Climate change poses increasing challenges to urban environments, with rising temperatures, sea-level rise, and altered precipitation patterns contributing to both flooding and drought. While much research has been dedicated to flood mitigation, urban drought has received comparatively less attention, despite its significant impact on vegetation, water availability, and overall ecosystem stability. The Paris Agreement of 2016 aims to limit global temperature increases, yet urban areas continue to experience extreme weather variations, necessitating a deeper understanding of their hydrological implications.

This thesis investigated the influence of urban environmental conditions on soil moisture dynamics, particularly during drought periods. The study aims to identify the relationship between green spaces in urban areas and soil moisture dynamics in relation to drought. It specifically examines how factors such as sun, shadow, vegetation type, and soil texture impact soil moisture retention and depletion. To achieve this research goal, the following three research questions are determined:

\begin{enumerate}[noitemsep]
\item How do urban environmental conditions affect soil moisture content in green spaces?
\item What is the effect of soil texture on soil moisture dynamics?
\item How do initial soil moisture conditions influence soil moisture dynamics during a drought period, as modelled using HYDRUS-1D?
\end{enumerate}

The study employs a combination of field measurements and HYDRUS-1D modelling, to analyse the soil moisture behaviour under different urban environmental conditions. Data collection took place at the campus of Delft University of Technology, where five distinct environmental conditions were selected as measurement points, sun, shadow, grass, trees and paved areas.

Soil moisture data was collected using the Profile Probe PR1 sensor (in combination with the HH2 Moisture Meter) at depths of 100mm, 200mm, 300mm, 600mm and 1000mm. Measurements were conducted manually over 10 weeks, 3 to 4 times a week, during the summer of 2024, with a total of 33 recorded sessions. Soil texture analysis was conducted using soil samples taken from depths of 150mm, 300mm, 500mm and 800mm. These samples were dried at 105$\degree$C for 24 hours and then sieved through six mesh sizes to determine the proportion of sand, silt and clay in each sample. The soil texture provided understanding of changes in soil moisture dynamics and was used for the critical input data for the HYDRUS-1D simulations.

HYDRUS-1D was employed to model the impact of initial soil moisture conditions and urban environmental conditions on the soil moisture dynamics during longer periods of drought. The model setup included defining soil hydraulic properties using the van Genuchten-Mualem equation and incorporating root water uptake parameters based on the Feddes approach. Monte Carlo simulations were conducted to optimize model performance, using 10.000 iterations to determine the best fitting parameters. The model was then applied to simulate soil moisture depletion during the extreme drought of 2018, to determine the effects of extremely wet or dry initial soil moisture conditions.

The measured soil moisture content results demonstrate significant variations in soil moisture retention among different urban environment conditions. Areas covered with vegetation exhibited higher moisture retention compared to paved surfaces. Within vegetated areas, shaded locations retained moisture for longer periods due to reduced evaporation rates. In contrast, measurement points in sunny areas experienced rapid soil moisture depletion, particularly in the upper 300mm of the soil.

Soil moisture at shallower depths, 100mm to 300mm, was highly responsive to precipitation events, while the deeper layers, 600mm and 1000mm, exhibited more stable moisture levels, indicating a stronger influence of soil texture and groundwater interactions. Statistical analysis using Kendall's and Spearman's correlation coefficients showed strong correlations between shaded grass-covered areas and tree-covered sites up to 300mm depth, but significant divergence beyond that, likely due to differences in root water uptake and soil texture.

Additionally, paved areas consistently maintained lower soil moisture levels across all depths due to limited infiltration, with only minor variations observed at the access tube edges where small gaps allowed some water entry. The modeling results confirmed that urban design choices, such as increasing permeable surfaces and optimizing vegetation placement, can significantly enhance urban resilience to drought.

Soil texture played a crucial role in soil moisture availability, with finer-textured soils (such as silt and clay) demonstrating superior retention capabilities compared to sandy soils, which facilitated rapid drainage.

Modeling results from HYDRUS-1D reinforced these findings, showing that initial soil moisture conditions had a notable influence on drought resilience. Wetter initial conditions resulted in prolonged moisture availability, while extremely dry conditions led to rapid soil desiccation. The impact of extreme initial soil moisture states was most pronounced in shaded grass areas and tree-covered locations, where higher retention capacity helped delay drought effects.

