Research On Non-Point Source Pollution Load Quantification For Watershed

With the increasing control strength of point source pollution, water pollution constitution of our country is being at a rapid change stage, and the proportion of non-point source pollution (NSP) load compared to total pollution load is gradually rising and its influence is increasing. As a result,the quantification of NSP becomes increasingly important for water pollution control and water environment comprehensive management. The complexity of source, ambiguity of mechanism and latency of formation for NSP make it difficult to quantify it. On the basis of investigation and monitoring, combining with the technology of'3S',this paper takes the Weihe river basin as an example to study the problem. Firstly, during flood and non-flood period in 2006, water quality and quantity at the Lin-tong section of the Weihe river were monitored, and the characterristic of NSP and its proportion compared to total pollution load are analyzed. Secondly, taking the weihe river basin and its subwatershed-the Heihe river watershed as the example, simulation and prediction of NSP for watershed under different data conditions is studied. Under the limited data condition, the statistical models of NSP annual load estimation are generally single-element regression models considering single variable at present. Pointing to this condition,several NSP load prediction methods considering multiple main relevant elements are proposed. Under enough data condition, the adaptability and reliability of AnnAGNPS model in the Heihe river watershed and SWAT model in the Weihe river basin are repectively studied by means of GIS. At the same time, the NSP output distribution of time and space in the heihe river watershed and the weihe river basin are analyzed, and the effects of best management practices (BMPs)are simulated. This research is not only important to comprehensively understand the cause of water pollution of the weihe river,but also important to water environment comprehensive management and water resources protection of it. Meanwhile, considering the universality of NSP in our country, the study methods and results can give references for other similar region and watershed.To sum up,main results of this study are listed as follows:1.From July to December in 2006, five storm events and three 24 hours normal flow events at the Lin-tong section were monitored. Raw water and clarified water quality of them was analyzed. The results indicates that: during the flood, the concentrations of SS, and the COD, TP as well as TN of raw water are higher than those in the non-flood period. The high values of the COD,TP and TN of raw water are related to natural humic substance in the surface layer soil. The total-N of clarified water is mainly made of dissolved nitrogen, and total-P is mainly made of particle phosphorus. TP and COD of raw water are closely related with SS. Mean concentration method was used to estimate NSP weighted mean concentration for each element. Water quality and quantity correlation method was used to establish correlation equation between NSP load and surface runoff for each element. The calculated NSP mean concentration and the established correlation equation are used to estimate NSP load of the Lin-tong section in the Weihe River from 1991 to 1999, the results of the two methods prove to be credible. The annual NSP load proportions compared to the total of the Lin-tong section from 2001 to 2007 are calculated. The NSP load proportion of COD, TP and TN of clarified water and inorganic nitrogen are repestively 38.17%,35.94%,33.32% and 30.45% in 2006,while which are repestively 54.10%,51.72%,48.82% and 45.53% from 2001 to 2007 on the whole.The effect of NSP to water quality is indispensable.2.The partial least square regressive method (PLS) is applied to build the model estimating the annual load of NSP, whose results are compared with the ones of least square method. The data series used in the study included NSP total-N load from 1976 to 1993 at the Hua-xian section, and environmental factor series such as flow, sediment, precipitation, etc.The first 15 years'data were used for training, and the last 3 years'data for testing. It is showed that PLS integrating the multi-regression, the principal component analysis and typical correlation analysis, can easily solve the multiple correlation problems in the multiple linear regressive analysis, and only need a few of data to build the model. The calculation results of PLS is credible, the estimated regressive parameters with PLS are robust. The method is feasible and practical.3. Support Vector Machine (SVM) method is applied in estimating annual NSP load at the Hua-xian section in the Wei River. The novel SVM method can transform the learning process into a secondary planning problem, and the global optimal solution can be obtained. This method avoids the potential shortcoming of artificial neural networks (ANN), which may be trapped in local optimums. The data series used in the study included NSP total-N load from 1976 to 1993, and environmental factor series such as flow, sediment, precipitation, etc. The first 15 years' data were used for training, and the last 3 years' data for testing. The SVM method performed better than that ANN and least square regression methods. This study indicated that the prediction of NSP could be improved by the SVM approach under limited data availability.4.Self-memory theory is applied to build the model estimating annual NSP load. Modified self-memory model of NSP loading is established based on improving common self-memory model. The data series of the Hua-xian section in the Wei River used in the study included NSP total-N load and environmental factor series such as flow, sediment and precipitation from 1976 to 1993. The first 15 years'data were used for training, and the last 3 years'data for testing. This study indicates that the modified self-memory method performed better, and the method can be used to predict NSP load.5.Taking shaanxi Heihe river watershed as study region, AnnAGNPS (Annualized Agricultural non-Point Source Model) foundation database is established using GIS(Geographic Information System) and relevant data to extract parameter.The model is calibrated and validated using observed stream flow, sediment load, inorganic nitrogen and total phosphorus month data from 1991 to 1998 in the Heiyukou section, which is used to judge the adaptability of the model in typical watershed in semi-arid region of Northeast of China. The results showed that the model can be used to long term simulation of the watershed NSP(non-point source pollution). Subsequently, Sensitivity of main parameters of the model is analyzed. Finally, the validated model is used to simulate the management measures. The results show that the reforestation project, which can simultaneously minify the amount of runoff, sediment, total nitrogen and total phosphorus should be adopted in Heihe watershed in order to control NSP.6.Weihe river basin above Hua-xian section is selected as the study area, with a drainage area of 10.65×104 km2. SWAT model is applied to simulate the producing and transporting process of flow, sediment and nitrogen non-point source pollution. Monthly flow, sediment and nitrogen pollutant data series from 1987 to 1988 are used to calibrate the correlative parameters of flow, sediment and nitrogen pollutant. The monthly flow, sediment and nitrogen pollutant data series from 1989 to 1990 are used to validate model. The results of calibration and validation show that the model is reasonable and available. The calibrated model is used to calculate the loadings of nitrogen non-point source pollutants of different typical years. Based on the simulated results, the spatial and temporal distribution of flow, sediment and non-point source pollution has been analyzed for the non-point source pollution control.