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Value of information of Structural Health Monitoring in asset management of flood defences
One of the most rapidly emerging measures in infrastructure asset management is Structural Health Monitoring (SHM), which aims at reducing uncertainty in structural performance by using monitoring equipment. As earthen flood defence structures typically have large strength uncertainties, such techniques can be particularly promising. However, insight in the key characteristics for successful SHM for flood defences is lacking, which hampers the practical implementation. In this study, we explore the benefits of pore pressure monitoring, one of the most promising SHM techniques for earthen flood defences. The approach is based on a Bayesian pre-posterior analysis, and results are evaluated based on the Value of Information (VoI) obtained from different monitoring strategies. We specifically investigate the effect on long-term reinforcement decisions. The results show that, next to the relative magnitude of reducible uncertainty, the combination of the probability of having a useful observation and the duration of a SHM effort determine the VoI. As it is likely that increasing loads due to climate change will result in more frequent future reinforcements, the influence of scenarios of different rates of increase in future loads is also investigated. It was found that, in all considered possible scenarios, monitoring yields a positive Value of Information, hence it is an economically efficient measure for flood defence asset management both now and in the future.
Watching the beach steadily disappearing : the evolution of understanding of retrogressive breach failures
Retrogressive breach failures or coastal flow slides occur naturally in the shoreface in fine sands near dynamic tidal channels or rivers. They sometimes retrogress into beaches, shoal margins and river banks where they can threaten infrastructure and cause severe coastal erosion and flood risk. Ever since the first reports were published in the Netherlands over a century ago, attempts have been made to understand the geo-mechanical mechanism of flow slides. In this paper we have established that events, observed during the active phase, are characterized by a slow and steady retrogression into the shoreline, often continuing for many hours. This can be explained by the breaching mechanism, as elaborated in this paper. Recently, further evidence has become available in the form of video footage of active events in Australia and elsewhere, often publicly posted on the internet. All these observations justify the new term ‘retrogressive breach failure’ (RBF event). The mechanism has been confirmed in small-scale flume tests and in a large-scale field experiment. With a better understanding of the geo-mechanical mechanism, current protection methods can be better understood and new defense strategies can be envisaged. In writing this paper, we hope that the coastal science and engineering communities will better recognize and understand these intriguing natural events.
To advance sustainable stewardship, we must document not only biodiversity but geodiversity
Despite many facets of sustainable development being underpinned by access to geological assets, key elements of geodiversity are yet to be incorporated into policy documents and international conventions. We, therefore, propose essential geodiversity variables (EGVs) describing features and processes of Earth’s abiotic surface and subsurface to advance science and sustainable stewardship, complementing the existing essential variables. These EGVs will enable more holistic and better-informed monitoring efforts, decision making, and responses to global change.
Mekong delta much lower than previously assumed in sea-level rise impact assessments
Deltas are low-relief landforms that are extremely vulnerable to sea-level rise. Impact assessments of relative sea-level rise in deltas primarily depend on elevation data accuracy and how well the vertical datum matches local sea level. Unfortunately, many major deltas are located in data-sparse regions, forcing researchers and policy makers to use low-resolution, global elevation data obtained from satellite platforms. Using a new, high-accuracy elevation model of the Vietnamese Mekong delta, we show that quality of global elevation data is insufficient and underscore the cruciality to convert to local tidal datum, which is often neglected. The novel elevation model shows that the Mekong delta has an extremely low mean elevation of ~0.8m above sea level, dramatically lower than the earlier assumed ~2.6 m. Our results imply major uncertainties in sea-level rise impact assessments for the Mekong delta and deltas worldwide, with errors potentially larger than a century of sea-level rise.
