Progress in the hydrologic simulation of time variant recharge areas of karst systems – Exemplified at a karst spring in Southern Spain |
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| Institution: | 1. Institute of Earth and Environmental Sciences, University of Freiburg, Germany;2. Department of Civil Engineering, University of Bristol, UK;3. Connected Waters Initiative Research Centre, UNSW Sydney, Sydney 2052, Australia |
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| Abstract: | A specific characteristic of karst systems is the occurrence of time variant recharge areas. In our study we present a new type of hydrological karst model and a new calibration approach both considering this specific characteristic. The new model type considers the spatial variability of karst system properties by distribution functions, and is compared to a simple reservoir model. Both models are applied to a karst system in Southern Spain where objective functions applied on hydrodynamic and hydrochemical information helped to determine model parameters playing a role for hydrodynamic response. Thereafter, the recharge area is determined separately for individual hydrological years and for the entire time series by calibrating the model to match the water balance. We show that hydrochemical information is crucial to find a reasonable set of parameters for both models. Considering different hydrological years, we find that the recharge area is changing significantly (from 28 to 53 km2). The newly developed model is able to reproduce this variation and provide acceptable simulation results for the entire time series of available data. The classic reservoir model shows inferior performance concerning hydrodynamics and fails to reproduce the water balance because it does not consider variations of recharge area. Our calibration approach allows identifying a variable recharge area and our new model is able to reproduce its variability. Hence we obtain a more realistic system representation, which can be of high significance when models are used for prediction, i.e. beyond the conditions they were calibrated, e.g. for land-use or climate change scenarios. |
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