Deltares

This study investigates windstorm impacts by combining high-resolution wind hazard data with a unique asset-level insurance loss dataset, specifically focusing on the Netherlands. We conduct statistical analyses to associate wind hazard characteristics with spatial data on windstorm losses at various spatial aggregation levels (four-digit to nationwide postal codes). Different wind hazard intensities (e.g. maximum wind gust, maximum hourly wind speed) are derived using meteorological data from 2017 to 2021 (the same period as the loss data). This data is based on station and downscaled ERA5 reanalysis data. Results show that the recorded gust has a good correlation with damage components (r = 0.41–0.61). The downscaled reanalysis data on gust and daily maximum (hourly mean) wind speed also have a good correlation (r = 0.38–0.59), albeit a bit smaller than the observed gust. When comparing different levels of aggregated data (PC4—four-digit postal code, PC2—two-digit postal code, and NL—national level), the correlation between claim and loss ratios becomes more pronounced as the level of aggregation increases. In addition, at the aggregated data level of two-digit postal codes, we see a wind speed threshold (around the 98th percentile of the records, ~ 22 m/s), where both losses and reported claims begin to rise as wind speed increases. Nevertheless, with lower wind speeds, damages and reported claims become meaningful using more aggregated data (NL). Our findings highlight the complex link between hazard and damage variables for windstorm losses, offering valuable insights for insurance portfolios, risk assessment, and management.

Information about reproductive habitat and migration pathways is of paramount importance to restore migratory fish species. This study assesses the availability of spawning and nursery habitats for the European sturgeon ( Acipenser sturio ) in the delta and lower Rhine (covering over 350 river kilometres) as part of a larger feasibility assessment for a future restoration of this critically endangered species. The general approach has three steps: (1) the identification of the species' specific habitat requirements, based on a systematic literature review; (2) the collection and preprocessing of data from two countries, including the 1D and 2D modelling of water depths and flow velocities; and (3) GIS‐based mapping of spawning and nursery habitat. Based on a HSI score of 1, we identify a total of 0.75 km² as minimal spawning habitat, potentially suitable for approximately 2500 female European sturgeons (one spawning site would use ~300 m²). This is sufficient, as currently, only an estimated maximum number of 750 adults exist. Suitable spawning habitat is mainly located in the German state of North Rhine‐Westphalia, whereas suitable nursery habitat is mainly located in the Netherlands. The availability is, however, significantly reduced by coastal infrastructure (damming) and inland navigation. The insights gained can be used to assess the current suitability of the river Rhine for the species' reintroduction and to identify opportunities for habitat restoration and protection for various life stages. The outcomes thus play an essential role in the conservation of the species. In addition, the modelling approach developed could be applied to other northwestern European rivers. This broader application would allow intercomparison and support decisions about which rivers are best suited for future reintroduction of the critically endangered European sturgeon.

Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US$1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50$770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.

The paper discusses over 10 years of experience (2009–2021) with dune development in a newly constructed coastal area in The Netherlands. The area (ca. 40 ha) was constructed by foreshore and beach nourishment and meant to compensate expected damage to existing dune vegetation, caused by nearby harbour extension and associated industrial activities. The development of the new dune was done applying the principles of ‘Building with Nature’, with as little human interference as possible. However, in the course of time several management measures were necessary to steer the vegetation succession in the right direction of the compensation targets. Dune development in natural aeolian coastal dunes differs from that in dunes built up from sea bottom sand. Before the compensation project there was little experience on how nourished marine sediments would affect the processes of sand transport, groundwater dynamics and vegetation development. After 10 years of development, the succession to the compensation targets is on its way. The project monitoring gave insights in the development of constructed dunes and in balancing between natural development and human intervention.

To enable detailed study of a wide variety of future health challenges, we have created future land use maps for the Netherlands for 2050, based on the Dutch One Health Shared Socio-economic Pathways (SSPs). This was done using the DynaCLUE modelling framework. Future land use is based on altitude, soil properties, groundwater, salinity, flood risk, agricultural land price, distance to transport hubs and climate. We also account for anticipated demand for different land use types, historic land use changes and potential spatial restrictions. These land use maps can be used to model many different health risks to people, animals and the environment, such as disease, water quality and pollution. In addition, the Netherlands can serve as an example for other rapidly urbanising deltas where many of the health risks will be similar.

