长江（万州段）水体溶解性有机物的荧光光谱分析

按照河床形态、水文条件、排污口分布、支流状况等特点从长江万州段及长江支流苎溪河选取8个断面进行采样，对水样中溶解性有机物（DOM）的荧光光谱特征进行了分析和研究。利用日立F 4500荧光分光光度计对长江水、普通自来水和纯水在紫外光激励下产生的荧光光谱及其特性进行了比较研究。同时，研究了不同水样、不同取样点的水体DOM的荧光特性和三维荧光光谱图。结果表明：长江水在波长290 nm左右的紫外光激励下能产生较强的荧光。荧光峰是350~550 nm 范围的宽谱峰，荧光峰值波长在450 nm左右。但是不同取样点水样的荧光峰强度明显有差异，在4号、5号、2号取样点的水样荧光强度明显高于其他取样点，这与采样点附近污染源排放有明显的关系。该研究方法可作为鉴别水质污染的一种有效的手段.

DETERMINATION ON EVOLUTION STAGE OF DEBRIS FLOW GULLY BASED ON BP NEURAL NETWORK

The determination of evolution stage of debris flow gully is the first step of forecasting，evaluation and control of debris flow and the scope and frequency of the debris flow.Utilizing artificial three ply intelligence BP neural network model,then selecting catchment area,main groove length,groove gradient ratio,average aspect,relative height difference,round ratio and relative cutting degree of the catchment evolution geomorphology as assessment index of the evolution stage of debris flow gully,the stage of debris flow gully was divided into four stages:young stage、developing stage、active period and decline stage.Authors pre treated the 80 debris flow data along Chengkun railway in Sichuan province (systematic classification、standardization) in order to avoid artificial error,secondly,network training the 80% of the data,and then built forecasting model,the simulation of the residual 20% of the data shows that the average relative error is 8.22% with satisfactory result.The evolution stage of the 6 debris flow gullies along Kundong railway was determined based on the model,the result showed that:the 6 debris flow gullies are in active period and the evolution score is between 3～3.5,so the monitor and forecast should be strengthened in these six debris flow gullies in order to avoid disasters.The intelligence BP neural network model can be used as an advantageous method to determinate the evolution stage of debris flow gully.The result can provide theoretical basis and technical support for debris flow forecasting，evaluation and control.