Decision Support Tool for Determination of WMPs Optimal Pattern (Case Study: Taleghan Reservoir Dam Watershed)

Document Type : Research

Authors

1 Soil Conservation and Watershed Management Department, AREEo, Mashhad, Iran

2 Department of Watershed Management Engineering, College of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran

3 Department of Water Engineering, College of Agriculture, Arak University, Arak, Iran

Abstract

Watershed management practices (WMPs) include methods to create, enhance, and maintain vegetation to reduce surface runoff in the watershed. The implementation of  WMPs at the watershed scale is an ongoing challenge that needs to take into account trade-offs between hydrological and economic objectives using optimization algorithm. This research demonstrate a methodology and decision support tool that suggests the optimal location of biological watershed management practices (including improvement rangeland cover) which minimize the cost and simultaneously reduce surface runoff to target levels cases (i.e. 10%, 15%, 20% and, 25%) at watershed scale. The decision support tool (SWAT-GA) consists of a semi-distributed hydrologic model, Soil and Water Assessment Tool (SWAT) which simulation of runoff in watershed, a genetic algorithm (GA), which serves as the optimization engine for the location of biological watershed management practices across the rangeland of the watershed. The proposed method was then applied to Taleghan watershed with an approximate area of 900 km2 that located in Alborz Mountain, Iran. Results indicate watershed management practices should use in 22%, 35%, 48% and 62% of total area of watershed to reduction 10%, 15%, 20% and 25%, respectively. The maximum decrease and increase runoff after the implementation of WMPs have been occurring in the spring and summer, respectively. Using this decision support tool, for each level of target goals, decision makers can select the optimal combination of watershed management practices.

Keywords

References

  1. Abbaspour K.C., 2011. User manual for swat-cup: swat calibration and uncertainty analysis programs. Swiss federal institute of aquatic science and technology, Eawag, Dübendorf, Switzerland, 95 p. Available at: http://www.eawag.ch/organisation/abteilungen /siam/software/swat/index_EN.

    Arabi M., Frankenberger J.R., Engel B.A. and Arnold J., 2007. Representation of agricultural conservation practices with SWAT, Hydrological Processes, 22(16):3042–3055.

    Arnold J.G., Srinivasan R., Muttiah R.S. and Williams J.R., 1998. Large-area hydrologic modeling and assessment: Part I. model development, Journal of the American Water Resources Association, 34 (1): 73–89.

    Artita K.S., Kaini P. and Nicklow J.W., 2013. Examining the possibilities: generating alternative watershed-scale bmp designs with evolutionary algorithms, Water Resources Management, 27:3849–3863.

    Giri, S., Nejadhashemi, A.P., Woznicki, S.A. and Zhang, Zh. 2014. Analysis of best management practice effectiveness and spatiotemporal variability based on different targeting strategies. Hydrological Processes. 28, 431–445.

    Kaini P., Artita K. and Nicklow J.W., 2012. Optimizing structural best management practices using swat and genetic algorithm to improve water quality goals, Water Resources Management, 26:1827–1845.

    Karamouz M., Taheriyoun M., Baghvand A., Tavakolifar H. and Emami, F., 2010. Optimization of watershed control strategies for reservoir eutrophication management, Journal of Irrigation and Drainage, 136 (12): 847-861.

    Maringanti C., Chaubey I. and Popp, J., 2009. Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control, Water Resources Research, 45: 1-15.

    Moriasi D.N., Arnold J.G., Van Liew M.W., Bingner R.L., Harmel R.D. and Veith T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, Transactions of the Asabe, 50(3):885–900.

    Neitsch S.L., Arnold J.G., Kiniry J.R., King K.W. and Williams J.R., 2009. Soil and water assessment tool (SWAT) theoretical documentation, Blackland Research Center, Texas Agricultural Experiment Station, Temple, Texas (BRC Report 02-05).

    Nicklow J.W. and Muleta M.K., 2001. Watershed management technique to control sediment yield in agriculturally dominated areas, Water International, 26(3): 435–443.

    Panagopoulos Y., Makropoulos C. and Mimikou M., 2012. Decision support for diffuse pollution management, Environmental Modelling and Software, 30: 57-70.

    Panagopoulos, Y., Makropoulos, C. and Mimikou, M. 2012. Decision support for diffuse pollution management. Environmental Modelling and Software, 30: 57-70.

    Sadoddin A., Sheikh V., Mostafazadeh R. and Halili M.Gh., 2010. Analysis of vegetation-based management scenarios using MCDM in the Ramian watershed, Golestan, Iran, International Journal of Plant Production, 4 (1): 51-62.

    Skardi, M.J., Afshar, A., Saadatpour, M. and Solis. S.S. 2014. Hybrid ACO-ANN-based multi-objective simulation-optimization model for pollutant load control at basin scale. Environmental Modeling and Assessment. DOI: 10.1007/s10666-014-9413-7 .

    Srivastava, P., Hamlett, J.M., Robillard, P.D. and Day, R.L. 2002. Watershed optimization of best management practices using AnnAGNPS and a genetic algorithm. Water Resources Research, 38(3):1-14.

    Strauss, P., Leone, A., Ripa, M.N., Turpin, N., Lescot, J.M. and Laplana, R. 2007. Using critical source areas for targeting cost-effective best management practices to mitigate phosphorus and sediment transfer at the watershed scale. Soil Use and Management, 23: (1), 144–153.

    Vafakhah M. and Mohseni Saravi, M., 2011. Optimizing management of soil erosion in orazan sub-basin, Iran, Journal of Agricultural Science and Technology (JAST), 13: 717-726.

    1. Yazdi J., Salehi Neyshabouri S.A.A., Niksokhan M.H., Sheshangosht S. and Elmi M., 2013. Optimal prioritisation of watershed management measures for flood risk mitigation on a watershed scale, Flood Risk Management, 10.1111/jfr3.12016.

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History

  • Receive Date: 03 February 2018
  • Accept Date: 03 February 2018

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