景观河流水质变化的研究与控制
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摘要
随着城市品味的逐渐提高，美化环境、恢复城市水生态环境成为许多城市今后的发展趋势，城市景观河流的治理和维护也将成为许多城市必须面临的问题。本文以天津市津河作为研究对象，在对河流水质监测、评价的基础上，建立了水质模型，进行水质模拟和预测。结合天津市有关景观水体环境保护规划和津河的实际状况，提出了水污染控制措施。
首先，在调研和原有数据的基础上，重新设置了津河10个监测断面，对津河进行为期一个月的水质监测，监测指标包括水温、溶解氧、总氮、氨氮、硝酸盐氮、亚硝酸盐氮、总磷、溶解性总磷、溶解性正磷、高锰酸钾指数和叶绿素共11项。
第二，以津河的水质监测数据和津河的单因子分析为基础，用内梅罗（N.L.Nemerow）污染指数法对津河水质进行综合评价。在此评价中，采用了两组评价因子，一组是地表水环境质量标准 (GB3838-2002)内的因子，一组除了标准内的水质因子，还包括了津河的主要污染物凯氏氮、亚硝酸盐氮、硝酸盐氮和叶绿素，这些污染物的标准是经过查阅资料自定的。
第三，根据津河的实际状况，选择了QUAL2E模型作为津河的水质模型。在模型参数估值中，一部分参数选用经验数据和经验公式，另一部分参数通过模型反求的方法对参数进行估值。参数反求的方法是根据津河的现实状况，由笔者提出的，在尝试的三种方法中模拟效果是最好的。
第四，以津河三组水质数据为原始数据，通过建立的模型对津河水质进行预测，水质变量溶解氧、BOD、叶绿素、有机氮、氨氮、亚硝酸盐氮、硝酸盐氮、有机磷、溶解性磷和温度的预测值与实际监测值均在所设定的误差范围20%之内，验证了模型的有效性。
第五，结合津河的实际污染状况以及模型的成果，量化治理措施，提出了切实可行的水污染控制措施。
本文的研究不但可以用作津河的水质预测评价，为治理技术的方案优化决策、水质管理和水质规划提供可靠的科学依据，而且可以为各种治理措施提供可行性论证。
With the development of cities, it will become a new developmental direction to beautify environment and to resume water ecology environment. At the same time, the problem of regulation of Scenic River must be faced by many cities. Taking the Jinhe River as a study object and based on monitor and assessment to Jinhe River, water quality model was built to simulate and predict water quality of the river. Combined with regulation of Scenic River of Tianjin and the real condition of Jinhe River, measures were put forward to control water pollution.
Firstly, Based on investigation and historical data, 10 monitor points were reset before water quality of Jinhe River was monitored for one month. The monitored water quality terms included temperature, dissolved oxygen, total nitrogen, ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, dissolved phosphorus, orthophosphate, chemical oxygen demand and chlorophyll a, which altogether were 11 terms.
Secondly, with water quality monitor data and based on single factor analysis to Jinhe River, comprehensive assessment to water quality of Jinhe River was given with Nemerow Pollutant Index. In this assessment, two groups of evaluation factors were used: one group is stipulated in "Environment quality standards for surface water (GB3838-2002)"; the other factors included main pollutants of Jinhe River, such as kjeldahl nitrogen, nitrite nitrogen, nitrate nitrogen and chlorophyll a, and the standards of some of them were given by the author on the basis of relative data.
Thirdly, water quality model QUAL2E was selected to simulate and predict water quality within Jinhe River according to the specific conditions of the river. Some of parameters were fixed by experience data and experience formula, the others were estimated by reasoning backward to the model. According to the current conditions of Jinhe River. The method of reasoning backward to the model was put forward by the author, which was proved the best one after comparing with the other two methods.
Fourthly, taking three groups of water quality data of Jinhe River as original data, prediction to water quality of the river was made. Compared with real monitored value, the error of predicted value of all of simulating terms, including dissolved oxygen, bio-chemical oxygen demand, chlorophyll a, organic nitrogen, ammonia
nitrogen, nitrite nitrogen, nitrate nitrogen, organic phosphorus, dissolved phosphorus and temperature, were basically within error limit of 20%, which validated the validity of the model.
Fifthly, coupled with the current pollution status of Jinhe River and the production of the model, feasible quantitative measures were put forward.
The study not only can predict water quality of Jinhe River and provide scientific proof to making decisions to the optimization to treatment techniques, water quality management and planning, but also can provide feasibility argumentation for water pollution prevention and cure measures.
