The influence of model structure on groundwater recharge rates in climate-change impact studies

Moeck, Christian; Brunner, Philip; Hunkeler, Daniel

The influence of model structure on groundwater recharge rates in climate-change impact studies | L’ influence de la structure du modèle sur le taux de recharge des eaux souterraines dans les études d’impact du changement climatique La influencia de la estructura del modelo en los ritmos de recarga del agua subterránea en los estudios de impacto del cambio climático 模型结构对气候变化研究中地下水补给率的影响 A influência da estrutura do modelo nas taxas de recarga das águas subterrâneas nos estudos sobre impactos da mudança climática

2016

Moeck, Christian | Brunner, Philip | Hunkeler, Daniel

Numerous modeling approaches are available to provide insight into the relationship between climate change and groundwater recharge. However, several aspects of how hydrological model choice and structure affect recharge predictions have not been fully explored, unlike the well-established variability of climate model chains—combination of global climate models (GCM) and regional climate models (RCM). Furthermore, the influence on predictions related to subsoil parameterization and the variability of observation data employed during calibration remain unclear. This paper compares and quantifies these different sources of uncertainty in a systematic way. The described numerical experiment is based on a heterogeneous two-dimensional reference model. Four simpler models were calibrated against the output of the reference model, and recharge predictions of both reference and simpler models were compared to evaluate the effect of model structure on climate-change impact studies. The results highlight that model simplification leads to different recharge rates under climate change, especially under extreme conditions, although the different models performed similarly under historical climate conditions. Extreme weather conditions lead to model bias in the predictions and therefore must be considered. Consequently, the chosen calibration strategy is important and, if possible, the calibration data set should include climatic extremes in order to minimise model bias introduced by the calibration. The results strongly suggest that ensembles of climate projections should be coupled with ensembles of hydrogeological models to produce credible predictions of future recharge and with the associated uncertainties.

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