This study provides a comprehensive review of the literature on climate risk insurance modeling to identify lessons learned and knowledge gaps to be addressed by future research. These models are increasingly relevant due to the rising losses attributable to climate change. Insurance models estimate risk for different perils and simulate risk‐related parameters for insurance schemes, such as premiums and deductibles. Most forward‐looking models indicate that climate change and socioeconomic developments highly exacerbate future risk and increase insurance premiums. Various studies recommend charging risk‐based premiums to incentivize adaptation efforts that limit this increase in climate risks. Other findings point toward introducing public–private insurance to cope with climate change and enhance risk spreading by introducing insurance purchase requirements or insurance products that cover multiple climate risks. Gaps that we identify in this literature include an underrepresentation of insurance assessments for developing countries and for hazards other than flooding. Additionally, we note a lack of research into insurance for non‐agricultural commercial sectors. Furthermore, less than half of the studies take a forward‐looking approach by incorporating climate change scenarios, and an even smaller percentage consider socioeconomic development scenarios. This limitation shows that current methods require additional development for assessing the effects of future climate risk on insurance. We recommend that future research develops such forward‐looking models, considers using a more refined spatial scale, broadens geographical and hazard coverage, and includes the commercial sector.

Aedes vexans (Meigen, 1830) is a floodwater mosquito species that may cause significant nuisance and can serve as a vector for multiple arboviruses. Its distribution is expected to shift in the future as a result of changes in climate and land use. Understanding these shifts is important for estimating future disease risk. This study aims to identify habitat suitability and probability of occurrence of A. vexans . Using the Netherlands as a case study, we utilised an occurrence dataset generated by the Netherlands Centre for Monitoring of Vectors. We employed an auto machine learning approach to model generation, using a variety of modelling methodologies, determining the optimal ratio of presence: Absence datapoints in the training data and ultimately creating a 10‐model ensemble. We selected predictor variables relating to weather, land use, soil properties, flood risk and salinity. The probability of A. vexans presence was predicted on a 1 km grid for both the current Dutch situation and for four scenarios for 2050. Our analysis identified temperature, soil type and land cover as the primary determinants influencing the probability of A. vexans occurrence. Future projections reveal an increase in the likelihood of A. vexans occurrence in the study area, particularly along major river corridors and in regions with increasing amounts of artificial and natural areas. Additionally, the mosquito season is predicted to become longer under all future scenarios. Insights provided in our study can also be applied to other similar areas, such as other north‐western European countries or other urban deltas. This study shows for the first time detailed future occurrence predictions and also future seasonal predictions for this mosquito species. Seasonal predictions allow researchers to study how disease risk changes throughout the year, something which is particularly valuable given the predicted lengthening of the mosquito (and thus disease transmission) season.

Land reclamations influence the morphodynamic evolution of estuaries and tidal basins, because an altered planform changes tidal dynamics and associated residual sediment transport. The morphodynamic response time to land reclamation is long, impacting the system for decades to centuries. Other human interventions (e.g., deepening of fairways or port construction) will add more morphodynamic adaptation timescales. Our understanding of the cumulative effects of anthropogenic interference with estuaries is limited because observations usually do not cover the complete morphological adaptation period. We aim to assess the impact of land reclamation works and other human interventions on an estuarine system by means of digital reconstructions of historical morphologies of the Ems Estuary over the past 500 years. Our analysis demonstrates that the intertidal‐subtidal area ratio altered due to land reclamation works and that the ratio partly restored after land reclamation ended. The land reclamation works have led to the degeneration of an ebb and flood channel system, transitioning the estuary from a multichannel to a single channel system. We infer that the 20th‐century intensification of channel dredging and re‐alignment works accelerated rather than caused this development. The centennial‐scale observations show that the Ems estuary evolution corresponds to a land reclamation response following tidal asymmetry‐based stability theory as it moves toward a new equilibrium configuration with modified tidal flats and channels. Considering the long history of land reclamation in the Ems Estuary, it provides an analogy for expected developments in comparable tidal systems where land reclamations were recently carried out.

Foam is widely used in soil conditioning during EPB shield tunnelling to ensure the efficiency and safety of face support and muck flow. Currently, the concentration of the foaming agent solution is chosen based on the recommendations of foaming agent suppliers, the half-life time of foam or the properties of the foam-soil mixture. This paper studies the foaming agent concentration (Cf) choice taking surface tension into consideration. Test results show that the Cf should be higher than the critical micelle concentration (CMC) to offset the influence of the expanding surface area during foam generation in shield tunnelling. The comparison between the capillary rise method and the platinum plate method shows that this offset can almost be accomplished when Cf is higher than 1% and fully accomplished when Cf is higher than 3%. Foam generation tests show that despite the differences in foam generation methods, the foaming ability of foaming agent solution and the stability of the generated foam are close to optimum at Cf of 1% and reach optimum at Cf of 3%. Slump tests show that foam with Cf lower than 1% is not stable enough in the foam-sand mixture for shield tunnelling. Both slump tests and field validation show that when Cf is higher than 3%, the increase of Cf has limited influence on soil conditioning performance.

