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Modelling best management practices for reducing nutrient losses from agricultural catchments under different climate trajectories.

How to achieve a 50% reduction in nutrient losses from agricultural catchments under different climate trajectories?
https://doi.org/10.5878/3j5c-yh37

This dataset contains all the geospatial information and HYPE inputs and outputs related to the publication of "How to achieve a 50% reduction in nutrient losses from agricultural catchments under different climate trajectories?". In this study, we build high-resolution geospatial data to build a semi-distributed water quantity and water quality model for two Swedish Agricultural Catchments in Hydrological Predictions of the Environment (HYPE). We calibrated and validated the model using discharge and water quality monitoring data from the streams in our study sites. We subsequently used the calibrated model to forecast the impacts of climate change on nutrient (Inorganic Nitrogen and Total Phosphorus) loads under three relative concentration pathways (RCP2.6, RCP4.5, and RCP 8.5) and three periods (2022-2035, 2050-2065, and 2085-2100). Finally, we backcasted a 50% reduction in nutrient loads using catchment mitigation scenarios (20% reduction in fertilisation, increasing in floodplain area, implementation of cover crops). This dataset contains all the monitoring data, model inputs (including parameterisation), and the model outputs. Moreover, it contains the R scripts with summary statistics and plotting and the summarised outputs of all model runs in csv files. The dataset contains three folders. 1. The Geopatial Information folder contains all the geospatial data for both study catchments. These include land cover, soil, DEM, and finally the Soil Land Cover maps, which were used to build the HYPE models. The coding of the geospatial shapefiles and raster files can be found in the Readme document. 2. The HYPE_model folder contains all of the HYPE model building blocks necessary to run the calibrated model for Hestadbäcken and Tullstorpån in seperate folders. It also contains the goodness-of-fit outcomes for both the calibrated model and the validation period. This folder also contains the future climate forecasts and the different mitigation scenario testing outcomes. 3. The outputs_and_data_analysis folder contains csv files with all of the model outcomes for IN, TP, and Q in both catchments for all combinations of RCP, period, and climate models. It also contains R scripts used to calculate trends, summary statistics, t-tests, and plot the figures. Moreover, it contains the outcomes of the percentages of change, correlation tests, and t-tests.

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Version 1
doris
Swedish University of Agricultural Sciences