How well can we model stream phosphorus concentrations in agricultural catchments?. (February 2015)

• Record Type: Journal Article
• Authors: Jackson-Blake, L.A.; Dunn, S.M.; Helliwell, R.C.; Skeffington, R.A.; Stutter, M.I.; Wade, A.J.
• Is Part Of: Environmental modelling & software. Volume 64(2015:Feb.)
• Page Start: 31
• Page End: 46
• Publication Date: 2015-02
• Subjects: Phosphorus -- Catchment modelling -- INCA -- Nash–Sutcliffe -- Diffuse pollution -- Daily data; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2014.11.002
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Mechanistic catchment-scale phosphorus models appear to perform poorly where diffuse sources dominate. We investigate the reasons for this for one model, INCA-P, testing model output against 18 months of daily data in a small Scottish catchment. We examine key model processes and provide recommendations for model improvement and simplification. Improvements to the particulate phosphorus simulation are especially needed. The model evaluation procedure is then generalised to provide a checklist for identifying why model performance may be poor or unreliable, incorporating calibration, data, structural and conceptual challenges. There needs to be greater recognition that current models struggle to produce positive Nash–Sutcliffe statistics in agricultural catchments when evaluated against daily data. Phosphorus modelling is difficult, but models are not as useless as this might suggest. We found a combination of correlation coefficients, bias, a comparison of distributions and a visual assessment of time series a better means of identifying realistic simulations. Highlights: We use daily data to test a mechanistic phosphorus model in an agricultural area. The model reproduces dissolved phosphorus dynamics but struggles with particulates. A number of potential model simplifications and improvements are highlighted. Nash–Sutcliffe is of limited use for measuring phosphorus model performance. We present a checklist for assessing why environmental models may underperform.