首先，在调研和原有数据的基础上，重新设置了津河10个监测断面，对津河进行为期一个月的水质监测，监测指标包括水温、溶解氧、总氮、氨氮、硝酸盐氮、亚硝酸盐氮、总磷、溶解性总磷、溶解性正磷、高锰酸钾指数和叶绿素共11项。
第二，以津河的水质监测数据和津河的单因子分析为基础，用内梅罗（N.L.Nemerow）污染指数法对津河水质进行综合评价。在此评价中，采用了两组评价因子，一组是地表水环境质量标准 (GB3838-2002)内的因子，一组除了标准内的水质因子，还包括了津河的主要污染物凯氏氮、亚硝酸盐氮、硝酸盐氮和叶绿素，这些污染物的标准是经过查阅资料自定的。
第三，根据津河的实际状况，选择了QUAL2E模型作为津河的水质模型。在模型参数估值中，一部分参数选用经验数据和经验公式，另一部分参数通过模型反求的方法对参数进行估值。参数反求的方法是根据津河的现实状况，由笔者提出的，在尝试的三种方法中模拟效果是最好的。
第四，以津河三组水质数据为原始数据，通过建立的模型对津河水质进行预测，水质变量溶解氧、BOD、叶绿素、有机氮、氨氮、亚硝酸盐氮、硝酸盐氮、有机磷、溶解性磷和温度的预测值与实际监测值均在所设定的误差范围20%之内，验证了模型的有效性。
第五，结合津河的实际污染状况以及模型的成果，量化治理措施，提出了切实可行的水污染控制措施。
本文的研究不但可以用作津河的水质预测评价，为治理技术的方案优化决策、水质管理和水质规划提供可靠的科学依据，而且可以为各种治理措施提供可行性论证。
With the development of cities, it will become a new developmental direction to beautify environment and to resume water ecology environment. At the same time, the problem of regulation of Scenic River must be faced by many cities. Taking the Jinhe River as a study object and based on monitor and assessment to Jinhe River, water quality model was built to simulate and predict water quality of the river. Combined with regulation of Scenic River of Tianjin and the real condition of Jinhe River, measures were put forward to control water pollution.
Firstly, Based on investigation and historical data, 10 monitor points were reset before water quality of Jinhe River was monitored for one month. The monitored water quality terms included temperature, dissolved oxygen, total nitrogen, ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, dissolved phosphorus, orthophosphate, chemical oxygen demand and chlorophyll a, which altogether were 11 terms.
Secondly, with water quality monitor data and based on single factor analysis to Jinhe River, comprehensive assessment to water quality of Jinhe River was given with Nemerow Pollutant Index. In this assessment, two groups of evaluation factors were used: one group is stipulated in "Environment quality standards for surface water (GB3838-2002)"; the other factors included main pollutants of Jinhe River, such as kjeldahl nitrogen, nitrite nitrogen, nitrate nitrogen and chlorophyll a, and the standards of some of them were given by the author on the basis of relative data.
Thirdly, water quality model QUAL2E was selected to simulate and predict water quality within Jinhe River according to the specific conditions of the river. Some of parameters were fixed by experience data and experience formula, the others were estimated by reasoning backward to the model. According to the current conditions of Jinhe River. The method of reasoning backward to the model was put forward by the author, which was proved the best one after comparing with the other two methods.
Fourthly, taking three groups of water quality data of Jinhe River as original data, prediction to water quality of the river was made. Compared with real monitored value, the error of predicted value of all of simulating terms, including dissolved oxygen, bio-chemical oxygen demand, chlorophyll a, organic nitrogen, ammonia
nitrogen, nitrite nitrogen, nitrate nitrogen, organic phosphorus, dissolved phosphorus and temperature, were basically within error limit of 20%, which validated the validity of the model.
Fifthly, coupled with the current pollution status of Jinhe River and the production of the model, feasible quantitative measures were put forward.
The study not only can predict water quality of Jinhe River and provide scientific proof to making decisions to the optimization to treatment techniques, water quality management and planning, but also can provide feasibility argumentation for water pollution prevention and cure measures.
