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Breach modelling: why, when and how?
No full textEarthen dams and flood embankments are critical infrastructure that play a vital role for many purposes. However, the potential for failure by breaching carries severe consequences to the people and the assets they serve. It is therefore important to understand the potential failure processes and impacts that can be associated with such failures. An integral part of any thorough risk assessment process is the prediction or modelling of the breach processes. To date, three approaches to breach modelling exist, namely, parametric, semi-physically based and physically based models.
This paper introduces and explains the advantages and disadvantages of each type of analysis. It also provides guidance for selecting the most appropriate method for common scenarios. An example of a physically based model (The EMBREA model) will also be described showing the significance of looking at the embankment design detail, the associated variations in failure processes and how this can significantly affect the consequences. An online version of EMBREA is also introduced which can be used by researchers and practitioners to accurately assess the risk of dam and/or embankment failure through overtopping or piping. The paper concludes by outlining the future direction of breach prediction methods globally with details on the current and planned research
Use of large datasets to support drought management planning and climate change assessments
Get PDFAdvantages and application of large stochastic and climate change datasets to drought and water supply management planning.
Water is considered to be one of the main mechanisms through which people will experience climate change. As a consequence of climate change and population growth, the number of people estimated to become exposed to water scarcity is projected to increase sharply in the future. Concerns regarding the potential implications of extreme, previously not experienced, droughts are also increasing.
Water supply planning in the UK has begun to move beyond using only the historic record to plan investments to maintain secure supplies. The UK has adopted the use of stochastically generated droughts to provide a more comprehensive understanding of resilience across a broad range of plausible drought events. Recent advancements in climate modelling captured within the latest UK Climate Projections 2018 could potentially begin to address the need for physically-based, plausible datasets that combine both natural climate variability and a changing climate in representing droughts of the future.
This poster focusses on applications and advantages of stochastic and climate change datasets, and discusses some of the potential issues associated with their use. Solutions to these issues are also discussed
Principles into practice: monitoring of dredging projects
No full textThere are no simple answers to the question “what should the monitoring of my dredging project comprise of?” Instead, there exists a set of principles which can be followed to guide experienced professionals in the design of monitoring (see for example CEDA, 2015 and Laboyrie et al., 2018). Principles (theory) and practice (reality) are often different however. In this paper we seek to provide a useful (quick reference) summary of the key principles (and process) to apply to monitoring design. We provide an explanation of the reality arising from applying these principles in the case of the physical monitoring of a 30Mm3 dredge in a temperate estuarine system
DAMSAT: A new Earth Observation based tool for monitoring tailings dams
No full textThe failures of tailings dams, which store mining waste, present a significant risk to the health of people and the environment, especially in many low income countries where the extractive industry contributes significantly to the economy. In countries such as Peru, despite the large revenues generated by mining, it often generates social discontent and inequalities owing to the impacts of tailings dam failures on ecosystem services and local communities’ livelihoods.
The rate of failure of tailings dams is increasing. It is essential that tailings dams are proactively monitored to reduce their probability of failure. Most recent tailings dams failures have been avoidable. However, there is generally a lack of transparency and accountability for these structures. In the past 10 years an increase in the global coverage and accuracy of Earth Observation (EO) based information has made it technically possible to use EO-based data to remotely monitor critical aspects of tailings dams, such as their deformation and the leakage of pollutants. An EO-based service, called DAMSAT, is being developed to help to allow tailings dams to be monitored cost effectively, and also help to forecast any potentially risk inducing behaviour from these structures several weeks in advance. The DAMSAT monitoring system is being piloted in Peru.
In recent years there have been a number of tailings dam failures in Peru. In 2008 the Peruvian Government declared a state of emergency at a mine near Lima over fears that arsenic, lead and cadmium from a tailings dam could pollute the main water supply for the capital. A low cost EO-based monitoring system could improve the transparency, safety and sustainability of mining operations, helping Peru to meet their Sustainable Development Goals related to clean water and sanitation, and responsible consumption and production
FACE programme: some learning points in flood and coastal erosion risk management
No full textThe Flood and Coastal Engineering (FACE) programme is providing BSc and MSc degrees for Environment Agency staff and others with an interest in flood and coastal erosion risk management. The programme includes an initial 2-year Foundation degree. FACE is sponsored by the Environment Agency and is being implemented by Brunel University and HR Wallingford. The presentation will provide a summary of the main areas of study covered by the degree courses.
In addition, some specific learning points covered in the FACE programme will be described to provide an insight into the courses and their importance for flood and coastal erosion risk management. It is intended that the learning points will be of general interest to conference participants and will be based on site visits and practical exercises undertaken by students.