The study's findings align with existing literature on urban drought dynamics, confirming that meteorological, agricultural and hydrological drought factors interact to shape soil moisture behaviour. Meteorological drought, characterized by prolonged low precipitation, was found to be a primary driver of soil moisture deficits, with its effects compounded by urban environmental conditions. The research underscores the critical role of green infrastructure in mitigating the adverse effects of drought by preserving soil moisture.

The limitations of the study are acknowledged, including the constraints of the HYDRUS-1D model, which assumes only vertical water flow and does not account for lateral redistribution. Additionally, the generic settings of the Profile Probe PR1 resulted in soil moisture values not specifically related to the soil type. Finally, only one drought event has been evaluated in the model, limiting the generalizability of the findings.

This research provides valuable insight into the interplay between urban environmental conditions and soil moisture dynamics during drought periods. The findings highlight the importance of green spaces in urban resilience to drought, demonstrating that shaded and vegetated areas significantly enhance moisture retention compared to exposed, paved environments. Soil texture and initial moisture conditions were identified as key determinants of drought response, with finer-textured soils and wetter initial states offering greater resilience.

The study emphasizes the necessity of integrating soil moisture considerations into urban planning and climate change adaptation strategies. Enhancing green infrastructure, optimizing soil management practices, and incorporating soil moisture monitoring into urban water management can help mitigate the impacts of future drought events. Future research should focus on expanding the dataset across multiple urban locations and improving model accuracy by integrating groundwater dynamics and lateral water flow processes.

The inspection of extensive and hard-to-access sewer systems is a challenging and expensive task. As these networks age and need to comply with stricter health and environmental regulations, the demand for effective inspection solutions has increased. The introduction of technologies like CCTV (closed-circuit television) and SSET (sewer scanner and evaluation technology) marked the initial automation steps in sewer inspections. Initially, images from these technologies were manually analyzed for defects, but over time, computer vision techniques have emerged as a highly promising method for automating image processing. However, these advanced computer vision methods are computationally intensive and typically rely on cloud-based architectures, which can be costly and sometimes impractical due to energy or communication limitations. A proposed solution is to shift the computational processes from the cloud to edge computing, which can address issues related to latency and scalability.

The Sewer-ML dataset, sourced from sewer inspection videos by Danish water utilities, comprises 1.3 million images annotated across 18 defect categories. This extensive multi-label dataset serves as a foundation for training and evaluating machine learning models within sewer system management. Model performance is evaluated using the $F2_{CIW}$ (class importance weight) score, which emphasizes recall and defect severity to ensure the accurate detection of critical defects, and the $F1_{Normal}$ score, which measures the model’s accuracy in identifying instances without defects, essential for efficient resource management.

The ResNet-101 and TResNet-L models, trained on the Sewer-ML dataset, underwent various compression methods including quantization, layer fusion, and pruning. Quantization was applied only to the ResNet-101, reducing its $F2_{CIW}$ and $F1_{Normal}$ scores by 2.52\% and 0.72\% respectively, while significantly boosting inference speed by up to 95\% on standard platforms and 174.50\% on L4 GPUs. Layer fusion was also implemented, further enhancing inference efficiency. Additionally, iterative pruning was performed, showing that while the TResNet-L could maintain performance up to an 80\% pruning rate, there was a noticeable initial drop in performance for both models.

The quantized ResNet-101, both the one with and without layer fusion,
even improve compared to the standard model in regards to correctly identifying
the highest CIW defect class present in pipes deemed defective in the validation
dataset. This model behaviour is positive because the priority of a sewer asset manager is the discovery of the defect that carry the highest risk with them if not treated
in time. This improved efficiency in defect recognition helps in optimizing repair
schedules and resource allocation, thus reducing operational costs as well.

In recent years, Sustainable Urban Drainage Systems (SUDS) have gained popularity for managing stormwater in urban areas. However, effective asset management of these systems remains challenging due to the widespread reliance on reactive maintenance. This thesis examines the condition of dry swales in Utrecht, Netherlands, and their role in managing stormwater under the municipality’s current maintenance framework.

A comprehensive visual inspection of 210 dry swales was conducted, alongside an evaluation of the area characteristics influencing component failures. The results indicate that only 67% of the swales function properly, with overflow failures being the most common issue, particularly due to clogging; 5% of swales were found to be in a failure state. Conversely, the vegetation layer emerged as the component requiring the most continuous maintenance, with only half of the swales sustaining a well-functioning vegetation layer. Notably, complete clogging issues in swale overflows were linked to a high percentage of impermeable areas within the catchment and a smaller length-to-width scale.

