A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations

Abstract

Abstract. Karst trough and valley landforms are prone to flooding, primarily because of the unique hydrogeological features of karst landforms, which are conducive to the spread of rapid runoff. Hydrological models that represent the complicated hydrological processes in karst regions are effective for predicting karst flooding, but their application has been hampered by their complex model structures and associated parameter set, especially for distributed hydrological models, which require large amounts of hydrogeological data. Distributed hydrological models for predicting flooding are highly dependent on distributed modelling, complicated boundary parameter settings and extensive hydrogeological data processing, which consumes large amounts of both time and computational power. Proposed here is a distributed physically based karst hydrological model known as the QMG (Qingmuguan) model. The structural design of this model is relatively simple, and it is generally divided into surface and underground double-layered structures. The parameters that represent the structural functions of each layer have clear physical meanings, and fewer parameters are included in this model than in the current distributed models. This allows karst areas to be modelled with only a small amount of necessary hydrogeological data. Eighteen flood processes across the karst underground river in the Qingmuguan karst trough valley are simulated by the QMG model, and the simulated values agree well with observations: the average values of the Nash–Sutcliffe coefficient and the water balance coefficient are both 0.92, while the average relative flow process error is 10 % and the flood peak error is 11 %. A sensitivity analysis shows that the infiltration coefficient, permeability coefficient and rock porosity are the parameters that require the most attention in model calibration and optimization. The improved predictability of karst flooding enabled by the proposed QMG model promotes a better mechanistic depiction of runoff generation and confluence in karst trough valleys.