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Casson, David R. (author), Werner, Micha (author), Weerts, Albrecht (author), Solomatine, D.P. (author)Hydrological modelling in the Canadian sub-Arctic is hindered by sparse meteorological and snowpack data. The snow water equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Global re-analysis datasets that provide gridded...journal article 2018
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Mukolwe, M.M. (author), Di Baldassarre, G. (author), Werner, M. (author), Solomatine, D.P. (author)This paper presents an analysis of uncertainty in hydraulic modelling of floods, focusing on the inaccuracy caused by inflow errors and parameter uncertainty. In particular, the study develops a method to propagate the uncertainty induced by, firstly, application of a stage–discharge rating curve and, secondly, parameterisation of a...journal article 2014
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Aguilar Lopez, J.P. (author), Andel, Schalk Jan Van (author), Werner, M (author), Solomatine, D.P. (author)Data for water management is increasingly easy to access, it has finer spatial and temporal resolution, and it is available from various sources. Precipitation data can be obtained from meteorological stations, radar, satellites and weather models. Land use data is also available from different satellite products and different providers. The...conference paper 2014
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Corzo, G.A. (author), Solomatine, D.P. (author), Hidayat, M.S. (author), De Wit, M. (author), Werner, M. (author), Uhlenbrook, S. (author), Price, R.K. (author)One of the challenges in river flow simulation modelling is increasing the accuracy of forecasts. This paper explores the complementary use of data-driven models, e.g. artificial neural networks (ANN) to improve the flow simulation accuracy of a semi-distributed process-based model. The IHMS-HBV model of the Meuse river basin is used in this...journal article 2009