Extreme weather events such as heat waves and heavy rainfall are becoming more frequent due to climate change, threatening the liveability of urban environments. High building and infrastructure densities and impervious surfaces intensify heat and flood risks. This vulnerability has led to an increase in climate adaptation strategies, which often include the implementation of Nature based Solutions (NbS). In the Netherlands, one of the most widely used NbS is the swale, a green ditch that facilitates drainage, infiltration, and rainwater storage. Swales are seen as cost-effective and no-regret measures that, just as other NbS, can have multiple functions which provide multiple benefits. Despite these potential benefits, practitioners struggle with the design, development and maintenance of swales, partly due to limited local monitoring practices.

The research had two main objectives: (1) to explore current practice in research and in Dutch municipalities to identify performance criteria and monitoring techniques for swales to track the key functions of swales, and (2) to investigate motivators and challenges for municipal swale monitoring and develop a communication tool to address these.
A systematic literature review identified five key swale functions: water quantity, water quality, biodiversity, liveability and wellbeing. Water quantity and water quality functions are relatively well studied, with swales proven to reduce runoff and remove certain pollutants when properly designed and maintained. However, research is still lacking for the functions biodiversity, liveability, and wellbeing. The connections between the different functions were also explored, which showed the importance of recognising the connections and the influences of the different functions on each other. From this review, eight criteria were identified: infiltration rate, soil moisture, in- and outflow of pollutants, soil quality, vegetation development, temperature, resident experience and resident usage. For each criterion, quick-scan and in-depth monitoring techniques were proposed.

A survey among municipal workers who are involved with urban water management (mainly from South Holland) found that swales are seen as multifunctional objects, where water quantity and biodiversity are the most important functions. Monitoring is not part of the current practice, and swales are often only assessed on the functions during the design. However, there is interest in the implementation of monitoring, especially for water quantity and water quality. The main motivators for monitoring are to know the effect of swales on the long term and the ability to identify problems in time. The main challenges are keeping track of data and ensuring sufficient resources, like staff and budget.

To overcome these challenges, a workshop was designed to motivate practitioners to start monitoring the multiple swale functions. The workshop is aimed at municipal staff responsible for the organisation of maintenance for the different functions. By learning about the different functions and monitoring possibilities, the participants can create a monitoring plan that serves as a starting point for the actual implementation of monitoring. Evaluation by experts indicated that this workshop can motivate the target audience, because it increases the audience's awareness of swales, encourages them to consider the different functions and lets them practice with measuring, monitoring and retrieving data. It also provides them with a concrete and practical output that can be used in practice.

This study offers a framework to improve swale monitoring in the Netherlands. An overview of performance criteria with corresponding monitoring techniques is provided together with a communication tool that can bridge the gap between knowledge and practice.

As flood intensities are increasing, Flood Early Warning Systems (FEWS) are becoming more crucial so the right mitigation measures can be taken. This study focused on the Phetchaburi river basin in Thailand, which experiences floods yearly. Currently, precipitation data from rain gauges are used in the FEWS for this region. However, weather radar is also available in Thailand. Weather radar is usually able to capture the spatial variability of precipitation in more detail. Therefore, this study aimed to research the effect of spatially distributed precipitation on flood modelling in the Phetchaburi river basin.

Using HEC-RAS, a hydrodynamic rainfall-runoff model of the Phetchaburi river basin was made. The area of interest was the middle reach of the Phetchaburi river and its two tributaries, lying in-between three reservoir dams upstream and the Phet Diversion Dam downstream. The Phetchaburi river and its tributaries were calibrated using measured dam outflow and water level data. Three types of precipitation data were used as input, namely homogeneous precipitation data and spatially distributed precipitation data obtained from weather radar and from rain gauges.

High infiltration rates were found for the Phetchaburi river basin. When homogeneous precipitation data was used as input, precipitation intensity would be too low, allowing all precipitation to infiltrate into the subsurface. Using homogenous precipitation data as input results in a underestimation of floods. On the contrary, precipitation intensities in spatially distributed precipitation data were high enough to exceed the soil infiltration capacity, leading to surface runoff and floods. When solely looking at the water balance, using precipitation data from weather radar and rain gauges as input lead to similar results. However, when it came to the water levels at specific locations, precipitation data from weather radar performed better. The density of the rain gauge network in the Phetchaburi river basin is too low to capture the spatial variability of the precipitation events in detail. This resulted in floods or the
lack thereof at the wrong locations. Weather radar captures the spatial variability of precipitation in greater detail than rain gauges can. This study showed that using precipitation data from weather radar as input results in more accurate flood modelling in the Phetchaburi river basin.

