| Since the 911 incident, the research on security early warning of water supply system has become very important in western developed countries. The early-warning system (EWS) on raw water, being an effective safeguard technique for the water supply, has made more and more domestic and abroad scholars begin to study it as the result of series of incidents of source surface water, At present, based on the online monitoring system of raw water quality with high fund input, the research and application of EWS is still confined to idealization although there are some finite knowledge and practical applications on it. Moreover because of some obstacles such as lacking of theories and divorcing from the reality of the plant the EWS's large scale application on source surface water of drinking water utilities is still very difficult during the special status of not developed economy in our nation.Based on the analysis of the characteristics of the source water pollution and deterioration, an innovated theory of taking different modes, according to the classification of the deteriorated water quality incident, to early warn is boldly proposed in this paper. The studied case is JIEYUAN water plants (JYWP) in Tianjin, whose key points are the algae-laden raw water and its treatment. The optimum ANN model to forecast the chlorophyll in the raw water is creatively established by the author by combining cluster analysis and artificial neural networks (ANN). The GPRS network is used to transmit point-to-point datum between the online monitoring system constructed for raw water of JYWP and the utility's control central; And the decision tree technique is first introduced to establish a model for predicting water quality based on the on-line monitoring system; Unifying the pilot-tests on the treatment of algae-laden waters, a water purification draft scheme and a warning decision diagram were proposed aimed at the algae-laden raw waters to provide guidance and advice for JYWP and other similar water plants. The achievements and innovation of this paper are as follows: (1) The theoretical frame of the raw water quality early warning system was completed and betteredThe surface water pollution is divided into three categories: sustained, periodic and accidental pollution, which respectively lead to lasting tendency, periodic discontinuity and accidental short time water quality deterioration. The first two can be early warned on the basis of water quality forecast and monitoring, while the latter can only be early warned based on the raw water contentious online monitoring; Before the sustained pollution and the periodic pollution which cause the raw water quality deterioration has not been well resolved at present, the traditional lab-monitoring information since water works begin for many years can be taken full advantage to establish the water quality EWS in respond to the sustained and the periodic water deterioration whether there are sufficient funds budget or not. But if there are a larger source of funds or accidental pollution risks, EWSs for raw water can be built on the base of online monitoring systems for water quality.(2) A prediction model for algae of raw water was established on the base of traditional lab-monitoring datum of raw water quality.Based on the day-to-day monitoring datum from JYWP, the relationship between indexes and the unusual line on each water quality indexes every month are studied by analyzing the correlation and box-plot; the law of the algae's changing month by month and the high level algae alert time are researched by the frequency analysis of water quality monitoring datum month by month; the law of the algae annual changes and its main influencing factors are studied through the wavelet analysis of chlorophyll changes in the source water; the relationship between the common water indexes and chlorophyll quantity in the raw water delayed of a few days is studied through the ROC curve analysis; An ANN model is created to forecast the chlorophyll in the raw water the day after tomorrow, whose input variables are the current water quality indexes: chlorophyll, turbidity, ammonia, temperature, pH, total alkalinity. Through simulation verification, the correlation coefficient of 0.86 between the predicted values and tested values of the chlorophyll is gained, and the average forecast accuracy rate is more than 85%.(3) A prediction model for algae of raw water was established on the online monitoring system for raw water qualityThe online monitoring system was build near the Xihe preliminary sedimentation inlet for raw water of JYWP, monitoring indexes as follows: turbidity, pH, dissolved oxygen, water temperature, redox potential, conductivity, ammonia nitrogen, orthophosphate, radar luminance. The point-to-point wireless data transmission between the online monitoring system and the TYWP control center is realized through the GPRS networks. After optimizing the system operation, the decision tree model for forecasting the chlorophyll of the next day in raw water is established based on the collecting datum from the online monitoring system; the average predicted accurate rate of the model can reach to 80% validating by simulation.(4) A water purification draft scheme and a warning decision diagram for the algae-laden raw water of JYWP and other similar water plants were proposed.After the investigation of the rebuilt water treatment process and the flow path of source water of JYWP, a detailed analysis about the potential of the water utility and related parts is carried out for the treatment of algae-laden water. Unifying pilot-tests, the corresponding response plans are proposed for the water plants and related sectors according to the quantity of algae in source water. Ultimately, the early-warning decision diagram against the treatment algae-laden raw water is proposed for JYWP and other similar water plants.
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