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Aqueduct Floods methodology
A consortium consisting of the World Resources Institute (WRI), Deltares, Vrije Universiteit Amsterdam’s Institute for Environmental Studies (IVM), Utrecht University (UU), and the Netherlands Environmental Assessment Agency (PBL), with funding support from the Netherlands Ministry of Infrastructure and Water Management and the World Bank, have developed Aqueduct Floods, a global tool providing actionable information to analyze flood risks and understand the costs and benefits of interventions, such as dikes, to reduce flood risk. According to new data from WRI's Aqueduct Floods Tool, by 2030 the number of people impacted by floods will double worldwide, from 65 million to 132 million due to riverine flooding and from 7 million to 15 million due to coastal flooding. The amount of urban property damaged by riverine floods will increase threefold, from $157 billion to $535 billion, while it will increase tenfold due to coastal storm surge and sea level rise, from $17 billion to $177 billion. By 2050, the numbers will be catastrophic: 191 million and 30 million people will be at risk of riverine and coastal flooding, respectively, each year. Aqueduct Floods finds that every $1 spent on flood protection infrastructure in India could result in $248 in avoided damages (when moving from 11-year flood protection in 2010 to 25-year flood protection in 2050) and would reduce the likelihood of these areas being flooded by half.
Fragmentation of plastic objects in a laboratory seawater microcosm
We studied the fragmentation of conventional thermoplastic and compostable plastic items in a laboratory seawater microcosm. In the microcosm, polyurethane foams, cellulose acetate cigarette filters, and compostable polyester and polylactic acid items readily sank, whereas polyethylene air pouches, latex balloons, polystyrene foams and polypropylene cups remained afloat. Microbial biofilms dominated by Cyanobacteria, Proteobacteria, Planctomycetes and Bacteriodetes grew on the plastics, and caused some of the polyethylene items to sink to the bottom. Electrical resistances (ER) of plastic items decreased as function of time, an indication that seawater had penetrated into microscopic crevices in the plastic that had developed over time. Rate constants for ER decrease in polyethylene items in the microcosm were similar to tensile elongation decrease of polyethylene sheets floating in sea, measured previously by others. Weight loss of plastic items was ≤ 1% per year for polyethylene, polystyrene and polypropylene, 3–5% for latex, polyethylene terephthalate and polyurethane, 15% for cellulose acetate, and 7–27% for polyester and polylactic acid compostable bags. The formation of microplastics observed in the microcosm was responsible for at least part of the weight loss. This study emphasizes the need to obtain experimental data on plastic litter degradation under conditions that are realistic for marine environments.
Anomaly kriging helps to remove bias in spatial model runoff estimates
The low spatial density of streamflow gauging stations limits the accuracy of spatial streamflow estimates in many parts of the world. Strategies to improve runoff estimates in the absence of dense measurements have tended to focus on estimating parameters of runoff models in ungauged regions, through so‐called parameter regionalization methods. However, parameter regionalization can be affected by overdependence on calibration at gauged sites, model parameter equifinality, and ensuing estimation errors. As a result, spatial model runoff estimates typically exhibit spatially correlated biases. This analysis attempts to enhance the use of observations in spatial runoff estimation. Specifically, we assessed the potential to reduce systematic errors by spatially interpolating residuals (i.e., errors) between prior grid‐based streamflow estimates for Australia at 0.05° × 0.05° grid from the Australian Bureau of Meteorology's calibrated, operational Australian Water Resources Assessment Landscape model (AWRA‐L) and streamflow gauging records from 780 unimpeded, relatively small catchments. We analyzed spatial autocorrelation in residuals and tested an efficient two‐step correction approach involving a uniform correction and subsequent kriging of residuals. The approach removed an average of 41% of systematic bias in the model estimates and also improved other model performance measures. Further reduction in errors at shorter timescales may be achievable through a temporally hierarchical correction scheme.
