بررسی کارایی مدل SWAT در تحلیل مکانی رواناب در حوزه‌های آبخیز فاقد داده‌های محلی خاک (مطالعه موردی : حوزه آبخیز دامغانرود)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده کویرشناسی، دانشگاه سمنان

2 هیات علمی دانشکده کویر شناسی دانشگاه سمنان

3 دانشکده کویر شناسی دانشگاه سمنان

4 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز

چکیده

رواناب در اقلیم‎ نیمه‎خشک سبب ایجاد سیلاب‎های خطرناکی می­شود. بنابراین تجزیه و تحلیل مکانی رواناب برای مدیریت بحران ضروری به نظر می‎رسد. مدل­های هیدرولوژیکی­ ابزارهایی بوده که به منظور شبیه‎سازی فرآیندهای مرتبط با چرخه آب و پیش­بینی رخدادهای آینده استفاده می‎شوند. در این بین، SWAT یکی از رایج­ترین این مدل­ها است که از مهمترین ورودی‎ها آن نقشه و اطلاعات خاک حوزه آبخیز می‎باشد. از طرف دیگر نقشه­های خاک هم از لحاظ کیفی و کمی در بسیاری از حوزه­های آبخیز در دسترس نیستند. هدف اصلی از این پژوهش تحلیل مکانی رواناب با استفاده از داده جهانی خاک بوسیله مدل هیدرولوژیکی SWAT در حوزه آبخیز دامغانرود در استان سمنان است. بدین منظور داده‎های اقلیمی در دوره زمانی سال‏های 2008 تا 2018 میلادی برای شبیه‎سازی رواناب استفاده شد. در این دوره زمانی داده­های سال‏های 2010 تا 2014 برای واسنجی و سال‎های 2015 تا 2018 برای اعتبارسنجی مدل استفاده شد. تحلیل حساسیت، واسنجی، اعتبارسنجی و عدم قطعیت مدل در نرم افزار  SWAT-CUPبا استفاده از الگوریتم SUFI-2  انجام شد. ارزیابی مدل با استفاده از آماره‎های ضرایب تبیین (R2) و ناش ساتکلیف (NS) انجام شد. پارامترهای شماره منحنی، متوسط طول شیب، ضریب زبری کانال مانینگ، هدایت هیدرولیکی اشباع خاک به عنوان پارامترهای حساس تعیین شدند. مقادیر آماره­های R2 و NS برای مرحله واسنجی مدل به ترتیب، 48/0، 47/0 و برای مرحله اعتبارسنجی به ترتیب 46/0، 45/0 بدست آمد. نتایج نشان داد عملکرد مدل در شبیه‎سازی رواناب با داده جهانی خاک قابل قبول بوده است. تحلیل مکانی رواناب با استفاده از روش میانگین وزنی رواناب به ازای واحد سطح انجام گرفت. نتایج تحلیل مکانی رواناب براساس میانگین وزنی رواناب نشان داد که مهم‏ترین زیرحوضه در تولید رواناب زیرحوضه شماره 5 (دارای کمترین فاصله به نقطه خروجی) و کم ‌اهمیت‎ترین آنها زیرحوضه­های 1 و 11 (دارای بیشترین فاصله از نقطه خروجی) بودند. بنابراین نتایج نشان داد که پارامترهای موثر در اولویت‎بندی رواناب شامل موقعیت مکانی زیرحوضه‎ها و کاربری اراضی بودند. نتایج کلی تحقیق نشان داد که مدل SWAT درتحلیل مکانی رواناب حوزه آبخیز به دلیل تقسیم‎بندی حوضه به واحدهای همگن امکان شناسایی مناطق بحرانی تولید رواناب را دارد.

