Investigating Inundation Impacts Caused by Extreme Sea Level Rise at Nacka Municipality

Detta är en Master-uppsats från KTH/Mark- och vattenteknik (flyttat 20130630)

Författare: Hilfi Amri; [2017]

Nyckelord: ;

Sammanfattning: Numerous efforts have been employed to explore plausible future sea level rise range as well as improving the ice sheet dynamic that was considered as the biggest challenge in sea level projections. These results in the availability of numerous corresponding Global Mean Sea Level (GMSL), a property that exhibits the problem of deep uncertainty. In the front of deep uncertainty problems, the paradigm "predict then act" is no longer sufficient, as decision makers are prompted with the more recent framework that could encompass the latter problem, in this case, the Robust Decision Making (RDM) approach. Nacka Municipality, one of the rapid growing municipalities in Stockholm, must face future sea level rise problem under this circumstance, which requires an input to be able to act against sea level rise while also sustaining the development in the area. This work will connect three main methods to provide an appropriate flood map for robust decision-making processes, namely the localization of GMSL, extreme value analysis, and hydrodynamic models. Localizing the GMSL is done by incorporating several important aspects (i.e. Vertical Land Motion, Ocean Dynamics, and Ice Melt Dynamic). Extreme value analysis was conducted to project the extreme value of sea level and the wind according to the desired return period outcome. While hydrodynamic model will provide a more representative interaction between the phase: sea, wind and bed properties. The latter will be done using a product created from the Danish Hydrological Institute (DHI) named MIKE 21 FM. The latter features flexible mesh as the main element and allows to incorporate the momentum equation into place. Furthermore, results will be based on two scenarios: extreme and low in two different time frame, namely 2100 and 2150. Results will explore the area span of the flood as well as the potentially impacted buildings. Additionally, both scenario results will be adjoined per time frame to provide a span of flood area between the low and the extreme scenarios.

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