Parameters for simple empirical catchment water quality models for simulating Escherichia coli in New Zealand rivers
E. coli is sampled at over 1000 long-term river water quality monitoring stations across New Zealand every month. Analyses associated with NPS-FM implementation commonly use a class of catchment model that we call process-based models. Calibration of process-based catchment E. coli models is challenging due to the complexity of the processes involved and data constraints. Combining all sources of uncertainty to fully characterise catchment model uncertainty is difficult and rarely undertaken. However, failing to quantify and report uncertainties can lead to overconfidence in the evidence produced by catchment modelling and limits the ability to make risk management-based decisions.
This study aimed to investigate the feasibility of fully empirical catchment E. coli models as an alternative to process-based models. This class of model is extremely simple and represents all processes leading to E. coli concentrations and loads in a receiving environment as the function of type of land in the upstream catchment. While this approach is an extremely simplified representation of reality, it offers some advantages in terms of transparency, ease of implementation, and defensibility as well as more easily estimated model uncertainty.
We defined a satisfactory empirical model for E. coli median concentrations. The model allows predictions of site-median E. coli concentrations, and the lower and upper bounds of the 90% prediction interval of this value, to be made for any catchment in New Zealand. The empirical model can also be used to simulate effects of land use change or mitigation actions on median E. coli concentrations by changing the proportion of catchment occupied by particular land-types and by applying appropriate changes to the model parameters.
Funding
Funded by the New Zealand Ministry for Business, Innovation and Employment’s Our Land and Water National Science Challenge (Toitu te Whenua, Toiora te Wai), as part of the project Mapping Freshwater Contaminants
History
Publication date
2024-06-28Project number
- Non revenue
Language
- English
Does this contain Māori information or data?
- No