level of complexity in process representation given data availability.

This study examines the uncertainties in groundwater abstraction for streamflow predictions over a sample of catchments in France. To this end, we use a parsimonious lumped hydrological model at the daily time step (GR6J), which represents groundwater storage through an exponential store (Michel et al, 2003). Groundwater abstraction is modelled by taking water from this exponential reservoir. We account for the uncertainties in both the water withdrawal input data and the hydrological model parameters (that describe the natural processes). We adopt annual abstraction data from the French national dataset (BNPE), that we temporally disaggregate using different assumptions. Regarding the model parameters, we select an ensemble of parameter sets that produce simulations that are consistent with the observations (streamflow, groundwater levels). Our results reveal that, beyond streamflow observations, piezometric data help to reduce the uncertainty in the parameters such as the capacity of the exponential store. Overall, our study shows the importance of accounting for groundwater abstraction and its uncertainties for streamflow predictions.

Michel, C., Perrin, C. & Andréassian, V., 2003. The exponential store: a correct formulation for rainfall-runoff modelling. Hydrological Sciences Journal, 48(1): 109-124, https://dx.doi.org/10.1623/hysj.48.1.109.43484