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

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Authors

  • Mary C. Ockenden
  • Wlodek Tych
  • Keith J. Beven
  • Adrian L. Collins
  • Robert Evans
  • Peter D. Falloon
  • Kirsty J. Forber
  • Kevin M. Hiscock
  • Michael J. Hollaway
  • Ron Kahana
  • Christopher J.A. Macleod
  • Martha L. Villamizar
  • Catherine Wearing
  • Paul J.A. Withers
  • Jian G. Zhou
  • Clare McW. H. Benskin
  • Sean Burke
  • Richard J. Cooper
  • Jim E. Freer
  • Philip M. Haygarth

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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 nonlinear 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.

Details

Original languageEnglish
Pages (from-to)6425-6444
Number of pages20
JournalHydrology and Earth System Sciences (HESS)
Volume21
Issue number12
DOIs
Publication statusPublished - 18 Dec 2017
Peer-reviewedYes

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