Stochastic Analysis Of Sudden Siltation Of Silty Sand In Open Channel

From Bohai Bay to the northern bank of Yangtze River, there exist many silt-sandy beaches. In recent years, the sea ports and the navigation channels are built or been building to satisfy rapid economic development in the above coastal areas, such as Jingtang Port and Cangzhou Port in Hebei province, Weifang Port and Dongying Port in Shandong province, and Rudong Port in Jiangsu province. Meanwhile, serious silt occurred in these nearshore areas. For example, Cangzhou Port plays an important role to transport the northern coal to the south and makes huge economic benefit since its completion in 2001. However, sudden silt occurred in its navigation channel under strong winds. The siltation volume may reach 1～3 Mm~3 after a strong wind. The siltation depth can be up to 1.5～2 m. So far, the maximum silt phenomenon had occurred after a 9-scale wind from 10th to 13th in the October of 2003. The total volume was 8.76 Mm~3 and the maximum silt depth was 3.5 m. The distribution length of silt area with 2m silt depth is more than 16km. The silty sand siltation severely influenced the normal operation of Cangzhou Port and made enormous economic loss. Because present two-dimensional and three-dimensional numerical model cannot be used to predict sand siltation under strong winds, how to calculate silt volume is put on the agenda. The main content of this paper is as follows:1. To collect oceanographic hydrological data, meteorological data, sediment data and the results of simulation and test, which conduce to the formula derivation for estimating siltation volume in open channel.2. Based on the concept of energy balance, an empirical formula is set up to hindcast the volume of silt- sand sudden siltation under strong winds. The coefficients of the equations are determined by using observed data. Then a historical series of siltation volumes can be hindcasted by sampling maximum annual wind observed from 1979 to 2003.3. On the base of effective wind energy, another empirical formula is also proposed to hindcast the siltation volume. A statistical series of annual maximum sudden siltation volumes is obtained for long-term prediction.4. Four kinds of univariate statistical distribution are utilized for sudden siltation stochastic analysis. The optimum distribution is selected with optimization theory. The return values of sudden siltation vulumes are estimated for engineering design of silt prevention.