Research papersHydrological modelling in a drinking water catchment area as a means of evaluating pathogen risk reduction

- Mitigation measures for microbial risk reduction were studied using a SWAT model.
- The most efficient measure was increased removal in wastewater treatment plants.
- Hydrological models can constitute an important part of a risk management decision support.

Waterborne outbreaks of gastrointestinal diseases are of great concern to drinking water producers and can give rise to substantial costs to the society. The World Health Organisation promotes an approach where the emphasis is on mitigating risks close to the contamination source. In order to handle microbial risks efficiently, there is a need for systematic risk management. In this paper we present a framework for microbial risk management of drinking water systems. The framework incorporates cost-benefit analysis as a decision support method. The hydrological Soil and Water Assessment Tool (SWAT) model, which was set up for the Stäket catchment area in Sweden, was used to simulate the effects of four different mitigation measures on microbial concentrations. The modelling results showed that the two mitigation measures that resulted in a significant (p < 0.05) reduction of Cryptosporidium spp. and Escherichia coli concentrations were a vegetative filter strip linked to cropland and improved treatment (by one Log10 unit) at the wastewater treatment plants. The mitigation measure with a vegetative filter strip linked to grazing areas resulted in a significant reduction of Cryptosporidium spp., but not of E. coli concentrations. The mitigation measure with enhancing the removal efficiency of all on-site wastewater treatment systems (total removal of 2 Log10 units) did not achieve any significant reduction of E. coli or Cryptosporidium spp. concentrations. The SWAT model was useful when characterising the effect of different mitigation measures on microbial concentrations. Hydrological modelling implemented within an appropriate risk management framework is a key decision support element as it identifies the most efficient alternative for microbial risk reduction.