Rockfall hazard assessment at Ajanta Cave,Aurangabad, Maharashtra,India

The Ajanta caves are situated in Deccan Trap basalt and declared as one of the World Heritage Sites by UNESCO. The present study aims to investigate and understand the damage of caves and to protect the life of the visitors from the rockfall phenomenon at and around the caves. Information related to the detached rock mass/block was acquired by using Barton–Bandis model in Universal Distinct Element Code. Parameters for rockfall simulation were determined by rigorous field study and laboratory experiment and then calibrated some of the parameters by back analysis. RocFall 4.0 program has been used to calculate maximum bounce heights, total kinetic energies, and translational velocities of the falling blocks of different weights. The maximum bounce height varies from 14.0 to 19.0 m for the weight of the block size ranging from 500 to 2,000 kg, whereas the maximum velocity and maximum kinetic energy are 30.0 m/s and 917.66 kJ, respectively. Finally, the results of simulation have been used to find out the position of the barrier and its capacity to design the protection barrier. The barrier capacity was found to be 325 kJ for 2,000 kg of falling blocks at a height of 50.0 m.     

Quantitative assessment of the residual risk in a rockfall protected area

Quantitative Risk Assessment (QRA) has become an indispensable tool for the management of landslide hazard and for planning risk mitigation measures. In this paper we present the evaluation of the rockfall risk at the Solà d’Andorra slope (Andorra Principality) before and after the implementation of risk mitigation works, in particular, the construction of protective fences. To calculate the risk level we have (i) identified the potential rockfall release areas, (ii) obtained the volume distribution of the falling rocks, (iii) determined the frequency of the rockfall events, and (iv) performed trajectographic analysis with a 3D numerical model (Eurobloc) that has provided both the expected travel distances and the kinetic energy of the blocks. The risk level at the developed area located at the foot of the rock cliff has been calculated taking into account the nature of the exposed elements and their vulnerability. In the Forat Negre basin, the most dangerous basin of the Solà d’Andorra, the construction of two lines of rockfall protection fences has reduced the annual probability of loss of life for the most exposed person inside the buildings, from 3.8×10⁻⁴ to 9.1×10⁻⁷ and the societal risk from 1.5×10⁻² of annual probability of loss of life to 1.2×10⁻⁵.     

Hazard assessment in rockfall-prone Himalayan slopes along National Highway-58, India: rating and simulation

A massive disaster occurred in June 2013 in Kedarnath, India, due to cloudburst and extremely heavy rain along the Chorabari glacier. The resulting flash floods further aggravated the instability of natural and hill cut slopes at different places on the downstream side. The village Rambara that existed in close proximity of Kedarnath was swept away under flow of debris and water. The immediate surrounding area, which housed over a hundred and fifty shops and hotels, was completely washed away leaving no trace of civilization. This calamity in Uttarakhand is considered as India’s worst natural disasters after the tsunami in December 2004. On the downstream of the affected areas lie other pilgrim destinations that witness innumerable footfalls every year. Investigation of the health of the slopes on the routes to these destinations is therefore very important to ensure minimal damage to humans and machinery. The Himalayan terrain is a tectonically active mountain belt, having a large number of unstable natural and road cut slopes. Such slopes with rugged topography lie in the high seismic vulnerability zone. Further, the instability is aggravated by natural and anthropogenic activities increasing at a rapid and uncontrollable rate. In the light of the Kedarnath tragedy, more advanced research is being conducted along the National Highways to monitor and prevent slope/structure failures. This study was conducted to evaluate the hazard potential along National Highway-58, near Saknidhar village of Devprayag district by analysing rockfall using hazard rating systems and numerical simulation. Rockfall hazard rating systems were applied to evaluate the conditions of the slopes and to identify the associated risks. Based on the field and laboratory analyses, the parameters required for numerical models were determined. The bounce height, roll-out distance, kinetic energy and speed of the detached blocks were determined by using a competent rockfall simulator. The results obtained were used to identify rockfall risk in the region. Optimization strategies were applied during investigation by modifying the slope angle, ditch width and ditch angle to assess the possibility of a hazard to occur in different scenarios. The simulation studies revealed that an increasing slope angle could significantly increase the kinetic energy of the rock blocks. However, an increase in the ditch angle and the ditch width reduces the energy of moving blocks. The maximum bounce height above the slope varied from 0.003 m to 0.8 m for 10-kg blocks, whereas the maximum velocity and the maximum kinetic energy under such circumstances were 7.882 m/s and 379.89 J, respectively. The barrier capacity was found to be 233.18 J for 10-kg falling blocks at a height of 10.02 m. From the optimization studies, it was found that the risk can be reduced by up to 13 % if the slope of 70° has a ditch angle of 15° while on a flat ditch, the maximum risk will be at an angle of 65°. If the ditch angle is increased, the vertical component of the falling blocks is more effective than that in case of a flat ditch. These optimization studies lay foundation for advanced research for mitigation of rockfall hazards in similar potential areas.

