Groundwater recharge predictions in contrasted climate: The effect of model complexity and calibration period on recharge rates. (May 2018)

• Record Type: Journal Article
• Authors: Moeck, Christian; von Freyberg, Jana; Schirmer, Mario
• Is Part Of: Environmental modelling & software. Volume 103(2018)
• Page Start: 74
• Page End: 89
• Publication Date: 2018-05
• Subjects: Groundwater recharge -- Model complexity -- Calibration period -- Split sample test -- Contrasted climate -- Droughts; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.02.005
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We systematically evaluated the effect of model complexity and calibration strategy on estimated recharge using four varyingly complex models and a unique long-term recharge data set. A differential split sample test was carried out by using six calibration periods with climatically contrasting conditions in a constrained Monte Carlo approach. All models performed better during calibration than during validation due to differences in model structures and climatic conditions. The two more complex, physically-based models predicted the observed recharge with relatively small uncertainties, even when calibration and prediction periods had different climatic conditions. In contrast, the more simplistic soil-water balance model significantly underestimated the recharge rates. The fourth, semi-mechanistic model captured the observed recharge rates, but with a larger uncertainty range than the physically-based models. Our results may have relevant implications for a broad range of applications when recharge models are used as decision-making tools. Highlights: Model performance is a function of the complexity of the chosen recharge model. Chosen calibration period becomes important when simplistic recharge models are used. Models performed best when validation period is very similar to the calibration period. No optimal calibration period allowing for equally good simulations with all models. Best results were obtained for the most contrasting calibration period.