Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

Mary Ockenden ,Adrian L Collins,Kevin M Hiscock,Sean Burke,Ron Kahana,Catherine Wearing,Martha L Villamizar ,Włodek Tych ,J E Freer ,P J A Withers ,Christopher Macleod ,Keith Beven ,Michael Hollaway ,Jian Guo Zhou ,Clare Mcwilliam Haldane Benskin ,R Evans ,Kirsty J Forber ,P D Falloon ,Richard J Cooper ,P M Haygarth

doi:10.5194/hess-21-6425-2017

Abstract

Abstract. Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with non-linear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary to capture the dynamic responses in small catchments (10–50 km2). The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future.

Highlights

The quality of both surface waters and groundwater is under increasing pressure from numerous sources, including intensive agricultural practices, water abstraction, climate change, and changes in food production and housing provisions to cope with population growth (Carpenter and Bennett, 2011)
Phosphorus (P) concentrations for water quality assessments are typically measured by manual or automatic sampling followed by laboratory analysis, often at monthly resolution, which do not capture the dynamic nature of P concentrations, and result in biased estimates of P load (Cassidy and Jordan, 2011)
High temporal resolution data of discharge and total P (TP) load have been used to identify simple transfer function models that capture the dynamics of rainfall–runoff and rainfall– phosphorus load in three diverse agricultural catchments

Summary

Introduction

The quality of both surface waters and groundwater is under increasing pressure from numerous sources, including intensive agricultural practices, water abstraction, climate change, and changes in food production and housing provisions to cope with population growth (Carpenter and Bennett, 2011). Phosphorus (P) concentrations for water quality assessments are typically measured by manual or automatic sampling followed by laboratory analysis, often at monthly resolution, which do not capture the dynamic nature of P concentrations, and result in biased estimates of P load (Cassidy and Jordan, 2011). Phosphorus concentration in rivers and streams is controlled by many factors, including rainfall, runoff, point sources, diffuse inputs, and in-stream P retention and processing. Some of these factors, for small catchments, change at timescales of minutes to hours, and the dynamics of P concentration and load need to be studied at similar timescales. Hourly time series of rainfall, runoff and P concentrations are used to help understand hydrological transport pathways of P for three contrasting agricultural catchments across the UK

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