The analysis further revealed that filter basins exhibited the highest percentage of functioning components, emphasising the critical role of the infiltration process. However, even minor deterioration in these basins could significantly impact overall swale performance. The study also identified that a larger impervious area within a swale’s catchment correlates with increased failure likelihood in various components. Factors such as tree density in a catchment area, impervious area, and the age of the swales were shown to contribute to issues like standing water and sediment accumulation in filter basins.

The investigation into sediment accumulation at overflows indicated that sediment tends to build up more in catchment areas with higher percentages of impermeable surfaces, although this phenomenon is influenced by multiple factors that warrant further research.

The findings underscore the necessity of improving the current reactive asset management of swales. By establishing a comprehensive database of inspection data, future research can better inform predictive asset management applications, incorporating parameters such as impervious area percentage, tree density, and swale age into machine learning models to predict swale failures.

Ultimately, the research emphasizes the importance of effective asset management for SUDS, not only to enhance swale efficiency but also to mitigate urban flooding risks. Regular inspection and monitoring are essential to understanding swales’ functionality and degradation over time, informing design improvements and promoting the adoption of sustainable urban drainage systems. This study contributes to the broader goal of creating more resilient and sustainable urban environments through robust asset management of SUDS.

This thesis aims to assess the applicability of the CRCTool for evaluating the effectiveness of NBS for mitigating tropical urban floods in the city center of Paramaribo. Assumptions related to urban flood mitigation were tested, a sensitivity analysis for the most sensitive parameters was performed, and the hydrological behaviour of groundwater processes, evapotranspiration, and percolation were critically assessed. In addition, the model outcomes were compared to a hydrodynamic model, developed in D-HYDRO, to determine the importance of spatial effects such as flow routing and elevation. It was found that the current state of the CRCTool restricts its applicability to areas with low rainfall and runoff volumes. The continuous modelling capabilities are limited due to the way hydrological fluxes are implemented. Minor model adjustments can be made to make the tool more suitable for areas with larger rainfall volumes. This research recommends implementing these adjustments and thoroughly testing the tool's performance. Additionally, to minimize the impact of flow routing and elevation, it is advised to test the tool on smaller areas where the hydrological conditions are more clearly defined.

Curaçao's coral reefs are subjected to a deteriorating momentum risking the health and therefore sustainability of this vital ecosystem. Despite the dependency of the Island's prosperity on the condition of the ecosystem, research suggests that wastewater management is likely to be a significant contributor to this effect. Incorporating both open literature results and information obtained from an extensive constructed research network, this study demonstrates essential aspects of the urban wastewater management system of Willemstad regarding the quantity and quality of the urban wastewater fluxes and their potential environmental implications. The system, which merely connects 33\% of Curaçao's population, is concluded to be outdated and insufficient with respect to capacity as well as treatment efficiency. Although it is solely designed for pure domestic wastewater, this study concluded and demonstrated the significant impact of illegal discharge onto this system by industrial sectors leading to both high contamination loading and increased wastewater volumes. The combination of these features is the major cause of wastewater discharge pathways into marine environments. Arising from the constructed urban wastewater flux model, which visualizes the wastewater management system, 14 discharge locations correlated to significant environmental contamination pathways are identified with Piscadera Bay, Rif Mangrove area, Playa Kanoa and Shut concluded as the utmost importance. Furthermore, the model revealed that the urban wastewater is predominantly directed towards the treatment plant Klein Hofje via either the northern trajectory (Bonam - Suffisant F - Garipitoweg - Argentianweg - Klein Hofje) or the southern one (SVB - Klein Hofje). Also, the quantity and quality of the fluxes are estimated based on the connected area and the potential industrial activities within it. However, validation of these estimations is recommended since no water quantity and quality analysis was performed or available for conducting the modelled estimations. Furthermore, since the system is partly a combined sewage system, hence harvesting stormwater fluxes as well, its effect is recommended to incorporate in the model and estimations for accuracy purposes. Lastly, the government reports that at least 90\% of all industrial wastewater is discharged either directly into the ocean or onto the sewer system. Since the actual ratio as well as the water quality remains unknown this is recommended for future research. Overall, this study enables tailored future research programs to overcome the discussed limitations and with that significantly contribute to eliminating the current existing white spot concerning the effect of urban wastewater fluxes on the marina ecosystem of Curaçao.

