Analysis of nationwide groundwater monitoring networks using lumped-parameter models

Many countries maintain nationwide groundwater networks to monitor the status of their groundwater resources. For effective groundwater resource management, it is fundamental to understand the groundwater dynamics measured in the individual monitoring wells. Nationwide monitoring networks typically cover multiple aquifer systems with different degrees of environmental complexity. The analysis of the data of such networks thus requires flexible modeling approaches. In this study, we assessed the applicability and performance of lumped-parameter models using impulse response functions, as implemented in the Pastas software, to simulate hydraulic head data from the nationwide groundwater monitoring network in Switzerland. The selected 28 monitoring wells in the network are situated in unconsolidated, relatively shallow aquifers across Switzerland. Given the very diverse topography in the study area, snowmelt processes affect some aquifers, while groundwater–surface water interactions are important in the valleys. Different linear and nonlinear models were tested to take precipitation and potential evaporation into account, with a new model developed as part of this study to account for the effect of snow processes on recharge generation. After generally good fits in both the calibration and evaluation were achieved, the models were used to identify and quantify which stresses (e.g., precipitation, river stages) control the groundwater dynamics. The results show that precipitation and evaporation explain large parts of the measured dynamics, and about half of the monitoring wells in the network appear to be influenced by river stages. Explicitly accounting for snow processes in the recharge generating process is found to improve the simulation of the head dynamics across Switzerland, particularly for wells in high-altitude aquifers. This study demonstrates for the first time the applicability of lumped-parameter models using impulse response functions to model heads in Switzerland, and more generally, in climatic settings where snow processes are impacting the head dynamics.