Floods are one of the most common types of natural disasters. They annually affect vast amounts of people and cause severe economic losses. While fluvial, coastal, and flash floods are well studied, pluvial floods (rain related) have received modest attention from researchers and decision-makers in comparison. There are several reasons for this, one is that it has been considered a fixed problem with infrastructure and other engineered solutions and another is that they are generally undramatic and small-scale. However, as cities expand, the environment’s ability to retain and dispose of excess water is inhibited and as the frequency of extreme weather events is expected to increase due to climate change, the risk associated with pluvial floods has become increasingly recognized. Commercial and open-source Urban pluvial flood models tend to require advanced modelling expertise, considerable computational power, large amounts of input data and are often expensive. Consequently, there is less knowledge of flood inundation caused by pluvial floods compared to other types. This thesis investigates the Bluespot model, which aims to provide an approachable tool to generate an overview of the effects of pluvial floods in urban areas. The model requires few input data and is relatively simple to perform. Results from the model are compared to the August 2021 flood event in Gävle, Sweden.The study finds that results ranged from accurate to over- and underestimated. Slope and incoming water were found to affect the outcome most. Blue spots without the influence of streams or other waterways, with a distinct slope were mapped with accuracy and showed consistency with coarser resolutions. Consequently, underpasses in the road network were mapped with especially good consistency. Further, blue spots within close distance to large flow accumulation were underestimated and the accuracy tended to decrease with a coarser resolution. The model cannot account for water outside blue spots, thus, when large volumes of water accumulate and spread beyond these boarders it generates poor results. These areas were found to be efficiently indicated by generating a heatmap from high-flow accumulation points. Thus, indicating low confidence and where a hydraulic flood model should be performed. Depending on the scope a 1-3m resolution is recommended for investigating effects on property etc and a 5-10m resolution is sufficient for investigating underpasses, however, a finer resolution will generate more accurate results.

Wetland ecosystems play an important role in the global hydrologic cycle, and their hydrologicregime is a major factor for their general functioning (carbon, biodiversity, biogeochemicalcycle etc.). However, the factors that govern the hydrologic regime of wetlands, such asmoisture imports into their catchments and moisture cycling in wetland areas, remain largelyunderstudied.Wetlands, seen as part of the terrestrial land, often rely on moisture imports from terrestrialevaporation and moisture recycling within their catchments. This could make them especiallysusceptible to changes in their hydrologic regime caused by land cover and hydroclimaticchanges in their catchments. Hence, this study aims to provide an overview of atmosphericmoisture imports into iconic wetlands worldwide and investigates the precipitationsheds of 40globally distributed catchments of Ramsar wetlands.Here we show that some of the wetlands have already been affected by precipitation changescaused by land cover changes within and outside of their catchments, as well as hydroclimaticchanges. According to our analysis, most of the studied wetland catchments show decreases inannual terrestrial precipitation, which are caused by precedent land cover changes. Thestrongest effects are seen in (sub)tropical wetlands in South America, Africa and Asia, andcatchments whose precipitationsheds include large agricultural areas.This shows that land cover changes can cause wetlands to be less resilient under current andfuture hydroclimatic and land cover changes. An overlap of multiple stressors, like climatechange and precipitation changes through land cover conversions, make wetlands in someregions especially vulnerable.Based on our results, current wetland decline rates and predictions of future agricultural andurban expansion, we find that wetland sites in China, India, South America and Sub-Saharanare especially threatened. This study indicates further that we have to incorporate downwindeffects to land cover changes in sustainable ecosystem management approaches.

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