     

Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates

With the recent transition to a more risk-based approach in flood management, flood risk models—being a key component in flood risk management—are becoming increasingly important. Such models combine information from four components: (1) the flood hazard (mostly inundation depth), (2) the exposure (e.g. land use), (3) the value of elements at risk and (4) the susceptibility of the elements at risk to hydrologic conditions (e.g. depth–damage curves). All these components contain, however, a certain degree of uncertainty which propagates through the calculation and accumulates in the final damage estimate. In this study, an effort has been made to assess the influence of uncertainty in these four components on the final damage estimate. Different land-use data sets and damage models have been used to represent the uncertainties in the exposure, value and susceptibility components. For the flood hazard component, inundation depth has been varied systematically to estimate the sensitivity of flood damage estimations to this component. The results indicate that, assuming the uncertainty in inundation depth is about 25 cm (about 15% of the mean inundation depth), the total uncertainty surrounding the final damage estimate in the case study area can amount to a factor 5–6. The value of elements at risk and depth–damage curves are the most important sources of uncertainty in flood damage estimates and can both introduce about a factor 2 of uncertainty in the final damage estimates. Very large uncertainties in inundation depth would be necessary to have a similar effect on the uncertainty of the final damage estimate, which seem highly unrealistic. Hence, in order to reduce the uncertainties surrounding potential flood damage estimates, these components deserve prioritisation in future flood damage research. While absolute estimates of flood damage exhibit considerable uncertainty (the above-mentioned factor 5–6), estimates for proportional changes in flood damages (defined as the change in flood damages as a percentage of a base situation) are much more robust.     

Quantitative risk assessment of slope hazards along a section of railway in the Canadian Cordillera—a methodology considering the uncertainty in the results

Railway alignments through the Canadian Cordillera are constantly exposed to slope instabilities. Proactive mitigation strategies have been in place for a few decades now, and instability record keeping has been recognized as an important aspect of them. Such a proactive strategy has enhanced the industry’s capacity to manage slope risks, and some sections have been recognized as critical due to the frequency of instabilities. At these locations, quantification of the risks becomes necessary. Risk analysis requires knowledge of some variables for which statistical data are scarce or not available, and elicitation of subjective probabilities is needed. A limitation of such approaches lies in the uncertainty associated to those elicited probabilities. In this paper, a quantitative risk analysis is presented for a section of railway across the Canadian Cordillera. The analysis focused on the risk to life of the freight train crews working along this section. Upper and lower bounds were elicited to cope with the uncertainties associated with this approach. A Monte Carlo simulation technique was then applied to obtain the probability distribution of the estimated risks. The risk probability distribution suggests that the risk to life of the crews is below previously published evaluation criteria and within acceptable levels. The risk assessment approach proposed focuses on providing a measure of the uncertainty associated with the estimated risk and is capable of handling distributions that cover more than two orders of magnitude.     

四川罗家青杠岭崩塌风险的定量评价研究

我国多山,崩塌灾害频繁发生,相应的风险评价也得到了越来越多的关注。由于崩塌发生和运移过程的高度不确定性以及历史数据的不完备,往往很难进行相应的定量风险评价。四川罗家青杠岭的崩塌现场非常典型,而且现场资料较全、历史数据较多并且明确,是开展崩塌风险定量研究的很好实例。通过现场工程地质调查、测绘和统计分析,确定了历史崩塌的物源区、堆积区、最大运移距离、年发生概率以及坡体上的4块典型危岩体A-D。基于历史崩塌堆积区的块石统计特征以及物源区危岩体失稳启动位置的不确定性,利用二维Rockfall模拟软件对所在坡面的恢复系数及摩擦系数进行了反演。在此基础上,对危岩体A-D失稳后的运动特征进行了随机性数值模拟和统计分析,从而确定了崩塌的到达概率。基于崩塌发生概率、到达概率、承灾体时空分布概率和易损性的乘积,作者对罗家青杠岭崩塌进行了定量风险评价。评价结果表明,危岩体A和D的风险值处于不可接受的风险区间,块石B和C的风险值处于警告的风险区间,严重威胁着坡脚附近居民的生命财产安全,有必要采取相应的防灾减灾措施。     

