A green-blue roof consists of a water storage layer with on top a substrate layer covered with vegetation. Due to the presence of the water storage layer, a green-blue roof is better capable of retaining heavy rain events. A movable valve makes it possible to manage the amount of water on the roof and the timing of drainage from the roof to the sewer system, while in addition the stored amount of water is made available to the vegetation layer via a passive capillary irrigation system. This could potentially result in a higher evapotranspiration rate and therewith a reduction of the sensible heat flux compared to green roofs. Because of its qualities, green-blue roofs have been added to the list of measures that contribute to mitigation of the Urban Heat Island (UHI) effect and pluvial flooding. However, during dry summers a third climate related challenge arises namely drought. The question arises whether it is sustainable to increase the amount of vegetation in cities, as this increases the water demand during droughts. During long dry spells it can be challenging to store enough water for vegetation and cooling while keeping sufficient empty storage available at the same time. A conflict in water related functionalities of the roof is the result. It was the aim of this thesis to investigate how implementation of green-blue roofs can be made climate resilient by defining its strengths and weaknesses regarding temperature management and water consumption and come up with possible ways to improve the roof system. By conducting a measurement campaign in the summer of 2020, it was investigated if the presence of a water storage layer indeed enhances the cooling effect of a green-blue roof on the indoor and outdoor environment. Thermal fluxes at a green-blue roof and a conventional black roof were analysed, as well as two situations with either an empty of full water storage layer at the green-blue roof. Furthermore, a bucket model was designed to study the climate resilience of green-blue roofs for the climate scenarios of the KNMI for 2050. Based on the results, it is concluded that additional adaptation measures are required to make sure green-blue roofs can still contribute to a better and more resilient urban area towards the future. Several measures are available to improve the performance on water retention and drought resilience, like valve management, enlargement of the storage capacity on the roof or on ground level and irrigation. Closing the water cycle locally is important to make green-blue roofs self-sustainable in water consumption, which reduces the risk on conflicts on water use during droughts. Only regarding UHI mitigation, other measures like creating shade could be more efficient as the enhanced cooling of the urban area due to unlimited water availability is small, unless largescale application of green-blue roofs.

The Kathmandu Valley in Nepal is facing the combined effects of population growth, rapid urbanization, economic development, and climate change. This results in serious water management challenges: growing freshwater demands, declining water tables, drying of streams, and deteriorating water quality. Insufficient surface water supplies have led to increased reliance on groundwater, especially during the dry winter and pre-monsoon seasons (November - May). Despite groundwater’s importance, it is sparsely measured, poorly understood, and insufficiently managed. As it is difficult and costly to measure all groundwater extractions in the Valley, a water balance approach is an alternative method to estimate total net groundwater pumping. Therefore, the aim of this research was to develop and evaluate potential methods for quantifying total pre-monsoon baseflow supplies by extrapolating baseflow measurements of a subsample of watersheds to unmeasured watersheds. Estimated baseflow was used, together with other water balance fluxes and changes in storage, to evaluate net groundwater pumping in the Valley. Three different methods were used: (1) Spatial Analysis, (2) Regression Model, and (3) Black Box (machine learning). All methods relied on streamflow data from 2017 to 2019, collected by citizen scientists from S4W-Nepal. Based on the three methods we presented, we cautiously conclude that it is possible to determine the pre-monsoon baseflow contributions from a sub-sample of head water catchments. Total baseflow estimates for the Valley using Spatial Analysis, Regression Model, Black Box were 2.32, 2.30, 2.65 m3/s respectively. These values show orders of magnitude that correspond with expected values. By using the average baseflow values of all three methods, we were able to close the water balance and make an assumption for the net groundwater pumping in the Valley. Based on a population of 3.5 million, a net groundwater extraction of 96 L/person/day during pre-monsoon was found. This striking outcome emphasizes the need for more discharge and groundwater extraction measurements, to decrease the uncertainties and to refine the methods.

Like other cities in Kathmandu Valley, Bhaktapur faces rapid urbanisation and population growth. Unsafe, new settlements are partly located at the floodplains and the government lags behind in implementing proper land-use policy to control unrestrained settlement. The rivers are not only constrained by uncontrolled settlements, but also by insufficient width and freeboard of bridges, and waste blockages causes problems. Combined with more extreme rain events during the monsoon due to climate change, flooding has become a reoccurring problem in Bhaktapur. To gain better understanding of the river and the corresponding flood risk, historical data is essential. Unfortunately, historical databases of water levels are non-existent for this river. Only starting from monsoon 2019, water levels and discharge have been measured on a regular basis. To reconstruct the missing historical data for a return level analysis, this research introduces the Classical Model for Structured Expert Judgment (SEJ) in combination with citizen science (CS). The objective of this research was to use Structured Expert Judgment in a flood risk analysis for the city of Bhaktapur. As a result of using SEJ, we were able to obtain sufficient water level data and estimate the return levels of extreme water levels of Hanumante river by fitting a Generalized Extreme Value distribution (GEV). This eventually led to a reverse Weibull fit, which in this case does not seem accurate. This research discusses in detail the advantages and issues of using Structured Expert Judgement in situations like this and also discusses the reliability of the results.

The goal of this research is to get a better understanding of the long-term changes of the river profile and bed composition of the Dutch Rhine for the coming 300 years, based on the effects of different changing boundary conditions. The focus is mainly on the following two hydrodynamic boundaries: sea level rise and more extreme discharge.

To study large-scale patterns in the environment, like for example the change of water quality, a constant amount of data over an array of locations and time is required. However, in Myanmar only little data is available about water related topics which makes it hard to monitor changes that are taking place. A relative new and cheap way of obtaining and collecting data is the use of citizen science or participatory monitoring. Therefore this project investigates if there is any support among the citizens of Myanmar to join participatory monitoring projects and to find out more about the different underlying motivations for people to participate. This research is done by making use of an interview method based on Q methodology and did not only focus on the different reasons for people to participate but it also checked whether the motivations of people differ for different groups in society by making a distinction in age, education level, geographical location and interest. The overall view is that people in Myanmar are open towards joining projects like this. Many young people seemed interested in the concept of participatory monitoring, also because this relative new method to collect information clearly involves normal people like them within projects in which they normally wouldn't get involved in that easily. The implementation of participatory monitoring does not need to cost a lot, since most citizens add little value to receiving payment or certificates in return for collecting measurements for the project. When there is enough attention for the social importance of the research and the 'duty of being a citizen' is emphasized, it must be possible to find a sufficient amount of volunteers that are willing to participate. But while the outcome seems quite positive, there are still a lot of questions that need to be answered, so future research is recommended.