How to Achieve a 50% Reduction in Nutrient Loads from Agricultural Catchments under Different Climate Trajectories?

Abstract

Under persistent eutrophication of European water bodies and a changing climate, there is an increasing need to evaluate mitigation measures for reducing nutrient losses from agricultural catchments. In this study, we set up a daily discharge and water quality model in Hydrological Predictions of the Environment for two contrasting agricultural catchments in Sweden to forecast the impacts of future climate trajectories on nutrient loads. The model predicted a slight increase in inorganic nitrogen (IN) and total phosphorus (TP) loads under RCP2.6, likely due to precipitation-driven mobilisation. Under RCP4.5 and RCP8.5, the IN loads were forecasted to decrease from 16%-26% and 21%-50% respectively, most likely due to temperature-driven increases in denitrification and evapotranspiration. No distinct trends in TP loads were observed. A 50% decrease in nutrient loads, as targeted by the European Green Deal, was backcasted using a combination of mitigation scenarios, including i) a 20% reduction in mineral fertiliser, ii) introducing cover crops, and iii) stream mitigation by increasing the size of floodplains and wetlands. Target TP load reductions could only be achieved by stream mitigation, which is likely due to legacy effects and secondary mobilisation within agricultural streams. Target IN load reductions were backcasted with a combination of stream mitigation, fertiliser reduction, and cover crops, wherein the required measures depended on the climate. Overall, the diverging responses of nutrients to climate change and mitigation scenarios indicate that water quality management needs to be tailored to the catchment characteristics, and to the spatial and time specific effects of climate change.

How to Achieve a 50% Reduction in Nutrient Losses From Agricultural Catchments Under Different Climate Trajectories?

“…All processed geospatial data, water quality and discharge data used for calibration, climate data, model set-up, and model outcomes are accessible open access (Wynants, 2024). The HYPE model (Pers et al, 2022), HYPE tools (Capell & Brendel, 2023), and R software (R Core Team, 2022) can be accessed open access.…”