The learning points will include problems related to flood water level and flow data and how they can be identified and corrected, a brief summary of how flood probability and flood risk maps are derived and the meaning of the information presented, and roles and responsibilities in flood resilience
D-MOSS: Dengue forecasting MOdel Satellite-based System
Get PDFD-MOSS, Dengue forecasting MOdel Satellite-based System, is a dengue fever early warning system for Vietnam
being developed by a project funded by the UK Space Agency’s International Partnerships Programme. The
D-MOSS project is developing a suite of innovative tools that will allow public health authorities to identify areas
of high risk for disease epidemics before an outbreak occurs, in order to target resources to reduce spreading of
epidemics and improve disease control.
Since 2000, there has been an increase of over 100% in the number of cases of dengue fever in Vietnam,
with 185,000 cases occurring in 2017 alone, and there is currently no system for forecasting future dengue
outbreaks.
The D-MOSS early warning platform includes a water availability component. Water availability directly
impacts dengue epidemics due to the provision of mosquito breeding sites. These dynamics are often non-linear;
too much rainfall can fill outdoor containers, while too little can lead to people storing water in open containers
within their homes. Both increase the population of Aedes aegypti mosquitoes and in turn the risk of dengue
outbreaks. However, water availability or water resource management is rarely accounted for in dengue prediction
models.
The system generates monthly water stress assessments and uses them as inputs to a component of the
dengue early warning system which also improves the skill of the system’s predictions. In addition, these
forecasts of water stress will help to improve Vietnam’s water management. Vietnam’s Sustainable Development
Strategy for 2011-2020 identifies one of the major challenges facing Vietnam as the issue of transboundary water management, because 63% of the surface water comes from upstream countries.
The D-MOSS project is developing a forecasting system in which Earth Observation datasets are combined
with weather forecasts and a hydrological model to predict the likelihood of future dengue epidemics up to eight
months in advance. The system is calibrated against historical data. The water availability forecasts are fed into statistical forecasting models of disease incidence. This dengue early warning system model integrates the water
stress forecast with a range of other covariates important for dengue transmission.
The D-MOSS project is within the first year of its three-year term and is currently focused on platform
and model development, while gathering the key input data and engaging with the Vietnamese government to
ensure that all components are fit for purpose. The portrayal system is designed to communicate the dengue
and water availability forecasts to the Vietnamese Ministries of Health and Natural Resources and Environment,
respectively. A user interface will also incorporate supporting information on recommended actions, provided by
the decision makers and based on the forecasts and associated uncertainty
Dynamic spatio-temporal generation of large-scale synthetic gridded precipitation: with improved spatial coherence of extremes
No full textWith the ongoing development of distributed hydrological models, flood risk analysis calls for synthetic, gridded precipitation data sets. The availability of large, coherent, gridded re-analysis data sets in combination with the increase in computational power, accommodates the development of new methodology to generate such synthetic data. We tracked moving precipitation fields and classified them using self-organising maps. For each class, we fitted a multivariate mixture model and generated a large set of synthetic, coherent descriptors, which we used to reconstruct moving synthetic precipitation fields. We introduced randomness in the original data set by replacing the observed precipitation fields in the original data set with the synthetic precipitation fields. The output is a continuous, gridded, hourly precipitation data set of a much longer duration, containing physically plausible and spatio-temporally coherent precipitation events. The proposed methodology implicitly provides an important improvement in the spatial coherence of precipitation extremes. We investigate the issue of unrealistic, sudden changes on the grid and demonstrate how a dynamic spatio-temporal generator can provide spatial smoothness in the probability distribution parameters and hence in the return level estimates
Tsunami scour at onshore structures
No full textTsunami induced scour at onshore coastal structures can cause exposure of the foundations and lead to failure. This paper presents experimental observations of a 147 s crest-led wave inundation, causing scouring and loading on 0.2 m wide square and 0.4 m wide rectangular onshore structures. At 1:50 Froude scale these equate to a 17.3 min inundation at 10 and 20 m wide structures. Scour development is measured using GoPro cameras situated inside the Perspex structures. The hydrostatic load is calculated from the integration of pressure readings along the front face of the structures, and the hydrodynamic loading is estimated from the approach flow velocity, as measured by a Vectrino II profiler. The results show that the maximum scour depth occurs during the inundation before significant slumping decreases the end scour depth. Both the in-test and final scour depths for the 0.4 m structure are greater, due to the larger blockage causing greater acceleration of the flow around the structure. For both structures, the hydrostatic loading is dominant over hydrodynamic load
WireWall – laboratory and field measurements of wave overtopping
No full textIn the UK £150bn of assets and 4 million people are at risk from coastal flooding, whilst the construction of sea wall defence schemes typically cost £10,000 per linear meter. With reductions in public funding and 3200 km of coastal defences, cost savings are required that do not cause a reduction in flood resistance. Increasingly there is a requirement to design new coastal flood defences with site specific tolerable hazard thresholds, with regard to wave overtopping during storms of varying severity. The traditional and preferred method for establishing these thresholds has always been physical modelling, but it is recognized that these can cost many 10s thousands of Euros. This is not always feasible, and coastal asset managers have long been looking for affordable methods that can be used to assess overtopping in the field.
