Using urban climate modelling and improved land use classifications to support climate change adaptation in urban environments: A case study for the city of Klagenfurt, Austria

This study outlines the results of current and future climate scenarios, and potentially realizable climate adaptation measures, for the city of Klagenfurt, Austria. For this purpose, we used the microscale urban climate model (MUKLIMO_3), in conjunction with the cuboid method, to calculate climate indices such as the average number of summer and hot days per year. For the baseline simulation, we used meteorological measurements from 1981 to 2010 from the weather station located at Klagenfurt Airport. Individual building structures and canopy cover from several land monitoring services were used to derive accurate properties for land use classes in the study domain. To characterize the effectiveness of climate adaptation strategies, we compared changes in the climate indices for several (future) climate adaptation scenarios to the reference simulation. Specifically, we considered two major adaptation pathways: (i) an increase in the albedo values of sealed areas (i.e., roofs, walls and streets) and (ii) an increase in green surfaces (i.e., lawns on streets and at roof level) and high vegetated areas (i.e., trees). The results indicate that some climate adaptation measures show higher potential in mitigating hot days than others, varying between reductions of 2.3 to 11.0%. An overall combination of adaptation measures leads to a maximum reduction of up to 44.0%, indicating a clear potential for reduction/mitigation of urban heat loads. Furthermore, the results for the future scenarios reveal the possibility to remain at the current level of urban heat load during the daytime over the next three decades for the overall combination of measures

A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions

Environmental modeling studies aim to infer the impacts on environmental variables that are caused by natural and human-induced changes in environmental systems. Changes in environmental systems are typically implemented as discrete scenarios in environmental models to simulate environmental variables under changing conditions. The scenario development of a model input usually involves several data sources and perhaps other models, which are potential sources of uncertainty. The setup and the parametrization of the implemented environmental model are additional sources of uncertainty for the simulation of environmental variables. Yet to draw well-informed conclusions from the model simulations it is essential to identify the dominant sources of uncertainty. In impact studies in two Austrian catchments the eco-hydrological model Soil and Water Assessment Tool (SWAT) was applied to simulate discharge and nitrate-nitrogen (NO3--N) loads under future changing conditions. For both catchments the SWAT model was set up with different spatial aggregations. Non-unique model parameter sets were identified that adequately reproduced observations of discharge and NO3--N loads. We developed scenarios of future changes for land use, point source emissions, and climate and implemented the scenario realizations in the different SWAT model setups with different model parametrizations, which resulted in 7000 combinations of scenarios and model setups for both catchments. With all model combinations we simulated daily discharge and NO3--N loads at the catchment outlets. The analysis of the 7000 generated model combinations of both case studies had two main goals: (i) to identify the dominant controls on the simulation of discharge and NO3--N loads in the two case studies and (ii) to assess how the considered inputs control the simulation of discharge and NO3--N loads. To assess the impact of the input scenarios, the model setup, and the parametrization on the simulation of discharge and NO3--N loads, we employed methods of global sensitivity analysis (GSA). The uncertainties in the simulation of discharge and NO3--N loads that resulted from the 7000 SWAT model combinations were evaluated visually. We present approaches for the visualization of the simulation uncertainties that support the diagnosis of how the analyzed inputs affected the simulation of discharge and NO3--N loads. Based on the GSA we identified climate change and the model parametrization as being the most influential model inputs for the simulation of discharge and NO3--N loads in both case studies. In contrast, the impact of the model setup on the simulation of discharge and NO3--N loads was low, and the changes in land use and point source emissions were found to have the lowest impact on the simulated discharge and NO3--N loads. The visual analysis of the uncertainty bands illustrated that the deviations in precipitation of the different climate scenarios to historic records dominated the changes in simulation outputs, while the differences in air temperature showed no considerable impact.</p

Urban Heat Island Hazard and Risk Indices for Austria

This collection contains two geotiffs: the UHI Hazard Index and the UHI Risk Index, both for Austria at a 100 m resolution. The methodology for their development is described in the attached factsheets (in English and German)