Rivers play a crucial role in delivering sediment to the oceans, with deltas acting as key zones for sediment deposition that support ecosystems, human populations, agriculture, and industry. The Vietnamese Mekong Delta, one of the world’s most important and densely populated river deltas, faces increasing stress as human interventions such as dam construction and sand mining disrupt natural sediment supply, intensifying subsidence, sea-level rise, and erosion. These pressures are further amplified by climate change, which contributes to extreme discharge events, saltwater intrusion, and coastal erosion. While considerable research addresses short-term changes, long-term projections remain limited. This study examines how human- and climate-driven factors shape sediment transport and bifurcation behaviour in the Song Hau distributary over 30 years, by evaluating branch flow
partitioning (symmetry) and the system’s ability to remain in equilibrium (stability).

A Delft3D 2D depth-averaged model, simulating both water flow and sediment movement, is used to examine how climatic and human drivers shape sediment transport and bifurcation behaviour in the tidally influenced Song Hau distributary. Scenarios of altered precipitation (AP), sea-level rise (SLR), sand mining (SM), and hydropower-induced discharge flattening (HD) reveal how changes in upstream discharge, downstream water levels, and bed lowering influence the system. The model performs well, with water flow results showing high accuracy (NSE = 0.90–0.94; RMSE = 0.07–0.21 m) and sediment transport reproduced within 10–20% of observed values, indicating good agreement with observed concentrations.

The results show that climate forcing, through altered precipitation and sea-level rise, generally reduces local extremes of sedimentation and erosion, leading to a more uniform distribution of sediment and flow across the bifurcation and faster stabilisation of sediment partitioning. Altered precipitation increases the system’s export capacity, while sea-level rise increases symmetry by reducing the effect of tides on flow partitioning. This helps maintain throughflow, ensuring consistent export of water and sediment to the sea through both branches. In contrast, human interventions such as sand mining and hydropower-induced discharge flattening increase asymmetry between the Dinh An and Tran De branches. Tran De becomes more dominant in exporting water and sediment, while Dinh An is prone to extreme sedimentation near the river mouth, reducing export capacity. Sand mining has nonlinear
effects, with increasing extraction rates indicating a threshold beyond which the system responds differently. Fluctuations in sediment and flow persist over time, preventing the system from reaching an unchanged sediment distribution. Discharge variability, moderated by hydropower dams, plays a key role in maintaining balanced flow and sediment distribution. Overall, climate change tends to stabilise the system, while anthropogenic interventions lead to more unpredictable outcomes, with sediment distribution being more sensitive than water flow.

The impacts of both human and climate drivers extend beyond the study area, influencing sediment export to the ocean. Ecosystems such as mangroves, which are vital for coastal protection, are highly vulnerable to sediment fluctuations. Effective regulation of human activities, including sand mining and discharge management, is crucial to maintain sediment balance and support the resilience of the delta and its ecosystems under increasing environmental pressures.

This study explores the feasibility of using CCTV cameras toestimate Total SuspendedSediment(TSS) concentrations in the Khlong Suan Mak River, located in Kamphaeng Phet Province, Thailand. Climate change has led to prolonged dry spells and intense precipitation in Thailand, causing significant sediment transport and deposition issues in river systems and water infrastructure. Traditional methods for monitoring TSS have inherent limitations, prompting the investigation of RGB image processing as a cost-effective alternative. Time-series RGB images were captured at multiple weir locations along the river, and pixel intensities were analyzed to estimate sediment concentrations. Synoptic and spatial sediment sampling estab lished baseline TSS values and sediment grain size distributions. Additionally, bathymetric profiles of three major reservoirs were developed to assess sediment accumulation patterns. Preliminary results demonstrated correlations between RGB intensity values, particularly in the green channel, and TSS under controlled conditions. However, field applications faced challenges due to fluctuating light intensities and minimal variability in TSS concentrations. These findings suggest that while RGB imaging shows promise for sediment monitoring, improvements in camera positioning and lighting control are essential. Future research could enhance accuracyby integrating advanced imaging technologies with this approach