Risk analysis for remediation of contaminated sites: the geostatistical approach

The assessment of the risks associated with contamination by elevated levels of pollutants is a major issue in most parts of the world. The risk arises from the presence of a pollutant and from the uncertainty associated with estimating its concentration, extent and trajectory. The uncertainty in the assessment comes from the difficulty of measuring the pollutant concentration values accurately at any given location and the impossibility of measuring it at all locations within a study zone. Estimations tend to give smoothed versions of reality, with the smoothing effect being inversely proportional to the amount of data. If risk is a measure of the probability of pollutant concentrations exceeding specified thresholds, then the variability is the key feature in risk assessment and risk analysis. For this reason, geostatistical simulations provide an appropriate way of quantifying risk by simulating possible “realities” and determining how many of these realities exceed the contamination thresholds, and, finally, provides a means of visualizing risk and the geological causes of risk. This study concerns multivariate simulations of organic and inorganic pollutants measured in terrain samples to assess the uncertainty for the risk analysis of a contaminated site, an industrial site in northern Italy that has to be remediated. The main geostatistical tools are used to model the local uncertainty of pollutant concentrations, which prevail at any unsampled site, in particular by means of stochastic simulation. These models of uncertainty have been used in the decision-making processes to identify the areas targeted for remediation.     

节理岩体关键块体稳定的概率分析

基于地下岩体受节理面的控制,节理面的几何和力学参数随机分布,从而导致岩体系统具有高度不确定性,提出以关键块体理论为基础,考虑节理几何和力学参数随机性的岩体开挖可靠度分析方法,并给出了块体稳定的总失效概率评价模型。以澳大利亚阿德莱德地区一铜矿地质条件为例,以节理面倾角、倾向、摩擦系数和黏聚力为随机变量,通过Monte Carlo模拟和概率图方法,进行了岩体可靠度和失效概率的计算。最后,采用条件概率的分析方法,计算了单面滑动块体的总失效概率。计算结果表明,块体沿单面滑动并且出现的概率为11.0%,总的失效概率为3.85%,超过一般岩体工程可允许的风险水平,认为该方法可以作为评价块体可靠性的依据。     

Rock slope stability and design in Arafat–Muzdalifa area,Saudi Arabia

The present contribution is a complete study extending before, during, and after the excavation of the mountain side that lying north of road 7. It includes slope stability analysis, rock cut design, and rockfall modeling for natural slope and rock cut face. Neoproterozoic granodiorite and biotite granite forming the slope body have medium to very high strengths. Mineral compositions and textures of these intact rocks control the strength values. These rocks are intensively dissected by fractures that are filled with montmorillonite and chlorite. The high plasticity and slippery nature of these filling materials represent the main problem that may face a rock cut designer because they damage the mechanical properties of these fractures. The problem begins with the selection of the rock mass classification that deals with the fracture fillings and extends during the stability analysis and the suggestion of mitigation and supporting measures. The rock masses building the natural slope are suffered by plane, wedge, and toppling failures. Therefore, two rock cut designs are suggested to avoid the hazards related to these failures and considering the construction cost as well. Rockfall modeling for the natural slope and rock cut designs was done to assess the hazards related to these falling of the blocks. The kinetic energy of falling blocks is represented on the roadway by the coverage distance and block rebound amplitude. Slope height has a positive effect on the values of these distance and amplitude, whereas the steepness of berm height has a negative effect on them. Coverage distance is a function to the location of rockfall barrier and to the width of road ditch, while the amplitude controls the barrier height.     

Prediction of the Bullet Effect for Rockfall Barriers: a Scaling Approach

The so-called “bullet effect” refers to the perforation of a rockfall protection mesh by impact of a small block, which has a kinetic energy lower than the design value, where the design value is determined through tests with relatively large blocks. Despite playing a key role in the overall performance of a flexible rockfall barrier, this phenomenon is still poorly understood at present. An innovative approach for quantitatively characterizing this effect based on dimensional analysis is proposed in this paper. The analysis rests on a hypothesis that the relevant variables in the impact problem can be combined into three strongly correlated dimensionless parameters. The relationship between these dimensionless parameters (i.e., the scaling relationship) is subsequently investigated and validated by means of data generated with a finite element model. The validation process shows that the dimensionless parameters are apt and that the proposed scaling relationship characterizes the bullet effect with a reasonable level of accuracy. An example from the literature involving numerical simulation of a full rock barrier is considered, and satisfactory agreement between the calculated performance of the barrier and that predicted by the established scaling relationship is observed.     

