Articles | Volume 21, issue 12
Research article
30 Nov 2017
Research article |  | 30 Nov 2017

On the value of water quality data and informative flow states in karst modelling

Andreas Hartmann, Juan Antonio Barberá, and Bartolomé Andreo

Abstract. If properly applied, karst hydrological models are a valuable tool for karst water resource management. If they are able to reproduce the relevant flow and storage processes of a karst system, they can be used for prediction of water resource availability when climate or land use are expected to change. A common challenge to apply karst simulation models is the limited availability of observations to identify their model parameters. In this study, we quantify the value of information when water quality data (NO3 and SO42−) is used in addition to discharge observations to estimate the parameters of a process-based karst simulation model at a test site in southern Spain. We use a three-step procedure to (1) confine an initial sample of 500 000 model parameter sets by discharge and water quality observations, (2) identify alterations of model parameter distributions through the confinement, and (3) quantify the strength of the confinement for the model parameters. We repeat this procedure for flow states, for which the system discharge is controlled by the unsaturated zone, the saturated zone, and the entire time period including times when the spring is influenced by a nearby river. Our results indicate that NO3 provides the most information to identify the model parameters controlling soil and epikarst dynamics during the unsaturated flow state. During the saturated flow state, SO42− and discharge observations provide the best information to identify the model parameters related to groundwater processes. We found reduced parameter identifiability when the entire time period is used as the river influence disturbs parameter estimation. We finally show that most reliable simulations are obtained when a combination of discharge and water quality date is used for the combined unsaturated and saturated flow states.

Short summary
In karst modeling, there is often an imbalance between the complexity of model structures and the data availability for parameterization. We present a new approach to quantify the value of water quality data for improved karst model parameterization. We show that focusing on “informative” time periods, which are time periods with decreased observation uncertainty, allows for further reduction of simulation uncertainty. Our approach is transferable to other sites with limited data availability.