کلیدواژه‌ها


عنوان مقاله [English]

Investigation of SWAT Model Efficiency in Spatial Analysis of Runoff in Watersheds without Local Soil Data (Case Study: Damghanrood Watershed)

نویسندگان [English]

  • Mahin Khosravi 1
  • aliasghar ةolfaghari 2
  • Seyed Hasan Kaboli 3
  • Heidar Ghafari 4
1 Faculty of Desert Studies, Semnan University
2 Faculty of Desert Studies; Semnan University
3 Faculty of Desert Studies; Semnan University
4 Soil science Department, Faculty of Agriculture, Shahid Chamran University of Ahvaz
چکیده [English]

In semi-arid area the dangerous floods are usually generation by runoff. Therefore, spatial analysis of runoff is necessary for crisis management. Hydrological models are useful tools for simulation of water cycle-related processes and predict future events. Among the hydrological models, SWAT is one of the most popular of these models which the soil map and information are one the most important input data in SWAT model. On the other hand, the qualitative and quantitative soil maps are not available in most of the watershed in Iran. The main purpose of this study was to determine the spatial analysis of runoff generation using global soil data and using SWAT model in Damghanrood watershed in Semnan province. For this purpose, climatic data from 2008 to 2018 were used to simulate runoff. The data from 2010 to 2014 was used for model calibration and data from 2015 to 2018 was used for model validation. Sensitivity analysis, calibration, validation and model uncertainty were performed in SWAT-CUP software using SUFI-2 algorithm. The model was evaluated with coefficients of determination (R2) and Nash Sutcliffe (NS) statistics. The parameters of curve number, mean slope length, manning channel roughness coefficient and saturated soil hydraulic conductivity were determined as more sensitive parameters. The values of the R2 and NS statistics were 0.48, 0.47 for the model calibration stage and 0.46 and 0.45 for the validation stage, respectively. The results showed that the performance of the model in runoff simulation with global soil data was acceptable. Spatial analysis of runoff was performed using the average weight of runoff per unit area. The results of spatial analysis of runoff showed that the most important sub-basins in runoff generation was sub-basin number 5 and the least important sub-basins were number 1 and 11. Results indicated that sub-basin location and land use were most effective variables in runoff prioritization. SWAT model divide the watershed into the homogeneous units, therefore, it is possible to determine the critical areas of runoff generation.

کلیدواژه‌ها [English]

  • Prioritization of sub-basins
  • Sensitivity analysis
  • Runoff
  1. Ababaei B., and Sohrabi T. 2009. Evaluation of SWAT model performance in Zayandehrud watershed, Journal of Soil and Water Conservation Research, 16(3): 48-58. (In Persian)

    Abbaspour K. C., Johnson C. A., and Van Genuchten M. Th. (2004). Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone, 3: 1340-1352.

    Abbaspour K. C. 2007. User manual for SWAT-CUP, SWAT calibration and uncertainty analysis programs. Eawag: Swiss Fed. Inst. Of Aquat. Sci. and Technol. Du¨bendorf, Switzerland.

    Abbaspour K. C. 2011. Swat-Cup2: SWAT Calibration and Uncertainty Programs Manual Version 2, Department of Systems Analysis, Integrated Assessment and Modeling (SIAM), Eawag. Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland.

    Abbaspour K.C., Rouholahnejad E., Vaghefi S., Srinivasan R., Yang H., and Klove B. 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.

    Agha-alizadeh F., Abbasi A., and Esmali A. 2020. Determining the effect of soil properties on runoff and sediment at suborder level using principal components analysis (Case study: Ardabil Plain). Applied Soil Research, 8(2): 129.141. (In Persian)

    Ahmadi T., Delberi M., and Afrasiab P. 2015. Zoning of hydraulic conductivity of saturated soil surface layer with loam and sandy loam texture of Sistan plain, Journal of Soil Research (Soil and Water Sciences), 31(4): 513-526. (In Persian)

    Akhavan S., Abedi Kupai J., Mousavi S. F., Abbaspour K., and Opium m. S. S. Islamian. 2010. Estimation of irrigation and runoff water using swat model in Hamedan spring basin. Journal of Agricultural Science and Technology and Natural Resources, Soil and Water Sciences, 14 (3): 9-23. (In Persian)

    Ansari M, R., Georgi m., Sayad Gh. A., Shorfa m., and Hamadi K. 2014. Simulation of runoff in the Yellow River watershed using the Arc Swat model. Irrigation Science and Engineering, 38 (4):97-107. (In Persian)

    Arnold J. G., Moriasi D. N., Gassman P. W., Abbaspour K. C., White M., Srinivasan J., Santhi

    1. C., Harmel R. D., van Griensven A., Van Liew M., Kannan W. N., and Jha M. K. 2012. SWAT: model use, calibration and validation. American Society of Agricultural and Biological Engineers. 55(4): 1491-1508.