The probability of proof in geomorphology —an example of the application of information theory to a new kind of glacigenetic morphological type,the ice-marginal ramp (Bortensander)

The scientific acceptance of presentations of proof is largely dependent upon the parts of mathematical logic upon which they are based. This explains the trend of introducing quantitative methods into tho disciplines which — due to the historical dimensions of their subjects — have so far followed a qualitative analysis of character coincidences i.e. a typogenetic form of reasoning. But the application of reductionistic quantification such as was followed in the GMK 25 project foundered because of the polymorphic structure of the phenomena. It was this that made geomorphological proof so difficult, since an inductive basis for general lawful relations can only be provided by regionally detailed observations of complexes with developments of their own. The application of information theory however e.g. in relation to the glacigenetic Type ‘Bortensander’ or ice-marginal ramps (IMR) now allows the determination of the probability of the coincidental occurrence of characteristics and a measure of the probability of the causal nexus upon which this is based. By transposing the basis of induction on to an abstract plane a high degree of proof of typogenetic arguments in geomorphology may be provided. The quantification here does not count the elements of the proof directly but is related to the occurrence of those indicators which form the empirically based qualitative units of the inductive key. The author gratefully acknowledges the translation of this paper rendered by Cyril A. Halstead, Glasgow     

Rock fall hazard along the railway corridor to Jerusalem,Israel, in the Soreq and Refaim valleys

We evaluate rock fall hazard along the railway corridor to Jerusalem, Israel, in the Soreq and Refaim valleys. For the purpose, we use a combination of historical information on past rock fall events, field surveys aided by the interpretation of aerial photographs, and numerical rock fall modeling. Historical information indicates that on July 11, 1927 an m _L 6.2 Dead-Sea transform earthquake caused rock falls in the studied area. The seismically induced rock falls damaged the railway tracks. Field observations revealed that the source area for the 1927 failures was located in the Aminadav formation, at the contact with the Moza formation. At the stratigraphic contact, rock blocks 10⁰–10¹ m³ in size are formed as a result of tensile stresses and associated fracturing in the dolomite of the Aminadav formation, combined with continuous creep of the blocks on the marl of the underlying Moza formation. We use topographical, geological, and geomorphological information to calibrate a three-dimensional numerical simulation of rock falls in the studied area. We use the results of the numerical modeling, and additional independent information, to assess rock fall hazard and the associated risk in the Soreq and Refaim valleys. Results indicate that in the studied area, rock fall risk to the railway line to Jerusalem is due primarily to Dead-Sea transform earthquakes, with m _L  > 6. We identify nine sections of the railway line where rock fall risk exists, for a total length of 2.5 km. We further note that seismically induced rock falls can produce damage to the road network in the studied area, make it difficult or impossible for earthquake casualties to reach hospitals in Jerusalem. We conclude offering recommendations on how to mitigate the risk posed by earthquake-induced rock falls in the studied area.     

Quantitative risk assessment of landslides with direct simulation of pre-failure to post-failure behaviors

Most previous studies on the quantitative risk assessment (QRA) of landslides focused on the probability of slope failure at the pre-failure stage and adopted empirical models for consequence analysis. The conventional approaches simplify the relationship between the pre-failure state and the post-failure behavior and cannot reasonably account for the effects of uncertainty on the entire landslide process. In this paper, an efficient QRA method that involves the direct simulation of the entire landslide process is proposed. A QRA formula that considers the probability of only those landslides that can impact the element at risk is used. The coupled Eulerian–Lagrangian method is used to simulate the entire landslide process and to identify slopes that can impact the element at risk and determine the failure consequences. The subset simulation method is adopted to efficiently estimate the probability of landslide impact, and parameter uncertainty is considered. Two case histories of landslides are investigated. First, the 2011 Baqiao loess landslide in Xi’an, China, is investigated, and the results of the proposed method are compared with those of the conventional approaches. Second, the proposed method is applied to assess the risk of the 2015 Ganjingzi landslide in the Three Gorges Reservoir. The effects of the risk mitigation works are also discussed.