Urbanization has led to increased impermeable surfaces, disrupting the natural hydrological cycle and resulting in more frequent urban flooding and pollution. There is an urgent need for cost-efficient and effective stormwater management solutions to improve stormwater quality and facilitate its reuse. FieldFactors' BlueBloqs system integrates stormwater collection, water treatment in a biofilter, and aquifer recharge. The BlueBloqs system's biofilters are soil-plant systems with a submerged zone. Before being used to recharge an aquifer, the effluent from a biofilter must meet specific water quality standards. Improvements in water quality within the biofilter are achieved mainly through static optimization (changing media materials, the depth of layers, and plant species) and dynamic optimization (controlling hydraulic behavior). Some research found that retention time plays a crucial role in the operation of a biofilter, influencing both the quality and quantity of the effluent. The central challenge lies in operating the biofilter's retention time to maximize water recharge while ensuring optimal water quality.

The objective of this research is to determine the optimal retention time for the biofilter to achieve the best water quality while maximizing the total amount of water to be recharged by controlling the pump. This thesis includes water quality measurement and water quantity simulation. In the water quality part, the performance of the biofilter at different retention time (2, 6, 16, and 24 hours) is evaluated in terms of the removal efficiency of turbidity, nutrients (nitrate and phosphorus), dissolved and particulate metals (Mn, Ca, Mg, Ba, Zn), UV254 and DOC with two different influent types (surface water and stormwater). In the water quantity part, Cromvliet Park, with an 8000 m2 collection area, was modelled using Python and SWMM to operate the biofilter with various retention time under one year of rainfall data (total rainfall 731mm). This modelling was done to calculate the total water volume available for recharge. The sections on water quality and quantity were integrated by controlling and evaluating the biofilter based on the retention time.

The results indicate that the efficiency of the biofilter's pollutant removal is influenced by several factors. Turbidity (40-90%) is effectively removed by the filtration in the biofilter. Nitrate removal efficiency was 12-49% with short retention times (2-6 hours) but fluctuated with longer durations (16-24 hours), decreasing to -84-13% and then changing to -6-0%. Measurements of dissolved oxygen in the effluent indicated that an increase in nitrate removal efficiency due to nitrification happened with longer retention time. For dissolved zinc, removal efficiency ranged from 10-60% with stormwater influent and 0-100% with surface water because of the adsorption competition of metals. Combined with the water quantity calculations performed in SWMM, it is advisable to set the optimal retention time for the biofilter at 4–6 hours. This duration allows for the maximization of water reuse while maintaining high nitrate removal efficiency.

This research analyses and evaluates the performance of the drainage system in Beira, Mozambique. It considers its formation, maintenance, failure modes and connections, to recommend improvements on its performance. The research identifies six primary failure modes - vegetation overgrowth, human interference, waste accumulation, sedimentation, underdimensioned structures and ’other’ - highlighting the disparities between technical design and real-world complexities. The study quantifies the presence of these failure modes by direct observations and transect walks, and uses hydraulic modeling software, D-FLOW FM 1D2D, to simulate their impact on inundation depths.

The results show that widespread flooding can be found even without failure modes. Additionally, it prioritises the risks of vegetation and human interference. Therefore, it recommends an increase of hydraulic capacity of a part of the system, proactive vegetation management, water level control, and community engagement in system management. It also underscores the importance of early land demarcation in urban planning, the implementation of flexible yet delineated canals, and the involvement of communities in flood adaptation.

This research explores the frequent urban flooding problems typically experienced in South-East Asian cities. Heavy rainfall during the monsoon period in combination with rapid urbanisation in the past decades causes an increasing amount of inundation events in the case study area Hanoi. The damage caused by these floods results in major economic losses that affect local citizens as well as governmental authorities. Flood waters are often heavily polluted with sewer water, threatening public health
and reducing the overall livability of Hanoi. In addition, inundated streets are difficult to navigate, and waves induced by vehicles can lead to dangerous situations for pedestrians and other road users. This research aims to have a better understanding of the failure mechanisms of Hanoi’s drainage system, and the risks associated with each mechanism. Since there is no standard methodology for probabilistic risk assessment of urban drainage systems, the methodology for levee assessment was adopted and adjusted to the field of urban drainage. This straight-forward method is transferable to other study areas and results in clear and comprehensive fault trees which are easily interpreted by drainage authorities.

