H13I-1698
An evaluation of Dynamic TOPMODEL for low flow simulation

Monday, 14 December 2015
Poster Hall (Moscone South)
Gemma Coxon1, Jim E Freer1, Niall Quinn1, Ross A Woods1, Thorsten Wagener2 and Nicholas J K Howden1, (1)University of Bristol, Bristol, United Kingdom, (2)University of Bristol, Civil Engineering, Bristol, United Kingdom
Abstract:
Hydrological models are essential tools for drought risk management, often providing input to water resource system models, aiding our understanding of low flow processes within catchments and providing low flow predictions. However, simulating low flows and droughts is challenging as hydrological systems often demonstrate threshold effects in connectivity, non-linear groundwater contributions and a greater influence of water resource system elements during low flow periods. These dynamic processes are typically not well represented in commonly used hydrological models due to data and model limitations. Furthermore, calibrated or behavioural models may not be effectively evaluated during more extreme drought periods. A better understanding of the processes that occur during low flows and how these are represented within models is thus required if we want to be able to provide robust and reliable predictions of future drought events.

In this study, we assess the performance of dynamic TOPMODEL for low flow simulation. Dynamic TOPMODEL was applied to a number of UK catchments in the Thames region using time series of observed rainfall and potential evapotranspiration data that captured multiple historic droughts over a period of several years. The model performance was assessed against the observed discharge time series using a limits of acceptability framework, which included uncertainty in the discharge time series. We evaluate the models against multiple signatures of catchment low-flow behaviour and investigate differences in model performance between catchments, model diagnostics and for different low flow periods. We also considered the impact of surface water and groundwater abstractions and discharges on the observed discharge time series and how this affected the model evaluation. From analysing the model performance, we suggest future improvements to Dynamic TOPMODEL to improve the representation of low flow processes within the model structure.