| In recent years, social and economic development and continuously increasing population result in more and more environmental issues. In China, total amount control on the basis of environmental management objective could not meet the requirements of regional environmental management. It is a good measure to control water pollution and improve regional environmental quality through implementing total amount control on the basis of environmental capacity. There are some key steps of implementing total amount control on the basis of environmental capacity,which include to analyze regional environmental baseline condition, to calculate the regional environmental capacity, and to conduct optimal allocation of total pollutant amount. In this paper, these key issues have been studied respectively. The research are composed of:identifying the main regional pollution source based on the understanding of the current condition of water pollution in this area, discussing the applicability of different water quality evaluation method, establishing the applicable regional water quality model for river water quality simulation of the target area by using GIS and the water quality model, identifying regional environmental capacity through water quality modeling analysis, conducting total amount allocation by introducing the Gini coefficient. Meanwhile, the forecast has been done for the variety pollution load of different years, quantitative analysis on the effects of various pollution control measures has been made, which provided the reference and guidance for the regional pollution control. The main research method and results are as follows:The investigation of 100 key enterprises has been conducted to understand the polluted water quantity, total amount of COD and NH3-N respectively. The enterprises mainly come from textile industry, paper making industry, food processing industry, waste water treatment plant, etc. The calculation has been done respectively on the quantity of the different type of pollution sources such as industrial pollution, domestic pollution, livestock pollution, agricultural nonpoint source pollution, etc, which is to identify the main pollution source of study area. Through the analysis, it has been found that the total amount of COD and NH3-N were 15,388.9 t/a and 2361.89 t/a respectively.Among which, the COD and NH3-N were 3,772.86t/a and 385.89t/a come from industrial wastewater, and they were 10,495.11t/a and 1,893.132t/a come from domestic wastewater in the study area, which has been found that the main pollution comes from domestic pollution. The main industrial pollution generated by textile industry, paper making industry and food processing industry. Sort by pollution:textile industry, paper making industry and food processing industry. The proportion of wastewater quantity, quntities of COD and NH3-N of these three industries occupied total amount of study area were 83%,87% and 92% respectively.By selecting single factor evaluation, fuzzy comprehensive evaluation method, grey evaluation, principal component analysis, and neural network of the regional water quality status of water quality in 26 water functional areas were evaluated. The main indicators were:dissolved oxygen, permanganate index, five-days biochemical oxygen demand, ammonia nitrogen, copper, zinc, volatile phenol, petroleum. The results showed that single-factor evaluation classify the water quality based on the evaluation of wors factor. The method can response to excessive pollution factor directly, but not fully reflect the water quality. Fuzzy comprehensive evaluation method and grey evaluation can avoid the shortcomings that the water quality level is not continuous, and can analyze the water quality in the same level. However, it can be found that the results of these two method high affect by weight coefficents and with low resolution. BP neural network implements a mapping from input to output, to determine the water level more clearly. However this method can not identify the major pollution factor. Principal component analysis can transformed large number of multiple factors into a small number of representative evaluation factors, and identify and sort the major pollution factors.The results showed:the results of five overall consistent evaluation methods, only the individual sections of a discrepancy in the evaluation results more in line with the actual situation. The evaluation results showed that water pollution monitoring sections are as follows:the dry season> normal water> wet period. From the comprehensive analysis of water quality in different period, the worst were Zhongda River and Yinzhou River. Yongjiang River and Fenghua River is comparably good from the overall situation. Yao Jiang, Jiang Yin upstream water quality is the best. More polluting river water concentrated in downstream of Yinzhou River, Zhongda River and Yin River, which these rivers can be treated as the key governance areas in the future.By using ArcGIS, the generalization has been done for targeting study area and the regional water quality model has been established by using WASP. The nine river sections of Yongjiang, Fenghua River, Yin Jiang and Yao River have been set as the simulations sections. COD and NH3-N have been selected as the main simulation pollutants. Meanwhile, The water quality model was calibrated by using the mornitoring data, and the sensitivity of key parameters were analyzed. The main parameters affecting COD were COD degration coefficient, flow and water temperature, the order of sensitivity from high to low were:COD degration coefficient, flow, water temperature, atmospheric reaeration coefficient and nitrification rate coefficient. The main parameters affecting NH3-N were flow and nitrification rate coefficient, followed by water temperature. The impact of COD degration coefficient on NH3-N is almost negligible. It was found that the variation trend of simulation data is consistent with the variation trend of monitoring data. The average error of simulation data and monitoring data of COD were less than 12%, and the error of of simulation data and monitoring data of NH3-N were less than 15% in average, which indicated that the established water quality model could be used to simulate water quality of the study area. It has been found that the concentration of COD and NH3-N reached the peak in the S-4 River Section in the dry season and normal season, and then gradually decreased. The concentration of COD and NH3-N reached the peak in S-5 River Section and S-4 River Section respectively in the wet season.. S-8 and S-9 reach the same performance in different period, and both of them were in the trend of increasing. The degree of water pollution of all river sections are as follows:The wet season, normal season, dry season. The water quality can not reach the requirements of water objective mainly was in November to next January, and the water quality during June to September quality was better.The regional pollution dynamic management system has been established by using water quality model and ArcGIS. The main functions of this system include:data queries, statistical analysis of environmental condition, data management, elevation analysis, water analysis, hydrological analysis,map making, etc, as well as the visual output of water quality simulation. Water quality simulation results by editing the assignment of the river, the water quality simulation results can be achieved visual output. While taking advantage of the fuction of data update, adding, deleting and modifying data in the database can be made, which to facilitate dynamic management of regional pollution.The calculation has been done by using the calibrated water quality model to get the environmental capacity of whole region and each section, and the environmental capacity of COD and NH3-N of the entire region were 12,900.72 t/a and 2,361.89 t/a respectively. It has been found that COD discharge in S-1 to S-5 River Sections were over the environmental capacity, COD discharge in S-6 to S-9 were less than the environmental capacity, in which S-4 and S-5 reach the most polluted river section, respectively, need to reduce 2,090.02t/a, and 1,177.49 t/a to meet the water objectives. And NH3-N discharge in S-1 to S-5 River Sections were over the environmental capacity, NH3-N discharge in S-6 to S-9 were less than the environmental capacity, in which S-4 was the most polluted river section, need to reduce 307.73 t/a to meet the water objectives. Meanwhile, an economic parameter Gini coefficient was introducted to total load allocation. Currenct pollution discharge, population, GDP, water resources and land area were selected as control indexes. The Gini coefficients with COD of final load allocation were 0.187,0.162,0.061 and 0.598 respectively. The Gini coefficients with NH3-N were 0.222,0.208,0.095 and 0.634. That can be concluded that the total load allocation is equitable based on the population, economic development, water resources. The allocation plan can be implemented well.Finally, water conservation potential were analyzed by using water balance model and effectiveness water saving and pollution remediation, industrial pretreatment, time limited industrial restructuring and non-point source pollution control were analyzed quantitatively. The water conservation potential of main water using enterprises could reach 6,614,448 m3/a which occupy 43.8% of the total quantity of water using. By using water conservation, administrative methods to achieve 587.8t/a and 810.8 t/a of COD reduction,74.5 t/a and 49.2 t/a of NH3-N reduction. Implementation of all mitigation measures can achieve 10,292.28t/a of COD reduction and 1555.03t/a of NH3-N reduction. Except S-5 river section, the other river section can reach requirement of water objectives in 2012; COD and NH3-N will dischage 12,217.19t/a and 1,910.67t/a respecively in 2015, S-5 and S-6 were not compliance with the requirement of water objectives, the rest river sections could meet requirement of water objectives.
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