引文
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[5]郭劲松，李胜海，龙腾锐. 水质模型及其研究进展. 重庆建筑大学学报. 2002，24(2)：109～115
[6]W﹒金士博. 水环境数学模型. 北京：中国建筑工业出版社，1987
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[8]EPA. The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Manual, EPA 600/3-87/007. U.S. Environment Protection Agency, Athens, Ga
[9]李炜. 环境水力学进展. 武汉水利电力大学出版社，1999
[10]Y.Cohen. Pollutants in a Multimedia Environment Plenum: New York, 1986, 7
[11]Andrews K.Takyi and Barbara J.Lence. Surface Water quality management using a multiple-realization chance constrained method[J]. Water resources research. 1999, 35(5): 1657～1669
[12]宋星原，雒文生. 河流水质过程的随机模拟研究. 武汉水利电力大学学报. 1993，26(6)：690～697
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[14]雒文生，宋星原. 用耦合模型法进行水质随机模拟的研究. 水利学报. 1995，3：12～27
[15]周志军. 水库垂直二维湍流与水温水质耦合模型. 水电能源科学. 1997，15(3)：1～7
[16]A.Baeza et al.. Spatial and temporal evolution of the levels of tritium in the Tagus River in its passage through Caceres(Spain) and the Alentejo(Portugal)[J]. Water Research. 2001, 35(3): 705～714
[17]J.M.P.Vieria and L.Lijklema. Development and Application of a Model for Region Quality Management[J]. Water research. 1989, 23(6): 767～778
[18]Amit K.Sinha et al.. Nonlinear optimization model for screening multipurpose reservoir system[J]. Journal of water resources planning and management. 1989, 115(5): 1011～1024
[19]S.Aliteza Taghavi et al.. Optinal control of ground-water quality management: nonlinear programming approach[J]. Journal of water resources planning and management. 1994, 120(6): 963～982
[20]Bin Zhang et al.. Prediction of water runoff using Bayesian concepts and modular neural network[J]. Water resources research. 2000, 36(3): 753～762
[21]Wu-Seng Lung. Fate and Transport modeling using a numerical tracer[J]. Water resources research. 1996, 32(1): 171～178
[22] Richard N.Palmer et al.. Optimization of water quality monitoring networks[J]. Journal of water resources planning and management. 1985, 111(4): 478～493
[23]Sharp W.E.. A topological optimum water sampling plan for river and stream[J]. Water resources research. 1971, 7(6): 753～761
[24]高建群，郑英铭. 京杭运河徐州段的水质模型研究. 上海环境科学. 1995，14(9)：8～25
[25]郭永彬，王焰新. 汉江中下游水质模拟与预测. 安全与环境工程. 2003，10(1)：4～7
[26]李鸿. 汛期市政排水对海河的污染及其水质模拟的研究. 天津大学硕士研究生毕业论文，2002
[27]陈伟,徐左正,叶舜涛等. 苏州河支流综合整治工程. 给水排水 2002,28(2)：31～34
[28]陈伟,叶舜涛. 苏州河河道曝氧探讨. 上海环境科学. 2001,20(5)：233～234
[29]朱坦,李洪远,李强. 津河水系的修复对天津城市生态环境的影响. 城市环境与城市生态. 2001,14(3)：16～17
[30]郦桂芬. 环境质量评价. 北京：中国环境科学出版社，1989
[31]陆雍森，马仲文，张爽. 环境评价. 上海：同济大学出版社，1990
[32]丁桑岚. 环境评价概论. 北京：化学工业出版社，2001：101～102
[33]陆雍森. 环境评价. 上海：同济大学出版社，1999
[34]郑崇杰，王绍林. 饱和水体富营养化评价. 安徽大学学报. 1990，14(1)：62～69
[35]严煦世，范谨初. 给水工程. 中国建筑工业出版社，1999
[36]天津市环境保护局. 天津市环境质量报告书，2001
[37]李树苑，张怀宇. 合理利用水资源加快污水再生利用城市杂用水. 天津：全国城市污水再生利用经验交流和技术研讨会，2003.10
[38]张朝能.水体中饱和溶解氧的求算方法探讨.环境科学研究.1999,12(2)：54～55
[39]王蕾，尹澄清，兰志文. 特定小流域水质模型的选择. 环境化学. 1993，
12(5)：387～393
[40]Andreja Drolc and Jana Zagorc Koncan. Water Quality Modelling of the River Sava. Slovenia. Water Research. 1996, 30(11): 2587～2592
[41]Andreja Drolc and Jana Zagorc Koncan. Calibration of QUAL2E Model for the River Sava. Slovenia. Water Science and Technology. 1999, 40(10): 111～118
[42]洪继华. QUAL2E模型在中小河流研究中的应用. 环境科学与技术. 1982，2：5～7
[43]田一平. QUAL-Ⅱ综合水质模型及其使用方法. 环境监测管理与技术. 1990，2(1)：32～35
[44]Uluatam S.S(1933b). Calibration of a steady-state model of water quality data from the Karasu River,Turkey.Europ. Water Pollution Control. 1993, 3: 35～40
[45]Van Der Beken A. The use of water quality models in Belgium. Water Science and Technology. 1987, 19: 1197～1202
