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PHD Thesis: A multiscale nested experiment for understanding and prediction of high rainfall and flood response spatial behaviour in the Eden catchment, Cumbria, UK.
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Dr Mark Wilkinson
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A deficiency in current understanding of flood response is the variation of flood generation at different spatial scales as a function of spatial and temporal variations in storm rainfall. There is a lack of studies showing the process of transformation from rainfall to stream flow at a range of consecutive scales. This process is complex and varies with catchment size. The aim of the project is therefore to investigate the relationship between rainfall spatial variability and flood response through a multiscale nested experiment. Hydrological data from an extensive, nested hydrometric network in the predominantly rural Upper Eden catchment, Cumbria, UK, were collected for a range of flood events. Seven storm rainfall events and the resulting flood responses were characterised over varying land uses and scales from a small upland catchment (1.1km2) to the basin outlet (616km2). A distributed hydrological model was used to investigate flood response with various representations of raingauge networks (both actual and virtual) to indicate the importance of accurately representing spatial and the temporal variability of storms for flood forecasting. For winter storms, the amount and duration of rainfall occurring in the headwater catchments is the dominant factor in flood peak generation. However, raingauge underestimation and rainshadow effects can degrade rainfall estimates. Uncertainty with storm data and its effect on understanding hydrological processes at different scales is found to be greatest in the most intense synoptic scale events. The lag times for each storm vary due to the antecedent catchment conditions and spatial scale of the storm. Spatial scaling of a convective storm within a nested catchment system is important in flood peak routing and timing. Flood peak increases with area according to a power law relationship that varies with storm type and antecedent conditions. Modelling demonstrates that improved rainfall estimates (including a virtual enhanced network) substantially improve our understanding of the flood peak formation within a nested basin and flood peak prediction.
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