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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorEvaristo, Jaivime
dc.contributor.authorPeregrina Gonzalez, Daniel
dc.date.accessioned2022-09-27T00:00:46Z
dc.date.available2022-09-27T00:00:46Z
dc.date.issued2022
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/42844
dc.description.abstractUnderstanding the spatial and temporal variability of droughts in cities around the globe is essential to adequately manage water resources and meet the needs of all urban users. As the use of hydrological models to simulate water availability over large regions of the world becomes feasible, establishing methods to turn model output into actionable insights is necessary. The use of globally available open data for drought hazard assessment based on hydrological models enables scientists and water managers to better understand how cities are affected by drought, regardless of the economic resources available to achieve this. Using metrics directly derived from hydrological model output makes it possible to maintain a high level of automation (and consistency) across cases, even when large samples of cities are assessed. In this thesis, I propose an automated approach to measure drought hazard at a city scale using a global hydrological model, apply it to four cities located in different regions, and assess the extent to which the approach can reproduce city-specific urban drought occurrences recorded in literature and a climate incident database. Results show that the approach can replicate most urban droughts reported in literature in the case study cities; however, several modelled droughts did not match drought incident records of a global database. This research expands existing hazard assessment methods by offering a fully automated approach to measure drought severity, frequency, and persistence based on modelled water storage. Additionally, it points out the practical challenges in determining thresholds for drought in cities. The developed approach can be used to achieve an initial understanding of the current drought hazard any city faces, and it sets the ground for hydrological model-driven assessment of future drought hazard in cities.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThe thesis describes an approach to quantify drought hazard in urban areas using PCR-GLOBWB 2 and Python; the approach is applied to four cities in different regions and the results are verified using satellite imagery (Google Earth Engine) and literature records.
dc.titleUrban drought hazard assessment using global open data and water balance model
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsUrban drought; climate hazard assessment; open data; hydrological models
dc.subject.courseuuWater Science and Management
dc.thesis.id10846


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