A combination of expert judgement, qualitative fieldwork and analysis of newspapers was used to obtain an overview of all failure mechanisms and presented in the form of a fault tree. To investigate the potential damage that could be done by each failure mechanism, a probabilistic risk assessment was done using the urban drainage modelling software PCSWMM, and the potential risk of each mechanism was quantified. For the mechanisms with an unacceptably high risk, potential solutions were proposed. Four failure mechanisms were found that pose an unacceptably high risk on the drainage system: increased catchment size, pipeline blockage, inaccessible drains, and design inaccuracies. Potential solutions are to incorporate Low Impact Development (LID) in the urban area such as green and blue roofs, infiltration trenches and rain barrels. This type of infrastructure reduces the hydraulic load on the drainage system by reducing the runoff peak. In this way, urbanisation goes hand in hand
with preserving the natural flows. Other recommended solutions are to revise the cleaning schedule to make it more efficient, and raise awareness among local inhabitants to enlarge their role in the functioning of Hanoi’s drainage system.

From 2018 to 2020, the city of Breda (NL) faced drought, with significant economic losses and water scarcity problems. The water board within which the city is located began to consider new possible water management practices, due to the unsustainability of the current ones. This study aims to investigate how a change of the current paradigm can improve the current approach in water management, shifting from a linear to a water management circular approach, and from command-and-control to adaptive. Starting from the case scenario of Breda, the study considers how through the reuse of management wastewater treatment plant effluent and stormwater, and the application of sewer mining units, it may affect the circularity and adaptability of the system. Then, based on Breda's experience, an attempt is made to investigate the concepts of circularity and adaptability. \\To be able to understand the current water situation and approach in the city of Breda, a water balance for the year 2020 was drafted. The water balance for 2020 for the city of Breda shows a positive value of 50 mm/year. The definitions of circularity and adaptability for a water management system were determined, and for each of the concepts a framework has been developed, to assess the level of circularity and adaptability before and after the interventions. Then, a workshop with local experts in the field was organized. Different strategies of interventions were proposed to them, in order to evaluate their suitability. Then, a final strategy was formulated, where wastewater effluent is employed as irrigation water for agriculture in the south of the municipality, stormwater discharge into wetlands to recharge aquifers and three sewer mining units in the rural area of Breda. These interventions showed a positive effect on the water system, since the volume of water stored in the system has increased, giving an overall better performance of the circularity and adaptability indicators. Moreover, the final strategy shows a better water balance of 100 mm/year. This research aims at creating a better understanding of concepts like circularity and adaptability. The study shows that there is a potential for re-using water to enhance the overall performance of the water system under certain conditions.

Sustainable Urban Drainage Systems (SUDS) are useful tools to manage rainwater and reduce pollutants in urban environments. Their use, as sustainable solutions, can mitigate the effects of climate change and urbanization. The existence of different definitions of performance is one reason for delaying more implementation of SUDS. Deciding on the Key Performance Indicators (KPIs) is one of the objectives of this thesis. WaterStreet, the chosen study area, is a living lab that permits the implementation, presentation, and testing of newly designed SUDS with the goal of facilitating their entrance into the market. WaterStreet could benefit from using sensors to provide the KPIs and other indicators of performance, but the sensors already implemented do not achieve that objective fully. So, the objective of this thesis is, to develop a comprehensive set of KPIs that describe the performance of SUDS and propose a monitoring network to measure the performance of SUDS implemented in WaterStreet.
To achieve that objective, information on the study area’s characteristics, like soil types, design of SUDS, and groundwater levels were gathered to find how water flows in, out, and around the study area including the SUDS. Additionally, the key stakeholders were determined with a stakeholder analysis, and literature was researched on the important indicators used to reflect the performance of SUDS for water quality and quantity. Interviews were performed to include the view of the key stakeholders on the indicators found in the literature. The two approaches explained above provide the data that need to be monitored on WaterStreet. Criteria for the quality of data that would be provided by the sensors are set, before concluding on suggestions. The suggested sensors and their limitations are based on results of published studies and reports.
Based on the findings of this thesis a distinction between the Key Performance Indicators (KPIs) and Indicators of Performance (IP) is made. In the first category, the indicators of overflowing volume, duration, and frequency are included along with rainfall and overflow from upstream drainage areas. In the second category the indicators, infiltration in the soil and through the first layer of SUDS, and storage in the soil and system are included. Both categories of indicators are suggested to be monitored in the study area of WaterStreet to increase the value of WaterStreet as a living lab. Indicators for water quality are not concluded due to the lack of information on the existing pollutants and their removal and remobilization mechanisms. Reduction of Total Suspended Solids (TSS) and Total Phosphorus (TP) are two possible indicators that are also considered as a proxy in Germany. Changes in pH and temperature are two indirect indicators that are found to affect the reduction and remobilization mechanisms and are therefore important to consider as well.
An acoustic disdrometer to measure rainfall, a sonar pulse sensor to measure groundwater levels, divers in an observation pipe in the system to measure the water level in the system and the infiltration in the soil, and lastly divers in a controlled volume downstream of the SUDS to measure the overflowing water downstream the SUDS, were the proposed sensors. The disdrometer and two of the sonar pulse sensors are already installed on WaterStreet while it is suggested to put divers in the individual systems and two more sonar pulse sensors. For the indicators, overflowing water from upstream and the rate of water entering the SUDS research on the runoff coefficient and the use of water balance are suggested, respectively.
An important consideration in this thesis is the characterization of hydraulic isolation from the top and bottom of the system, allowing the interpretation of the data from monitoring, to represent only one system’s response. Suggestions to include a controlled volume to capture the overflow downstream of the SUDS and a drainpipe to ensure a drainage depth of 0.5 m, are made, to help ensure hydraulic isolation from top and bottom respectively. Based on this study, only half of the systems placed on WaterStreet are isolated, not considering the possibility that the groundwater table can get even higher resulting in even fewer systems isolated. Additionally, from analyzing the hydraulic response on the SUDS in WaterStreet, it was concluded that all 5 studied systems out of 8 total were being over-dimensioned, meaning that the storage in the SUDS would not be full even with rainfall of once in 100 years. From the same analysis, it was also concluded that the infiltration through the first layer is the prevalent overflowing mechanism of 3 out of 4 studies SUDS. Both the previous findings are important to realize a hydraulic response to rainfall proportionally to real implementations. This is an essential consideration from living labs because they try to bring lab and real implementation closer. Lastly, pollutants to be used as KPIs for water quality performance of SUDS should be researched more based on the principle of not shifting problems downstream.

