Due to climate change, extreme phenomena like droughts are going to be intensified. Even though droughts in agriculture have been studied, regarding urban environment their consequences are rather unexplored. Cities are susceptible to droughts and the estimation of their vulnerability is the first step for their protection. The objective of this thesis is to determine vulnerability of cities to groundwater and soil moisture droughts. Since drought is a complex phenomenon which is difficult to define, its analysis is not straightforward especially in cities. For that reason, an urban drought categorization framework is created. In the current research, two of the four drought categories were studied (groundwater and soil moisture droughts). A case study for the vulnerability calculation was chosen for Leiden, the Netherlands. Before determining its vulnerability, different techniques to identify drought exposure characteristics were investigated. More specifically, regarding deficit and duration, the following methods were used: (i) fixed, (ii) variable, (iii) moving window method, and (iv) median groundwater level as threshold for the case of groundwater droughts. Spatial analysis was performed to estimate the areal extent of droughts whereas frequency distribution analysis is assessed of the minima of monthly blocks. A similar approach was applied for soil moisture droughts. Soil moisture is modeled via the lumped Urban Water Balance Model. Vulnerability was estimated as the aggregation of exposure and sensitivity (physical and social). For both components of vulnerability, their indicators were normalized. Out of the four drought characteristics (deficit, duration, spatial extent, and frequency), only the two first were included as exposure indicators for the vulnerability estimation. The indicators' weights were computed using the Analytical Hierarchy Process (AHP). Vulnerability estimation was applied for both groundwater and soil moisture droughts separately. One of the main results is that variable threshold performance is higher than fixed threshold and moving window for deficit and duration estimation regarding groundwater droughts. However, a combination of fixed and variable threshold can provide a profound insight into drought exposure. That applies to soil moisture droughts too. To increase performance of deficit and duration identification, pooling can be applied. An inter-event time of around 10 days for the case of variable threshold and 30th percentile is suggested regarding groundwater droughts. The analysis on soil moisture droughts was not sufficient to draw conclusions regarding inter-event time. Vulnerability follows sensitivity patterns - rather than exposure pattern - for both groundwater and soil moisture droughts at both fine and coarse space resolution. Besides, out of all indicators used, those which contribute to vulnerability variation the most were determined for both studied types of droughts. Those indicators are: `land use' and `percentage of households belonging to the lowest 40% income nationwide' for groundwater droughts whereas for soil moisture ones, it is `green areas'. Another result is that the differences in vulnerability vary marginally using different techniques to identify drought events for both studied types of droughts. Therefore, even applying a sophisticated technique to identify drought events, will not lead to significant improvement regarding vulnerability estimation. All aforementioned conclusions regarding vulnerability are highly uncertain since drought experts assigned different indicators' weights; the convergence of opinions was low. Based on the proposed methodology, water managers would be able to determine vulnerability of cities to droughts and policy makers would be able to protect the regions which are highly vulnerable. Consequently, the adverse impacts of droughts on cities could be mitigated, reducing residents' hardship.

This research aims to identify the key stakeholders, explain factors that influence water, sanitation, and hygiene (WASH) behaviours, determine the chance of bacterial contamination in water, and hygiene and sanitary practises in East Sumba. The interview results show that DinKes (health agency), PAMSIMAS (rural water company), and the village board are the key players that connect the upper administrative units to the local communities. The data obtained also show that the root causes that influence the WASH condition are low education level, upbringing norms, weak economy, and geography. The water quality testing results show that in terms of E. coli 14% and 12% of the respondents had a high chance of contamination in their water source and household respectively. These numbers are 25% and 29% in terms of total coliforms. Approximately 59% respondents still use poor sanitation facilities, which includes open defecation (33%) and unimproved latrines (26%). The other 14% respondents are listed under limited sanitation service, and 27% of the respondents had their own toilet, however, it is difficult to conclude if these people fall under the basic or safely managed category of sanitation services.