A quantitative model for danger degree evaluation of staged operation of earth dam reservoir in flood season and its application

Based on the natural disaster risk evaluation mode, a quantitative danger degree evaluation model was developed to evaluate the danger degree of earth dam reservoir staged operation in the flood season. A formula for the overtopping risk rate of the earth dam reservoir staged operation was established, with consideration of the joint effect of flood and wind waves in the flood sub-seasons with the Monte Carlo method, and the integrated overtopping risk rate for the whole flood season was obtained via the total probability approach. A composite normalized function was used to transform the dam overtopping risk rate into the danger degree, on a scale of 0-1. Danger degree gradating criteria were divided by four significant characteristic values of the dam overtopping rate, and corresponding guidelines for danger evaluation are explained in detail in this paper. Examples indicated that the dam overtopping danger degree of the Chengbihe Reservoir in China was 0.33-0.57, within the range of moderate danger level, and the flood-limiting water level （FLWL） can be adjusted to 185.00 m for the early and main flood seasons, and 185.00-187.50 m for the late flood season. The proposed quantitative model offers a theoretical basis for determination of the value of the danger degree of an earth dam reservoir under normal operation as well as the optimal scheduling scheme for the reservoir in each stage of the flood season.

The Operational Forecasting of Total Precipitation in Flood Seasons (April to September) of 5 Years (1983-1987)

Ⅰ.INTRODUCTION We have discovered that there exists a good corresponding relationship between theanomalous axes of soil temperature at a depth of 1.6m in winter (December to February) andprecipitations in following flood season (Tang et al., 1982a). We have also designed a simplethermodynamical model and applied it to the forecasting of precipitations in the flood season(Tang et al., 1982 b,c). The practical forecast started from 1975. Before 1980, however, therewere only 40-50 stations in China for measuring the soil temperature at a 1.6m depth. Since1980, the stations have been increased to a total of about 180, but no available mean valueshad been obtained from newly added stations before 1982. Therefore the analysis and map-ping of anomalies of soil temperature was not performed until 1983, and from then on theprecision of analysis has been greatly improved. The following is the actual situation of forecast in five years from 1983 to 1987.

Risk analysis of dynamic control of reservoir limited water level by considering flood forecast error

Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively increased by using flood forecast information and flood control forecast operation mode. In this paper, Dahuofang Reservoir is selected as a case study. At first, the distribution pattern and the bound of forecast error which is a key source of risk are analyzed. Then, based on the definition of flood risk, the risk of dynamic control of reservoir flood limited water level within different flood forecast error bounds is studied. The results show that, the dynamic control of reservoir flood limited water level with flood forecast information can increase the floodwater utilization rate without increasing flood control risk effectively and it is feasible in practice.

Assessing Flood Risk Using Reservoir Flood Control Rules

The application of conventional flood operation regulation is restricted due to insufficient description of flood control rules for the Pubugou Reservoir in southern China. Based on the requirements of different flood control objects, this paper proposes to optimize flood control rules with punishment mechanism by defining different parameters of flood control rules in response to flood inflow forecast and reservoir water level. A genetic algorithm is adopted for solving parameter optimization problem. The failure risk and overflow volume of the downstream insufficient flood control capacity are assessed through the reservoir operation policies. The results show that an optimised regulation can provide better performance than the current flood control rules.