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研究生:陳建中
研究生(外文):Jeng-Chung Chen
論文名稱:都會水環境污染控制系統之最佳化操作策略分析
論文名稱(外文):Optimal Operation of Water Pollution Control System in the Urban Region
指導教授:張乃斌張乃斌引用關係
指導教授(外文):Ni-Bin Chang
學位類別:博士
校院名稱:國立成功大學
系所名稱:環境工程學系碩博士班
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:172
中文關鍵詞:系統分析水污染模式人工智慧都會河川永續發展
外文關鍵詞:urban riversustainabilityartificial intelligencewater pollution modelsystems analysis
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都會區水環境生態的維護已成為人類文明永續發展所不可缺少之一環,因此先進國家無不致力於推動下水道系統及河川生態復育之建設工作,其中包括污水截流系統、下水道管線、污水處理廠、海洋放流管線等水污染控制工程,對於污染管理者而言,面對如此複雜的污染控制系統,如何發揮其全系統最大效益將是一大挑戰,本論文之研究目標即為如何有效管理水污染控制系統以降低水環境生態衝擊進而確保都會的永續發展。研究重點包括以下幾個問題,首先是暴雨時期之洪峰溢流對於都會河川之生態衝擊評估,其次是如何操控污水截流系統以達到暴雨污染衝擊的最小化,以及面對進流水狀況變化時如何維持污水處理污水處理廠及海洋放流管系統之最佳化操作,此外廢水回收再利用的可行性也應予以探討,最後是如何將此研究成果發展成網際網路決策支援系統。綜合以上之研究方向,本論文研究選擇以高雄市作為案例探討,針對都會水環境系統之複雜性進行系統分析,研究成果包括下列四個項目:
·第一部分乃在於開發暴雨逕流及水污染傳輸模式,首先在PCSWMM2000系統中建立各子集水區之RUNOFF與TRANSPORT分析模組並以此率定出暴雨逕流模式中之各項參數值,然後將這些經過驗證後的資訊結合USEPA SWMM4以推估暴雨時集水區地表逕流帶入承受水體之污染量,再以愛河水理水質傳輸模式(LRHWQ)模擬出暴雨逕流水污染對於愛河下游河段水質溶氧之可能變化及生態衝擊。
· 第二部分建立水污染控制系統之優化管理模式,並以此評判各種合流式下水道截流系統閘門之操控策略,將達到水環境生態衝擊最小化作為控制目標,同時針對截流後海岸污水處理廠及海洋放流系統面臨污染負荷突增時尋求最佳之操作策略,配合CORMIX海洋排放模擬模式之分析以協助管理者瞭解污水海放後可能之環境風險,分析結果顯示針對暴雨逕流污染的控制設置滯洪池是有必要的,而且若要藉由操控截流閘門以達到生態衝擊的最小化僅在於中小型降雨(降雨強度小於100mm/hr)且初始水質不算太差時(BOD小於60mg/L)才可行。
· 第三部分則運用人工智慧理論評估陸域污水處理系統放流水之回收再利用,以類神經網路所建立之放流水預報模式彌補污水廠運轉初期操作經驗之不足,並協助管理者進行適當之污水回收決策,以水中氮營養鹽之預測為例,當總氮濃度預測偏高時放流水將不宜作為地下水體的補注之用,而過高的氨氮濃度則不宜供給水產養殖。
· 第四部份
修改相關之模擬模式及優化模式分析功能,使其可執行線上分析能力,配合知識管理與網際網路地理資訊系統分析功能,建立網際網路決策支援系統,提供更為快速有效地的操控分析。
Many river systems in the urban region have been suffering from the wastewater discharges during the urbanization process for centuries. As a result, the proper control of storm water and domestic wastewater effluents has been becoming an integral part of the sustainable development plan. It is recognized that engineered systems, including sewer system, interceptor system, wastewater treatment plants, and outfall pipes are all essential urban infrastructures for water pollution control in the city of Kaohsiung, South Taiwan. However, increasing complexity over time in such an integrated system has resulted in a higher challenge to minimize the ecological impact due to sewage disposal. So, it is the aim of this study to utilize recent advances of systems engineering and information technologies in analyzing the complexity of operation of the urban sewer system as sea land interactions in many coastal cities has continuously received wide attention. To fulfill the ultimate goal of environmental restoration with regards to the ecosystem integrity in the complex urban river system, several key issues are worthwhile exploring. First, “to what extent must environmental restoration of the Love River in terms of ecological integrity be tied with the storm water impact?” Second, “to what degree should the basis for decision-making be made concerning the optimal operation of gates in the interceptor system in terms of the potential storm water impact under different estuary situation?” Third, what level must the optimal operation of ocean outfall system be imposed to handle the combined sewer overflows in order to meet the environmental integrity in the coastal region?” Fourth, “what is the possibility of using artificial intelligence techniques to manage wastewater reclamation and to mitigate the overall impacts of combined sewer overflows?” Finally, “could recent advances of Internet information technology be applied to building up the real-time on-line operation capacity for the urban sewer infrastructure system?” Therefore, this study is designed to addresses those critical issues by a holistic approach leading to achieve the following study goals based on the interdisciplinary principles of environmental science, policy, management, and technology for the city of Kaohsiung in South Taiwan. It achieves the following items:
· At first, calibrating and verifying the simulation model of SWMM to address the process of storm water runoff is required. The efforts will merit a credit by using well validated RUNOFF and TRANSPORT modules in the SWMM as a means to provide reliable inputs for the validated water quality simulation model (LRHWQ). Thus the integrated modeling system could smoothly link the storm water impact with the resultant DO levels in the receiving water body from both spatial and temporal stands.
