Because of the uncertainty regarding the potential loss of life, it is difficult to use societal life risk criteria for dams established based on existing methods and the related research. Based on existing dam safety standards, dam safety conditions, and the opinions of the public on dam risks, an innovative methodology, i.e. P–P curve, was proposed to establish societal life risk criteria for dams. The annual probability of dam failure, population at risk, and dam height, which have the most significant and direct impacts on the potential loss of life, were selected as the basic indices. Taking China as an example, societal life risk criteria for the dams of five types of reservoirs were established; in these criteria, the heights of 30 m and 70 m were proposed as the bases for upgrading the risk criteria for the dams of small-type reservoirs, medium-type and large (2)-type reservoirs, respectively. The proposed methodology was designed to be more practical in determining the risk levels for dams because the values of the basic indices are considerably easier to determine than those of risk criteria based on the existing methods.@en

Dam breaches often have catastrophic consequences in downstream areas. Hydrodynamic factors and the evacuation potential of the population at risk (PAR) have significant impacts on the loss of life (LOL) caused by dam breaches. However, the existing comprehensive evaluation models have not conducted in-depth research on the evacuation potential of populations. Thus, limited guidance is available for relevant departments to formulate emergency plans to reduce the potential LOL. Therefore, a new comprehensive evaluation model was proposed in this study. According to the relevant references and disaster theory, the main influencing factors and the process through which the LOL is caused by dam breaches were determined. The specific occurrence process was divided into six stages: a dam breach causes flood, the flood puts the PAR, the PAR complete the preparation work, the PAR evacuate, the un-evacuated population shelter themselves inside buildings, and flood causes the death of the exposed population. To calculate the LOL, the parameters relevant at each stage were defined. Furthermore, the Hydrologic Engineering Center's River Analysis System, Geographic Information System, and related materials were used to simulate the flood routing and evacuation potential of the PAR, quantifying the parameters in the model. The model was applied to 14 towns in the downstream areas of the Luhun Reservoir in Henan Province, China, and its accuracy was verified by comparing the results obtained from the two existing models. In addition, the specific suggestions for reducing the potential LOL were proposed based on the results of the simulation.@en

Both hydrodynamic factors and social factors have large impacts on the loss of life caused by dam failure. Relatively large uncertainty intervals of the influencing factors lead to changes in the potential loss of life. Based on an analysis of the formation mechanism of loss of life, the influencing factors were identified. Combined with interval theory, a method for calculating loss of life and determining the impacts of the influencing factors on loss of life was proposed. The intervals of the exposure rate of the population at risk and the mortality of the exposed population, which are impacted by the major influencing factors such as the flood severity, warning time, understanding of dam failure, and building vulnerability, were recommended. Furthermore, a range of correction coefficients caused by the minor influencing factors, such as the dam failure time, rescue ability, and age distribution, was analyzed. The proposed method was validated by analyzing the losses of life in 21 flooded regions after 10 dam failure events and 2 flash river floods, in which the intervals of the estimated results all contained the actual loss of life. In addition, the ratios of the upper bounds to the corresponding lower bounds of the intervals were all less than 10, which is in accordance with the characteristic that the results of different existing methods vary within an order of magnitude. This is the first work that pays careful attention to the uncertainty intervals of loss of life estimates, and the proposed method effectively determined the severity of the potential loss of life caused by dam failure. @en

When a dam breaks, huge floods will be generated that may inundate urban areas, enterprises, farmlands, and infrastructure and cause giant economic losses. Economic risk criteria are a kind of basis for determining dam risk levels and to decide whether risk control measures should be taken or not. However, compared to loss-of-life risk criteria, much fewer economic risk criteria for dams have been proposed and implemented for two main reasons: (a) The ability of most areas to endure economic losses caused by dam breach changes over time because of the constant development of their economic levels; and (b) Economic development levels in an area are distinct from the levels in other areas, resulting in significant differences in the ability of different areas to endure economic losses caused by a dam breach. Therefore, an equivalent economic scale (EES) that indicates the relative economic level of an area to the whole country in a given period of time is a preferred measure. It was shown in this paper that EES has much more stable values than do ordinary economic measures; therefore, it was taken as the basic index for establishing economic risk criteria. Furthermore, due to the distinct economic loss rates of different industries, the index of industrial economic contribution (IEC) was introduced to determine the correction coefficient to modify the ESS to reflect the potential economic loss of the area to be evaluated. This is the first research that pays careful attention to the change of ability to endure economic losses, in which the established economic risk criteria are applicable over a relatively long time and for different areas based on the consideration of the relative level of the economy and the industrial economic contribution.@en