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Abstract. The propagation of spatio-temporal errors in precipitation estimates to runoff errors in the output from the conceptual hydrological HBV model was investigated. The study region was the Gimån catchment in central Sweden, and the period year 2002. Five precipitation sources were considered: NWP model (H22), weather radar (RAD), precipitation gauges (PTH), and two versions of a mesoscale analysis system (M11, M22). To define the baseline estimates of precipitation and runoff, used to define seasonal precipitation and runoff biases, the mesoscale climate analysis M11 was used. The main precipitation biases were a systematic overestimation of precipitation by H22, in particular during winter and early spring, and a pronounced local overestimation by RAD during autumn, in the western part of the catchment. These overestimations in some cases exceeded 50% in terms of seasonal subcatchment relative accumulated volume bias, but generally the bias was within ±20%. The precipitation data from the different sources were used to drive the HBV model, set up and calibrated for two stations in Gimån, both for continuous simulation during 2002 and for forecasting of the spring flood peak. In summer, autumn and winter all sources agreed well. In spring H22 overestimated the accumulated runoff volume by ~50% and peak discharge by almost 100%, owing to both overestimated snow depth and precipitation during the spring flood. PTH overestimated spring runoff volumes by ~15% owing to overestimated winter precipitation. The results demonstrate how biases in precipitation estimates may exhibit a substantial space-time variability, and may further become either magnified or reduced when applied for hydrological purposes, depending on both temporal and spatial variations in the catchment. Thus, the uncertainty in precipitation estimates should preferably be specified as a function of both time and space.

The Austrian school of economics is an unorthodox approach to economics whose adherents have mostly been libertarian in their political outlook. This dissertation explores the connections between Austrian economic theory and libertarian political philosophy, and casts doubt on the claim often propounded that Austrian economics itself naturally leads to libertarianism. Instead it is claimed here that Austrian economics is an open-ended theory that can lead to very different political conclusions, depending on the normative principles with which it is combined. Therefore it is crucial to analyze both the economic theory and the ethics of any political thinker of the Austrian school, and the bulk of the analysis must lean on the latter since the economic theory itself does not lead to the types of libertarianism that is put forward by the most famous economists and philosophers of the Austrian school. The ethical theories of four Austrian school proponents are analyzed in this dissertation: Ludwig von Mises, F. A. Hayek, Murray Rothbard and Hans-Hermann Hoppe. The conclusion is that there are several problems with their theories, although the problems are of different kinds, ranging from metaethics to empirical application and operationalization.

Abstract. As the risk of a forest fire is largely influenced by weather, evaluating its tendency under a changing climate becomes important for management and decision making. Currently, biases in climate models make it difficult to realistically estimate the future climate and consequent impact on fire risk. A distribution-based scaling (DBS) approach was developed as a post-processing tool that intends to correct systematic biases in climate modelling outputs. In this study, we used two projections, one driven by historical reanalysis (ERA40) and one from a global climate model (ECHAM5) for future projection, both having been dynamically downscaled by a regional climate model (RCA3). The effects of the post-processing tool on relative humidity and wind speed were studied in addition to the primary variables precipitation and temperature. Finally, the Canadian Fire Weather Index system was used to evaluate the influence of changing meteorological conditions on the moisture content in fuel layers and the fire-spread risk. The forest fire risk results using DBS are proven to better reflect risk using observations than that using raw climate outputs. For future periods, southern Sweden is likely to have a higher fire risk than today, whereas northern Sweden will have a lower risk of forest fire.