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تاثیر افزایش دما بر ذوب برف و رواناب رودخانه در ماههای گرم سال و تحلیل متغیرهای اقلیمی در حوضه تمر، ایران | ||
تحقیقات آب و خاک ایران | ||
دوره 53، شماره 7، مهر 1401، صفحه 1611-1624 اصل مقاله (2.08 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2022.339312.669213 | ||
نویسندگان | ||
پروا محمدی1؛ کیومرث ابراهیمی* 2؛ جواد بذرافشان3 | ||
1گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران، کرج ایران | ||
2گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران، کرج، ایران | ||
3گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
چکیده | ||
گرم شدن زمین باعث تغییرات الگوی بارندگی و کاهش ذخایر برف شده است. هدف مقالهی حاضر ارزیابی تأثیر افزایش دما بر ذوب برف و رواناب رودخانه در ماههای گرم سال و تحلیل متغیرهای اقلیمی در حوضه تمر میباشد. بدین منظور سطح پوشش برف از تصاویر روزانه ماهواره مودیس استخراج و براساس ارتفاع و با کاربرد نرمافزار GIS محدودهی مطالعات به چهار ناحیه تقسیم شد. به منظور شبیهسازی رواناب ناشی از ذوب برف از دادههای مشاهداتی دبی ایستگاه هیدرومتری تمر، بارش ایستگاه قرناق و میانگین دمای ایستگاه گیداغ (سالهای1395-1392) برای واسنجی و (سالهای 1398-1396) برای صحتسنجی استفاده شد. سطح پوشش برف در مرحله واسنجی در دی ماه به بیشترین مقادیر برابر 28 درصد در ناحیه سوم و 8/28 درصد در ناحیه چهارم رسید. در مرحله صحتسنجی نیز نواحی سوم و چهارم در بهمن ماه بیشترین درصدها را به ترتیب برابر با 8/45 و 2/30 بهخود اختصاص دادند. مقایسه نتایج رواناب شبیهسازی شده و مشاهداتی نشان داد که سهم رواناب ناشی از ذوب برف در گذر از بهمن به فروردین ماه قابل توجه است. بطوریکه بیشترین افزایش مقدار رواناب مربوط به سال آبی 1398-1397 از 8/1 به 1/39 درصد برآورد شد. همچنین بیشترین و کمترین درصد ذوب برف در سالهای 1394-1393 و 1398-1397 به ترتیب به مقدار 19 و 3/3 درصد بوده است. نتایج تحلیل حساسیت پارامترهای مدل شامل آهنگ کاهش دما، دمای بحرانی، زمان تأخیر، فاکتور درجه_روز، ضرایب X و Y، ضریب رواناب بارش و ضریب رواناب برف نشان داد که پارامترهای ضریب رواناب باران و X از تأثیرگذارترین پارامترها هستند. تأثیر دما و بارندگی بر فرآیند رواناب نیز در ماههای مختلف متفاوت ثبت شد. | ||
کلیدواژهها | ||
حوضه کوهستانی؛ سیلاب؛ مدل هیدرولوژیکی؛ منابع آب؛ نوسانات اقلیمی | ||
عنوان مقاله [English] | ||
Improving the precision of Snowmelt runoff simulation and sensitivity analysis of parameters and climatic variables in the Tamar basin, Iran | ||
نویسندگان [English] | ||
Parva Mohammadi1؛ Kumars Ebrahimi2؛ Javad Bazrafshan3 | ||
1Engineering Department of Water Resources, Department of Irrigation and Water Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran | ||
2Irrigation and Reclamation Engineering Department, Faculty of Agricultural Engineering & Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran | ||
3Irrigation and Reclamation Engineering Department, Faculty of Agricultural Engineering & Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran | ||
چکیده [English] | ||
Global warming has changed rainfall patterns and reduced snow sources. The main objective of this research was to investigate the impact of temperature increase on snowmelt and river runoff in hot months of the year along with analysis of climate variables in Tamar basin, Iran. For this purpose, the snow cover area was extracted from the daily images of Modis Satellite, based on elevation. Then, the study area was divided into four districts. Discharge flow measured data of Tamar hydrometric station, precipitation of Qarnaq and average temperature of Gidagh stations were used from 2013 to 2016 for calibration and from 2017 to 2019 for verification, to simulate snowmelt runoff. Snow cover extent, in calibration stage and january, reached the highest values of 28% and 28.8% in the third and fourth districts, respectively. Furthermore, in the verification stage, the third and fourth districts in February had the highest percentages of 45.8 and 30.2, respectively. Comparison of simulated and measured