Sveriges geomorfologi har till största del bildats under den senaste glaciationens erosion och depositions processer. Vid denna glaciations avsmältning rann smältvattnet bort från glaciären i isälvarna genom tunnlar under inlandsisen. Från dessa isälvar bildas åsar när materialet som transporterats med glaciären förs med i det turbulenta flödet i isälven innan det avsätts och bygger upp dessa långsträckta terrängformer. Isälvarnas position under inlandsisen bestäms av hydrauliska potentialen vilken bestämmer rörelseriktningen för vatten under glaciären. I vissa områden kommer den ha en lägre potential och andra en högre potential beroende på isens tjocklek och formen av den underliggande terrängen. Där den hydrauliska potentialen konvergerar kommer isälvar bildas av de stora mängder smältvatten som transporteras bort. Syftet med detta projekt var att bekräfta åsbildningen i Svealand genom att göra en modellering av den hydrauliska potentialen under inlandsisen i ArcGIS. Två modelleringsalgoritmer för flödesriktning kallade D8 och D-infinity, jämfördes också för att avföra vilken av dessa som bäst modellerar smältvattnets flödesvägar under inlandsisen. Tidsintervallen 11 000, 12 000 och 13 000 år sedan valdes för denna undersökning då inlandsisen då gick från att ligga strax söder om Svealand till mellersta Svealand. Mellan 11 000 och 10 000 år sedan avsmälte glaciären väldigt hastigt och retirerade till Kaledoniderna i norra Sverige och används därför ej i denna undersökning.   I ArcGIS beräknades hydropotentialen för de olika tidpunkterna varefter sänkor i rastret fylldes upp. Flödesriktningen och flödesackumulationen beräknades för både D8 och D-infinity. Från flödesackumulationen togs isälvarna fram genom en omklassning av rastret. För att avgöra vilken flödesriktningsalgoritm som modellerade smältvattnets flödesvägar under inlandsisen bäst användes ett verktyg som summerade antalet pixlar av isälvar som låg under polygoner över nutida åsar i Svealand. Från detta beräknades en procentskillnad mellan D8 och D-infinity för att avgöra vilken av dem som stämde bäst överens med de nutida åsarna. En karta för varje tidsintervall som undersöktes samanställdes med de modellerade isälvarna och de nutida åsarna i Svealand för att visuellt avgöra om det gick urskilja en kronologisk bildningsföljd av åsarna.  D-infinity beräknades modellera isälvarna upp till 2,5 procentenheter bättre än D8. Skillnaden mellan modelleringsalgoritmerna minskade i takt med att glaciärtäckningen av Svealand minskade. I kartorna som sammanställdes gick en viss kronologisk trend att se. Vissa åsar som när de låg långt från inlandsisens kant blev inte modellerade som isälvar förrän inlandsisens kant kom närmare dem. Vissa modellerade isälvar låg inte direkt på de nutida åsarna utan lite till sidan av dem vilket skulle kunna bero på att den rumsliga upplösningen som modelleringen gjordes i var för grov eller att fler faktorer behöver tas med i modelleringen. Till exempel skulle snävare tidsintervall kunnat användas i modelleringen för att bekräfta den kronologiska bildningsföljden av åsar. Transmissivitetens koppling till den hydrauliska potentialen och avståndet mellan isälvar hade möjligtvis också förbättrat modelleringen av isälvarnas rumsliga position. / Sweden's geomorphology has largely been formed during the recent glaciation erosion deposition processes of recent glaciation. During the deglaciation, the meltwater ran away from the glacier in the channel ice streams through tunnels under the ice sheet from which eskers were formed. The position of the glaciers in the ice sheet is determined by the hydraulic potential, which determines the direction of movement of water below the glacier. In some areas, it will have a lower potential and others a higher potential depending on the thickness of the ice and the shape of the underlying terrain. In places where the hydraulic potential converges, ice rivers will be formed by the large amounts of melt water transported away. The purpose of this project was to confirm the esker formation in Svealand by modelling the hydraulic potential during the glaciation in ArcGIS. Two flow direction modelling algorithms, D8 and D-infinity, were also compared to determine which of these best models the meltwater flow paths under the ice sheet. The years 11,000, 12,000 and 13,000 years ago were chosen for this study as the ice sheet then went from lying just south of Svealand to central Svealand. Between 11,000 and 10,000 years ago, the glacier melted very rapidly and retreated to the Caledonids in northern Sweden and is therefore not used in this study. In ArcGIS, the hydraulic potential for the different time intervals was calculated, after which sinks in the grid were filled up, the flow direction and the flow accumulation were calculated for both D8 and D-infinity. From the flow accumulation, the channel ice streams were generated by a reclassification of the grid. To determine which flow direction algorithm best modelled the meltwater flow paths under the ice sheet, a tool was used that summed the number of pixels of channel ice stream that were below polygons over current eskers in Svealand. From this, a percentage between D8 and D-infinity was calculated to determine which of them best matched the current eskers. A map for each assessed year was compiled with the modelled channel ice streams, ice sheet edge and the current eskers in Svealand to visually determine whether a chronological sequence of the eskers could be discerned. D-infinity was estimated to model the channel ice streams up to 2.5 percentage points better than D8. The difference between the modelling algorithms decreased as the glacier coverage of Svealand decreased. In the maps that were compiled, a chronological trend could be inferred to a certain point. Some eskers that, when they were far from the edge of the ice sheet, were not modelled as channel ice streams until the edge of the ice sheet were much closer to them. The modelling could be improved by increasing the resolution in which the modelling was made as it might have been too coarse or that more factors need to be included in the modelling. For example, narrower time intervals could be used in the modelling to confirm the chronological sequence of ridges. The connection between the transmissivity and the hydraulic potential and the distance between ice rivers may have also improved the modelling of the spatial position of the ice rivers.

