Pond Designing Optimization Using Multi-ObjectiveAnt Colony Algorithm and SWAT Model

Subject Areas : environmental management

Abbas  Afshar ¹ (Professor of the Civil Engineering Department, Iran University of Science and Technology, Tehran, Iran)
Mohammad Javad  Emami Skardi ² (MSC Student of Civil Engineering Department, Iran University of Science and Technology, Tehran, Iran)
Farzin  Jeirani ³ (MSC student of Agricultural Department, Tarbiat Modares University, Tehran, Iran)

Received: 2011-11-01 Accepted : 2012-02-09 Published : 2014-12-22

Keywords: : Loading sediment, Multi-objective Ant Colony Alg, SWAT model, watershed, Wet Detention Pond,

Abstract :

Non-point source management has an imperative role in water resource management.  One of the most effective structures in the field of non-point source management is wet detention pond. However, generating the cost-effective pond configurations that satisfy system-wide aims for total target sediment removal will be much more effective and efficient; but most of these structures are designed individually. In order to generate the cost-effective pond configurations, coupling the optimization algorithm with hydrologic simulation model is one of the best applied methods.  Materials and Method In this paper, an optimization-simulation model is presented for generating a cost-effective pond configuration in the watersheds.  Obviously, more and larger ponds can catch more total suspended solids (TSS) from the watershed, but this will consequently lead to the increase of the cost of pond constructing.  Multi-objective ant colony optimization algorithm is applied for determining a Pareto front between two opposing goals namely the loading TSS from the watershed and related cost of the pond designing.  Result and Discussion The Pareto front can be used by the watershed authorities for a better controlling of the loading sediment from the watershed.  The applicability of the model is studied in a watershed in the west of Iran.

References:

1. Schueler, T.R., 1992. A Current Assessment of Urban Best Management Practices.  Metropolitan Washington Council of Governments.


2. Maryland Department of the Environment, 1986. Feasibility and Design of Wet Ponds to Achieve Water Quality Control. Sediment and Storm Water Administration.


3. Tolson, B. A. and C. A. Shoemaker. 2004. “Watershed modeling of the Cannonsville basin using SWAT2000: Model development, calibration and validation for the prediction of flow, sediment and phosphorus transport tothe Cannonsville reservoir”. Technical Report, School of Civil and Environmental Engineering, Cornell Univ., Ithaca, N. Y.


4. Rostamian et al (2008). “Application of a SWAT model for estimating runoff and sediment in two mountainous basins in central Iran”. Hydrological Sciences–Journal–des Sciences Hydrologiques, 53(5) October 2008


5. Shepherd, B., D. Harper and A. Millington. 1999. “Modelling catchment-scale nutrient transport to watercourses in the U.K”. Hydrobiologia 395/396: 227-237.


6. Abbaspour, K. C., Van Genuchten M. Th., Schulin R., and Schlappi E., 1997. “A sequential uncertainty domain inverse procedure for estimating subsurface flow and transport parameters”. Water Resour. Res. 33(8): 1879-1892.


7. Karamouz; Taheriyoun; Baghvand; Tavakolifar and Emami, F., 2010. “Optimization of Watershed Control Strategies for Reservoir Eutrophication Management”. Journal of Irrigation and Drainage Engineering, © ASCE, 136(12): 847–861.


8. صادقی، «شناسایی و اولویت‌بندی مناطق مولد فرسایش در حوضه‌ قره­سو»، دانشگاه آزاد اسلامی واحد علوم تحقیقات، استاد راهنما دکتر بهرام ثقفیان، استاد مشاور دکتر بنفشه زهرایی 1389.
   
   
   1. Simpson A.R., Maier H.R., Foong W.K., Phang K.Y., Seah H.Y. and Tan C.H. 2001. “Selection of Parameters for Ant Colony Optimization Applied to the Optimal Design Of Water Distribution System”, Proc., Int. Congress on Modelling and Simulation, Canberra, Australia, 1931–1936.
   
   

10. Jalali, M. R., Afshar, A., Marino, M., Hon.M.ASCE. A., 2006. "Multi-reservoir Operation by Adaptive Pheromone Re-initiated Ant Colony Optimization Algorithme".  ASCE (WRPM).

