Sensitivity analysis of an integrated numerical flow model output to key model parameters used in common qualitative vulnerability assessment methods

Abstract

Qualitative vulnerability assessment methods applied in karst aquifers rely on key factors in the hydrological compartments and are usually assigned different weights according to their projected impact on the groundwater vulnerability. Based on an integrated numerical groundwater model on a snow-governed karst catchment area (El Assal Spring- Lebanon), the aim of this work is to quantify the importance of the most influential parameters on recharge and spring discharge and to outline the potential parameters that are often not accounted for in standard calibration methods, when in fact they do play a role in assessing the intrinsic vulnerability of a system. The assessment of the model sensitivity and ranking of parameters are conducted using an automated calibration tool for local sensitivity analysis in addition to a variance based local sensitivity assessment of model output time series (recharge and discharge) for two consecutive years (2016-2017). The impact of each parameter was normalized to estimate standardized weights for each of the process based key-controlling parameters. Parameters to which the model was sensitive were factors related to soil, 2) fast infiltration (bypass function) typical of karst aquifers, 3) climatic parameters (melting temperature and degree day coefficient) and 4) aquifer hydraulic properties that play a major role in groundwater vulnerability inducing a temporal effect and varied recession. Other less important parameters play different roles according to different assigned weights proportional to their ranking. Additionally, the effect of slope-geomorphology (e.g., dolines) was further examined. In general, this study shows that the weighing coefficients assigned to key vulnerability factors in the qualitative assessment methods need to be reevaluated based on a process-based approach.