دوره 8، شماره 15 - ( بهار و تابستان 1396 )                   جلد 8 شماره 15 صفحات 45-60 | برگشت به فهرست نسخه ها


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Simulation of Discharge and Nitrate in Tallar Basin using SWAT Model. jwmr. 2017; 8 (15) :45-60
URL: http://jwmr.sanru.ac.ir/article-1-841-fa.html
محمدی مازیار، کاویان عطااله، غلامی لیلا. شبیه‌سازی دبی و نیترات آب در حوزه آبخیز تالار با استفاده از مدل SWAT. پ‍‍ژوهشنامه مديريت حوزه آبخيز. 1396; 8 (15) :45-60

URL: http://jwmr.sanru.ac.ir/article-1-841-fa.html


چکیده:   (2162 مشاهده)
به­منظور کنترل و کاهش آلودگی در آب­های سطحی در مقیاس حوزه­های آبخیز به برنامه­ها و اقدامات زیست-محیطی در جهت کاهش این آلاینده­ها نیاز می­باشد و هم­چنین برای اطمینان از مقرون به صرفه بودن این اقدامات در مرحله اول نیاز است تا مناطق بحرانی تولید کننده رواناب­های آلوده شناسایی شوند. مدل­های هیدرولوژیکی فرآیند مبنا ابزاری مناسب در شبیه­سازی فرآیندهای حوزه آبخیز می­باشند. در این مطالعه برای شبیه­سازی دبی و نیترات در حوزه رودخانه تالار از مدل نیمه­فیزیکی SWAT استفاده شده است. نتایج حاصل از مدل­سازی با استفاده از نرم­افزار SWAT-CUP آنالیز حساسیت واسنجی و صحت سنجی شد و سپس توسط شاخص­های آماری مورد ارزیابی قرار گرفت. برای آنالیز حساسیت دبی و نیترات از 25  و 11 پارامتر استفاده شد که شماره­ی منحنی به­عنوان حساس­ترین پارامتر شناخته شد. ضریب تبیین، واسنجی دبی و نیترات به­ترتیب با مقادیر 68/0 و 75/0 و صحت­سنجی آن­ها نیز به­ترتیب با مقادیر 65/0 و 83/0 محاسبه  شد. ضریب نش ساتکلیف  برای واسنجی دبی و نیترات
به­ترتیب 67/0 و 84/0 و در مرحله صحت­سنجی 62/0 و 63/0 به­دست آمد. در نهایت نیز نقشه دبی و نیترات خروجی از هر زیرحوزه تهیه شد. نتایج حاصل ازاین مطالعه نشان داد که مدل
SWAT قادر به شبیه­سازی کمی و کیفی آب رودخانه تالار
می­باشد، از این­رو می­توان از این مدل به­عنوان ابزاری مناسب در مدیریت و برنامه­ریزی منابع آب در این حوزه آبخیز استفاده کرد.
متن کامل [PDF 1368 kb]   (1174 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: تخصصي
دریافت: 1396/6/27 | ویرایش نهایی: 1396/6/27 | پذیرش: 1396/6/27 | انتشار: 1396/6/27

فهرست منابع
1. Ababaee, B. and T. Sohrabi. 2011. Evaluate the performance of the SWAT model in Zayandehrud Watershed. Journal of Water Conservation Research, 16: 41-58.
2. Abbaspour, K.C. 2011. User Manual for SWAT-CUP4, SWAT Calibration and Uncertainty Analysis Programs. Swiss Federal Institute of Aquatic Science and Technology, Eawag, Duebendorf, Switzerland, from http://www.eawag.ch. 100 pp.