In the context of climate change and urbanization, sustainable urban drainage systems (SUDS) are widely adopted measures to manage stormwater in the city on-site. However, their performance in practice often differs from modelled and laboratory-scale predictions due to the variability in properties of real sediments (in terms of size, shape, density and coagulation) compared to the silicate standard Millisil®W4. Clogging is a common source of failure. 
The SediSubstrator L is a decentralized stormwater treatment device installed as a pre-treatment step to mitigate clogging in a storage and infiltration system on the Rooseveltlaan in Amsterdam. It consists of a sedimentation pipe with a flow-separating grate, the SediPipe, and a filter-adsorbent, the SediSorp+. It is purported to remove 80 % of TSS by DiBT (the technical authority in the German construction sector) test principles that use Millisil®W4 to simulate real sediments. The full-scale unit was monitored in the city throughout May-September 2022 to assess its performance. 
The stormwater runoff discharged from the catchment had high concentrations of lead (54 μg/L) and zinc (790 μg/L), likely due to contact with gutters and old roofing material, amplified by the relative contribution of these roofs to the total catchment discharge (accounting for 50 % of the area contributing to runoff). The sediment (TSS) concentration was low, equivalent to 20 mg/L on average. The sediments were also light and fine—with an organic fraction of 66 % and with 78 % of diameter smaller than 63 μm.
In the SediSubstrator L, the TSS removal efficiency was 34 % on average. This corresponds to an estimated caught load of 2.7 kg for this period. The removal efficiency was shown to increase with an increasing stormwater TSS concentration, with longer antecedent dry periods and with lower TSS organic fractions. Turbidity dynamics in the system suggest that while a net sequestration of solids occurs in the SediPipe, there is a resuspension of fine solids. This was observed in a camera inspection to occur from solids which settle on or near the grate. In an extreme rainfall event on September 28th 2022, water collected on the section of the street connected to the SediSubstrator, the cause of which is still subject to speculation. The observed SediSorp+ filter resistance across the summer was not indicative of gradual clogging, but an inspection showed signs of decayed organic matter throughout the full length of the filter bedas well as traces of cement in two of the four cartridges. It is possible that these two effects together with turbulent inflows prompted the acute clogging behavior.