    Asgari H., M. Jafari M. Alavi Panah S, K. Farhadi S., and Razmi M. 2014. Spatial variation analysis of some soil properties using geostatistics and remote sensing. Journal of Environmental Erosion Research. 4(2): 53-71. (In Persian)

    Asgharpour M.J. 2007. Multi-Criteria Decision Making. University of Tehran Press. Pages 22-20 and 89-76. (In Persian)

    Bhandari R., Thakali R., Kandissounon G.A.A.D., Kalra A., and Ahmad S. 2018. Effects of Soil Data Resolution on the Simulated Stream Flow and Water Quality: Application of Watershed-Based SWAT Model. In World Environmental and Water Resources Congress 2018: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management (pp. 376-386). Reston, VA: American Society of Civil Engineers.

    Farrokhzadeh B., Ildermi A., R. Ataeian B., and Nowruz M. 2015. Estimation of suspended load

    estimation under the influence of land use change using SWAT model (Case study: Yelfan watershed). Journal of Environmental Erosion Research. 5(3): 28-46.  (In Persian)

    Foody G.M., Ghoneim E.M., and Arnell N.W. 2004. Predicting locations sensitive to flash flooding in an arid environment. Journal of Hydrology, 292(1-4):48-58.

    Ghanizadeh S., Safadoust A., Nael M. and Yousefi Y. 2019. Comparison of sediment content in runoff and drainage water under two different slopes and cultivation types. Applied Soil Research, 6(4): 109-120. (In Persian)

    Gyamfi C., Ndambuki JM., and Salim RW. 2016. Application of SWAT model to the Olifants basin: calibration, validation and uncertainty analysis. Journal of Water Resource and Protection, 8: 397-410.

    Huang J., Wu P., and Xining Z. 2013. Effects of rainfall intensity, underlying surface and slope gradient on soil infiltration under simulated rainfall experiments, Catena, 104: 93-102.

    Hosseini S. H., Architects H., and Architects H. 2015. Using SWAT model and SWAT-CUP software in simulation and analysis of hydrological uncertainty in arid and semi-arid watersheds (Case study: Zashk watershed in Torqabeh-Shandiz). Master Thesis, Islamic Azad University, Torbat-e Jam Branch. (In Persian)

    Hyung –Kyung J., Jong –Yoon P., Hyun-Kyo J., Hyung-Jin S., Hyung-Joong K., and seong-joon K. 2011.The uncertainty analysis of SWAT simulated stream flow and water quality applied to Chungju dam watershed of South Korea. dep of civil and environmental system eng, konkuk university Seoul, South korea: 29 pp.

    Jha M.K., and Afreen S., 2020. Flooding urban landscapes: Analysis using combined hydrodynamic and hydrologic modeling approaches. Water, 12(7): 1986.

    Joh H.K., Park J.Y., Shin H.J., Lee J.W., and Kim S.J. 2011. The uncertainty analysis of SWAT

               simulated streamflow applied to chungju dam watershed. In Proceedings of the Korea Water Resources Association Conference (pp. 29-29). Korea Water Resources Association.

    Kavian A., and Mohammadi M. 2019. The effect of spatial accuracy of digital elevation models on hydrological simulation. Journal of Watershed Management, 10 (19): 36-45.  (In Persian)

    Khosroshahi M., and Saghafian B. 2005. Determining the sensitivity of the effect of some factors affecting flood flooding in basins using hydrographic analysis of basin outlet and application of the HEC-HMS model. Quarterly Journal of Forests, Rangelands and Watershed Management Organization, 67: 23 - 37. (In Persian)

    Lal  R. 2005. Soil erosion and carbon dynamics. Soil and Tillage Research, 81(2): 137-142.

    Li K.Y., Coe M.T., Ramankutty N., and De Jong R. (2007). Modeling the hydrological impact of land-use change in West Africa. Journal of Hydrology, 337(3-4): 258-268.

