Living With Peak Discharge Uncertainty: The Self-learning Dike

Although river dikes still play a key role for flood protection in the Netherlands\ud there is a growing interest for other measures to deal with larger peak discharges, such as\ud lowering or widening the floodplains. Regardless of the strategy chosen the assessment of\ud its effect on the flood risk depends on the peak discharge statistics. A problem here is that\ud the statistical analysis of peak discharges relies on probability distributions based on the\ud limited time series of extreme discharges. The extrapolation of these distributions are\ud subject to considerable uncertainty, because there is a measuring record of only about 100\ud years and the natural variability can be expected to change as a result of climate change.\ud This raises the question whether a more direct response to the effects of climate change is\ud possible. The natural variability of the peak discharge changes, the changes in this\ud variability due to e.g. climate change and the new statistical distribution can only be\ud established after the actual change has happened. Even with regular updates of the\ud statistical distributions it is inherent that the actions taken to reduce the flood risk are not\ud anticipatory but delayed. As an alternative, this paper presents an adaptive or so-called selflearning\ud approach to deal with the uncertainty in the peak discharge statistics. The\ud difference with the probabilistic design of flood defense works, which depends on the\ud analysis and prediction of uncertain peak discharges, is that the dike is adapted in direct\ud response to peak water levels exceeding the dike height minus a certain safety margin. The\ud results indicate that, on average, adaptive flood management based on observed peak water\ud levels is at least as safe as a probabilistic approach, which necessarily relies on uncertain\ud discharge statistics. Other advantages of the adaptive strategy are also obvious: the rule of\ud response is simple and easy to communicate to the public, and peak water levels are less\ud difficult to measure. In general the example demonstrates that flood management can be\ud based on a direct response to the effects of climate change, without tedious statistical\ud analysis of peak discharge records

Adapting to climate change: the self-learning dike

A problem with the current probabilistic flood prevention strategy in the Netherlands is that it builds on knowledge about the probability distributions for extreme discharges, which are subject to considerable uncertainties due to limited peak discharge records and climate change. It is inherent to this strategy that the actions taken to reduce the flood risk are not anticipatory but following. In the historic flood prevention strategy (practised until the 1950s), referred to as the ‘self-learning dike’, the dike height is kept at a level equal to the highest recorded water level in history plus a certain\ud safety margin. The two flood-prevention strategies are compared on the basis of the average flooding safety during a 100-year period, with the Rhine River at Lobith taken as case example. The results indicate that the self-learning dike performs as well, even slightly better, as the probabilistic design in terms of safety and reasonably in terms of the size and number of adaptations of the dike height, even under climate change

Time-constrained project scheduling with adjacent resources

We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with Adjacent Resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by job groups. As soon as a job of such a group starts, the adjacent resource units are occupied, and they are not released before all jobs of that group are completed. The developed decomposition method separates the adjacent resource assignment from the rest of the scheduling problem. Test results demonstrate the applicability of the decomposition method. The presented decomposition forms a first promising approach for the TCPSP with adjacent resources and may form a good basis to develop more elaborated methods

Роль генетического компонента предрасположенности к раку молочной железы у женщин различных этнических групп населения Крыма

