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Title: A diagnostic framework for the evaluation of multiple hydrological model structures from a UK national assessment of discharge uncertainties
Author: Coxon, Gemma Rachael
ISNI:       0000 0004 5915 3415
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2015
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Hydrological modelling is an inexact science where we have incomplete knowledge and understanding of hydrological systems. This has important implications for how we evaluate and discriminate between competing hypotheses of hydrological behaviour as model evaluation is tempered by the information, uncertainty and error within the available data used for model evaluation. This thesis presents multiple studies that investigate the different choices that matter for hydrological model evaluation by developing a diagnostic framework for the evaluation of multiple hydrological model structures that incorporates a UK national assessment of discharge uncertainties. There is a particular emphasis on (l) testing multiple hypotheses of catchment behaviour, (2) developing novel frameworks to quantify the quality of river discharge data and (3) accounting for observational discharge uncertainties in model diagnostics. The first results chapter provides evidence that the value of diagnostics to discriminate between model structures is dependent on catchment characteristics. Furthermore, these results contribute to a better understanding of the links between model structure choice, model performance and catchment characteristics and dynamics. The second results chapter focuses on the development of a novel generalised framework to estimate discharge uncertainties at many gauging stations with a variety of different errors in the stage-discharge relationship. Significantly, it was shown that despite regional differences in the type of gauging station, the number of historical rating curves and stage-discharge measurements, discharge uncertainties are highly place specific. The third results chapter emphasises the importance of recognising data quality in model evaluation frameworks and demonstrates that the choice of discharge uncertainty estimate impacts model identification. Overall, this thesis presents results that are important for the development of model evaluation frameworks and provides guidance to the hydrological community on how to test and reject competing hypotheses of catchment behaviour.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available