Governance bodemdaling : handelingsperspectieven
Als gevolg van bodemdaling staan diverse maatschappelijke functies onder druk en worden de grenzen van het bodem- en watersysteem bereikt. Het Planbureau voor de Leefomgeving heeft inmiddels duidelijk gemaakt dat er hoge kosten met bodemdaling gemoeid zijn. Met name in het stedelijk gebied kunnen de kosten van herstel van schade en frequenter onderhoud aan infrastructuur oplopen tot EURO 5,2 miljard in het jaar 2020. Bodemdaling, door de hoge mate van complexiteit met zowel interne als externe afhankelijkheden in het socio-technisch systeem en de betrokkenheid van verschillende actoren, wordt als gevolg hiervan een steeds belangrijker (en gevoeliger) onderwerp binnen beleidsontwikkeling. In een onderzoek dat is uitgevoerd door Deltares en de Erasmus Governance Design Studio in opdracht van het Uitvoeringsprogramma Bodem en Ondergrond is antwoord gegeven op de vraag ‘Welke handelingsperspectieven t.a.v. governance zijn te ontwikkelen en bruikbaar voor omgaan met bodemdaling in stedelijk en landelijk gebied?’ Hierbij is een methodiek uitgewerkt waarmee handelingsperspectieven voor bodemdaling kunnen worden ontwikkeld. De term handelingsperspectief wordt gedefinieerd als: een samenspel van bestuurlijk-juridische, technische en ruimtelijke maatregelen. Elk handelingsperspectief bevat de rolverdeling, stijl van sturing en een set maatregelen, waardoor de handelingsruimte voor het omgaan met -in dit geval- bodemdaling verkend wordt. De aanpak is ontwikkeld en getoetst in twee praktijkcases: Zaanstad en Rotterdam.
Large scale flood hazard analysis by including defence failures on the Dutch river system
To make informed flood risk management (FRM) decisions in large protected river systems, flood risk and hazard analyses should include the potential for dike breaching. ‘Load interdependency’ analyses attempt to include the system-wide effects of dike breaching while accounting for the uncertainty of both river loads and dike fragility. The intensive stochastic computation required for these analyses often precludes the use of complex hydraulic models, but simpler models may miss spatial inundation interactions such as flows that ‘cascade’ between compartmentalised regions and overland flows that ‘shortcut’ between river branches. The potential for these interactions in the Netherlands has previously been identified, and so a schematisation of the Dutch floodplain and protection system is here developed for use in a load interdependency analysis. The approach allows for the spatial distribution of hazard to be quantified under various scenarios and return periods. The results demonstrate the importance of including spatial inundation interactions on hazard estimation at three specific locations, and for the system in general. The modelling approach can be used at a local scale to focus flood-risk analysis and management on the relevant causes of inundation, and at a system-wide scale to estimate the overall impact of large-scale measures.
Selecting the optimal method to calculate daily global reference potential evaporation from CFSR reanalysis data for application in a hydrological model study
Potential evaporation (PET) is one of the main inputs of hydrological models. Yet, there is limited consensus on which PET equation is most applicable in hydrological climate impact assessments. In this study six different methods to derive global scale reference PET daily time series from Climate Forecast System Reanalysis (CFSR) data are compared: Penman-Monteith, Priestley-Taylor and original and re-calibrated versions of the Hargreaves and Blaney-Criddle method. The calculated PET time series are (1) evaluated against global monthly Penman-Monteith PET time series calculated from CRU data and (2) tested on their usability for modeling of global discharge cycles. A major finding is that for part of the investigated basins the selection of a PET method may have only a minor influence on the resulting river flow. Within the hydrological model used in this study the bias related to the PET method tends to decrease while going from PET, AET and runoff to discharge calculations. However, the performance of individual PET methods appears to be spatially variable, which stresses the necessity to select the most accurate and spatially stable PET method. The lowest root mean squared differences and the least significant deviations (95% significance level) between monthly CFSR derived PET time series and CRU derived PET were obtained for a cell-specific re-calibrated Blaney-Criddle equation. However, results show that this re-calibrated form is likely to be unstable under changing climate conditions and less reliable for the calculation of daily time series. Although often recommended, the Penman-Monteith equation applied to the CFSR data did not outperform the other methods in a evaluation against PET derived with the Penman-Monteith equation from CRU data. In arid regions (e.g. Sahara, central Australia, US deserts), the equation resulted in relatively low PET values and, consequently, led to relatively high discharge values for dry basins (e.g. Orange, Murray and Zambezi). Furthermore, the Penman-Monteith equation has a high data demand and the equation is sensitive to input data inaccuracy. Therefore, we recommend the re-calibrated form of the Hargreaves equation which globally gave reference PET values comparable to CRU derived values for multiple climate conditions. The resulting gridded daily PET time series provide a new reference dataset that can be used for future hydrological impact assessments in further research, or more specifically, for the statistical downscaling of daily PET derived from raw GCM data.
