Hooftman, D.A.P., Ziv, G. orcid.org/0000-0002-6776-0763, Evans, P.M. et al. (1 more author) (2025) Validation of the InVEST nutrient retention model across Europe with attribution of model errors. Environmental Modelling & Software, 193. 106657. ISSN: 1364-8152
Abstract
Intensive fertilisation of farmland leads to substantial nutrient escape into the environment, polluting land, water, and the atmosphere. We used the InVEST NDR model to investigate nitrogen (N) and phosphorus (P) run-off and retention across the European continent at 25 × 25 m resolution, and validated outputs against empirical measurements at 2251 river locations. Mean nutrient retention across Europe was estimated as 93 % for N and 92 % for P, through accumulation by standing vegetation and the soil. Modelled nutrient export to streams matched well to empirical measurements. Model-based uncertainties were related to seasonality, the balance between surface and sub-surface flows, and extremes in slope and rainfall. Uncertainties related to empirical data suggested enhancements to monitoring programmes that would improve nutrient export and erosion modelling, which included higher resolution fertiliser and manure data, differentiation of grassland types, including stocking density categories, and in-river nutrient measurements at low flow.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Agriculture, Ecosystem services, Eutrophication, Fertiliser, Grassland, Land cover, Nutrient retention |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Sep 2025 12:37 |
Last Modified: | 24 Sep 2025 12:37 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.envsoft.2025.106657 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:232023 |