Optimal Prioritization of Best Management Practices Through a Simulation-Optimization Model to Sediment Load Reduction

Document Type : Original Research

Authors
1 Department of Watershed ManagementFaculty of Natural ResourcesTarbiat Modarres UniversityP.O.Box 46417-76489, Noor, Mazandaran ProvinceIranAlternative E-mail:vafakhah2000@gmail.comWebsite: http://www.modares.ac.ir/~vafakhahTel: +98 11 44998102 and Fax: +98 11 44553499Mobile: +98 9123179699
2 Department of Watershed Management Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Iran
Abstract
Aims Watershed management practices are as appropriate solutions to control nonpoint sources of pollution at watershed scale. Nevertheless, the best way to allocate limited resources is a challenge for watershed management efforts. Therefore, to achieve the most suitable strategies, manager requires the use of mathematical techniques to assign management practices priority. In this regards, in the present study, an optimization-based Decision Support Tool (DST) was used to assign the optimal combinations of management practices at the Taleghan Dam Watershed, Alborz Province, Iran.

Materials & Methods To achieve the present research goals, Soil and Water Assessment Tool (SWAT) was applied to determine the sediment yield at outlet of the watershed under different combinations of management measures and was coupled with a genetic algorithm in MATLAB computer software, which provides as the optimization engine.

Findings The results of optimization in the Taleghan Dam Watershed showed that implementation costs for 10% and 20% sediment reduction in optimal solution were obtained 110300$ and 235500$, respectively. The cost-effectiveness ratio of scenarios 10% and 20% sediment reduction obtained about 11030 and 11770.5 (dollars for 1% sediment reduction), respectively. The results also showed that filter strip and seeding are the most cost effective option for sediment load control. Conversely, the grade stabilization structure and detention pond are the least cost-effective option.

Conclusion This tool is transferable to other watersheds and therefore, is one of the effective approaches of watershed management.
Keywords

