Hydrological models play an important role in water resource management and flood risk management. However, there is a lack of comparative analysis on the performance of those models to guide hydrologists to choose suitable models for the individual catchment conditions. This paper describes a two-level meta-analysis to develop a matching system between catchment complexity (based on catchment significant features CSFs) and model complexity (based on model types). The objective is to use the available CSFs information for choosing the most suitable model type for a given catchment. In this study, the CSFs include the elements of climate, soil type, land cover and catchment scale. Through the literature review, 119 assessments of flow model simulations based on 28 papers are chosen, with a total of 76 catchments. Specific choices of model and model types in small, medium and large catchments are explored. In particular, it is interesting to find that semi-distributed models are the most suitable model type for catchments with the area over 3000km2.
Zhuo, Lu and Han, Dawei, "Build A Matching System Between Catchment Complexity And Model Complexity For Better Flow Modelling" (2014). CUNY Academic Works.