Comparative performance assessment of hydrological models

Abstract

Water resources management decisions are made based on information from predictive models that are capable of simulating the behavior of hydrological systems. More of these models are in use today and it is becoming increasingly difficult to choose which model to use for particular space and time scales as well as climate. In addition, as a result of climate change there is a an increase in the degree of randomness in hydrological systems leading to reduced predictability of these systems and thus different models are prone to perform differently under varying conditions. Meta-analysis was conducted involving seven commonly applied models in hydrological assessment to try and establish patterns that these models exhibit under varying situations. This was achieved by looking at the homogeneity of the studies at the various space and time scales. In addition to the meta-analysis, a second stage of analysis looking at the variation in performance of the models with catchment characteristics such as climate, mean altitude and catchment size was assessed. Results from the review study showed varied performance with respect to the catchment characteristic and are important in aiding decision making regarding hydrological model selection.