· Once the interactive relationship between the storm water impact and the resultant estuary water quality is available, it is possible to engage in building an optimal gate operation model for minimizing the ecological impact due to the release of combined sewer overflows on one hand, and minimize the impact of ocean outfall by proper treatment of the intercepted combined sewer overflows on the other hand. The model of CORMIX is needed to assist in the assessment of pollutant diffusion in the marine environment. Based on the findings in this study, construction of a storage pond is inevitable. Yet the optimal solutions for sizing the storage pond in the sewer system can only be found in those cases when the rainfall intensity is below 100 mm/hr or the initial BOD5 concentration is smaller than 60 mg/L.
· In order to reduce the generation of wastewater effluents, applying the algorithms of artificial intelligent to handle wastewater treatment plant may help assess the recycling potential of the treated wastewater effluents. As a result, the neural network model selected in this study can be used as an on-line numerical tool for predicting effluent NH4+-N and total nitrogen contents and thereby, providing valuable and immediate information of the potential impacts of reuse actions to the aquatic environment.
· A decision support system is therefore developed in this study to include all the efforts of various simulation and optimization analyses in the architecture of a web-based environment.
CONTENTS
中文摘要 I
ABSTRACT III
誌謝 V
CONTENTS VI
LIST OF FIGURES VIII
LIST OF TABLES XI
CHAPTER
I. INTRODUCTION 1-1
1.1 Background of the Urban Water Environment 1-1
1.1.1 Study Area 1-1
1.1.2 Problem Identification 1-3
1.2 Research Objectives 1-13
1.3 Methodologies and Study Framework 1-15
II. LITERATURE REVIEW 2-1
2.1 Water Quality Simulation Models 2-1
2.1.1 Simulation of Storm Runoff 2-2
2.1.2 Fates and Transports of Pollutants in the Aquatic Environment 2-4
2.2 Storm Water Pollution Control 2-5
2.3 System Analysis for Wastewater Treatment and Ocean Outfall Process 2-6
2.4 Real-time Control with the aid of Artificial Intelligence 2-8
2.5 Wastewater Reclamation 2-11
2.6 Decision Support System 2-12
III. VALIDATION OF SIMULATION MODELS 3-1
3.1 Water Quality Sampling and Analysis 3-1
3.2 Model Development: SWMM Analysis 3-5
3.3 Model Development of LRHWQ 3-10
3.4 Model Calibration and Verification 3-14
3.5 Model Integration 3-29
IV. OPTIMAL MANAGEMENT OF WATER POLLUTION CONTROL
SYSTEM 4-1
4.1 Optimal Operation Model of Sewer System 4-1
4.2 Optimal Management of Ocean Outfall System 4-5
4.3 Real-time Control of Wastewater Treatment Plant 4-12
4.4 Multiple Objectives Analysis of Wastewater Reclamation 4-23
V. WEB BASED DECISION SUPPORT SYSTEM 5-1
5.1 The Architecture of Web Based DSS 5-1
5.2 Database Design and Management 5-2
5.3 Sharing-Vision Modeling on the Web 5-6
5.3.1 Modeling Analyses 5-6
5.3.2 Optimization Analyses 5-6
5.3.3 Knowledge Management 5-7
VI. RESULTS AND DISCUSSIONS 6-1
6.1 Storm Impact to an Estuarine Ecological System 6-1
6.2 Minimizing Ecological Risk During Combined Sewage Overflow 6-5
6.3 Optimal Control of CSO for Coastal Wastewater Treatment Ocean and
Outfall System 6-14
6.4 A Neural-Fuzzy Control Scheme in Aeration Control 6-21
6.5 Wastewater Reclamation Potential 6-31
6.6 The Development of Web-based DSS 6-33
6.6.1 Share-Version Decision Analysis 6-34
6.6.2 Generating Optimal Gate Operating Strategy 6-36
VII. CONCLUSIONS AND SUGGESTIONS 7-1
7.1 Conclusions 7-1
7.2 Suggestions and Future Work 7-2
7.2.1 Suggestions 7-2
7.2.2 Future Work 7-5
REFERENCES i i
APPENDIX: NOTATION xiii
自述 A-1
Abu-Rizaiza, O. S. (1999). Modification of the standards of wastewater reuse in Saudi Arabia. Water Research, 33(11), 2601-2608.
Alan, G. H. (1995) .Water Pollution and Fish Physiology. Lewis Publishers.