runoff data revealed that the portion of runoff due to snowmelt is significant by passing from February to April. So that the highest increase (from 1.8% to 39.1%) in runoff amount was corresponded to the water year of 2018-2019. The highest and the lowest percentages of snowmelt in water years of 2014-2015 and 2017-2018 were 19 and 3.3 percent, respectively. The results of sensitivity analysis of model parameters including temperature decrease rate, critical temperature, delay time, degree-day factor, X and Y coefficients, precipitation runoff coefficient and snow runoff coefficient showed that the rainfall coefficient and X parameters are the most effective parameters. The effect of temperature and rainfall on runoff process was varied in different months. | ||
کلیدواژهها [English] | ||
Climate variability, Floods, Hydrological model, Mountain basin, Water resources | ||
مراجع | ||
Aalinejad, M. H., Jahanbakhsh ASL, S. (2021). Simulation of runoff from Gamasiab basin snowmelt with SRM model. Jsaeh, 8 (1), 21-36 (In Farsi). Almasi, P., Moghaddam Nia, A., Khalighi Sigaroodi, S., Salajeghe, A., Soltani Koopaei, S. (2021). Performance Evaluation of WetSpa Hydrological Model for Runoff Simulation in Semi-arid Climatic Conditions (Case Study: Menderjan Basin). Iranian Journal of Soil and Water Research, 52(2), 469-482 (In Farsi). Artimani, M., Zeinivand, H., Tahmasebipour, N. (2019). Performance evaluation of SRM and HBV model in simulation of snowmelt runoff in Bujin Basin. Iran-Water Resources Research, 15(2), 228-241 (In Farsi). Birodian, N., and Jandaghi, N. (2006). Estimation of snowmelt runoff by SRM model and comparison with hydrographic data in Ziarat river basin. Agricultural Sciences and Natural Resources, 12 (6), 181-188 (In Farsi). Chelamallu, H. P., Venkataraman, G., Murti, M. V. R., Arora, M., & Singh, G. (2014, July). Comparison of SRM and SNOWMOD models using modis snow cover data for Bhagirathi river basin in the Himalayas. In 2014 IEEE Geoscience and Remote Sensing Symposium (pp. 4010-4013). IEEE. DeWalle, D. R., & Rango, A. (2008). Principles of snow hydrology. Cambridge University Press. Dey, B., Sharma, V. K., & Rango, A. (1989). A test of snowmelt-runoff model for a major river basin in western Himalayas. Hydrology Research, 20(3), 167-178. Fattahi, I., Delavar, M., & Ghasemi, E. (2011). Snow melt runoff simulation in mountainous areas using SRM model (Case study of Bazoft Watershed Area). Geographic Applied Research Journal 2(23) (In Farsi). Gholizadeh Atani. M. (2014). Effect of snowmelt runoff in floods using remote sensing techniques in Alamoutrood basin. Master dissertation, BU-Ali Sina University, Iran (In Farsi). Golshan, M., Kavian, A., Ruohani, H., Esmali Ouri, A. (2015). Effect of Scale on SWAT Model Performance in Simulation of Runoff (Case Study: Haraz Catchment in Mazandaran Province). Iranian Journal of Soil and Water Research, 46(2), 293-303 (In Farsi). Goudarzi, Sh. (2015). Snowmelt Runoff Simulation by SRM Snowmelt Model and Satellite Data of MODIS (Case study: Orumia Siminerood Basin). Master dissertation, Faculty of Agriculture, Ferdowsi University of mashhad, Iran (In Farsi). Hamby, D. M. (1994). A review of techniques for parameter sensitivity analysis of environmental models. Environmental monitoring and assessment, 32(2), 135-154. HassanPour Darvishi, H., Ebrahimi, H. (2014). Investigation of Snow Impact on Runoff Simulation in Catchment (Case Study: Bar Catchment, Neyshabour). Iranian Journal of Irrigation & Drainage, 8(4), 857-864 (In Farsi). Hayat, H., Akbar, T. A., Tahir, A. A., Hassan, Q. K., Dewan, A., & Irshad, M. (2019). Simulating current and future river-flows in the Karakoram and Himalayan regions of Pakistan using snowmelt-runoff model and RCP scenarios. Water, 11(4), 761. Jin, H., Ju, Q., Yu, Z., Hao, J., Gu, H., Gu, H., & Li, W. (2019). Simulation