11. Jalali M.R. 2005. “Optimal design and operation of hydro systems by ant colony algorithms: new heuristic Approach”, Ph.D. Thesis, Department of Civil Engineering, Iran University of Science and Technology

12. Jalali M.R., Afshar A. and Marino M.A. 2006. “Improved ant colony optimization algorithm for reservoir operation ” , Scientica Iranica, Vol:13(3), PP:295-302

13. Jalali M. R., Afshar A. and Marino M.A.2006. “Reservoir Operation by Ant Colony Optimization Algorithms”, Iranian Journal of Science and Technology, Transaction B, Engineering, Vol:30, No:B1,PP:107-117

14. Jalali M.R., Afshar A. and Marino M.A.2007. “Multi-colony ant algorithm for continuous multi-reservoir operation optimization problems”, Water Resource Management, Vol: 21, PP: 1429–1447

15. Madadgar S. and A. Afshar 2009. “An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems”, Water Resource Management, Vol: 23, PP: 2119–2139.

1. Afshar M.H. and Marino M.A. 2006. “Application of an ant algorithm for layout optimization of tree networks”, Engineering Optimization, Vol: 38(3), PP:353–369

17. Afshar, M. H. 2008. “Layout and size optimization of tree-like pipe networks by incremental solution building ants ”, Source: Canadian Journal of Civil Engineering, VOL: 35(2), PP: 129-139

18. Dorigo, M., 1992. "Optimization, learning and natural algorithms." Ph.D. Thesis, Politecnico di Milano, Milan, Italy.

1. جلالی، محمد رضا، «طراحی و بهره برداری بهینه هیدروسیستم ها با الگوریتم جامعه مورچه ها، یک رهیافت فراکاوشی جدید»، دانشگاه علم و صنعت ایران، به راهنمایی دکتر عباس افشار، 1384.

20. Mariano, C. E., Morales E., 1999. "A Multiple Objective Ant-Q Algorithm for the Design of Water Distribution Irrigation Networks". Technical Report HC-9904, Instituto Mexicano de Tecnologia Del Agua.

21. Iredi S., D., Middendrof M. (2001), "Bi-Criterion Optimization with multi colony ant algorithms”, in: Proceeding of the First international Conference on Evolutionary Multi-Criterion Optimization. " Lecture Notes in Computer Science, Springer, Berlin

22. Baran, B., Schaerer M., 2003. "A Multi-objective Ant Colony System for Vehicle Routing Problem with Time Windows". Twenty first IASTED International Conference on Applied Informatics, Insbruck, Austria, February 10-13, pp. 97-102.

23. Doerner, K., Gutjahr W.J., Hartl R.F., Strauss C., Stummer C., 2004. "Pareto Ant Colony Optimization: A Metaheuristic Approach to Multiobjective Portfolio Selection". Annals of Operations Research, to appear.

24. Dorigo, M., Stutzle, T., 2004. "Ant Colony Optimization. Cambridge." MA: MIT Press.

25. Afshar, A., Sharifi, F., Jalali, M. R., 2008. "Non-dominated ARCHRIVING Multi-coloni and Ant Algorithm for Multi Objective Optimization; Application to Multi propose Reservoir Operation", journal of Engineering Optimization, (under publication).

1. Arnold, J.G., Williams, J.R., Nicks, A.D., and Sammons N.B., 1990. "SWRRB, a basin scale simulation model for soil and water resources management". Texas A&M University Press, College Station, TX.

27. Arnold, J. G., Muttiah, R. S., Srinivasan, R., and Allen, P. M., 2000. "Regional estimation of base flow and groundwater recharge in the upper Mississippi River basin". J. Hydrol, 227(1): 21–40.

28. Center for Watershed Protection, 1998. Cost and Benefits of Storm Water BMPs.

29. Northern Virginia Planning District Commission, Engineers and Surveyors Institute, 1992. Northern Virginia BMP Handbook.

1. عباس افشار و محمد جواد امامی اسکارردی، «طراحی بهینه حوضچه­های بازداشت در حوضه­های آبریز با استفاده از شبیه­ساز سوات و الگوریتم بهینه­ساز جامعه مورچگان: رویکرد تئوری بازی­های همکارانه»، اولین همایش ملی مدیریت منابع آب اراضی ساحلی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، گروه مهندسی آب. 1389.


2. مصطفوی، سید اصغر، «تخصیص بار چند آلاینده در سیستم های رودخانه ای با رویکرد چند هدفه»، دانشگاه علم و صنعت ایران، به راهنمایی دکتر عباس افشار، 1389.