Akan, A. O., Schafran, G. C., Pommerenk, P. and Harrell, L. J. (2000). Modeling storm-water runoff quantity and quality from marine drydocks. Journal of Environmental Engineering, 126(1), 5-11.
Amirtharajah, A. (1978) Optimum backwashing of sand filters. Journal of the Environmental Engineering Division, 917-931.
Aoi, T., Okaniwa, Y., Hagiwara, K., Motomura, K., Iwaihara, E., Imai, M. and Serizawa, Y. (1992). A direct ammonium control system using fuzzy inference in a high-load biological denitrification process treating collected human excreta. Water Science & Technol. 26(5-6), 1325-1334.
Argent, R. M. & Grayson, R. B. (2001). Design of information systems for environmental managers: an example using interface prototyping. Environmental Modelling and Software 16, 433-438.
Asano, T. and Levine, A. D. (1996). Wastewater reclamation recycling and reuse: past, present, and future. Water Science & Technology, 33(10-11), 1-4.
Asano, T., Maeda, M. and Takaki, M. (1996). Wastewater reclamation and reuse in Japan: overview and implementation examples. Water Science & Technology, 34(11), 219-226.
Attrill, M. J. (editor) (1998) A rehabilitated estuarine ecosystem: the environment and ecology of the Thames Estuary. Kluwer Academic Publishers, London.
Balslev, P., Lynggaard-Jensen, A. and Nickelsen, C. (1996). Nutrient sensor based real-time on-line process control of a wastewater treatment plant using recirculation. Water Science & Technology, 33(1), 183-192.
Bettess, R., Pitfield, R.A. and Price, R.K. (1978). A surcharging model for storm sewer systems. In: Halliwell, P.R. (Ed.), Urban Storm Drainage. Pentech Press, London, 306–316.
Bhaduri, B., Minner, M., Tatalovich, S. and Harbor, J. (2001). Long-term hydrologic impact of urbanization: a tale of two models. Journal of Water Resources Planning and Management, 127(1), 13-19.
Bikangaga, J.H. and Nassehi, V. (1995). Application of computer modeling techniques to the determination of optimum effluent discharge policies in tidal water systems. Water Research, 29, 2367-2375.
Bjorlenius, B. and Reinius, L. G.. (1998). Use of on-line data to evaluate the activity in the biological stage at a wastewater treatment plant. Water Science & Technology, 37(9), 33-40.
Blumberg, A. F., Khan, L. A. and St. John, J. P. (1999). Three-dimensional hydrodynamic model of New York Harbor region. Journal of Hydraulic Engineering, 125(8), 799-816.
Bonazountas, M., Kallidromitous, D., and Dimou, N. (1988). OUTFALL: A sea outfall model. Proceedings of the 2nd International Conference of Environmental Software, Porto Carras, Greece, 95-109.
Boscolo, A., Mangiavacchi, C., Drius, F., Rongione, F., Pavan, F. and Cecchi, F. (1993). Fuzzy control of an anaerobic digester for the treatment of the organic fraction of the MSW, Water Science & Technology, 27(2), 57-68.
Boston, T. and Stockwell, D. (1994). Interactive species distribution reporting, mapping and modeling using the World Wide Web. Proc. of Second International WWW Conference’ 94: Mosaic and the Web, Chicago, USA.
Brown, L. C. and Barnwell, T. O. (1987) The enhanced stream water quality model QUAL2E and QUAL2E-UNCAS: Document and User Manual, EPA/600/3-87/007, U. S. Environmental Protection Agency, Environmental Research Laboratory, Athens, GA.
Burian, S. J., Streit, G. E., McPherson, T. N., Brown, M. J. and Turin, H. J. (2001) Modeling the atmospheric deposition and stormwater washoff of nitrogen compounds. Environmental Modeling & Software, 16, 467-479.
Carmichael, J. J. and Strzepek, K. M. (2000) Mutiple-organic-pollutant simulation/optimization model of industrial and municipal wastewater loading to a riverine environment. Water Resources Research, 36(5), 1325-1332.
Cerda, A., Oms, M. T., Forteza, R. and Cerda, V. (1997). Total nitrogen determination by flow injection using on-line microware-assisted digestion. Analytica Chimica Acta, 351,273-279.
Chang, N. B., Wei, Y. L., Tseng, C. C., and Kao, C. Y., (1997) The design of a GIS-based decision support system for chemical emergency preparedness and response in an urban environment. Computers, Environment and Urban System, 21(1), pp. 67-94.
Chang, N. B. and Wang, S. F. (1995a). Optimal planning of coastal wastewater treatment and disposal systems. Coastal Management, 23, 153-166.
Chang, N. B. and Wang, S. F. (1995b). A grey nonlinear programming approach for planning coastal wastewater treatment and disposal systems. Water Science and Technology, 32(2), 19-29.
Chang, N. B. and Wang, S. F. (1996). The development of an environmental decision support system for municipal solid waste management. Computers, Environment and Urban System, 20(3), pp. 201-212.
Chang, N. B and Chen, W. C. (2000). Fuzzy controller design for municipal incinerators with the aid of genetic algorithms and genetic programming techniques. Waste Management & Research, 18(5), 341-351.
