Continuum: a distributed hydrological model for water management and flood forecasting

Abstract

Abstract. Full process description and distributed hydrological models are very useful tools in hydrology as they can be applied in different contexts and for a wide range of aims such as flood and drought forecasting, water management, prediction of impact on the hydrologic cycle due to natural and human changes to catchment features in present and changing climates. Since they must mimic a variety of physical processes they can be very complex and with a high degree of parameterization. This complexity can be increased by the need to relate the state variables to observations in order to allow data assimilation. In this work a model, aiming at balancing the need to reproduce the physical processes with the practical goal of avoiding over-parameterization, is presented. The model is designed to be implemented in different contexts with a special focus on data scarce environments. All the main hydrological phenomena are modeled in a distributed way. Mass balance and energy balance are solved explicitly. Land surface temperature, which is particularly suited to being extensively observed and assimilated, is an explicit state variable. An objective performance evaluation, based on both traditional and satellite derived data, is presented with a specific reference to the application in an Italian catchment. The model has been calibrated and validated using different data sets on two nested outlet sections and the capability of the model in reproducing both the stream-flow measurements and the land surface temperature retrieved by satellite measurements, has been investigated.