Water and mass transport in distributary channel networks play an important role in nourishing fluvial and coastal wetlands, and are largely determined by the morphological configurations of channel bifurcations. While the morphological equilibrium of a single channel bifurcation has been extensively studied, the equilibrium configurations of channel networks with connecting channels linking the bifurcating branches, that is, the “bifurcation‐connecting channel” units that are commonly found in rivers, deltas and estuaries, remain elusive. In this simple yet representative channel network of the “bifurcation‐connecting channel” unit, we observed through numerical simulations an oscillatory water partitioning under moderate Shields stress and channel aspect ratio, in addition to the steady‐state solutions reported in previous studies. The oscillatory water partitioning indicates a newly discovered periodic solution, which is an emergent behavior under constant boundary conditions. We found that the periodic solution is primarily due to the dynamic interactions between bifurcation instability and water surface slope advantage in the two branches modulated by the reversable discharges through the connecting channel, under moderate Shields stress and channel aspect ratio. In such cases, the developed slope advantage in the subordinate branch can suppress the deepening of the dominant branch and eventually lead to the shifting of the dominant branch. In contrast, the channel network attains a steady‐state solution when the slope advantage or the bifurcation instability is dominant with relatively low and high Shields stress (or channel aspect ratio). Our results improve the understanding on the evolution and restoration of channel networks under increasing human interventions in global deltas.

Syn‐sedimentary compaction or consolidation is an important process in deltaic environments because it affects both the local morphodynamics and hydrodynamics as well as the delta‐scale accommodation space. However, the impact of syn‐depositional compaction on the sediment distribution and the interdependency between different delta areas related to the sediment budget are not fully understood. This paper simulates syn‐depositional compaction using improved 1D grain‐size compaction formulations, integrated into hydrodynamic and morphodynamic modelling software Delft3D. The updated code is used to model sedimentation in mud‐rich deltas under various compaction rate scenarios, which represents the maximum compaction rate potential of sediment that experiences the highest overburden stress in the delta. The simulated deltas are analysed by first classifying their plan‐view area development into depositional elements: distributary channel, underfilled channel, delta plain, mouth bar, delta front and pro delta depositional elements. Then, sedimentation by mass, accommodation space and depositional segment metrics are calculated using the interpreted depositional elements. The results for zero compaction rate scenarios (0 mm year⁻¹) show that limited space‐varying and temporal‐varying accommodation is available to deposit sediment in the delta plain depositional element. Therefore, the sedimentation mainly occurs in the mouth bar depositional element. For low‐mid compaction rate scenarios (0.01–1 mm year⁻¹), the additional syn‐depositional accommodation space in the delta plain depositional element increases sedimentation in this area, limiting sedimentation in the mouth bar depositional element. For high compaction rate scenarios (>1 mm year⁻¹), a further increase in the accommodation space in the delta plain depositional element leads to lateral sedimentation attributed to channel relocation, where the sedimentation mainly occurs in the mouth bar depositional element. This study shows that, although considered a gradual process, syn‐sedimentary compaction does impact long‐term delta evolution by influencing the distribution of sedimentation in the delta.

Remote sensing technologies have the potential to support monitoring of floating plastic litter in aquatic environments. An experimental campaign was carried out in a large-scale hydrodynamic test facility to explore the detectability of floating plastics in ocean waves, comparing and contrasting different microwave and optical remote sensing technologies. The extensive experiments revealed that detection of plastics was feasible with microwave measurement techniques using X and Ku-bands with VV polarization at a plastic threshold concentration of 1 item/m² or 1–10 g/m². The optical measurements further revealed that spectral and polarization properties in the visible and infrared spectrum had diagnostic information unique to the floating plastics. This assessment presents a crucial step towards enabling the detection of aquatic plastics using advanced remote sensing technologies. We demonstrate that remote sensing has the potential for global targeting of plastic litter hotspots, which is needed for supporting effective clean-up efforts and scientific evidence-based policy making.

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

Overexploitation of groundwater for irrigation can ultimately threaten the viability of agriculture itself, because the falling groundwater levels become too deep to sustain the increasing costs of groundwater extraction, an economic limit is reached. In order to evaluate possible adaptation strategies to avoid or postpone reaching the economic limit, we developed the microeconomic heuristic model HELGA (hydro-economic limits as a global analysis). HELGA considers the interaction of groundwater with irrigation at the farm level with a global scale application in mind. HELGA evaluates the development of the costs and revenue of groundwater-fed irrigated agriculture from the farmer’s perspective. As long as the farm remains economically viable, the farmer can invest to access deeper groundwater, but in the long run the famer may have to adapt to keep farming profitable. We applied HELGA in five locations within the conterminous USA. In most cases, recharge is large enough to save a farmer from reaching the economic limit. Where groundwater is overexploited, the increasing energy cost of groundwater pumping is one of the main drivers limiting groundwater use. Additionally, the increasing costs of the water infrastructure (i.e. deeper wells) is a crucial factor that explains where and when the economic limit is reached. If farmers change crops wisely or fallow part of their land, they are able to access groundwater longer and postpone the moment the economic limit is reached. Using HELGA, we show that proper and timely adaptation measures increases the profitable lifetime of groundwater and helps to conserve this resource for future generations.