Recent advances in technology mean existing wave height sensors can now measure at the high frequencies (a few 100 Hz) required to obtain overtopping data, making this the ideal time to initiate a step-change in coastal hazard monitoring capabilities. By converting the existing wave measurement technology into an overtopping monitoring system "WireWall", we can measure the excursions of overtopping volumes and velocities in the lee of a structure. These then can be readily integrated to obtain wave-by-wave volumes and overtopping discharges (l/s/m). At Crosby in the north west of England, the 900 m sea wall will reach the end of its design life in the next 5 years. Deployments of WireWall at this site will provide site-specific data and calibrated overtopping that will feed into the design of a new sea wall.
Before deployment in the field, an extensive set of tests were carried out in a 2D wave flume. Starting with known wave conditions from a buoy near the Crosby sea wall, and values from a joint probability wave and water level study, a representation of the sea wall has been tested. Extensive testing was performed to calibrate the WireWall rig. Using traditional methods of assessing wave overtopping in the flume, the WireWall measurements could be directly calibrated against the known volumes collected in the overtopping tanks. At the time of writing, analysis of the laboratory and the flume wave overtopping data is ongoing. The paper describes how WireWall works, describes the laboratory measurements, the field deployments and presents and compares the analysis from the two systems.
A successful deployment of the calibrated WireWall rig at Crosby was during the winter of 2018/2019, where waves can be seen overtopping the sea wall is shown in Fig. 1
Characterization and mapping of a deep-sea sponge ground on the Tropic Seamount (Northeast Tropical Atlantic): Implications for spatial management in the high seas
No full textFerromanganese crusts occurring on seamounts are a potential resource for rare earth elements that are critical for low-carbon technologies. Seamounts, however, host vulnerable marine ecosystems (VMEs), which means that spatial management is needed to address potential conflicts between mineral extraction and the conservation of deep-sea biodiversity. Exploration of the Tropic Seamount, located in an Area Beyond National Jurisdiction (ABNJ) in the subtropical North Atlantic, revealed large amounts of rare earth elements, as well as numerous VMEs, including high-density octocoral gardens, Solenosmilia variabilis patch reefs, xenophyophores, crinoid fields and deep-sea sponge grounds. This study focuses on the extensive monospecific grounds of the hexactinellid sponge Poliopogon amadou (Thomson, 1878). Deep-sea sponge grounds provide structurally complex habitat, augmenting local biodiversity. To understand the potential extent of these sponge grounds and inform spatial management, we produced the first ensemble species distribution model and local habitat suitability maps for P. amadou in the Atlantic employing Maximum Entropy (Maxent), General Additive Models (GAMs), and Random Forest (RF). The main factors driving the distribution of the sponge were depth and maximum current speed. The sponge grounds occurred in a marked bathymetric belt (2,500 – 3,000 m) within the upper North Atlantic Deep Water mass (2.5∘C, 34.7 psu, O2 6.7–7 mg ml-1), with a preference for areas bathed by moderately strong currents (0.2 – 0.4 ms-1). GAMs, Maxent and RF showed similar performance in terms of evaluation statistics but a different prediction, with RF showing the highest differences. This algorithm only retained depth and maximum currents whereas GAM and Maxent included bathymetric position index, slope, aspect and backscatter. In these latter two models, P. amadou showed a preference for high backscatter values and areas slightly elevated, flat or with gentle slopes and with a NE orientation. The lack of significant differences in model performance permitted to merge all predictions using an ensemble model approach. Our results contribute toward understanding the environmental drivers and biogeography of the species in the Atlantic. Furthermore, we present a case toward designating the Tropic Seamount as an Ecologically or Biologically Significant marine Area (EBSA) as a contribution to address biodiversity conservation in ABNJs