Stream-scale flow experiment reveals large influence of understory growth on vegetation roughness
Vegetation is a key source of flow resistance in natural channels and floodplains. It is therefore important to accurately model the flow resistance to inform decision makers and managers. However, it is challenging to predict the resistance of real vegetation, because vegetation models are based on relatively small-scale lab experiments with mostly artificial vegetation. Experimental tests of real vegetation under field conditions are scarce. The purpose of this study is to measure the flow resistance of a submerged willow patch, where small herbaceous vegetation was allowed to grow in between the willow stems to simulate field conditions. Detailed flow velocity measurements were performed during an full scale experiment of flow around a submerged patch of willows. The parameter values of the willow vegetation model, as well as the friction coefficients of the vegetated banks and unvegetated channel bed, were computed simultaneously using Bayesian inference using a 2D hydrodynamic model. Results show that the presence of understory growth greatly affects flow patterns and the value of the effective vegetation density parameter. Measured flow velocities in the patch with understory growth were very low, and the patch has relatively high deflection. After removal of this undergrowth, flow velocities in the patch increased and deflection of the vegetation canopy decreased. We show that estimating vegetation density using an often-used rigid cylinder estimator based on vegetation sampling, underestimated the effective value by more than an order of magnitude. We argue that proposed extensions to existing vegetation models, which can take into account understory growth and reconfiguration, could be tested under field conditions using the approach followed in this paper.
Historic storms and the hidden value of coastal wetlands for nature-based flood defence
Global change amplifies coastal flood risks and motivates a paradigm shift towards nature-based coastal defence, where engineered structures are supplemented with coastal wetlands such as saltmarshes. Although experiments and models indicate that such natural defences can attenuate storm waves, there is still limited field evidence on how much they add safety to engineered structures during severe storms. Using well-documented historic data from the 1717 and 1953 flood disasters in Northwest Europe, we show that saltmarshes can reduce both the chance and impact of the breaching of engineered defences. Historic lessons also reveal a key but unrecognized natural flood defence mechanism: saltmarshes lower flood magnitude by confining breach size when engineered defences have failed, which is shown to be highly effective even with long-term sea level rise. These findings provide new insights into the mechanisms and benefits of nature-based mitigation of flood hazards, and should stimulate the development of novel safety designs that smartly harness different natural coastal defence functions.
Climate change induced socio-economic tipping points : review and stakeholder consultation for policy relevant research
Tipping points have become a key concept in research on climate change, indicating points of abrupt transition in biophysical systems as well as transformative changes in adaptation and mitigation strategies. However, the potential existence of tipping points in socio-economic systems has remained underexplored, whereas they might be highly policy relevant. This paper describes characteristics of climate change induced socio-economic tipping points (SETPs) to guide future research on SETPs to inform climate policy. We review existing literature to create a tipping point typology and to derive the following SETP definition: a climate change induced, abrupt change of a socio-economic system, into a new, fundamentally different state. Through stakeholder consultation, we identify 22 candidate SETP examples with policy relevance for Europe. Three of these are described in higher detail to identify their tipping point characteristics (stable states, mechanisms and abrupt change): the collapse of winter sports tourism, farmland abandonment and sea-level rise-induced migration. We find that stakeholder perceptions play an important role in describing SETPs. The role of climate drivers is difficult to isolate from other drivers because of complex interplays with socio-economic factors. In some cases, the rate of change rather than the magnitude of change causes a tipping point. The clearest SETPs are found on small system scales. On a national to continental scale, SETPs are less obvious because they are difficult to separate from their associated economic substitution effects and policy response. Some proposed adaptation measures are so transformative that their implementations can be considered an SETP in terms of 'response to climate change'. Future research can focus on identification and impact analysis of tipping points using stylized models, on the exceedance of stakeholder-defined critical thresholds in the RCP/SSP space and on the macro-economic impacts of new system states.