Chang, N. B., Chen, W. C., and Shieh, W. K. (2001a). Optimal control of wastewater treatment plants via integrated neural network and genetic algorithms. Civil Engineering and Environmental Systems, 18, 1-17.
Chang, N. B, Chen, W. C., and Chen, J. C. (2001b). GA-based neural-fuzzy controller design for municipal incinerators. Fuzzy Sets and Systems, in press.
Chang, Y. C., Chang, N. B., Ma, G. D. (2001). Internet web-based information system for handling scrap vehicles disposal in Taiwan. Environmental Modeling and Assessment, 6(4), pp. 1-14.
Charpentier, J. and Martin, G. (1996). New approach to oxygen requirement for low-load activated sludge. Water Research, 30(10), 2347-2356.
Chen, C. W., Herr, J., Ziemelis, L., Goldstein, R. A., and Olmsted, L. (1999). Decision support system for total maximum daily load. Journal of Environmental Engineering, ASCE, 125(7), pp. 653-659.
Chen, C. Y. (2001) personal communication.
Chen, J. C., Chang, N. B., and Shieh, W. K. (2001). Assessing wastewater reclamation potential by neural networks model. Engineering Applications of Artificial Intelligence, in review.
Chen, J. C., Chang, N. B. and Chen C. Y. (2002a) Minimizing ecological risk of combined sewage overflow in an urban river system by a system-based approach. Journal of Environmental Engineering, ASCE, in review.
Chen, J. C., Chang, N. B., Fen, C. S. and Chen C. Y. (2002b) Assessing the ecological impact from storm flooding in an urban river system by an estuarine water quality model. Civil Engineering and Environmental Systems, in review.
Chen, M. H. and Hsiao, J. S. (1996). The reproductive biology of the gizzard shad, Nematalosa come (Richarson, 1846), in the Kaohsiung River and its harbor area, Southern Taiwan. Zoological Studies, 35(4): 261-271.
Chen, M. H., Wen, D. J. and Chen, C. Y. (1999). Reproduction and estuarine utilization of the grey mullet, Liza macrolepis (Smith, 1846), in the area of Kaohsiung harbour, southern Taiwan. Fish. Sci. (in press).
Chen, W. C., Chang, N. B., and Shieh, W. K. (2001a). Advanced hybrid fuzzy neural controller for industrial wastewater treatment. Journal of Environmental Engineering, ASCE, 127(11), 1-12.
Chen, W. C., Chang, N. B., and Shieh, W. K. (2001b). GA-based fuzzy neural control scheme for municipal wastewater treatment. Water Environment Research, in review.
Clark, R. M. (1983). Optimizing GAC systems. Journal of Environmental Engineering, 139-156.
Cohen, A., Janssen, G., Brewster, S. D., Seeley, R., Boogert, A. A., Grahan, A. A., Mardani, M. R., Clarke, N. and Kasabov, N. K. (1997). Application of computational intelligence for on-line control of a sequencing batch reactor (SBR) at Morrinsville sewage treatment plant. Water Science & Technology, 35(10), 63-71.
Cote, M., Grandjean, B. P. A., Lessard, P. and Thibault, J. (1995). Dynamic modeling of the activated sludge process: improving prediction using neural networks. Water Research, 29(4), 995-1004.
Cubillo, F. and Rodriguez, B. (1992). System for control of river water quality for the community of Madrid using QUAL2E. Water Science & Technology, 26, 24-30.
Culevski, N. (1996). Artificial neural networks and genetic algorithms: computational models. Ph.D. thesis, California State University, Long Beach, USA.
Curtis, L. D. and Tarang, K. (1997). A steady-state model of the Willamette River: implications for flow control of dissolved oxygen and phytoplankton biomass. in River Water Quality: Dynamics and Restoration, editor, Antonius Laenen and David A. Dunnette, 163-185.
Czogala, E., Rawilk, T. (1989). Modeling of a fuzzy controller with application to the control of biological process, Fuzzy Sets System, 31, 13-22.
Delgado, M., Gomez, A. F., and Martin, F. (1997). A fuzzy clustering-based rapid prototyping for fuzzy rule-based modeling. IEEE Transaction Fuzzy System, 5(2), 223-233.
Dochain, D and Vanrolleghem, P.A. (2001) Dynamical Modeling and Estimation in Wastewater Treatment Process. IWA Press, London, UK.
Duke, L. D., Lo, T. S. and Turner, M. W. (1999). Chemical constituents in storm flow vs. dry weather discharges in California storm water conveyances. Journal of the American Water Resource Association, 35(4),821-836.
EI-Sharif, A. and Hansen, D. (2001). Application of SWMM to the flooding problem in Truro, Nova Scotia. Canadian Water Resources Journal, 26(4), 439-459.
Enbutsu, I., Baba, K., Hara, N., Waseda, K. and Nogita, S. (1993). Integration of multi AI paradigms for intelligent operation support systems-fuzzy rule extraction from a neural network. Water Science & Technology, 28(11/12), 333-340.
