Modelled impacts of policies and climate change on land use and water quality in Austria

Abstract

Climate change is a major driver of land use with implications for the quality and quantity of water resources. We apply a novel integrated impact modelling framework (IIMF) to analyze climate change impacts until 2040 and stakeholder driven scenarios on water protection policies for sustainable management of land and water resources in Austria. The IIMF mainly consists of the sequentially linked bio-physical process model EPIC, the regional land use optimization model PASMA[grid], the quantitative precipitation/runoff TUWmodel, and the nutrient emission model MONERIS. Three climate scenarios with identical temperature trends but diverging precipitation patterns shall represent uncertainty ranges from climate change, i.e. a dry and wet situation. Water protection policies are clustered to two policy portfolios WAP_I and WAP_II, which are targeted to regions (WAP_I) or applied at the national scale (WAP_II). Policies cover agri-environmental programs and legal standards and tackle management measures such as restrictions in fertilizer, soil and crop rotation management as well as establishment of buffer strips. Results show that average national agricultural gross margin varies by ±2%, but regional impacts are more pronounced particularly under a climate scenario with decreasing precipitation sums. WAP_I can alleviate pressures compared to the business as usual scenario but does not lead to the achievement of environmental quality standards for P in all rivers. WAP_II further reduces total nutrient emissions but at higher total private land use costs. At the national average, total private land use costs for reducing nutrient emission loads in surface waters are 60–200 €/kg total N and 120–250 €/kg total P with precipitation and the degree of regional targeting as drivers. To conclude, the IIMF is able to capture the interfaces between climate change, land use, and water quality in a policy context. Despite efforts to improve model linkages and the robustness of model output, uncertainty propagations in integrated modelling frameworks need to be tackled in subsequent studies.