Study on reservoir time-varying design flood of inflow based on Poisson process with time-dependent parameters

The time-varying design flood can make full use of the measured data, which can provide the reservoir with the basis of both flood control and operation scheduling. This paper adopts peak over threshold method for flood sampling in unit periods and Poisson process with time-dependent parameters model for simulation of reservoirs time-varying design flood. Considering the relationship between the model parameters and hypothesis, this paper presents the over-threshold intensity, the fitting degree of Poisson distribution and the design flood parameters are the time-varying design flood unit period and threshold discriminant basis, deduced Longyangxia reservoir time-varying design flood process at 9 kinds of design frequencies. The time-varying design flood of inflow is closer to the reservoir actual inflow conditions, which can be used to adjust the operating water level in flood season and make plans for resource utilization of flood in the basin.

50 years return period wet-snow load estimation based on weather station data for overhead line design purpose

Historically, as far as wet-snow loads were concerned, overhead line design was often based on experience or on long-term applications with positive results. New standards like CENELEC EN 50341-1 (2012) take into account for the overhead line design characteristic loads, i.e. 50 years return period loads. This article proposes a method to estimate characteristic wet-snow loads based on meteorological data recorded at weather stations. The model used to calculate those loads is mainly inspired by a recent article written by Nygaard et al. (2013a) in which a new parameterization is proposed for the classical cylindrical wet-snow accretion model as described in ISO 12494 annex C. After a complete description of the model and its parameterization adapted to French wet-snow events, the statistical issues are examined. Then, the model is used with the meteorological data of 87 weather stations in order to calculate wet-snow loads whose relevance has been positively tested according to real damages recorded in a complete wet-snow event database. At last, the characteristic loads of those 87 stations have been determined according to all the loads generated by the model and processed by a POT (Peak Over Threshold) method.