ENSURF : multi-model sea level forecast - implementation and validation results for the IBIROOS and Western Mediterranean regions
ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast that makes use of several storm surge or circulation models and near-real time tide gauge data in the region, with the following main goals: 1. providing easy access to existing forecasts, as well as to its performance and model validation, by means of an adequate visualization tool ; 2. generation of better forecasts of sea level, including confidence intervals, by means of the Bayesian Model Average technique (BMA). The Bayesian Model Average technique generates an overall forecast probability density function (PDF) by making a weighted average of the individual forecasts PDF's; the weights represent the Bayesian likelihood that a model will give the correct forecast and are continuously updated based on the performance of the models during a recent training period. This implies the technique needs the availability of sea level data from tide gauges in near-real time. The system was implemented for the European Atlantic facade (IBIROOS region) and Western Mediterranean coast based on the MATROOS visualization tool developed by Deltares. Results of validation of the different models and BMA implementation for the main harbours are presented for these regions where this kind of activity is performed for the first time. The system is currently operational at Puertos del Estado and has proved to be useful in the detection of calibration problems in some of the circulation models, in the identification of the systematic differences between baroclinic and barotropic models for sea level forecasts and to demonstrate the feasibility of providing an overall probabilistic forecast, based on the BMA method.
Inception of a global atlas of sea levels since the Last Glacial Maximum (introduction)
Determining the rates, mechanisms, and geographic variability of relative sea-level (RSL) change following the Last Glacial Maximum (LGM) provides insight into the sensitivity of ice sheets to climate change, the response of the solid Earth and gravity field to ice-mass redistribution, and constrains statistical and physical models used to project future sea-level rise. To do so in a scientifically robust way requires standardized datasets that enable broad spatial comparisons that minimize bias. As part of a larger goal to develop a unified, spatially-comprehensive post-LGM global RSL database, in this special issue we provide a standardized global synthesis of regional RSL data that resulted from the first ‘Geographic variability of HOLocene relative SEA level (HOLSEA)’ meetings in Mt Hood, Oregon (2016) and St Lucia, South Africa (2017). The HOLSEA meetings brought together sea-level researchers to agree upon a consistent protocol to standardize, interpret, and incorporate realistic uncertainties of RSL data. This special issue provides RSL data from ten geographical regions including new databases from Atlantic Europe and the Russian Arctic and revised/expanded databases from Atlantic Canada, the British Isles, the Netherlands, the western Mediterranean, the Adriatic, Israel, Peninsular Malaysia, Southeast Asia, and the Indian Ocean. In total, the database derived from this special issue includes 5634 (5290 validated) index (n ¼ 3202) and limiting points (n ¼ 2088) that span from ~20,000 years ago to present. Progress in improving the standardization of sea-level databases has also been accompanied by advancements in statistical and analytical methods used to infer spatial patterns and rates of RSL change from geological data that have a spatially and temporally sparse distribution and geochronological and elevational uncertainties. This special issue marks the inception of a unified, spatially-comprehensive post-LGM global RSL database.
State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management
Combining metamodels with data assimilation schemes allows the incorporation of up-to-date information in metamodels, offering new opportunities for operational water resources management. We developed a data assimilation scheme for the unsaturated zone metamodel MetaSWAP using OpenDA, which is an open source data assimilation framework. A twin experiment showed the feasibility of applying an Ensemble Kalman Filter as a data assimilation method for updating metamodels. Furthermore, we assessed the accuracy of root zone soil moisture model estimates when assimilating the regional SMAP L3 Enhanced surface soil moisture product. The model accuracy is assessed using in situ soil moisture measurements collected at 12 locations in the Twente region, the Netherlands. Although the accuracy of the model estimates does not improve in terms of correlation coefficient, the accuracy does improve in terms of Root Mean Square Error and bias. Therefore, the assimilation of surface soil moisture observations has value for updating root zone soil moisture model estimates. In addition, the accuracy of the model estimates improves on both regional and local spatial scales. The increasing availability of remotely sensed soil moisture data will lead to new possibilities for integrating metamodelling and data assimilation in operational water resources management. However, we expect that significant investments in computational capacities are necessary for effective implementation in decision-making.