Use this URL to cite or link to this record in EThOS:
Title: The prediction of reservoir sedimentation across England and Wales
Author: Manning, Christopher.
Awarding Body: Nottingham Trent University
Current Institution: Nottingham Trent University
Date of Award: 2004
Availability of Full Text:
Access from EThOS:
The principal aim of this thesis is to produce a comprehensive assessment of the spatial variation of reservoir sedimentation for the population of surface water storage reservoirs, exhibiting a degree of catchment-coupling, across England and Wales. This is the first time that such a study has been undertaken. To achieve this, a valid model had to be developed to predict reservoir sedimentation for those sites where no direct measurements were available. Using readily available secondary data describing catchment and reservoir basin factors identified to influence reservoir sedimentation, two lumped-empirical models were developed. The first model used the traditional modelling technique of multiple regression; the second used fuzzy set multi-criteria evaluation (MCE), a technique not previously applied to reservoir sedimentation modelling. Both techniques were applied to a population data set (established herein). The models were validated using primary data from bathymetric surveys. Through multiple regression, models predicting reservoir annual percentage capacity loss (APL) could not be verified and validated due to violations of the assumptions of the technique. A major reason for these failures was the inability of the approach to account for uncertainty and error associated with the quantification of the dependent and independent variables, and the specification of the respective relationships. Through fuzzy set MCE, a model predicting the degree of reservoir sedimentation for the population data set was verified and validated to a reasonably good level; as was an associated defuzzification model converting the predicted fuzzy number to a predicted APL rate. The fuzzy set MCE modelling technique was identified as the most suitable for accomplishing the principal aim because, unlike multiple regression, it was able to account for uncertainty and error associated with the quantification and specification of the catchment and reservoir basin factors that influence reservoir sedimentation. Upon operationalization, the fuzzy set MCE model and associated defuzzification model identified the upland areas of Cumbria, Wales, the southern Pennines and the southwest as experiencing the largest levels of reservoir sedimentation. This is primarilly attributed to these areas having high mean annual rainfall and large areas of highly erosive soil types. The outputs of the fuzzy set MCE model and associated defuzzification model allow attention to be focused by reservoir undertakers on areas where sustainability of water supply may be most sensitive to loss of reservoir capacity from sedimentation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available