     

A quantitative vulnerability function for fluvial sediment transport

In quantitative risk assessment, risk is expressed as a function of hazard, elements at risk exposed, and vulnerability. Vulnerability is defined as the expected degree of loss for an element at risk as a consequence of a certain event, following a natural-scientific approach combined with economic methods of loss appraisal. The resulting value ranges from 0 (no damage) to 1 (complete destruction). With respect to torrent processes, i.e., fluvial sediment transport, this concept of vulnerability—though widely acknowledged—did not result in sound quantitative relationships between process intensities and associated degrees of loss so far, even if considerable loss occurred during recent years. To close this gap and establish this relationship, data from three well-documented torrent events in the Austrian Alps were used to derive a quantitative vulnerability function applicable to residential buildings located on torrent fans. The method applied followed a spatially explicit empirical approach within a GIS environment and was based on process intensities, the spatial characteristics of elements at risk, and average reconstruction values on a local scale. Additionally, loss data were collected from responsible administrative bodies and analysed on an object level. The results suggest a modified Weibull distribution to fit best to the observed damage pattern if intensity is quantified in absolute values, and a modified Frechet distribution if intensity is quantified relatively in relation to the individual building height. Additionally, uncertainties resulting from such an empirical approach were studied; in relation to the data quality a 90% confidence band was found to represent the data range appropriately. The vulnerability relationship obtained allows for an enhanced quantification of torrent risk, but also for an inclusion in comprehensive vulnerability models including physical, social, economic, and institutional vulnerability. As a result, vulnerability to mountain hazards might decrease in the future.     

Proton migration in portlandite inferred from activation energy of self-diffusion and potential energy curve of OH bond

A fundamental mechanism on the atomic level for self-diffusion in the proton layer of portlandite, Ca(OH)₂, was investigated by conducting hydrogen–deuterium (H–D) exchange diffusion experiments and by deriving potential energy curves of OH vibrations from optical absorption measurements. Synthetic single crystals of portlandite were used in H–D experiments between 250 and 450°C at 150 MPa. Arrhenius parameters for proton diffusion perpendicular to the c-axis gave a frequency factor of 1.0 × 10⁻¹⁰ m²/s and activation energy of 0.61 eV (58.5 kJ/mol). The activation energy corresponds to the height of the potential barrier between two oxygen atoms across an interlayer. The potential barrier height was also theoretically estimated using the OH potential energy curve (OH-PEC) determined by optical absorption measurements. Experimental and theoretical results suggest that the potential barrier height cannot be simply determined by overlapping two OH-PECs. The potential barrier derived theoretically was 3.11 eV. This is too high for the activation energy of the proton diffusion. It implies that the interaction between a diffusing proton and the vacancy of a proton site, and the shortening of interlayer oxygen distance by thermal vibration reduce the potential barrier.     

Rockfall Hazard Analysis From Discrete Fracture Network Modelling with Finite Persistence Discontinuities

Developing an accurate representation of the rock mass fabric is a key element in rock fall hazard analysis. The orientation, persistence and density of fractures control the volume and shape of unstable blocks or compartments. In this study, the discrete fracture modelling technique and digital photogrammetry were used to accurately depict the fabric. A volume distribution of unstable blocks was derived combining polyhedral modelling and kinematic analyses. For each block size, probabilities of failure and probabilities of propagation were calculated. A complete energy distribution was obtained by considering, for each block size, its occurrence in the rock mass, its probability of falling, its probability to reach a given location, and the resulting distribution of energies at each location. This distribution was then used with an energy–frequency diagram to assess the hazard.     

Probabilistic disaggregation of a spatial portfolio of exposure for natural hazard risk assessment

In natural hazard risk assessment situations are encountered where information on the portfolio of exposure is only available in a spatially aggregated form, hindering a precise risk assessment. Recourse might be found in the spatial disaggregation of the portfolio of exposure to the resolution of the hazard model. Given the uncertainty inherent to any disaggregation, it is argued that the disaggregation should be performed probabilistically. In this paper, a methodology for probabilistic disaggregation of spatially aggregated values is presented. The methodology is exemplified with the disaggregation of a portfolio of buildings in two communes in Switzerland and the results are compared to sample observations. The relevance of probabilistic disaggregation uncertainty in natural hazard risk assessment is illustrated with the example of a simple flood risk assessment.     