of snowmelt runoff and sensitivity analysis in the Nyang River Basin, southeastern Qinghai-Tibetan Plateau, China. Natural Hazards, 99(2), 931-950. Karandish, F., Porhemat, J., & Ebrahimi, K. (2016). Determining the basic parameter in snow melt process for estimating flood hydrograph in Karoun basin, Iranian Water Research Journal, 10(21), 133. (In Farsi). Karimi, H., Zeinivand, H., Tahmasebipour, N., Haghizadeh, A., & Miryaghoubzadeh, M. (2016). Comparison of SRM and WetSpa models efficiency for snowmelt runoff simulation. Environmental earth sciences, 75(8), 664. Legates, D. R., & McCabe Jr, G. J. (1999). Evaluating the use of “goodness‐of‐fit” measures in hydrologic and hydroclimatic model validation. Water resources research, 35(1), 233-241. Li, X., & Williams, M. W. (2008). Snowmelt runoff modelling in an arid mountain watershed, Tarim Basin, China. Hydrological processes, 22(19), 3931-3940. McCuen, R. H. (1998). Hydrologic analysis and design. Printice-Hall Pub. Inc. NJ, 548. Mohammadi Ghaleni, M., & Ebrahimi, K. (2019). Sensitivity analysis of Qual2kw model in the modeling of water quality parameters of Sefidrud. Iranian Journal of Irrigation & Drainage, 13(5), 1233-1245 (In Farsi). Mohammadi, A. (2013). Assessment of Snowmelt Runoff Modeling (SRM) in Simulation and Forecasting Stream Flow Snowmelt Runoff by Satellite Imagery. Master dissertation, Campus of Aboureihan Department of Irrigation and Drainage, University of Tehran, Iran (In Farsi). Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885-900. Mousavi, S., Sarmadian, F., Rahmani, A. (2020). Modelling and Prediction of Soil Classes Using Boosting Regression Tree and Random Forests Machine Learning Algorithms in Some Part of Qazvin Plain. Iranian Journal of Soil and Water Research, 50(10), 2525-2538 (In Farsi). Okhovat. S. (2016). Snowmelt runoff modeling with SRM and by GIS and RS (Case study of Lar Dam basin). Master dissertation, Shahrood University of Technology, Iran (In Farsi). Ouatiki, H., Boudhar, A., Ouhinou, A., Beljadid, A., Leblanc, M., & Chehbouni, A. (2020). Sensitivity and Interdependency Analysis of the HBV Conceptual Model Parameters in a Semi-Arid Mountainous Watershed. Water, 12(9), 2440. Pangali Sharma, T. P., Zhang, J., Khanal, N. R., Prodhan, F. A., Paudel, B., Shi, L., & Nepal, N. (2020). Assimilation of snowmelt runoff model (SRM) using satellite remote sensing data in Budhi Gandaki River Basin, Nepal. Remote Sensing, 12(12), 1951. Raeisi, M. B., Vafakhah, M., Moradi, H. R. (2021). Comparison of Degree-Day and Radiation base of Snowmelt Runoff Model (SRM) for Estimating Runoff from Snow Melting. Journal of Watershed Management Research; 12 (23), 1-11 (In Farsi). Rango, A., & Martinec, J. (1998). The snowmelt runoff model (SRM) user/s manual, version 4, URL: fttp. hydrolab. arsusda. gov/pub/srm/srm4. pdf. Rashidi, M., Haji biglo, M., Sarbazi, M., Ghaderi, M. (2017). Estimation of Snowmelt Runoff in Northern Khorasan Basin by using winSRM Model (Case Study: Darband Samalghan Basin). Irrigation Sciences and Engineering, 40(2), 159-171 (In Farsi). Tekeli, A. E., Akyürek, Z., Şorman, A. A., Şensoy, A., & Şorman, A. Ü. (2005). Using MODIS snow cover maps in modeling snowmelt runoff process in the eastern part of Turkey. Remote Sensing of Environment, 97(2), 216-230. Torabi Poodeh, H., Yousefi, H., Samadi, A., Arshia, A., Shamsi, Z., & Yarahmadi, Y. (2021). Evaluation of snow cover changes trend using GEE and TFPW-MK test (Case Study: Marber Basin-Isfahan). Iranian journal of Ecohydrology, 8(1), 195-204 (In Farsi). Zhang, X., Qin, X., Xu, C., & Liu, Y. (2018). Simulation of runoff and glacier mass balance and sensitivity analysis in a glacierized basin, North-Eastern Qinhai-Tibetan Plateau, China. Water, 10(9), 1259. | ||
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