This thesis investigates the potential of Nature-based Solutions (NbS) to address urban water management challenges in Paramaribo, Suriname. The city, characterized by intense rainfall and inadequate drainage infrastructure, frequently faces significant flooding, highlighting the urgent need for sustainable and resilient solutions. The research focuses on the applicability of NbS as an alternative to traditional grey infrastructure, particularly in the context of rapidly urbanizing tropical environments, where such solutions are still relatively unexplored.

Paramaribo faces a range of urban water management challenges, including high surface runoff and socio-economic impacts from frequent flooding. These issues are exacerbated by rapid urbanization, leading to extensive soil sealing that reduces the natural capacity for water infiltration. Against this backdrop, the thesis explores the potential of NbS as a promising but underutilized solution, particularly in tropical settings where existing literature on this topic is sparse. The study emphasizes that small-scale investigations, such as this one, can be critical in addressing the gap between theoretical research and practical implementation.

The literature review discusses various types of NbS, such as green roofs, bioswales, and permeable pavements, highlighting their potential benefits, including runoff reduction, water quality improvement, and biodiversity enhancement. However, in the context of Paramaribo, these co-benefits work differently.

The research focuses on a study area around Wakapasi in Paramaribo, using it as a small-scale case study to explore broader urban challenges. The selection of a smaller study area allows for detailed investigation, offering valuable insights into the effective implementation of NbS in similar contexts. The study acknowledges that while NbS holds promise, the challenges of ensuring their effectiveness in tropical environments must be critically examined.

Methodologically, the study employs a Multi-Criteria Analysis (MCA) to evaluate different NbS options based on effectiveness, cost, and social acceptability. Semi-structured interviews with local stakeholders and think-tank discussions emphasize the importance of local knowledge and institutional support, advocating for a bottom-up, participative approach to climate adaptation. The full-scale bioswale tests at AdeKUS provide empirical data, but the results are presented with critical nuance. While the bioswale tests did not show an emptying time of less than 24 hours, which is typically desirable to avoid standing water, the tests did not attract mosquitoes or pests. Additionally, the potential for preferential flow due to vegetation growth is noted, which could significantly increase infiltration rates over time, potentially by tenfold, once native vegetation fully establishes.

The results offer a mixed assessment of the potential for NbS in Paramaribo. On one hand, the bioswale tests demonstrate tangible measures that can be integrated into urban landscapes, providing proof of efficacy within a clearly defined context. The study also provides a clear description of the conditions under which NbS designs should be implemented based on the context of the region, offering practical guidance for future projects. However, the research also highlights the limitations and challenges, particularly in achieving rapid infiltration rates in combination with heavy rainfall and the uncertainties associated with long-term performance.

The study concludes by reflecting on the broader implications for urban water management in Paramaribo and similar tropical environments. The findings suggest that NbS could play a significant role in enhancing urban resilience, but their success depends on careful design, robust stakeholder engagement, and adaptive management strategies and the potential effects need to be researched further. The thesis emphasizes the potential for a bottom-up implementation strategy, where local involvement and incremental, evidence-based approaches guide the deployment of NbS. However, it also underscores the importance of remaining critical about the efficacy of these solutions, as the success of NbS is not guaranteed and must be rigorously tested and adapted to local conditions.

Urban stormwater management is put under pressure by increasing urbanisation and climate change leading to more frequent urban flooding. Such flooding can introduce ecological and public health issues by releasing contaminated water into the environment. Upgrading traditional grey infrastructure and implementing blue-green infrastructure (BGI) can be limited in their applicability for flood mitigation making Real-Time Control (RTC) an increasingly popular alternative due to its cost-effectiveness and potential performance benefits.
This thesis investigated the accuracy of rainfall forecasts and examined how forecast-informed RTC procedures could reduce flooding frequency and overflow depth while minimising negative side effects. The rainfall forecast accuracy was assessed based on three key properties: rainfall depth, forecast horizon, and mean forecast intensity. Using the insights from this assessment, three forecast-informed RTC procedures were designed to enhance the flood mitigation performance of a reactive RTC.
With perfect forecast data, flooding was completely prevented for two of the procedures, which used the longest but distinct horizons. The procedure using the shortest horizon was not able to prevent every flooding event due to the restriction in pre-emptive water release ahead of the forecasted rainfall events. The forecast accuracy analysis showed that the accuracy declined with increasing rainfall depth and lengthening horizon. Furthermore, the results indicated a shift from underestimation to overestimation of the rainfall depth as the mean forecast intensity increased. Applying the real forecast data, all designed forecast-informed procedures demonstrated reduction in total overflow depth of up to 70%, with the reduction linked to pump operation. However, the flood mitigation performance did not align with the expected results based on forecast accuracy, indicating that the procedures’ logic and implementation played a significant role in determining their effectiveness.
The findings highlight the trade-offs inherent in using forecast-informed RTC procedures, particularly the balance between the uncertainties of longer forecast horizons and the need for sufficient lead time to take preventive action. By addressing these challenges, this thesis provides practical insights to inform the design and implementation of advanced RTC systems, marking a critical step toward more sustainable and resilient urban water management.

Urban wastewater systems can impact the urban ecology by untreated wastewater discharges through combined sewer overflow (CSO) events, or by partial treatment of the wastewater at the wastewater treatment plant (WWTP). CSO events can cause oxygen depletion, eutrophication, and the discharge of pathogens. The partial treatment of the wastewater causes an increased concentration of ammonium in the WWTP effluent, which can lead to toxic ammonium levels in the receiving river water. These problems can be (partially) mitigated by optimizing the existing infrastructure. Optimization of the available storage will help handle the increased pressure on the urban drainage system (UDS) and the stricter environmental regulations simultaneously. A method to control the dynamic performance of the combined sewer system is Real-Time Control (RTC). A RTC strategy controls the combined sewer system dynamically based on real-time information about the system state. This research aims to develop a RTC strategy that decreases the negative ecological impact of the combined sewer system on the river by optimizing the available in-sewer volume. By doing so, the objectives to reduce the total amount of spilled CSO volume and to decrease the ammonium peaks towards the WWTP should be met. This research is applied to the case study of Geldrop-Mierlo, this is a municipality located in the UDS of Eindhoven. The trade-off between those two objectives was explored in the Wastewater Process simulator WEST. Rainfall events with a maximum intensity of 3.1 mm/hr and higher or rainfall events with maximum intensity < 3 mm/hr and total rainfall depth of > 4.8 mm, were found to be more likely to cause DO dips. The objective function which is used in the optimization process is dependent on the forecasted rainfall and the trade-off described above. The UDS is modeled in a full-hydrodynamic (FH) model and a simplified conceptual model. The conceptual model is made to reduce the computation time. The catchment of the FH model is split up into 3 different catchments, and each is modeled as a reservoir in the conceptual model. The characteristics of each reservoir are dependent on the characteristics of these catchments in the FH model. The characteristics that are included are storage curve, outflow dynamics, and CSO dynamics. Both models are calibrated and validated. The UDS is controlled with the Model Predictive Control (MPC) methodology using a Genetic Algorithm (GA) to find the optimal solution to minimize the negative ecological impact of the UDS on the river. Both the FH model and simplified model are used in the MPC optimization. Based on the analysis of the case study, the optimization results show that the impact of the MPC procedure on the receiving river is not significant. The reasons for this are location specific, but the main findings are that 1) the hydraulic constraints of the catchments restrict the MPC procedure from working, 2) although the calibration results of the conceptual model indicated accurate results, this does not guarantee that the model is also accurate enough to use in the MPC procedure.