EPA, Taiwan, http://www.epa.gov.tw/water pollution/g02001.htm, 1993-1999.
Estaben, M., Polit, M and Steyer, J.P. (1997). Fuzzy control for an anaerobic digester. Control Engineering Practice, 5(98), 1303-1310.
Faby, J.A., Brissaud, F. and Bontoux, J. (1999). Wastewater reuse in France: water quality standards and wastewater treatment technologies. Water Science & Technology, 40(4-5), 37-42.
Falconer R.A. and Lin B. (1997). Three-dimensional modeling of water quality in the humber estuary. Water Research, 31, 1092-1102.
Farrel, A. and Hart, M. (1998). What does sustainability really mean? the search for useful indicators. Environment, 40(9): 4-15.
Fen, Chiu-Shia (1994) The hydraulic and water quality model of Love River in Kaohsiung. Report of Tainan Hydraulics Laboratory, no.156.
Fontes, Lima, F. J. and Neves, N.M.S. (1992). Oceanic disposal of the treated wastewater from the Camacari Petrochemical Complex – environmental and technical considerations. Water Science and Technology, 25(9), 73-84
Foxon, T. J., Butler, D., Dawes, J. K., Hytchinson, D., Leach, M. A., Pearson, P. J. G. and Rose, D. (2000). An assessment of water demand management options from a system approach. Journal of the Chartered Institution of Water and Environmental Management, 14(3), 171-178.
Fruge, D. W. (1995). Coastal Zone ’95, Edge, B. L., Ed.; ASCE Press. Tampa, Florida, pp 35-36.
Fu, C. and Poch, M. (1995). System identification and real-time pattern recognition by neural networks for an activated sludge process. Environment International, 21(1), 57-69.
Fu, C. S. and Poch, M. (1995). Fuzzy modeling pattern recognition for dynamic process and its application for an activated sludge process. Chemic Engineering Science, 50(23), 3715-3725.
Fu, C. S. and Poch, M. (1998). Fuzzy model and decision of COD control for an activated sludge process. Fuzzy Sets System, 41, 281-292.
Geiger, W.P. and Dorsch, H.R. (1980). Quantity–quality simulation (QQS): a detailed continuous planning model for urban runoff control. Model Description, Testing and Applications. US Environmental Protection Agency, Cincinnati, OH. Report EPA/600/2-80-011.
Gorokhovich, Y., Khanbilvardi, R., Janus, L., Goldsmith, V. and Stern, D. (2000). Spatially distributed modeling of stream flow during storm events. Journal of the American Water Resources Association, 36(3), 523-539.
Grum, M. (1998). Incorporating concepts from physical theory into stochastic modeling of urban runoff pollution. Water Science & Technology, 37(1), 179-185.
Havno, K., Madsen, M.N. and Dorge, J. (1995). MIKE II — A generalized river modeling package. In: Singh, V.P. (Ed.), Computer Models of Watershed Hydrology. Water Resources Publications, Colorado, 733–782.
Heath, A. G. (1995). Water Pollution and Fish Physiology Lewis Publishers.
Heniche, M., Secretan, Y., Boudreau, P. and Leclerc, M. (2000) Two-dimensional finite element drying-wetting shallow water model for rivers and estuaries. Advances in Water Resource, 23(4), 359-372.
Heitz, L. F., Khosrowpanah, S. and Nelson, J. (2000) Sizing of surface water runoff detention ponds for water quality improvement. Journal of the American Water Resource Association, 36(3), 541-548.
Hsu, M. H., Kuo, A. Y., Liu, W. C. and Kuo, J. T. (1999). Water quality modelling of the Tanshui estuarine system in northern Taiwan. Journal of Environment Science and Health, 34(7), 1415-1453.
Hsu, M. H., Chen, S. H. and Chang, T. J. (2000). Inundation simulation for urban drainage basin with storm sewer system. Journal of Hydrology, 234(1), 21-37.
Huber, W.C. and Dickinson, R.E. (1988). Storm Water Management Model User's Manual, Version 4, EPA/600/3-88/001a (NTIS PB88-236641/AS), Environmental Protection Agency, Athens, GA.
Huang Y.H. and Chen M.H. (1996). A study on species composition and seasonal abundance of ichthyoplankton in Kaohsiung River, its harbour area and the nearby coastal waters, southern Taiwan. Master Thesis, NSYU, Taiwan.
IISD (1999). Indicators for Sustainable Development: Theory, Method and Application. A Report to Balton Group (Hartmut Bossel, Editor). Canada, International Institute for Sustainable Development.
Ishibuchi, H., Nozaki, K., and Yamamoto, N. (1993). Selecting fuzzy rules by genetic algorithm for classification problem. Proc. 2nd IEEE Int. Conf. on Fuzzy Systems, San Francisco, 1119-1124.
James, W. and James, R. C. editors (1999). Water System Models “Hydrology”: Users Guide to SWMM4 Runoff and Supporting Modules. Computational Hydraulics International, University of Florida, Gainesville, Florida, USA.
Jones, E. (1964). Fish and River Pollution. Butterworths & Co Press, 5-26.
