Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

Abstract

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study is applied in the Brue catchment, located in UK. The first methodological step is to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model are implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge are generated as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location are assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that different model structures can provide different improvements of model performances, and, different optimal location of the sensors.