Time integrative sampling properties of Speedisk and silicone rubber passive samplers determined by chemical analysis and in vitro bioassay testing
Compared to grab samples, passive samplers have the advantage that they sample over a longer time period and can detect lower compound concentrations in water quality monitoring campaigns. To allow the determination of time-weighted average concentrations, however, sampler uptake should remain linear in time over the entire sampling period. Therefore, the time integrative or linear uptake properties of adsorption-based Speedisks and partitioning-based silicone rubber samplers were assessed with respect to chemically analyzed single compounds and measured bioactivity in in vitro bioassays. Both sampler types were deployed in consecutive and overlapping time series in a WTTP effluent and in the river Meuse up to 105 days. Extracts were chemically analyzed for PCBs, PAHs and pesticides and tested in the Aliivibrio fischeri and DR-LUC bioassays. Speedisks showed time integrative sampling for the detected pesticides as well as for bioassay responses at both sampling locations for the entire sampling period. The silicone rubber samplers showed poor linear uptake in time for the unknown compounds causing bioassay responses. The bioassay results indicate that conversion of a bioassay response to a passive sampler extract into a time-weighted average bioactivity per liter water seems justified for Speedisks, confirming that concentrations in the samplers correspond to a single volume of sampled water for all compounds. The bioassay results also indicate that a similar conversion for silicone rubber extracts should be interpreted with caution. In principle, it is also impossible, because the concentration of each compound contributing to the bioassay response corresponds to a different sampled water volume.
Laminar-turbulent transition of a non-Newtonian fluid flow
Transition from laminar to turbulent flow of non-Newtonian fluids is investigated using velocimetry data. These data are obtained by applying particle image velocimetry to images obtained through ultrasound imaging (echography). This yielded the observation of intermittent structures (puffs and slugs) that are formed during transition. Post its observation, transition is characterized using the friction factor curves and turbulence intensity. Further, a number of models used to predict transition are assessed. This showed the Reynolds number based model by Slatter and the stability parameter based model by Hanks to be most suitable for non-Newtonian fluids with yield stress and low behaviour index.
Prediction of mean wave overtopping discharge using gradient boosting decision trees
Wave overtopping is an important design criterion for coastal structures such as dikes, breakwaters and promenades. Hence, the prediction of the expected wave overtopping discharge is an important research topic. Existing prediction tools consist of empirical overtopping formulae, machine learning techniques like neural networks, and numerical models. In this paper, an innovative machine learning method -gradient boosting decision trees- is applied to the prediction of mean wave overtopping discharges. This new machine learning model is trained using the CLASH wave overtopping database. Optimizations to its performance are realized by using feature engineering and hyperparameter tuning. The model is shown to outperform an existing neural network model by reducing the error on the prediction of the CLASH database by a factor of 2.8. The model predictions follow physically realistic trends for variations of important features, and behave regularly in regions of the input parameter space with little or no data coverage.
Morphodynamic evolution of a fringing sandy shoal : from tidal levees to sea level rise
Intertidal shoals are vital components of estuaries. Tides, waves, and sediment supply shape the profile of estuarine shoals. Ensuring their sustainability requires an understanding of how such systems will react to sea level rise (SLR). In contrast to mudflats, sandy shoals have drawn limited attention in research. Inspired by a channel‐shoal system in the Western Scheldt Estuary (Netherlands), this research investigates governing processes of the long‐term morphodynamic evolution of intertidal estuarine sandy shoals across different timescales. We apply a high‐resolution process‐based numerical model (Delft3D) to generate a channel‐shoal system in equilibrium and expose the equilibrium profile to variations in wave forcing and SLR. Combined tidal action and wave forcing initiate ridge formation at the seaward shoal edge, which slowly propagates landward until a linear equilibrium profile develops within 200 years. Model simulations in which forcing conditions have been varied to reproduce observations show that the bed is most dynamic near the channel‐shoal interface. A decrease/increase in wave forcing causes the formation/erosion of small tidal levees at the shoal edge, which shows good resemblance to observed features. The profile recovers when regular wave forcing applies again. Sandy shoals accrete in response to SLR with a long (decades) bed‐level adaptation lag eventually leading to intertidal area loss. This lag depends on the forcing conditions and is lowest near the channel and gradually increases landward. Adding mud makes the shoal more resilient to SLR. Our study suggests that processes near the channel‐shoal interface are crucial to understanding the long‐term morphodynamic development of sandy shoals.