Protecting water resource quality is a global concern, as both solute and colloidal contaminants from various sources can infiltrate into soil and eventually pollute groundwater. Understanding the fate and transport of colloidal contaminants- such as engineered nano- and micro-particles, as well as biological entities like bacteria and viruses- is crucial for mitigating their associated risks. The transport and deposition of the colloidal contaminants are complex and multiscale processes in porous media.
This dissertation explored the application of DNA-based particles as potential tracer agents. Advances in nanotechnology and molecular biology have enabled the development of synthetic DNA-based particles that synthetic DNA act as “barcodes”. These particles are highly detectable and quantifiable at low concentrations using qPCR techniques, making them ideal for mapping contamination pathways, determining aquifer hydraulic connectivity, tracking multiple sources simultaneously, and serving as surrogates for tracking the transport and pathways of colloidal contaminants.
DNA-based particles have recently been used as tracers in hydrological studies. The focus of the dissertation is on DNA-based particles with a core-shell structure made of silica encapsulating double-stranded DNA (referred to as DNAcol). Since DNA-based particles can be classified as colloidal particles, this research aims to better understand the mechanisms governing their transport and fate under varying physicochemical conditions. By examining its responses to different tested conditions, the study seeks to identify the environmental conditions in which this tracer can be most effectively applied.

Landslides are one of the most widespread natural hazards, causing thousands of casualties every year and significant economic damage worldwide. In mountainous regions of Thailand, damages and fatalities due to landslides have increased over the last decades due to intensified human interventions.

This research aims to contribute to the development of a near real-time, joint early warning system for flash floods and landslides in Khao Yai National Park, Thailand. Spatial and temporal landslide occurrences in Khao Yai National Park were assessed. To extend the available landslide inventory, the detection of historical landslides was automated on the Google Earth Engine platform using remotely sensed relative changes in NDVI. Predisposing factors of landslide occurrence were determined using the frequency ratio method. A susceptibility map was then derived by linking the detected landslides to the predisposing factors: slope angle, aspect, land use, lithology, and distance to road. Validation with the landslide inventory shows excellent classification performance.

The temporal probability was assessed using a physically-based multi-hazard model. The hydrological model includes the driving hydrological processes for each grid cell. The streamflow model output was calibrated using observed nested river discharge events. The model performance was tested under spatially distributed precipitation forcing of varying quality. The results show good performance in predicting streamflow and landslide occurrence based on modeled antecedent conditions when using high-quality weather radar information as forcing.

This research demonstrates the effectiveness of integrating fully distributed physically-based modeling with high-resolution spatial rainfall observations from weather radar. The findings are expected to enhance the development of a multi-hazard early warning system and improve disaster risk management in northeastern Thailand.

The Karnali River in Bardia National Park (BNP), Nepal, is crucial for sustaining the habitats of endangered Bengal Tigers. However, gathering data to analyze this remote river’s behavior presents significant challenges due to the remote and mountainous terrain of BNP.

This thesis explores an approach using the altimetry satellite Sentinel-6 to measure river water surface elevations (WSEs), specifically utilizing the innovative Polygon-Informed Cross-Track Altimetry (PICTA) method. By integrating fully-focused Synthetic Aperture
Radar (FF-SAR) data from Sentinel-6 with a static river polygon, we aimed to retrack WSEs and unlock new insights into the Karnali River’s dynamics.

The objective of this thesis was to evaluate the performance and potential of the PICTA method in deriving precise river level profiles for the Karnali River. The research questions addressed include: How does PICTA compare to in-situ water surface height measurements? How well does it align with the SWOT mission, which also measures river water levels? How do river level profiles change over time? And how does the use of a static river polygon influence water level uncertainty for the dynamic Karnali River?

The PICTA method successfully derived water surface elevations for a 10-kilometer-long section of the Karnali River. Over a year-long period from February 2023 to February 2024, we generated 38 detailed PICTA river level profiles. These profiles revealed the relationship between measured WSE fluctuations, river slope, and river width over time. We observed that both WSE fluctuations and river slope decreased at sections where the Karnali River could overflow its banks during high water. Notable gaps in the profiles, such as transitions from
a single channel to a multichannel system, provided insights into the interaction between river characteristics and the PICTA algorithm.
The PICTA-derived WSE time series closely matched in-situ measurements at the river gauge station at Chisapani, Nepal, showing similar seasonal trends and peak differences. When comparing PICTA and SWOT profiles, we observed a mean bias near zero and a scaled MAD of approximately 20 cm. Dynamic river polygons based on SWOT data further improved the agreement, reducing the scaled MAD by 10 cm and increasing retracked PICTA data points. Using a static river polygon introduced WSE uncertainties ranging from 5 cm in the summer to 20 cm in the winter, averaging 10 cm over time. This study suggests that dynamic polygons could enhance the accuracy of PICTA derived WSEs. Ultimately, PICTA’s ability to capture and relate seasonal trends to local hydraulic behavior underscores its significant potential. This research advances our understanding of the Karnali River’s dynamics and demonstrates
PICTA’s ability to derive river water levels in a remote, mountainous region. These insights could constribute to support better conservation efforts for BNP’s vital Bengal Tiger habitats.