Kalker, T. J. J., van Goor, C. P., Roeleveld, P. J., Ruland, M. F. and Babuska, R. (1999). “Fuzzy control of aeration in an activated sludge wastewater treatment plant: design, simulation and evaluation. Water Science & Technology, 39(4), 71-77.
Kaohsiung County Government, Taiwan, Handbook of Observing Coastal Biota in Kaohsiung County, 1999.
Kiriakidis K. (1998). Fuzzy model-based control of complex plants. IEEE Transaction Fuzzy System, 6(4), 517-529.
Krejci, V. (1996). Integrated approach to the point-non point-pollution abatement urban drainage. Water Science & Technology, 33(4-5), 9-15.
Latimer, J. S. and Quinn, J. G. (1996). Historical trends and current inputs of hydrohobic compounds in an urban estuary: the sedimentary record. Environment Science Technology, 30, pp 623-633.
Leeuw, E. J., Kramer, J. F., Bult, B. A. and Wijcherson, M. H. (1996). Optimization of nutrient removal with on-line monitoring and dynamic simulation. Water Science & Technology, 33(1), 203-209.
Lee, D. S. and Park, J. M. (1999). Neural network modeling for on-line estimation of nutrient dynamics in a sequentially-operated batch reactor. Journal of Biotechnology, 75, 229-239.
Lenzi, M. A. and Luzio, M. D. (1997). Surface runoff, soil erosion and water quality modeling in the Alpone watershed using AGNPS integrated with a Geographic Information System. European Journal of Agronomy, 6, 1-14.
Letcher, R. A., Jakeman, A. J., Calfas, M., Linforth, S., Baginska, B. and Lawrence, I. (2002). A comparison of catchment water quality models and direct estimation techniques. Environmental Modeling & Software, 17, 77-85.
Lin C.T., Juang C.F. and Li C.P. (1999). Temperature control with a neural fuzzy inference network. IEEE T. Sys. Man Cy. C. 29(3), 440-451.
Lin, C. T. and Lee, C. S. G. (1991). Neural-network-based fuzzy logic control and decision system. IEEE Transactions on Computers, 40(12), 1320-1336.
Lo, J.C. and Chen, Y.M. (1999). Stability issues on Takagi–Sugeno fuzzy model—parametric approach. IEEE Transactions on Fuzzy Systems, 7(5), 597-607.
Londong, J. and Wachtl, P. (1996). Six years of practical experience with the operation of on-line analysers. Water Science & Technology, 33(1), 159-164.
Luk, G. K. (1999). Evaluation of dual-purpose detention pond designs with Storm Water Management Model(SWMM). Canadian Water Resources Journal, 24(4), 331-348.
Lung, W. S. and Sobeck, R. G. Jr. (1999). Renewed use of BOD/DO models in water quality management. Journal of Water Resources Planning and Management, 125(4), 222-227.
Lynch G. P. (1996). Maintaining ocean outfall system integrity. Ocean Conference Record IEEE 2, 624-628.
Maclennan, G. A. (1994). The application of genetic algorithms to neural networks. MS thesis, Dalhousie University, Canada.
Manesis S.A., Sapidis D.J. and King R.E. (1998). Intelligent control of wastewater treatment plants. Artificial Intelligence in Engineering, 12, 275-281.
Marsili-Libelli S. and Muller A. (1996). Adaptive fuzzy pattern recognition in the anaerobic digestion process. Pattern Recognition Letters, 17, 651-659.
Melvasalo, T. (2000). Regional marine environmental management and the GPA-LBA: perspectives and the need for scientific support. Ocean and Coastal Management, 43, pp. 713-724.
Mishra S., Dash, P.K. and Panda, G. (2000). TS-fuzzy controller for UPFC in a Mutimachine power system. IEE. Proc.-Gener. Transm. Distrib., 147(1), 15-22.
Mitchell, V. G., Mein, R. G. and McMahon, T. A. (2001). Modeling the urban water cycle. Environmental Modeling & Software, 16, 615-629.
Muller, A., Marsili-Libelli, S., Aivasidis, A., Lloyd, T., Kroner, and Wandrey, C. (1997). Fuzzy control of disturbances in a wastewater treatment process. Water Research, 31(12), 3157-3167.
Murphy, J. L., Ring, J. D. and Seiler, J. F. (2000). Davis book CSO storage facility in Bangor, Maine. Journal of New England Water Environment Association, 34(2), 163-171.
Nelen F. (1993) On the potential of real time control of urban drainage systems. Water Science & Technology, 27(5-6), 111-122.
Ng B., Turner A., Tyler A.O., Falconer R.A. and Millward G.E. (1996) Modeling contaminant geochemistry in estuaries. Water Research, 30, 63-74.
Ning, S. K., Chang, N. B., Yang, L., Chen, H. W., and Hsu, H, Y. (2001). Assessing pollution prevention program by QUAL2E simulation analysis for water quality management in the Kao-Ping River basin, Taiwan. Journal of Environment Management, 61(1), 61-76, 2001.