A Fixed-Path Markov Chain Algorithm for Conditional Simulation of Discrete Spatial Variables

The Markov chain random field (MCRF) theory provided the theoretical foundation for a nonlinear Markov chain geostatistics. In a MCRF, the single Markov chain is also called a “spatial Markov chain” (SMC). This paper introduces an efficient fixed-path SMC algorithm for conditional simulation of discrete spatial variables (i.e., multinomial classes) on point samples with incorporation of interclass dependencies. The algorithm considers four nearest known neighbors in orthogonal directions. Transiograms are estimated from samples and are model-fitted to provide parameter input to the simulation algorithm. Results from a simulation example show that this efficient method can effectively capture the spatial patterns of the target variable and fairly generate all classes. Because of the incorporation of interclass dependencies in the simulation algorithm, simulated realizations are relatively imitative of each other in patterns. Large-scale patterns are well produced in realizations. Spatial uncertainty is visualized as occurrence probability maps, and transition zones between classes are demonstrated by maximum occurrence probability maps. Transiogram analysis shows that the algorithm can reproduce the spatial structure of multinomial classes described by transiograms with some ergodic fluctuations. A special characteristic of the method is that when simulation is conditioned on a number of sample points, simulated transiograms have the tendency to follow the experimental ones, which implies that conditioning sample data play a crucial role in determining spatial patterns of multinomial classes. The efficient algorithm may provide a powerful tool for large-scale structure simulation and spatial uncertainty analysis of discrete spatial variables.     

Percolation-theory and fuzzy rule-based probability estimation of fault leakage at geologic carbon sequestration sites

Leakage of CO₂ and displaced brine from geologic carbon sequestration (GCS) sites into potable groundwater or to the near-surface environment is a primary concern for safety and effectiveness of GCS. The focus of this study is on the estimation of the probability of CO₂ leakage along conduits such as faults and fractures. This probability is controlled by (1) the probability that the CO₂ plume encounters a conductive fault that could serve as a conduit for CO₂ to leak through the sealing formation, and (2) the probability that the conductive fault(s) intersected by the CO₂ plume are connected to other conductive faults in such a way that a connected flow path is formed to allow CO₂ to leak to environmental resources that may be impacted by leakage. This work is designed to fit into the certification framework for geological CO₂ storage, which represents vulnerable resources such as potable groundwater, health and safety, and the near-surface environment as discrete “compartments.” The method we propose for calculating the probability of the network of conduits intersecting the CO₂ plume and one or more compartments includes four steps: (1) assuming that a random network of conduits follows a power-law distribution, a critical conduit density is calculated based on percolation theory; for densities sufficiently smaller than this critical density, the leakage probability is zero; (2) for systems with a conduit density around or above the critical density, we perform a Monte Carlo simulation, generating realizations of conduit networks to determine the leakage probability of the CO₂ plume (P _leak) for different conduit length distributions, densities and CO₂ plume sizes; (3) from the results of Step 2, we construct fuzzy rules to relate P _leak to system characteristics such as system size, CO₂ plume size, and parameters describing conduit length distribution and uncertainty; (4) finally, we determine the CO₂ leakage probability for a given system using fuzzy rules. The method can be extended to apply to brine leakage risk by using the size of the pressure perturbation above some cut-off value as the effective plume size. The proposed method provides a quick way of estimating the probability of CO₂ or brine leaking into a compartment for evaluation of GCS leakage risk. In addition, the proposed method incorporates the uncertainty in the system parameters and provides the uncertainty range of the estimated probability.     

Adapting to climate change: a comparison of two strategies for dike heightening

In the Netherlands the current dike design policy is to design flood defence structures corresponding to an agreed flooding probability with an extra safety board of at least 0.5 m. For river dikes a return period of 1,250 years is used to determine the design water levels. A problem with this strategy is that it builds on assumptions with regard to the intrinsically uncertain probability distributions for the peak discharges. The uncertainty is considerable and due to (1) the measuring records that are limited to about 100 years and (2) the changing natural variability as a result of climate change. Although the probability distributions are regularly updated based on new discharge data the nature of the statistics is such that a change in the natural variability of the peak discharge affects the probability distribution only long after the actual change has happened. Here we compare the performance of the probabilistic dike design strategy with the older strategy, referred to as the ‘self-learning dike’. The basic principle of the latter strategy is that the dike height is kept at a level equal to the highest recorded water level plus a certain safety margin. The two flood prevention strategies are compared on the basis of the flooding safety over a 100-year period. The Rhine gauge station at Lobith serves as case study. The results indicate that the self-learning dike performs better than the probabilistic design in terms of safety and costs, both under current and climate change conditions.