The simple accumulation-based network identification method (ANIM) in a raster Geographic Information System (GIS) posed by O'Callaghan and Mark (1984) has been criticized for producing a spatially uniform drainage density (Tarboton 2002) at the watershed scale. This criticism casts doubt on the use of ANIMs for deriving properties such as overland flow length for nonpoint source pollution models, without calibrating the accumulation threshold value. However, the basic assumption that underlies ANIMs is that convergent topography will yield a more rapid accumulation of cells, and thus, more extensive flow networks, with divergent, or planar terrain yielding sparser networks. Previous studies have focused on networks that are coarser than the hill-slope scale, and have relied upon visual inspection of drainage networks to suggest that ANIMs lack the ability to produce diverse networks. In this study overland flow lengths were calculated on a sub-watershed basis, with standard deviation, and range calculated for sub-watershed populations as a means of quantifying the diversity of overland flow lengths produced by ANIM at the hill slope scale. Linear regression and Spearman ranking analyses were used to determine if the methods represented trends in overland flow length as suggested by manual delineation of contour lines. Three ANIMs were analyzed: the flow accumulation method (O'Callaghan and Mark, 1984), the terrain curvature method (Tarboton, 2000) and the ridge accumulation method (introduced in this study). All three methods were shown to produce non-zero standard deviations and ranges using a single support area threshold, with the terrain curvature method producing the most diverse networks, followed by the ridge accumulation method, and then the flow accumulation method. At an analysis unit size of 20 ha, the terrain curvature method produced a standard deviation that was most similar to those suggested by the contour crenulations, -13.5%, followed by the ridge accumulation method, -21.5%, and the flow accumulation method, -61.6%. The ridge accumulation produced the most similar range, -19.1%, followed by terrain curvature, -24.9%, and flow accumulation, -65.4%. While the flow accumulation networks had a much narrower range of predicted flow lengths, it had the highest Spearman ranking coefficient, Rs=0.722, and linear regression coefficient, R2=0.602. The terrain curvature method was second, Rs=0.641, R2=0.469, and then ridge accumulation, Rs=0.602, R2=0.490. For all methods, as threshold values were varied, areas of dissimilar morphology (as evidenced by the common stream metric stream frequency) experienced changes in overland flow lengths at different rates. This results in an inconsistency in ranking of sub-watersheds at different thresholds. When thresholds were varied to produce average overland flow lengths from 75 m to 150 m, the terrain curvature method showed the lowest incidence of rank change, 16.05%, followed by the ridge accumulation method, 16.73%, then flow accumulation, 25.18%. The results of this investigation suggest that for all three methods, a causal relationship exists between threshold area, underlying morphology, and predicted overland flow length. This causal relationship enables ANIMs to represent contour network trends in overland flow length with a single threshold value, but also results in the introduction of rank change error as threshold values are varied. Calibration of threshold value (varying threshold in order to better match observed overland flow lengths) is an effective means of increasing the accuracy of ANIM predictions, and may be necessary when comparing areas with different stream frequencies. It was shown that the flow accumulation method produces less diverse networks than the terrain curvature and ridge accumulation methods. However, the results of rank and regression analyses suggest that further investigation is required to determine if these more diverse ANIM are in fact more accurate than the flow accumulation method. / Master of Science

Skyfall har blivit mer och mer frekventa i Sverige till följd av den globala uppvärmningen och de klimatförändringar som sker, och kraftiga skyfall kan leda till omfattande skador som ibland är svåra att förutse. Studien undersöker potentiella samband mellan skador på byggnader som uppstod vid ett skyfallsevent i Jönköping 2013 och byggnadernas omgivande topografi, hydrologi samt hårdgjorda ytor. Tidigare studier inom området har undersökt samband mellan flera variabler och skadade områden, men genom att studera topografi/hydrologi samt hårdgjorda ytor tillsammans med försäkringsdata, undersöks dessa förutsättningars påverkan mer specifikt i detta arbete. Olika stora buffertzoner runt byggnader användes för att extrahera flödesackumulering baserade på höjddata för analys av hydrologin samt klassificerad data för analys av andel hårdgjord yta. Data från hela studieområdet samt ett mindre område koncentrerat till två villakvarter studerades och på extraherad data utfördes visualiseringar, statistiska beräkningar och T-tester för att undersöka potentiella samband. Resultaten visade att den större buffertzonen på 50 m med metoden identifierar ett större antal skadade byggnader än de mindre buffertzonerna. En klassificerad hårdgjord yta kan vara användbar för att identifiera mer sårbara områden i ett större perspektiv medan flödesackumulerad data på grund av sin stora variation verkar lämpa sig bättre för analyser av mindre områden. / Due to global warming and climate change, heavy rainfalls have become more frequent in Sweden and can lead to extensive damage that is sometimes difficult to predict. This study examines potential correlations between damage to buildings that occurred during a cloudburst event in Jönköping in 2013 and the surrounding hydrology, topography and degree of surface sealing. Previous studies in the field have examined correlations between several variables and damaged areas, but by studying hydrology and impervious surfaces individually and their correlation with insurance data, their impact is examined more specifically in this study. Different sized buffer zones around buildings were used to extract flow-accumulation data and percentage of impervious surfaces. Data from the entire study area and a smaller area concentrated on two residential blocks were studied and visualizations, statistical calculations and T-tests were performed on extracted data to investigate potential correlations. The results showed that the larger 50 m buffer zone with the method identifies a larger number of damaged buildings than the smaller buffer zones. Classified impervious surface can be useful for identifying more vulnerable areas in a larger perspective while flow-accumulation data due to its large variation seems better suited for analysis of smaller areas.