3. Abbaspour, K., E. Rouholahnejad, S. Vaghefi, R. Srinivasan, H. Yang and B. Kløve. 2015. A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model. Journal of Hydrology, 524: 733-752. [DOI:10.1016/j.jhydrol.2015.03.027]
4. Abbaspour, K., J. Yang, I. Maximov, R. Siber, K. Bogner, J. Mieleitner and R. Srinivasan. 2007. "Spatially- Distributed Modelling of Hydrology and Water Quality in the Prealpine/Alpine Thur Watershed Using SWAT. Journal of Hydrology, 333: 413-430. [DOI:10.1016/j.jhydrol.2006.09.014]
5. Ahearn, D., R. Sheibley, R. Dahlgren, M. Anderson, J. Johnson and K. Tate. 2005. Land Use and Land Cover Influence on Water Quality in the Last Free-Flowing River Draining the Western Sierra Nevada, California. Journal of Hydrology, 313: 234-247. [DOI:10.1016/j.jhydrol.2005.02.038]
6. Arabi, M., J. Frakenberger, B. Engel and J. Arnold. 2008. Representation of agricultural management practices with SWAT. Hydrological processes, 22: 3042-3055. [DOI:10.1002/hyp.6890]
7. Arabi, M., R. Govindaraju, M. Hantush and B. Engel. 2006. Role of watershed subdivision on modeling the effectiveness of Best Management Practices with SWAT. Journal of the American Water Resources Association, 42: 513-528. [DOI:10.1111/j.1752-1688.2006.tb03854.x]
8. Arheimer, B., L. Andersson, J. Alkan-Olsson and A. Jonsson. 2007. Using catchment models for establishment of measure plans according to the WFD. Water Science and Technology, 56: 21-28. [DOI:10.2166/wst.2007.432]
9. Arheimer, B., M. Löwgren, B. Pers and J. Rosberg. 2005. Integrated catchment modelling for nutrient reduction: scenarios showing impacts, potential and cost of measures. Ambio, 34: 513-520. [DOI:10.1579/0044-7447-34.7.513]
10. Arnold, J. and P. Allen.1996. Estimating hydrologic budgets for three Illinois watersheds. Journal of Hydrology, 34: 57-77. [DOI:10.1016/0022-1694(95)02782-3]
11. Arnold, J., J. Kiniry, R. Rinivasan, J. wiliams, E. Haney and S. Neitsch. 2012. Soil and water assessment tool theoretical documentation version 2012. College Station: Texas Water Resources Institute.
12. Arnold, J., R. Srinivasan, R. Muttiah and J. Williams. 1998. Large area hydrologic modeling and assessment part I: Model development1. Journal of the American Water Resources Association, 34: 73-89. [DOI:10.1111/j.1752-1688.1998.tb05961.x]
13. Bagnold, R. 1977. Bedload transport in natural rivers. Water resourse research, 13: 303-312. [DOI:10.1029/WR013i002p00303]
14. Barlund, I., T. Kirkkala, O. Malve and J. Kamari. 2007. Assessing SWAT model performance in the evaluation of management actions for the implementation of the Water Framework Directive in a Finnish catchment. Environmental Modelling and Software, 22: 719-724. [DOI:10.1016/j.envsoft.2005.12.030]
15. Behera, S. and R. Panda. 2006. Evaluation of Management Alternatives for an Agricultural Watershed in a Sub-Humid Subtropical Region Using a Physical Process Based Model. Agriculture Ecosystems & Environment, 113: 62-72. [DOI:10.1016/j.agee.2005.08.032]
16. Boluwade, A. and C. Madramootoo. 2013. Modeling the Impacts of Spatial Heterogeneity in the Castor Watershed on Runoff, Sediment, and Phosphorus Loss Using SWAT: I. Impacts of Spatial Variability of Soil Properties. Water Air Soil Pollution, 224, 1692. [DOI:10.1007/s11270-013-1692-0]
17. Brown, L. and T. Brown. 1987. The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Manual, Report EPA/600/3/87/007, US Environmental Protection Agency, Athens, GA.
18. Cao, W., W. Bowden, T. Davie and A.Fenemor. 2006. Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability Hydrological Processes Journal, 20: 1057-1073. [DOI:10.1002/hyp.5933]
19. Castillo, R., I. Güneralp and B. Güneralp. 2014. Influence of changes in developed land and precipitation on hydrology. Applied Geography, 47: 154-167. [DOI:10.1016/j.apgeog.2013.12.009]
20. Chaplot, V., A. Saleh and D. Jaynes. 2005. Effect of the accuracy of spatial rainfall information on the modelling of water, sediment, and NO3-N loads at the watershed level. Journal of Hydrology, 312: 223-234. [DOI:10.1016/j.jhydrol.2005.02.019]
21. Chow, V., D. Maidment and L. Mays. 1988. Applied Hydrology. McGraw-Hill, New York. 572 pp.
22. Cibin, R., K.P. Sudheer and I. Chaubey. 2010. Sensitivity and identifiability of stream flow generation parameters of the SWAT model. Hydrological Processes, 24: 1133-1148. [DOI:10.1002/hyp.7568]
23. Das, S., R. Ruda, B.Gharabaghi, P. Goel, A. Singh and I. Ahmed. 2007. Comparing the Performance of SWAT and AnnAGNPS Model in a Watershed in Ontario. ASABE publishing paper: 701P0207. ASABE, St. Joseph, MI, USA.