NRC (1999). Our Common Journey - A Transition Towards Sustainability. Washington, DC, National Academy Press: 363 pp.
O’Connor D.J. (1960) Oxygen balance of an estuary. ASCE, Journal of Environment Engineering, 86, 35-55.
Park, H. and Johnson, T. J. (1998). Hydrodynamic modeling in solving combined sewer problem: a case study. Water Research, 32(6),1948-1956.
Paul, E., Plisson-Saune, S., Mauret, M. and Cantet, J. (1998). Process state evaluation of alternating oxic-anoxic activated sludge using ORP, pH and DO. Water Science & Technology, 38(3), 299-306.
Peha, J. M. (2001) Bridging the divide between technologists and policy-makers. IEEE Spectrum, pp. 15-20.
Perianez R., Abril J.M. and Garcia-Leon M. (1996) Modelling the suspended matter distribution in an estuarine system: application to the Odiel river in southwest Spain. Ecological Modelling, 87, 169-179.
Price, R.K. and Kidd, C.H.R. (1978). A design and simulation method for storm sewers. In: Halliwell, P.R. (Ed.), International Conference on Urban Storm Drainage. Pentech Press, London, pp. 327–337.
Rauch, W., Thurner, N. and Harremoes, P. (1998a). Required accuracy of rainfall data for integrated urban drainage modeling. Water Science & Technology, 37(11), 81-89.
Rauch, W., Henze, M., Koncsos, L., Reichert, P., Shanahan, P., Somlyody, L. and Vanrolleghem, P. (1998b) River water quality modeling: I. State of the art. Water Science & Technology, 38(11), 237-244.
Rauch, W. and Harremoes, P. (1999) Genetic algorithm in real time control applied to minize transient pollution from urban wastewater system. Water Research, 33(5), 1265-1277.
Rauscher, H. M. (1999) Ecosystem management decision support for federal forests in the United States: A review. Forest Ecology and Management, 114, 173-197.
Reda A. L.L. and Beck M.B. (1999) Simulation model for real-time decision support in controlling the impacts of storm sewage discharges. Water Science & Technology, 39, 225-233.
Roesner, L.A., Aldrich, J.A. and R.E. (1988). Dickinson, Storm Water Management Model User's Manual, Version 4: Addendum I, EXTRAN, EPA/600/3-88/001b (NTIS PB88236658/AS), Environmental Protection Agency, Athens, GA.
Ruan, M. and Wiggers, J. B. M. (1997). Application of time-series analysis to urban storm drainage. Water Science & Technology, 36(5), 125-131.
Sandhu, S. S. (1995). Training of feedforward neural networks with quardratic random optimization and genetic algorithms. MS thesis, University of Nevada at Reno, USA.
Seaman, G. A. (1995). Coastal Zone ’95, Edge, B. L., Ed.; ASCE Press. Tampa, Florida, 70-71.
Shelef, G. and Azov, Y. (1996). The coming ERA of intensive wastewater reuse in the Mediterranean region. Water Science & Technology, 33(10-11), 115-125.
Shih, C. S. and DeFilippi, J. A. (1970) System optimization of waste treatment plant process design. Journal of Sanitary Engineering Division, 409-421.
Sigua, G. C. and Steward, J. S. (2000). Establishing load reduction targets for the Indian River Lagoon, Florida. Journal of American Water Resource Association, 36(1), 123-132.
Sorensen, J., Thornberg, D. E. and Nielsen, M. K. (1994). Optimization of a nitrogen-removing biological wastewater treatment plant using on-line measurements. Water Environment Research, 66(3), 236-242.
Soyupak, S., Oguz, M., Mukhallalati, L., and Yurteri, C. (1994). Planning and design strategies for marine outfalls on the Turkish Black Sea coast. European Water Pollution Control, 4(1), 31-34.
Spall, J. C. and Cristion, J.A. (1997). A neural network controller for systems with unmodeled dynamics with applications to wastewater treatment. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 27(3), 369-375.
Stallings, R. B., Clark, D. E. and Freedman, S. D. (1999). Maximizing use of existing wastewater system to control CSO discharges in Gardiner, Maine. Journal of New England Water Environment Association, 33(2), 165-177.
Steyer, J. P., Rolland, D. Bouvier, J. C. and Moleta, R. (1997). Hybrid fuzzy neural network for diagnosis-application to the anaerobic treatment of wine distillery wastewater in a fluidized bed reactor. Water Science & Technology, 36(6-7), 209-217.
Su, M.C., Liu, C.W., and Tsay, S.S. (1999). Neural-network-based fuzzy model and its application to transient stability prediction in power systems. IEEE Transactions on Systems, Man and Cybernetics-part C: applications and reviews, 29(1), 149-157.
Takagi, T. and Sugeno, M. (1985). Fuzzy identification of systems and its application to modeling and control. IEEE Transaction on Systems, Man, and Cybernetics, 15(1), 116-132.
Tanik, A., Sarikaya, H. Z., Eroglu, V., Orhon, D. and Ozturk, I. (1996). Potential for reuse of treated effluent in Istanbul. Water Science & Technology, 33(10-11), 107-113.
