Baseline and business-as-usual (BAU) agricultural footprints for major farm types across England

Daten und Ressourcen

This Dataset is currently private and won't be accessible to anyone outside the organization. If you want to publish this dataset, please send an email to data.stewards@rothamsted.ac.uk

Cite this as

Retrieved: 22:12 26 Nov 2024 (UTC)
Authors
Name ORCID Affiliation

Abstract

Recent June Agricultural Census (2016) data at EU WFD waterbody scale were integrated with UKCP18 baseline rainfall (1981-2010) and NatMap 1000 soil data to generate representative model farms for 89 Water Management Catchments (WMCs) across England. For each WMC, baseline agricultural footprints (zero uptake of on-farm best management interventions) and business-as-usual (BAU) footprints (with existing uptake of on-farm best management interventions) for the arable and lowland grazing livestock farms were quantified using the Catchment Systems Model (CSM). The farm scale estimates include nitrate, phosphorus, sediment, methane, nitrous oxide, ammonia, FIOs, pesticides and energy use. Results are available for 860 cereal farms, 944 general cropping farms, 623 dairy farms, 933 lowland gazing farms and 826 miixed farms. Each has a unique combination of major robust farm type (RFT), annual average rainfall (AAR) band and soil drainage status.

Methods

Within each water management catchment (WMC), farm type-specific summaries of holding number, cropping areas and livestock populations were averaged to represent typical farm structures for the model farms. Fertiliser application rates by major farm types as reported by British Farm Practice Survey for year 2011 to 2016 were downloaded (https://www.gov.uk/government/collections/fertiliser-usage) and averaged to characterise the nutrient inputs. Typical manure spreading rates were assumed from Defra funded work.
For the scenario under business-as-usual (BAU), farm type-specific uptake rates of best management measures updated in 2019 were used. Separate rates were used to represent the impact of nitrate vulnerable zone (NVZ) regulations where appropriate.
Excel VBA routines were developed to automate the model farm creation, measure impact assessments, data extraction and analysis. More details on the modelling methodology can be found in the papers listed in the 'Related Output'.

Technical Information

Simple Leaflet Map
Funder Information
Award Number Award Title Funder Name



Private Information
Responsible Person Yusheng Zhang
Research Infrastructure Used
Data Locations NICCEE RR_LabArchives folder
Associated Notebooks

      
Experiment Code Type
Experiment Code
Withdrawal Reason