There is interest in using the SediSubstrator beyond the city of Amsterdam to reduce phosphorus loadings in the road runoff discharged to sensitive nature areas. On the Rooseveltlaan, the average total phosphorus removal efficiency was 18 % (50 % for dissolved, readily bioavailable ortho-phosphate). Interactions with settled sediments generated ortho-phosphate in the SediPipe, and fine particulate and colloidal organic phosphorus was shown remobilized in both the SediPipe and SediSorp+. The removal of ortho-phosphate in theSediSorp+ in natural rainfall was good (on average 50 %) and was shown to be consistent at different contact times (approximately 10-30 minutes). 
The installed unit should be monitored over a longer time period of two years for statistical significance and to capture seasonal variation in loads. Nevertheless, the removal efficiency observed on site is consistent with the results of a sedimentation model developed according to Ferguson & Church (2004), using a stormwater sediment particle density as measured at another location in the city. Design adaptations are recommended to improve the SediSubstrator L to the conditions observed in Amsterdam: namely, better site selection, a longer SediPipe section (24 m) and a second filter stage to better capture the fine suspended solids.

Urban climate adaptation is generally attained --- in a hydrological perspective -- by implementing stormwater management techniques, such as grey, blue and green adaptation measures. Implementing such multi-functional adaptation measures touches on the interests of many stakeholders who need to work together to find resilient and suiting solutions in urban climate adaptation. To facilitate this cooperation, Deltares developed the Adaptation Support Tool. The AST defines eight different performance indicators to compare the effectiveness of urban runoff reduction measures, among which the runoff volume reduction factor. This factor is defined as the rate at which a specific adaptation measure increases the return time of the extreme runoff event. This factor is determined by the underlying model of the AST, the Urban Water Balance Model (UWBM).
The UWBM has the benefit of using long times series instead of single precipitation events (design storms) as input to determine the effectiveness of measures; antecedent conditions for every extreme event are therefore known. Currently, the UWBM is only determining the runoff volume reduction factor. At the same time, the literature shows the importance of analysing the effectiveness of measures using both flow peak reduction and storage peak reduction. Exploration of the possibility to implement these two reduction factors into the UWBM forms the challenge of this study.
This research aims to define a flow peak- and storage peak reduction factor based on modelling systems in the UWBM using long time series. Because the model describes these factors over the measure area, the second goal of this study is to investigate the possibility of converting this measure factor to a whole project area factor and combining this factor for a combination of measures. Main conclusions of this research are as follows: A flow peak reduction factor can be empirically determined based on the proposed method in this study. A storage peak reduction factor can not be empirically determined based on the proposed method in this study. It is recommended to do more research into the analysis of the storage peaks using time series, since it can give an extra insight into the effectiveness of measures. Converting the found flow peak reduction factor for the measure area to the project area with multiple interventions is substantiated with a proposed equation. However, it is recommended to do more research into the conversion equation to be used in the Adaptation Support Tool. By determining the flow peak reduction factor together with the runoff volume reduction factor, the effectiveness of urban runoff reduction measures in a project area can be quantified and used to compare alternative solutions for their effectiveness in flood risk reduction. The added flow peak reduction factor gives a more thorough insight into this effectiveness of measures.

Urban Drainage Systems (UDS) are one of the most vital yet, complex infrastructures that support people's livelihood in urban areas. However, due to their mainly underground infrastructure and complexity, the planning and management of UDS are usually associated with high investment, which stakeholders sometimes overlook. As long-lived infrastructures, UDS’s limited capability is being put under constantly increasing pressures. Amongst the pressures, the global effects of climate change on rainfall extremes is the most important. As climate change affects the rainfall extremes and the overall hourly and daily rainfall events, urban flooding issues are becoming more costly to manage. Several rehabilitation efforts have been made to address this issue with minimum cost and optimal performance in flood reduction by increasing the resiliency of UDS in order to minimise the duration and magnitude of urban flooding.

Rehabilitation of UDS can be done in several ways, including implementing Green-Blue-Grey Infrastructures (G-B-G measures). The combination of G-B-G measures can increase the resiliency of the UDS to withstand higher intensity rainfall by reducing both the peak flow and enlarging the capacity of the UDS system. Therefore, this thesis aims to develop a method to find the optimal way to rehabilitate an existing UDS to reduce the risk of flooding under the climate change rainfall scenarios.

The method developed coupled a hydrodynamic model, Storm Water Management Model (SWMM), and Genetic Algorithm (GA) to find the optimal solution to rehabilitate UDS. The effect of climate change was incorporated by simulating the solutions using composite design storms that represent the increase in hourly and daily rainfall extremes for 2030, 2050, and 2085. The objective function of this optimisation problem becomes the minimisation of the total cost to implement the measures for the rehabilitation of UDS, under the constraint that no flooding can happen on the system when tested against the climate change rainfall scenarios. Therefore, the decision variables of this optimisation are the size and location for each implemented measure, while the penalty cost is associated with the cost of each m3 of flooding.