Результаты клинико-генеалогического и генетико-математического методов исследования 57 здоровых и 214 больных раком молочной железы (РМЖ) женщин показали, что частота заболевания злокачественными новообразованиями родственников I степени родства пациентов с РМЖ как крымско-татарской, так и славянских этнических групп более высокая (10,44%), чем в крымской популяции в целом (7,36%). Возникновение РМЖ у женщин крымско-татарской этнической группы в большей мере обусловлено генетической предрасположенностью к злокачественному росту по сравнению со славянской группой, о чем свидетельствуют появления РМЖ в более молодом возрасте как у пробандов-татарок, так и их родственниц (53,4 ± 3,6 и 46,5 ± 11,2 года соответственно в сравнении с 59,8 ± 1,9 и 54,9 ± 8,3 года у славянок), более частое развитие РМЖ у родственниц татарок (48,3 ± 11,1 против 25,6 ± 6,6%), более высокая соотносительная доля наследственных факторов в возникновении рака (генетический компонент 58,5 против 44,5%, р 0,05). Ключевые слова: этнические особенности, злокачественные новообразования, рак молочной железы, наследственность.A clinical/genealogical and genetic mathematic study of 57 healthy subjects and 214 breast cancer (BC) patients showed that malignant neoplasm is more frequent in immediate (degree 1) relatives of BC patients in both Crimean Tartar and Slavic populations compared to the general population (10.44% versus 7.36% respectively). In the Crimean Tartar population, genetic burden plays a more considerable role in BC frequency compared to the Slavic population. This conclusion is based on a number of findings, including: younger age of BC manifestation in both probands and their relatives (53.4 ± 3.6 and 46.5 ± 11.2 in Tartars versus 59.8 ± 1.9 and 54.9 ± 8.3 in Slavs), higher frequency of BC in relatives (48.3 ± 11.1 versus 25.6 ± 6.6% respectively), higher correlative share of genetic factors in the development of malignancy (genetic component: 58.5 against 44.5%, р 0.05). Key Words: ethnic specifics, malignancy, breast cancer, hereditation

A methodology to determine the contribution of stakeholders to the robustness of environmental policy decisions

A methodology is developed in this paper to test the effectiveness of successful stakeholder participation in creating substantively more robust policy, and to identify the factors responsible for that. The comparison is made to a more traditional management of government policy, in which experts in administrative agencies perform the policy analyses. The methodology compares the substantive robustness of the preferred alternative developed in a stakeholder participation process to the robustness of the preferred alternative developed for the same case in an expert-based process. It comprises a case study design that enables realistic performance of both processes, ensures their comparability and guards their quality. The developed methodology appears promising and is currently being applied. A systematic investigation of the relation between stakeholder contribution and the robustness of policy analyses helps formulating arguments for stakeholder involvement. Furthermore it can improve the effectiveness of a participation activity

Earth observation tool for monitoring coastal eutrophication

ISECA is an Interreg project running until September 2014 that aims to advance and disseminate scientific knowledge related to eutrophication in the 2Seas area (English Channel and North Sea).The main objective of ISECA is to develop a demonstration prototype of an information system for monitoring eutrophication of coastal waters.This information system combines in-situ, satellite information and models outputs

Nitrogen source apportionment for the catchment, estuary and adjacent coastal waters of the Scheldt.

Using the systems approach framework (SAF), a coupled model suite was developed for simulating land-use decision making in response to nutrient abatement costs and water and nutrient fluxes in the hydrological network of the Scheldt River, and nutrient fluxes in the estuary and adjacent coastal sea. The purpose was to assess the efficiency of different long-term water quality improvement measures in current and future climate and societal settings, targeting nitrogen (N) load reduction. The spatial-dynamic model suite consists of two dynamically linked modules: PCRaster is used for the drainage network and is combined with ExtendSim modules for farming decision making and estuarine N dispersal. Model predictions of annual mean flow and total N concentrations compared well with data available for river and estuary (r² ≥ 0.83). Source apportionment was carried out to societal sectors and administrative regions; both households and agriculture are the major sources of N, with the regions of Flanders and Wallonia contributing most. Load reductions by different measures implemented in the model were comparable (~75% remaining after 30 yr), but costs differed greatly. Increasing domestic sewage connectivity was more effective, at comparatively low cost (47% remaining). The two climate scenarios did not lead to major differences in load compared with the business-as-usual scenario (~88% remaining). Thus, this spatially explicit model of water flow and N fluxes in the Scheldt catchment can be used to compare different long-term policy options for N load reduction to river, estuary, and receiving sea in terms of their effectiveness, cost, and optimal location of implementation