This perspective article explores the role of data visualisation in decision-making under deep uncertainty (DMDU), a growing discipline tackling complex socio-environmental challenges, such as climate impacts and adaptation, natural resource management, and preparedness for extreme events. We discuss the role of visualisation for both analysis (or exploratory) purposes, as well as communication (or explanatory) purposes, including to stakeholders and the public. We identify a lack of comprehensive guidelines on how visualisations are currently used and their potential in enhancing DMDU processes. Drawing on literature and insights from a recent workshop, we identify key challenges DMDU analysts face when visualising data: managing complexity and dimensionality, effectively communicating uncertainty, and ensuring user engagement and interpretability. We propose a research agenda to address these challenges, by taxonomising and evaluating the effectiveness of different visual forms in decision-making contexts, and fostering interdisciplinary collaboration. We argue that, through these efforts, we can improve the communication and usability of DMDU analyses, ultimately aiding in more informed and adaptive decision-making in the face of deep uncertainty.

Background: The world is experiencing rapid anthropogenic-driven changes in climate, biodiversity, and pollution. While most insect species are declining due to these changes, disease-transmitting mosquitoes, might thrive. However, the quantitative impacts of these changes on mosquito populations are not well understood. Our study aims to evaluate the individual and combined effects of climate and land use/cover related factors on the potential future spatiotemporal distribution of Culex pipiens in the Netherlands for four One Health change scenarios Methods: We developed a random forest species distribution model, trained and cross-validated by Cx. pipiens trapping data as the response variable and climate and land use/cover related factors as explanatory variables. We used this model to estimate the spatiotemporal distribution of Cx. pipiens for previously established One Health scenarios and disentangled and evaluated the effects of climate and land use/cover changes. Results: Our results reveal that climatic factors are the main predictor underlying the temporal distribution of Cx. pipiens , while land use/cover factors shape their spatial distribution. Under One Health scenarios with greater levels of climate change, our results indicate a lengthening of the period that Cx. pipiens occurs and sustained high abundances during the summer months. Furthermore, our results suggest that land use/cover might mitigate the effects of climate change. Conclusions: Our study underscores the complex interplay of climate and land use/cover changes on the spatiotemporal distributions of Cx. pipiens , emphasizing the need to simultaneously consider climate and land use/cover impacts when adapting to Cx. pipiens related risks. Especially, the negative impact of increasing tree cover on mosquito abundance linked with targeted larval control might be an interesting avenue to explore.

This paper introduces a novel application of spatial-temporal graph neural networks (ST-GNNs) to predict groundwater levels. Groundwater level prediction is inherently complex, influenced by various hydrological, meteorological, and anthropogenic factors. Traditional prediction models often struggle with the nonlinearity and non-stationary characteristics of groundwater data. Our study leverages the capabilities of ST-GNNs to address these challenges in the Overbetuwe area, Netherlands. We utilize a comprehensive dataset encompassing 395 groundwater level time series and auxiliary data such as precipitation, evaporation, river stages, and pumping well data. The graph-based framework of our ST-GNN model facilitates the integration of spatial interconnectivity and temporal dynamics, capturing the complex interactions within the groundwater system. Our modified Multivariate Time Graph Neural Network model shows significant improvements over traditional methods, particularly in handling missing data and forecasting future groundwater levels with minimal bias. The model’s performance is rigorously evaluated when trained and applied with both synthetic and measured data, demonstrating superior accuracy and robustness in comparison to traditional numerical models in long-term forecasting. The study’s findings highlight the potential of ST-GNNs in environmental modeling, offering a significant step forward in predictive modeling of groundwater levels.

Knowing the depth at which groundwater can be found below the land surface is critical for understanding its potential accessibility by ecosystems and society. Uncertainty in global scale water table depth (WTD) limits our ability to assess groundwater’s role in a water cycle altered by changing climate, land cover, and human water use. Global groundwater models offer a top–down pathway to gain this knowledge, but their uncertainty is currently poorly quantified. Here, we investigate four global groundwater models and reveal steady-state WTD disagreements of more than 100 m for one-third of the global land area. We find that model estimates of land areas with shallow groundwater at <10 m depth vary from 10% to 71% (mean of 23%). This uncertainty directly translates into subsequent assessments, as land areas with potential groundwater accessibility for forests, population, and areas equipped for irrigation, differ substantially depending on the chosen model. We explore reasons for these differences and find that contrary to observations, 3 out of 4 models show deeper water tables in humid than in arid climates and greatly overestimate how strongly topographic slope controls WTD. These results highlight substantial uncertainty associated with any global-scale groundwater analysis, which should be considered and ultimately reduced.