喀拉喀什河悬移质沙量和过滤设备选型研究

Study on suspended sediment load and filtration equipment selection in Karakax river

河流悬移质沙量的有效预测是节水灌区供水管网安全有效运行的重要保障,针对干旱节水灌区悬移质沙量来量预测不精确的客观实际,以喀拉喀什河乌鲁瓦提水文站多年实测流量资料为基础,通过推移质输沙率与流量之间的关系,以3%的推悬比,处理得到多年悬移质沙量。利用Matlab对数据进行小波方差分析,得出悬移质沙量随时间尺度变化的趋势和周期性,结合BP神经网络模型对不同周期下的悬移质沙量进行预测。结果表明,应用小波分析与BP神经网络模型预测悬移质沙量的精度较高,预测结果将为灌区过滤设备的选型提供有力支撑,进而有力地保障灌区的供水安全。

Accurate determination of suspended sediment load in a river is an important guarantee that make the water supply pipe networks of water-saving irrigation district operation safely and efficiently. Due to the forecast amount of suspended load was inaccuracy in the arid and water-saving irrigation area,based on the observed flow data for years at the Uluranti Hydrologic Station in the Karakash River,by the relationship between sediment transport rate and the flow discharge in this paper,with 3% ratio of bedload to suspended load,by a multi-year suspended sediment. The trend and periodicity of the changes in the time scale of suspended load are obtained by Matlab software. At the same time,this paper predicted the amount of suspended load in different cycles,based on the BP neural network model. Results show that the calculated suspended sediment discharge is reasonble by applying wavelet analysis and BP neural network model. The predictive result will provide a valuable support for the selection of the filtration equipment in irrigation area.