Based on the analysis of the case study, the most appropriate Green-Blue measures to be implemented is Rain Barrels, Infiltration Trenches, and Pervious Pavements. Meanwhile, for grey measures, it is best to consider pipe and pump replacements and increasing the CSOs’ weirs. The optimisation was done using the developed formal method and manual trial-and-error. The results of the formal optimisation have been confirmed to outperform the result from manual optimisation using the traditional trial-and-error method. The optimal solutions proved that a combination of both grey and G-B measures produced the lowest cost to reduce flooding. Although the solutions can be adapted over time from 2030 until 2085, the results show that adaptive solutions might not be needed when the solution for 2085 is better implemented from the year 2030. Overall, it can be projected that in the future, the combination of G-B-G measures can produce an economically optimal solution to be implemented in order to achieve zero floodings in the case study location.

Due to the predicted impacts of climate change on the frequency of storm events, water managers are challenged to improve and adapt the current urban infrastructure. Cities need to be able to deal with the adverse effects due to more frequent and heavier rainfall. This implies the need for sustainable urban drainage systems (SUDS) that can deal with these challenges. SUDS can be seen as designs that can improve both, the quantitative as well as qualitative characteristics of stormwater. The study area in the south of Amsterdam will be equipped with a SUDS, namely a SediSubstrator L by Fränkische Rohrwerke. The objective is to remove particles from stormwater discharge to prevent clogging of the infiltration facility (AquaBASE) installed in sequence. Additionally, it can remove harmful pollutants which are adsorbed to the fine particles.
This research aims to investigate the characteristics of the sediments in stormwater in theory and develop an appropriate sampling strategy to monitor the relevant parameters in the field. The long-term objective hereby is to determine the removal efficiency of the SediSubstrator L using a finite amount of parameters. To do so, a threefold approach composed by a detailed literature review, stormwater sediment sampling as well as a model simulation was used.
Based on the identified parameters to be assessed, a specific monitoring and sampling setup is proposed to determine the removal efficiency of stormwater sediments in the study area. Along with the efficiency, the volume of sediments that are caught by the facility can be approximated. The latter needs to be removed once the entire storage volume of the sedimentation facility is filled. It is recommended that Waternet uses measured stormwater data to improve the model, while monitoring the efficiency under field conditions. Once the results of the model and the actual field measurements match, the model can be used to simulate the sediment removal for long time series. In this way the cleaning intervals can be predicted, while avoiding expensive long-term measurements to do so.

As climate change takes hold, extreme weather events increasingly pressure the performance of the railway infrastructure. A first insight has been obtained into the impacts of climate change for the train system and the railway network, but there are almost no studies on the impact of our changing climate on railway stations. This study therefore aims to provide insight into the risks of climate change-induced hazards for railway stations in The Netherlands and the associated effects on the functionality of the station for passengers. Scenarios of climate change show that the Netherlands will experience increasingly intense rainfall, dryer, hotter summers and warmer, wetter winters. This poses a number of risks to the operation, reliability, availability and safety of train stations in a country with the busiest and densest rail network of the European Union. In this study, a method was created to study the risks of climate extremes for train stations on the basis of thirteen identified threats, and risk matrices were developed to support ProRail in defining their attitude towards climate risks. Results show that Dutch railway stations are vulnerable to climate change and demonstrate that there are many aspects of climate change at stations that require attention. The most important nodes in the station network, and stations that have a relatively high number of boarding and disembarking passengers per day, are at a higher risk than the national average. The results of this study show that this could have implications for a relatively high number of travellers in terms of their safety and contentment, and it could have socio-economic consequences for both ProRail and NS, as well as for the accessibility of The Netherlands. The local applicability of the risk assessment methodology was tested in five case studies on stations with very different characteristics, sizes and locations. The case studies have demonstrated that many of the identified risks appear to be relevant and appropriate on a local scale as well, but that risk is situation-specific. Furthermore, the case studies provide strategic long-term quantitative insights on adaptation strategies for all stations in the Netherlands, projecting the cases onto comparative situations.

Gouda deals with land subsidence and groundwater problems. A solution to these challenges is the application of Drainage-Infiltration-Transport (DIT) sewers, on which research is lacking. This thesis provides provides infiltration and drainage capacity values on DIT sewers and helps to understand the governing processes.

Identify the barriers within Arcadis by evaluating internal approaches, knowledge and differences in domains to increase the action perspective in the approach of climate-proof cities. The data was collected by performing 24 interviews and this was analysed and structured using the PRIMO-chain model.