24. Davison, P., P. Withers, E. Lord, M. Betson and J. Stromqvist. 2008. PSYCHIC-a processbased model of phosphorus and sediment mobilisation and delivery within agricultural catchments. Part 1: model description and parameterisation. Journal of Hydrology, 350: 290-302. [DOI:10.1016/j.jhydrol.2007.10.036]
25. Demissie, A., F. Saathoff, Y. Seleshi and A. Gebissa. 2013. Evaluating the Effectiveness of Best Management Practices in Gilgel Gibe Basin Watershed-Ethiopia. Journal of Civil Engineering and Architecture, 7: 1240-1252. [DOI:10.17265/1934-7359/2013.10.007]
26. Dillaha, T. and B. Beasley. 1983. Distributed Parameter Modeling of Sediment Movement and Particle Size Distributions. American Society of Agricultural Engineers, 26: 1766-1772. [DOI:10.13031/2013.33840]
27. Gassman, P., M. Reyes, C. Green and J. Arnold. 2007. The soil and water assessment tool: historical development, applications and future research directions. Transactions of the ASABE, 50: 1211-1250. [DOI:10.13031/2013.23637]
28. Hargreaves, G. and Z. Samani. 1985. Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1: 96-99. [DOI:10.13031/2013.26773]
29. Hesse, C., K. Krysanova, J. Päzolt and F. Hattermann. 2008. Eco-hydrological modeling in a highly regulated lowland catchment to find measures for improving water quality. Ecological Modelling, 218: 135-148. [DOI:10.1016/j.ecolmodel.2008.06.035]
30. Hosseini, M., M. Tabatabai, M. Goudarzi and S. Hejazi. 2013. Assessment of current components using SWAT model for estimating runoff future periods affected by climate change. Journal of Climatology, 1: 48-53.
31. Kavian, A., M. Golshan, H. Rouhani and A. Esmaeeli uri.2015. Mazandaran Haraz river basin runoff and sediment load simulation using the model SWAT. Physical Geography Research, 47: 197-211.
32. Lam, Q., B. Schmalz and N. Fohrer. 2011. The impact of agricultural Best Management Practices on water quality in a North German lowland catchment. Environ Monit Assess, 183: 351-379. [DOI:10.1007/s10661-011-1926-9]
33. Mohammad, A. and M. Adam.2010. The Impact of Vegetative Cover Type on Runoff and Soil Erosion Under Different Land Uses. Catena, 81: 97-103. [DOI:10.1016/j.catena.2010.01.008]
34. Molina-Navarro, E., D. Trolle, S. Martínez-Pérez, A. Sastre-Merln and E. Jeppesen. 2014. Hydrological and water quality impact assessment of a Mediterranean limno-reservoir under climate change and land use management scenarios. Journal of Hydrology, 2014: 354-366. [DOI:10.1016/j.jhydrol.2013.11.053]
35. Monteith, J. 1965. Evaporation and environment. In: Fogg, G.F. (Ed.), The State and Movement of Water in Living Organisms. Cambridge University Press, Cambridge, pp: 205-234.
36. Moriasi, D., G. Arnold, M. Van Liew, R. Bingner, R. Harmel and T. Veith. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50: 885-900. [DOI:10.13031/2013.23153]
37. Nash, J. and J. Sutcliffe. 1970. River flow forecasting through conceptual models: Part 1. A discussion of principles. Journal of Hydrology, 10: 282-290. [DOI:10.1016/0022-1694(70)90255-6]
38. Nossent, J. 2012. Sensitivity and uncertainty analysis in view of the parameter estimation of a SWAT model of the river Kleine nete, Belgium. PhD thesis. Vrije Universiteit Brussel, 462 pp.
39. Oki, T. and S. Kanae. 2006. Global hydrological cycles and world water resources. Science, 1068-1072, 313. [DOI:10.1126/science.1128845]
40. Pongpetch, N., P. Chandraseka, C. Yossapol, S. Dasananda and T. Kongjun. 2015. Genotoxicity Assessmen the critical Areas And Nonpoint Source Pollution Reduction Best Management Practices in Lam Takong River Basin, Thailand. Environment Asia, 8: 41-52.
