This data set was generated by running 30 year long continuous biophysical simulation models of crop growth and corresponding generation of diffuse water/air pollutants using real weather data. The data was generated by calibrating the EPIC/APEX crop growth model for two English catchments (the Eden and Wensum). The modelled data approximates the per hectare impact of farm management practices on crop growth and it's environment impact in terms of diffuse pollution: nitrogen, phosphorus, sediment, air emissions, soil carbon loss etc. This interdisciplinary research investigates novel cost-effective approaches to controlling diffuse water pollution (DP) from agriculture. It involves using recent advances in surveillance science and risk profiling that permit identifying land, which is more likely to contribute to pollution. The aim is to quantify the economic and environmental benefits of using spatially targeted regulation on high-risk land i.e. pollution prone and hydrologically connected to rivers. Thus farmers will mainly take control measures, and regulators will mostly inspect practices, on targeted high-risk land. The research models and quantifies the benefit to farmers and regulators from adopting a micro-targeted approach to multi-pollutant DP regulation using Bio-physical Economic Modelling of two English catchments. The study: 1) investigates the transferability of policy recommendations across catchments making them more broadly applicable, 2) determines the 'hidden transaction costs' of policies through structured surveys of farmers, 3) investigates the use of novel economic incentives that encourage spatial coordination of abatement effort, 4) analyses the trade-off between various agricultural externalities (pollution swapping) and, 5) investigates spatial targeting land retirement to increase farmland biodiversity. This spatially targeted approach should reduce the cost of complying with environmental standards - thus benefiting regulators, farmers and the environment.

Biophysical simulation modelling of crop growth and associated catchment pollution generation processes using the EPIC/APEX model.