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[51]熊万永. 福州内河引水冲污工程的实践与认识. 中国给水排水. 2000，16(7)：26～28
[2]傅国伟，程声通. 水污染控制规划[M]. 北京：清华大学出版社，1985
[3]谢永明. 环境水质模型概论[M]. 中国科技大学出版社，1996
[4]叶常明. 水环境数学模型的研究进展. 环境科学进展. 1993，1(1)：74～81
[5]郭劲松，李胜海，龙腾锐. 水质模型及其研究进展. 重庆建筑大学学报. 2002，24(2)：109～115
[6]W﹒金士博. 水环境数学模型. 北京：中国建筑工业出版社，1987
[7]傅国伟. 河流水质数学模型与模拟计算. 北京：中国环境科学出版社， 1987
[8]EPA. The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Manual, EPA 600/3-87/007. U.S. Environment Protection Agency, Athens, Ga
[9]李炜. 环境水力学进展. 武汉水利电力大学出版社，1999
[10]Y.Cohen. Pollutants in a Multimedia Environment Plenum: New York, 1986, 7
[11]Andrews K.Takyi and Barbara J.Lence. Surface Water quality management using a multiple-realization chance constrained method[J]. Water resources research. 1999, 35(5): 1657～1669
[12]宋星原，雒文生. 河流水质过程的随机模拟研究. 武汉水利电力大学学报. 1993，26(6)：690～697
[13]雒文生，宋星原. 确定－随机联合模型法水质模拟与预测. 水电能源科学. 1994，12(1)：1～8
[14]雒文生，宋星原. 用耦合模型法进行水质随机模拟的研究. 水利学报. 1995，3：12～27
[15]周志军. 水库垂直二维湍流与水温水质耦合模型. 水电能源科学. 1997，15(3)：1～7
[16]A.Baeza et al.. Spatial and temporal evolution of the levels of tritium in the Tagus River in its passage through Caceres(Spain) and the Alentejo(Portugal)[J]. Water Research. 2001, 35(3): 705～714
[17]J.M.P.Vieria and L.Lijklema. Development and Application of a Model for Region Quality Management[J]. Water research. 1989, 23(6): 767～778
[18]Amit K.Sinha et al.. Nonlinear optimization model for screening multipurpose reservoir system[J]. Journal of water resources planning and management. 1989, 115(5): 1011～1024
[19]S.Aliteza Taghavi et al.. Optinal control of ground-water quality management: nonlinear programming approach[J]. Journal of water resources planning and management. 1994, 120(6): 963～982
[20]Bin Zhang et al.. Prediction of water runoff using Bayesian concepts and modular neural network[J]. Water resources research. 2000, 36(3): 753～762
[21]Wu-Seng Lung. Fate and Transport modeling using a numerical tracer[J]. Water resources research. 1996, 32(1): 171～178
[22] Richard N.Palmer et al.. Optimization of water quality monitoring networks[J]. Journal of water resources planning and management. 1985, 111(4): 478～493
[23]Sharp W.E.. A topological optimum water sampling plan for river and stream[J]. Water resources research. 1971, 7(6): 753～761
[24]高建群，郑英铭. 京杭运河徐州段的水质模型研究. 上海环境科学. 1995，14(9)：8～25
[25]郭永彬，王焰新. 汉江中下游水质模拟与预测. 安全与环境工程. 2003，10(1)：4～7
[26]李鸿. 汛期市政排水对海河的污染及其水质模拟的研究. 天津大学硕士研究生毕业论文，2002
[27]陈伟,徐左正,叶舜涛等. 苏州河支流综合整治工程. 给水排水 2002,28(2)：31～34
[28]陈伟,叶舜涛. 苏州河河道曝氧探讨. 上海环境科学. 2001,20(5)：233～234
[29]朱坦,李洪远,李强. 津河水系的修复对天津城市生态环境的影响. 城市环境与城市生态. 2001,14(3)：16～17
[30]郦桂芬. 环境质量评价. 北京：中国环境科学出版社，1989
[31]陆雍森，马仲文，张爽. 环境评价. 上海：同济大学出版社，1990
[32]丁桑岚. 环境评价概论. 北京：化学工业出版社，2001：101～102
[33]陆雍森. 环境评价. 上海：同济大学出版社，1999
[34]郑崇杰，王绍林. 饱和水体富营养化评价. 安徽大学学报. 1990，14(1)：62～69
[35]严煦世，范谨初. 给水工程. 中国建筑工业出版社，1999
[36]天津市环境保护局. 天津市环境质量报告书，2001
[37]李树苑，张怀宇. 合理利用水资源加快污水再生利用城市杂用水. 天津：全国城市污水再生利用经验交流和技术研讨会，2003.10
[38]张朝能.水体中饱和溶解氧的求算方法探讨.环境科学研究.1999,12(2)：54～55
[39]王蕾，尹澄清，兰志文. 特定小流域水质模型的选择. 环境化学. 1993，
12(5)：387～393
[40]Andreja Drolc and Jana Zagorc Koncan. Water Quality Modelling of the River Sava. Slovenia. Water Research. 1996, 30(11): 2587～2592
[41]Andreja Drolc and Jana Zagorc Koncan. Calibration of QUAL2E Model for the River Sava. Slovenia. Water Science and Technology. 1999, 40(10): 111～118
[42]洪继华. QUAL2E模型在中小河流研究中的应用. 环境科学与技术. 1982，2：5～7
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