TY - JOUR

T1 - Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

AU - Ockenden, Mary

AU - Tych, Wlodzimierz

AU - Beven, Keith John

AU - Collins, Adrian

AU - Evans, Robert

AU - Falloon, Peter

AU - Forber, Kirsty Jessica

AU - Hiscock, Kevin

AU - Hollaway, Michael John

AU - Kahana, Ron

AU - Macleod, Christopher J.A.

AU - Villamizar, Martha

AU - Wearing, Catherine Louise

AU - Withers, Paul J.A

AU - Zhou, Jian

AU - Benskin, Clare McWilliam Haldane

AU - Burke, Sean

AU - Cooper, Richard

AU - Freer, Jim

AU - Haygarth, Philip Matthew

PY - 2017/12/18

Y1 - 2017/12/18

N2 - 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 dynamicsin three contrasting agricultural catchments in the UK. 10 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 nonlinear rainfall input was appropriate for predicting seasonal 15 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 20 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.

AB - 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 dynamicsin three contrasting agricultural catchments in the UK. 10 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 nonlinear rainfall input was appropriate for predicting seasonal 15 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 20 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.

KW - PHOSPHORUS

KW - DISCHARGE

KW - Data-based mechanistic modelling

KW - Newby Beck

KW - Blackwater

KW - Wylye

U2 - 10.5194/hess-21-6425-2017

DO - 10.5194/hess-21-6425-2017

M3 - Journal article

VL - 21

SP - 6425

EP - 6444

JO - Hydrology and Earth System Sciences

JF - Hydrology and Earth System Sciences

SN - 1027-5606

ER -