Abstract
<p>Many countries maintain nationwide groundwater networks to monitor the status of their groundwater resources. To assess the current water availability as well as help forecast future changes, it is fundamental to understand and predict groundwater dynamics observed in the individual monitoring wells. Nationwide monitoring networks typically cover multiple aquifer systems with different degree of environmental complexity. Understanding these aquifer systems is challenging, as the development of physically-based, distributed groundwater models is time-consuming and costly. As an attractive alternative, statistical and conceptual lumped-parameter models may be applied to analyze monitoring networks. The advantage of these models over physically-based models is that the conceptual parameterization is relatively simple and computation is efficient, while typically results are robust.</p><p>In this study, we analyze the long-term groundwater-monitoring network of Switzerland using conceptual, lumped-parameter models implemented in the Pastas software package. The 29 monitoring wells in the network are situated in unconsolidated aquifers across Switzerland, ranging from high altitude alpine aquifers to pre-alpine aquifers systems on the Swiss plateau. Given the very diverse topography in Switzerland, snowmelt processes affect some aquifers, while groundwater-surface water interactions are important in the valleys. The models are used to identify and quantify which driving forces (e.g., precipitation, river levels) control the groundwater dynamics, and how fast the groundwater systems respond to changes in these stresses. The results show that precipitation and evaporation explain large parts of the observed dynamics, while about half of the monitoring wells in the network appear to be influenced by river level fluctuations. Explicitly accounting for snow processes in the recharge generating process is found to improve the simulation of the water table dynamics for only a few wells in high-altitude aquifers. The models developed in this study lead to a better understanding of the observed groundwater dynamics across Switzerland and will be used in future studies to explore the sensitivity of the groundwater resources to climatic changes.</p>
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