    Memarian H., Memarian H., and Hosseini S. H. 2017. Using SWAT model and SWAT-CUP software in simulation and analysis of hydrological uncertainty in arid and semi-arid watersheds (Case study: Zashk watershed in Torqabeh-Shandiz). Rainwater Catchment Systems, 7(2): 35-44. (In Persian)

    Moriasi D., 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 ASAE, 50(3): 885-900.

    Moazenzadeh R., Qahraman B., Saleh A., and Davari K. 2020. Simulation of runoff using SWAT model on an annual scale) Case study: Neishabour Catchment (Journal of Soil and Water Knowledge. 29(4): 57-70. (In Persian)

    Moghli M. 2015. Flood prioritization of hydrological units of dalaki basin using HEC-HMS

              simulation. Quantitative Geomorphological Research, 3(4): 12. (In Persian)

    Nash J.E., and J.V. Sutcliffe. 1970. River flow forecasting though conceptual models. Journal of Hydrology, 10: 282-290.

    Nohegar A., Qashqaeizadeh N., and Hali Saz A. 2012. Determining flood-generating areas and prioritizing flooding under basins (Case study: Jamash watershed in Hormozgan province). Earth Knowledge Research, 3 (1): 14-25. (In Persian)

    Rezaei Tavabh K. 2015. Limnological study and determination of biological value of Damghanrood river in Semnan province. The first annual conference of Iranian agricultural research, Kharazmi Higher Institute of Science and Technology, Shiraz. (In Persian)

    Rouholahnejad E., Abbaspour K.C., Vejdani M., Srinivasan R., Schulin R., and Lehmann A. 2012. Parallelization framework for calibration of hydrological models. Environ. Modell. Software 31: 28– 36.

    Saghafian B., Ghermezcheshmeh B., and Kheirkhah M. M. 2010. "Iso-flood severity mapping: a new tool for distributed flood source identification", Nat Hazards, 55: 557-570.

    Saghafian B., and Farazjoo H. 2007. Determining flood generating areas and prioritizing flooding of hydrological units in Golestan dam basin. Iranian Journal of Watershed Management Science and Engineering. 1: 1-11. (In Persian)

    Saraie B., Talebi A., Mazidi A., and Parvizi S. 2020. Prioritization of Sardab-Rood watershed from flooding viewpoint using the SWAT model. Journal of Natural Environmental Hazards, Issue 23(9): 85-98. (In Persian)

    Shawul AA., Alamirew T., and Dinka M. O. 2013. Calibration and validation of SWAT model and estimation of water balance components of Shaya mountainous watershed, Southeastern Ethiopia. Hydrology and Earth System Sciences, 10: 13955- 13978.

    Taghvaye Salimi E., Nohegar A., Malekian A., Hosseini M., and Holisaz A. 2016. Runoff simulation using SWAT model and SUFI-2 algorithm (Case study: Shafaroud watershed, Guilan Province, Iran). Caspian Journal of Environmental Sciences, 14(1): 69-80.

    Trinh T., Kavvas M.L., Ishida K., Ercan A., Chen Z.Q., Anderson M.L., Ho C., and Nguyen T. 2018. Integrating global land-cover and soil datasets to update saturated hydraulic conductivity parameterization in hydrologic modeling. Science of The Total Environment, 631: 279-288.

    World Meteorological Organization. 2011. Manual of Flood Forecasting and Warning, wmo No, 1072.

    Wang L., and Liang T. 2015. Distribution characteristics of phosphorus in the sediments and overlying Water of Poyang Lake. PLoS ONE, 10: 5.

    Yu D., Xie P., Dong X., Hu X., Liu J., Li Y., Peng T., Ma H., Wang K., and Xu S. 2018. Improvement of the SWAT model for event-based flood simulation on a sub-daily timescale. Hydrology and Earth System Sciences22(9): 5001-5019.

    Zairi M., and Shafaei Bajestan M. 2018. The effect of river spiral removal on the flow pattern and sediment of Karun river using software. Journal of Water Resources Engineering, 11(38): 95-106. (In Persian)