Development of a risk based approach to surface water abstraction

Pollution resulting from rainfall driven processes is known to adversely affect surface water quality. It arises from a variety of agricultural and urban point and non-point sources and atmospheric deposition. The issue, in addition to ecological impacts, is especially problematic in areas where surface water is used for drinking water supply. This study aims to investigate and develop tools to understand and manage water quality risks to water abstraction sites. The project focuses on risks caused by acute rainfall driven loadings and investigates short-term dynamics of water quality parameters.
First part of the thesis describes the deployment and testing of a commercially available water quality probe, interned to provide real time estimations of bacterial water quality in surface waters. The probe is evaluated based on direct comparison of E. coli quantified using standard techniques collected during wet weather events. It is not recommend as a current robust methodology to characterize E. coli loadings or provide early warning to bathing water or water abstraction sites.
Second part of the thesis proposes and tests a new modelling approach to describe the temporal dynamics of E. coli in the case study catchment based on Storm overflow asset and rainfall data. The developed model enables reasonable approximations of arrival times and durations of E. coli at the water abstraction site and is therefore judged to be fit for purpose in providing useful information to abstraction operators for decision making purposes.
The final part of the thesis presents a new methodology to reduce the impact of pesticide runoff on water abstraction sites. It is based on an inverse modelling/optimisation approach to identify priority areas for catchment mitigation. The methodology developed was found to be effective in reducing modelled pesticide levels at the water abstraction site based on the selective targeting of mitigation options in the catchment.