A method for uncertainty constraint of catchment discharge and phosphorus load estimates |
| |
| Authors: | Michael J Hollaway Keith J Beven Clare Mc W H Benskin Adrian L Collins Robert Evans Peter D Falloon Kirsty J Forber Kevin M Hiscock Ron Kahana Christopher J A Macleod Mary C Ockenden Martha L Villamizar Catherine Wearing Paul J A Withers Jian G Zhou Nicholas J Barber Philip M Haygarth |
| |
| Institution: | 1. Lancaster Environment Centre, Lancaster University, Lancaster, UK;2. North Wyke, Rothamsted Research, Okehampton, UK;3. Global Sustainability Institute, Anglia Ruskin University, Cambridge, UK;4. Met Office Hadley Centre, Exeter, UK;5. School of Environmental Sciences, University of East Anglia, Norwich, UK;6. James Hutton Institute, Aberdeen, UK;7. School of Engineering, Liverpool University, Liverpool, UK;8. School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester, UK;9. Geography Department, Durham University, Durham, UK |
| |
| Abstract: | River discharge and nutrient measurements are subject to aleatory and epistemic uncertainties. In this study, we present a novel method for estimating these uncertainties in colocated discharge and phosphorus (P) measurements. The “voting point”‐based method constrains the derived stage‐discharge rating curve both on the fit to available gaugings and to the catchment water balance. This helps reduce the uncertainty beyond the range of available gaugings and during out of bank situations. In the example presented here, for the top 5% of flows, uncertainties are shown to be 139% using a traditional power law fit, compared with 40% when using our updated “voting point” method. Furthermore, the method is extended to in situ and lab analysed nutrient concentration data pairings, with lower uncertainties (81%) shown for high concentrations (top 5%) than when a traditional regression is applied (102%). Overall, for both discharge and nutrient data, the method presented goes some way to accounting for epistemic uncertainties associated with nonstationary physical characteristics of the monitoring site. |
| |
| Keywords: | discharge epistemic and aleatory uncertainty nutrient load rating curve voting point |
|
|
