CLUES model calibration: residual analysis to investigate potential sources of model error

ABSTRACT

This paper presents the results of the latest calibrations of the CLUES model for each of total nitrogen, total phosphorus and Escherichia coli. The model provides estimates of in-stream annual loads of these contaminants for every river reach in the New Zealand River Environments Classification and has been used in New Zealand for catchment planning and policy development. CLUES has been calibrated nationally against loads estimated from data collected from water quality monitoring stations located across the country which could lead to parameter bias. To ascertain whether there is any systematic bias, the calibration residuals were evaluated against regional (geographical) location and a range of upstream catchment characteristics, namely land use, soil drainage properties, slope, network order, proportion of baseflow in total stream flow, climate, geology and source of flow. We found that CLUES gives reasonable load estimates at the catchment scale (Nash-Sutcliff efficiencies >0.8 for all the contaminants). However, there was significant uncertainty in the parameterisation. While several significant relationships were found between upstream catchment characteristics and the model residuals, these relationships were weak and are unlikely to point to any systematic bias in the calibration.

KEYWORDS:

• Overseer
• SPARROW
• SPASMO
• total nitrogen
• total phosphorus
• E. coli
• annual loads
• uncertainty
• bias
• error

Acknowledgments

Special thanks to Dr Sharleen Yalden (NIWA) for help interpreting the methods used to estimating contaminant loads for calibration. The Baseflow Index values for the water quality monitoring sites were calculated for this paper by Dr Shailesh Singh (NIWA) and estimated values of hydraulic conductivity and porosity were provided by Dr Rogier Westerhoff (GNS Science).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was funded as an output from the Sources and Flows Programme of the Our Land and Water National Science Challenge [Ministry of Business, Innovation and Employment contract C10X1507].