Browsing by Author "Chiverton, Andrew"
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Item Open Access The influence of catchment characteristics on river flow variability(Cranfield University, 2015-08-05) Chiverton, Andrew; Hannaford, Jamie; Holman, Ian P.; Prudhomme, Christel; Hess, Tim M.; Bloomfield, JohnHydrology is yet to fully understand the role that catchment characteristics have in determining a river’s response to precipitation variability. This thesis assesses the influence that catchment characteristics have on modulating a river’s response to changes in precipitation throughout the UK. Central to this aim is the concept of the precipitation- to-flow relationship (the transformation of precipitation into river flow), which is characterised using the Variogram, a way of indexing temporal dependence (i.e. the average relationship between river flow on a given day and river flow on the previous days). Firstly, 116 catchments were grouped into four clusters, based on the shape of their variogram, which significantly differed in their catchment characteristics demonstrating that catchment characteristics control how, on average, precipitation is transformed into river flow. Furthermore, over 70% of un-gauged catchments could be clustered correctly using information about their soil type, slope and the percentage of arable land. Secondly, a new method which identifies the changes in the variogram parameters over 5-year overlapping moving windows was developed to investigate temporal changes in the variogram parameters. This method was successfully demonstrated to detect changes in multiple aspects of artificially perturbed river flow time series (e.g. seasonality, linear changes and variability). On average >70% of the variability in the catchment variogram parameters was explained by the precipitation characteristics, although there was large variability between catchments. Finally, the influence that the catchment characteristics have on the temporal changes in the variogram parameters was analysed, demonstrating that rivers in relatively impermeable upland catchments have a relationship with precipitation which is closer to linear and less variable than lowland, permeable catchments. This thesis contributes significant new knowledge that can be used for both assessing how individual catchments are likely to respond to projected changes in precipitation and in informing data transfer to un-gauged catchments.Item Open Access Which catchment characteristics control the temporal dependence structure of daily river flows?(John Wiley & Sons, Ltd, 2014-12-31T00:00:00Z) Chiverton, Andrew; Hannaford, Jamie; Holman, Ian P.; Corstanje, Ronald; Prudhomme, Christel; Bloomfield, John; Hess, Tim M.Hydrological classification systems seek to provide information about the dominant processes in the catchment to enable information to be transferred between catchments. Currently, there is no widely agreed-upon system for classifying river catchments. This paper develops a novel approach to classifying catchments based on the temporal dependence structure of daily mean river flow time series, applied to 116 near-natural ‘benchmark' catchments in the UK. The classification system is validated using 49 independent catchments. Temporal dependence in river flow data is driven by the flow pathways, connectivity and storage within the catchment and can thus be used to assess the influence catchment characteristics have on moderating the precipitation-to-flow relationship. Semi-variograms were computed for the 116 benchmark catchments to provide a robust and efficient way of characterising temporal dependence. Cluster analysis was performed on the semi-variograms, resulting in four distinct clusters. The influence of a wide range of catchment characteristics on the semi-variogram shape was investigated, including: elevation, land cover, physiographic characteristics, soil type and geology. Geology, depth to gleyed layer in soils, slope of the catchment and the percentage of arable land were significantly different between the clusters. These characteristics drive the temporal dependence structure by influencing the rate at which water moves through the catchment and/or the storage in the catchment. Quadratic discriminant analysis was used to show that a model with five catchment characteristics is able to predict the temporal dependence structure for un-gauged catchments. This method could form the basis for future regionalisation strategies, as a way of transferring information on the precipitation-to-flow relationship between gauged and un-gauged catchments.