Subjects


1. Arabkhedri M. A Review on Major Water Erosion Factors in Iran. Land Manag.2014; 2(1): 17- 26 (In Persian)
2. Noor H, Vafakhah M, Mohammady M. Comparison of different targeting methods for watershed management practices implementation in Taleghan dam watershed, Iran. Water SciTechnol: Water Supply.2016;16(6):1484-1496
3. Merriman K, Daggupati P, Srinivasan R, Toussant C, Russell A, Hayhurst B. Assessing the Impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek Watershed, Ohio. Water.2018;10(10),1299.
4. Briak H, Mrabet R, Moussadek R, Aboumaria K. Use of a calibrated SWAT model to evaluate the effects of agricultural BMPs on sediments of the Kalaya river basin (North of Morocco). Inter Soil Water Conserve Res. 2019; 7(2),176-83
5. Muleta MK, Nicklow JW. Evolutionary algorithms for multiobjective evaluation of watershed management decisions. J Hydroinform. 2002; 4.2: 83-97
6. Panagopoulos Y, Makropoulos C, Mimikou M. Decision support for diffuse pollution management. Environ Model Soft. 2012;30: 57-70
7. Qin CZ, Gao HR, Zhu LJ, Zhu AX, Liu JZ, Wu H. Spatial optimization of watershed best management practices based on slope position units. J Soil Water Conserv. 2018;73(5), 504-517
8. Artita KS, Kaini P, Nicklow JW. Examining the possibilities: generating alternative watershed-scale bmp designs with evolutionary algorithms. Water Resour Manage.2013;27:3849–3863
9. Nicklow JW, Muleta MK. Watershed management technique to control sediment yield in agriculturallydominated areas. Water Int.2001; 26(3): 435–443
10. Kaini P, Artita K, Nicklow JW. Optimizing structural best management practices using swat and genetic algorithm to improve water quality goals. Water Resour Manage.2012;26:1827–1845
11. Zhu LJ, Qin CZ, Zhu A, Liu J, Wu H. Effects of different spatial configuration units for the spatial optimization of watershed best management practice scenarios. Water.2019;11(2), 262
12. Arnold JG, Srinivasan R, Muttiah RS, Williams JR.Large-area hydrologic modeling and assessment: Part I model development. J Am Water Resour As.1998;34 (1): 73–89
13. Meghdadi AR. Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study. Environ Monit Assess.2013; 185:9803–9817
14. Christopher SF, Tank JL, Mahl UH, Yen H, Arnold JG, Trentman MT, Sowa SP, Herbert ME, Ross JA, White MJ, Royer TV. Modeling nutrient removal using watershed-scale implementation of the two-stage ditch. Ecol Eng.2017;108, 358-69
15. Karamouz M, Taheriyoun M, Baghvand A, Tavakolifar H, EmamiF.Optimization of watershed control strategies for dam eutrophication management. J Irrig Drain Eng.2010; 136 (12): 847-861
16. Maringanti C, Chaubey I, Arabi M, Engel B.Application of a multi-objective optimization method to provide least cost alternatives for NPS pollution control. Environ Manage.2011;48: 448-461
17. Srivastava P, Hamlett JM, Robillard PD, Day RL.Watershed optimization of best management practices using AnnAGNPS and a genetic algorithm. Water Resour Res.2002;38(3),3-1.
18. EmamiSkardi MJ, Afshar A, Solis SS. Simulation-optimization model for non-point source pollution management in watersheds: Application of cooperative game theory. KSCE J Civil Eng.2013;17(6),1232-40
19. Arabi M, Govindaraju RS, Hantush, MM. Cost-effective allocation of watershed management practices using a genetic algorithm. Water Resour Res.2006;DOI: 10.1029/2006WR004931
20. Chiang L, Chaubey I, Maringanti Ch, Huang T. Comparing the selection and placement of best management practices in improving water quality using a multiobjective optimization and targeting method. Int J Environ Res Public Health.2014;11, 2992-3014
21. Naseri F, Azari M, Dastorani M.T. Spatial optimization of soil and water conservation practices using coupled SWAT model and evolutionary algorithm. Int Soil Water Conserv Res. 2021;‏ In Press
22. Tuppad P, Kannan N, Srinivasan R, Rossi CG, Arnold JG.Simulation of agricultural management alternatives for watershed protection. Water Resour Manage.2010;24:3115–3144
23. Geng R, Yin P, Sharpley AN. A coupled model system to optimize the best management practices for nonpoint source pollution control. J Clean Prod.2019;220, 581-92
24. Volk M, Liersch S, Schmidt G. Towards the implementation of the European Water Framework Directive? Lessons learned from water quality simulations in an agricultural watershed. Land Use Pol. 2009;26 (3), 580–588
25. Noor H, Fazli S, Rostami M, Kalat AB. Cost-effectiveness analysis of different watershed management scenarios developed by simulation–optimization model. Water Sci Technol: Water Supply.2017;17(5):1316-1324.‏
26. Neitsch SL, Arnold JG, Kiniry JR, Williams JR.Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute, College Station, TWRI Report TR-406, Texas, 2011.
27. Noor H, Vafakhah M, Taheriyoun M, Moghaddasi M.Comparison of single-site and multi-site based calibrations of SWAT in Taleghan Watershed, Iran. Int J Eng.2014; 27(11):1645-1652
28. Abbaspour KC.SWAT-CUP user manual, Federal Institute of Aquatic Science and Technology (Eawag), Switzerland, 2011;105 pp
29. Hosseini SH, Khaleghi MR. Application of SWAT model and SWAT-CUP software in simulation and analysis of sediment uncertainty in arid and semi-arid watersheds (case study: the Zoshk–Abardeh watershed). Model Earth Syst Environ. 2020; 6(4):2003-2013
30. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, VeithTL.Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE.2007;50(3): 885–900
31. Hosseini M, Ghafouri AM, M. Amin MS, Tabatabaei MR, Goodarzi M, AbdeKolahchi A. Effects of land use changes on water balance in Taleghan Catchment, Iran. J Agri Sci Technol.2012;14:1161-1174
32. Vafakhah M, Nouri A, AlavipanahSK.Snowmelt-runoff estimation using radiation SRM model in Taleghan Dam Watershed. Environ Earth Sci.2014;73:993-1003
33. VAUT. General study of Taleghan Watershed: Soil Science Report, Faculty of Agriculture, University of Tehran; 1993.
34. Akhavan S, Abedi-Koupai J, Mousavi SF, Afyuni M, Eslamian SS, Abbaspour KC. Application of SWAT model to investigate nitrate leaching in Hamadan–Bahar Watershed, Iran. AgricEcosyst Environ.2010;139 (4): 675–688
35. Norouzi Nazar M, Asgari E, Baaghideh M, Lotfi S. Quantifying the Long-Term Flood Regulation Ecosystem Service under Climate Change Using SWAT Model. ECOPERSIA. 2020; 8(3):169-180
36. Raeisi A, Talebi A, Abdollahi K, Torabi Haghighi A. Effective Factors on Runoff Generation and Hydrologic Sensitivity in a Mountainous Watersheds (A Case Study: Farsan Watershed, Upstream of Karoun River). ECOPERSIA. 2020; 8(1):15-21
37. Mahzari S, Kiani F, Azimi M, Khormali F. Using SWAT model to determine runoff, sediment yield and nitrate loss in Gorganrood watershed, Iran. ECOPERSIA.2016;4(2),1359-1377
38. Strauss P, Leone A, Ripa M, Turpin N, Lescot JM, Laplana R. Using critical source areas for targeting cost‐effective best management practices to mitigate phosphorus and sediment transfer at the watershed scale. Soil Use Man.2007; 23:144-153