Tay J.H. and Zhang X. (2000). A fast predicting neural fuzzy model for high-rate anaerobic wastewater treatment system. Water Research, 34(11), 2849-2860.
Tchobanoglous, G. and Angelakis, A. N. (1996). Technologies for wastewater treatment appropriate for reuse: potential for applications in Greece. Water Science & Technology, 33(10-11), 15-24.
Thomann R. V. and Mueller, J. A. (1987) Principles of surface water quality modeling and control. Harper & Row Press.
Timothy D. S. and Russell, N. C. (1997) Upper Clear Creek/Standley Lake, Colorado Water-Quality Assessment in River Water Quality: Dynamics and Restoration, editor: Antonius Laenen and David A. Dunnette, CRC Press Inc., New York, 339-345.
Tong R.M., Beck M.B. and Latten A. (1980). Fuzzy control of the activated sludge wastewater treatment process. Automatica, 16, 659-701.
Tsai, Y. P., Ouyang, C. F., Chiang, W. L. and Wu, M. Y. (1994). Construction of an on-line fuzzy controller for the dynamic activated sludge process. Water Research, 28(4), 913-921.
Tsai, Y. P., Ouyang, C. F., Wu, M. Y. and Chiang, W. L. (1996). Effluent suspended solid control of activated sludge process by fuzzy control approach. Water Environment Research, 68(6), 1045-1053.
Uchimura k., Nakamura E. and Fujita S. (1997) Characteristic of stormwater runoff and its control in Japan. Water Science Technology, 36,141-147.
Van Engers, T. M. and Glassee, E. (2001) Facilitating the legislation process using a shared conceptual model. IEEE Intelligent System, 50-57.
Vaughan, W. J.; Russell, C. S. (1982). Freshwater Recreational Fish; The National Benefits of Water Pollution Control. Resource for the Future Press, 40-41.
Vazquez J., Bellefleur D., Gilbert D. and Grandjean B. (1997) Real time control of a combined sewer network using graph theory. Water Science Technology, 36, 301-308.
Wareham, D. G., Hall, K. J. and Mavinic, D. S. (1993). Real-time control of aerobic-anoxic sludge digestion using ORP. Journal of Environmental Engineering, 119(1), 120-136.
Watanabe, S., Baba, K., Yoda, M., Wu, W. C., Enbutsu, I., Hiraoka, M. and Tsumura, K. (1993). Intelligent operation support system for activated sludge process. Water Science & Technology, 128(11), 325-332.
Whitehead P.G., Williams R.J. and Lewis D.R. (1997). Quality simulation along river systems (QUASAR): model theory and development. The Science of the Total Enviornment, 194/195, 447-456.
Williams, V. (1996). Evolutionary neural networks: models and applications. Aston University, Ph.D. dissertation, United Kingdom.
Wright R.M and McDonnel A.J. (1979). In-stream deoxygenation rate prediction. ASCE, Journal of Environment Engineering, 105, 323-335.
Wu, C. F. J.; Hamada, M. (2000). Experiments Planning, Analysis, and Parameter Design Optimization. Wiley-Interscience Press, 153-203.
Yager, R.R.; Filev, D.P.; Sadeghi, T. (1994). Analysis of flexible structured fuzzy logic controllers. IEEE Transactions on Systems, Man and Cybernetics, 24(7), 1035-1043.
Yi, C., Cao, Z. and Kandel, A. (1990). Application of fuzzy reasoning to the control of an activated sludge plant. Fuzzy Sets and Systems, 38, 1-14.
Yu, R. F., Liaw, S. L., Chang, C. N. and Cheng, W. Y. (1998). Applying real-time control to enhance the performance of nitrogen removal in the continuous-flow SBR system. Water Science & Technology, 38(3), 271-280.
Zhang, Y., Swift, D.J.P., Fan, S., Niedoroda, A.W. and Reed, C.W. (1999) Two-dimensional numerical modeling of storm deposition on the northern California shelf. Marine Geology 154, 155-167.
Zhu, J., Zurcher, J., Rao, M. and Meng, M. Q-H. (1998). An on-line wastewater quality predication system based on a time-delay neural network. Eng. Applications of Artificial Intelligence, 11, 747-758.
Zhu, Y., Zheng, J., Mao, L. and Yan, Y. (2000) Three-dimensional nonlinear numerical model with inclined pressure for saltwater intrusion at Yangtze River estuary. Journal of Hydrodynamics, 12(1), 57-66.
Zimmermann, H. J. (1991). Fuzzy Sets Theory-and Its Applications, Second, Revised Edition, 31-32.
Zoppou, C. (2001). Review of urban storm water models. Environmental Modeling & Software, 16, 195-231.
Zug, M., Phan, L., Bellefleur, D. and Scrivener, O. (1999). Pollution wash-off modeling on impervious surfaces: calibration, validation, transposition. Water Science & Technology, 39(2), 17-24.
Zug, M., Girard, R., Phan, L. Rossi, L. and Bellefleur, D. (1998). COD modeling in sewer networks. Water Science & Technology, 38(10), 49-56.
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