41. Priestley, C. and R. Taylor. 1972. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Rev, 100: 81-92. https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2 [DOI:10.1175/1520-0493(1972)1002.3.CO;2]
42. Rode, M., G. Arhonditsis, D. Balin, T. Kebede, V. Krysanova, A. Van Griensven and A. Van Der Zee. 2010. New challenges in integrated water quality modelling. Hydrol. Process, 24: 3447-3461. [DOI:10.1002/hyp.7766]
43. Sahu, M. and R. Gu. 2009. Modelling the effects of riparian buffer zone and contour strips on stream water quality. Ecological Engineering, 35: 1167-1177. [DOI:10.1016/j.ecoleng.2009.03.015]
44. Shao, Y., R. Lunetta, A. Macpherson, J. Luo and G. Chen. 2013. Assessing Sediment Yield for Selected Watersheds in the Laurentian Great Lakes Basin Under Future Agricultural Scenarios. Environmental Management, 51: 59-69. [DOI:10.1007/s00267-012-9903-9]
45. Shrestha, S. and F. Kazama. 2007. Assessment of Surface Water Quality Using Multivariate Statistical Techniques: A Case Study of the Fuji River Basin, Japan. Environmental Modelling & Software, 22: 464-475. [DOI:10.1016/j.envsoft.2006.02.001]
46. Stehler, A., P. Debels and H. Alcayaga. 2008. Hydrological modelling with SWAT under conditions of limited data availability: evaluation of results from a Chilean case study. Hydrological Sciences Journal, 55: 588-601. [DOI:10.1623/hysj.53.3.588]
47. Tesfahunegn, G., P. Vlek and L. Tamene. 2013. Application of SWAT model to assess erosion hotspot for sub-catchment management at Mai-Negus catchment in northern Ethiopia. East African Journal of Science and Technology, 2: 97-123.
48. Van Griensven, A., T. Meixner, S. Grunwald, T. Bishop, A. Diluzio and R. Srinivasan. 2006. A global sensitivity analysis tool for the parameters of multi-variable catchment models. Journal of Hydrology, 324: 10-23. [DOI:10.1016/j.jhydrol.2005.09.008]
49. Vörösmarty, C., P. McIntyre, M. Gessner, D. Dudgeon, A. Prusevich and P. Green. 2013. Global threats to human water security and river biodiversity. Nature, 467: 555-561. [DOI:10.1038/nature09440]
50. Wang, S., S. Kang, L. Zhang and F. Li. 2008. Modeling hydrological response to different land use and climate change scenarios in the Zamu River basin of northwest China. Hydrological Processes, 22: 2502-2510. [DOI:10.1002/hyp.6846]
51. Wang, X. and A. Melesse. 2006. Effects of STATSGO and SSURGO as inputs on SWAT model's snowmelt simulation. Journal of the American Water Resources Association, 42: 1217-1236. [DOI:10.1111/j.1752-1688.2006.tb05608.x]
52. Williams , J. and H. Berndt. 1977. Sediment yield prediction based on watershed hydrology. American Society of Agricultural Engineers, 20: 1100-1104. [DOI:10.13031/2013.35710]
53. Williams, R. 1980. SPNM, a model for predicting sediment phosphorous, and nitrogen from agricultural basins. Water Resources Bulletin, 16: 843-848. [DOI:10.1111/j.1752-1688.1980.tb02497.x]
54. Yang, Y. and L. Wang. 2010. review of modelling tools for implementation of the EU water framework directive in handling diffuse water pollution. Water Resources Management, 24: 1819-1843. [DOI:10.1007/s11269-009-9526-y]
55. Yuan, Y., R. Bingner and R. Rebich. 2003. Evaluation of AnnAGNPS nitrogen loading an agricultural watershed. Journal of the American Water Resources Association, 39: 457-466. [DOI:10.1111/j.1752-1688.2003.tb04398.x]
56. Zahabioun, B., M. Goudarzi and A. Masah Yavani. 2010. Application of SWAT model for estimating runoff in future periods affected by climate change. Journal of Climatology, 3-4, 43-58.
57. Zahedi, E., A. Talebi, S.A. Tabatabaei, A. Raeisi and M. Asiayi. 2016. Subsurface flow simulations to determine potential areas of groundwater dam using SWAT model (Case Study: Doroongar Watershed, Dargaz). Journal of Watershed Management Research, 7: 206-215. [DOI:10.29252/jwmr.7.14.215]
58. Zarif Moazam, M.S., S.H.R. Sadeghi and S.Kh. Mirnia. 2016. Variability of interactions between some soil properties and runoff generation time (Case study: Kojoor watershed). Journal of Watershed Management Research, 7: 1-11. [DOI:10.18869/acadpub.jwmr.7.13.11]
59. Zhai, X., Y. Zhang, X. Wang, J. Xia and T. Liang. 2012. Non-point source pollution modelling using Soil and Water Assessment Tool and its parameter sensitivity analysis in Xin'anjiang catchment, China. HYDROLOGICAL PROCESSES, 28: 1627-1640. [DOI:10.1002/hyp.9688]
60. Zhang, P., Y. Liu, Y. Pan and Z. Yu. 2013. Land use pattern optimization based on CLUE-S and SWAT model for agricultural non-point source pollution control. Mathematical and Computer Modelling, 588-595. [DOI:10.1016/j.mcm.2011.10.061]

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