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شبیه سازی بارش-روانآب با نرم افزار eWater Source در آبخیز چهل چای، استان گلستان | ||
| پژوهش های آبخیزداری | ||
| مقاله 3، دوره 34، شماره 1 - شماره پیاپی 130، فروردین 1400، صفحه 16-29 اصل مقاله (2.19 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2020.342744.1334 | ||
| نویسندگان | ||
| مهدی تیموری* 1؛ احسان الوندی2 | ||
| 1استادیار مجتمع آموزش عالی شیروان | ||
| 2دانشآموختهی دکترای علوم و مهندسی آبخیزداری، دانشگاه علوم کشاورزی و منابع طبیعی گرگان | ||
| چکیده | ||
| بهدلیل ناهمگنی آبخیزها و ناخطی بودن رفتارهای آبشناسی و فرسایشی، شناخت کامل رابطههای آنها بسیار پیچیده و مشکل است. بنابراین در ارزیابی و بررسی کردن این سامانهها، نیاز به فرآیند شبیهسازی است. در این پژوهش برای شبیهسازی کردن روانآب آبخیز چهلچای (256 کیلومترمربع) در استان گلستان، دو نرمافزار بارش روانآب GR4J و IHACRES در eWater Source با هم مقایسه شد. برای شبیهسازی بارش-روانآب آبخیز چهلچای موقعیت آبخیز با نرمافزار رقومی ارتفاع (DEM)، موقعیت زیرحوزهها، ایستگاهها، و خروجی آبخیز، واحدهای عملیاتی (بر اساس نقشهی کاربری زمین) و شبکهی آبراه آبخیز در محیط Source شبیهسازی کرده شد. نرمافزارهای GR4J و IHACRES در محیط Source بهکار گرفته شد. دادههای مجموعهی زمانی پیوسته در گام زمانی روزانه در نظر گرفته شد. برای اجرای نرمافزارها مجموعهی زمانی بارش روزانهی سالهای 1380 تا 1389 و تبخیر و تعرق سالهای 1380 تا 1389 از ایستگاه لزوره بهکار گرفته شد. این نرمافزارها در محیط eWater Source اجرا کرده شد. دادههای مشاهدهیی آبدهی جریان (1380 تا 1389)، ایستگاه آبسنجی لزوره برای واسنجی نرمافزارها بهکار گرفته شد. نتیجهی ارزیابی نرمافزارهای GR4J و IHACRES دقت شبیهسازی جریان را بر اساس معیار نش- ساتکلیف بهترتیب 0/79 و 0/73 در دورهی واسنجی (1380-1389) و 0/76 و 0/68 در دورهی اعتبارسنجی (1389-1394) نشان میدهد. بنابراین میتوان نتیجه گرفت که کارآیی این نرمافزارها در شبیهسازی جریان خوب است. نتیجهی ارزیابی نشاندهندهی کارآیی بهتر نرمافزار GR4J از IHACRES در شبیهسازی جریان روزانه است. بر پایهی توانمندیهای زیاد نرمافزار eWater Source، این محیط ابزار شبیهسازی مدیریتی مناسبی برای آبخیز دانسته میشود. | ||
| کلیدواژهها | ||
| بارش-روانآب؛ حوزه رودخانه گرگان رود؛ نرم افزار GR4J؛ IHACRES؛ eWater Source | ||
| عنوان مقاله [English] | ||
| Rainfall-Runoff Modeling Using the eWater Source in the Chel-Chay Watershed, the Province of Golestan | ||
| نویسندگان [English] | ||
| Mehdi Teimouri1؛ Ehsan Alvandi2 | ||
| 1Assistant professor Higher Education Complex of Shirvan, Khorsasn Shomali, Shirvan, Iran | ||
| 2Ph.D. Graduate in Watershed Management Sciences and Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Golestan, Gorgan, Iran | ||
| چکیده [English] | ||
| It is very complex and difficult to fully understand the relationships in watersheds due to the heterogeneity and non-linear nature of hydrological and erosive behaviors. Therefore, the evaluation of watersheds requires a modeling process. After introducing the features of the eWater Source software as a management modeling environment for watersheds, two rainfall-runoff models of the GR4J and the IHACRES were compared to simulate the runoff of the Chel-Chay Watershed in the eWater Source environment. Chel-Chay Watershed, with an area of 256 square kilometers is located in Province of Golestan. In order to simulate the rainfall -runoff, the position of the watershed, sub-watersheds, stations, watershed outlet, operational units (based on land use map) and the watershed waterway network was simulated using the digital height model (DEM) in the Source environment. The GR4J and the IHACRES models were used. In this rainfall -runoff models, the continuous time series data were considered in the daily time steps. The time series of the daily precipitation of the years (2001 to 2010), and the daily evaporation and transpiration (during the same period) were used to implement the models. The models were implemented in the eWater Source environment. The discharge data for the period (2001-2010) were used to calibrate the models. The accuracy of the flow simulation based on the Nash-Sutcliffe criterion for the GR4J and the IHACRES models in the calibration period (2001-2010) were 0.79 and 0.73, and in the validation period (2011-2015) were 0.76 and 0.68, respectively. Therefore, it may be concluded that these models performed well in the simulation. The evaluation of results indicates that the GR4J model performs better than the IHACRES model for simulating the daily flow. Due to the high capabilities of the eWater Source software, this environment is recommended as a management model for the discharge of watersheds. | ||
| کلیدواژهها [English] | ||
| GR4J model, IHACRES model, rain-runoff, the eWater Source software, the Gorganroud River | ||
| مراجع | ||
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Baghel D, Gaur A, Karthik M, Dohare D. 2019. Global trends in environmental flow assessment: An overview. Journal of the Institution of Engineers, 100 (2): 191–197. Black DC, Wallbrink PJ, Jordan PW. 2014. Towards best practice implementation and application of models for analysis of water resources management scenarios. Environmental Modelling & Software, 52 (3): 136–148 Close AF, Mamalai O, Sharma P. 2004. The River Murray flow and salinity models: MSM-BIGMOD. In: Dogramaci, S., Waterhouse, A (Eds.), Engineering Salinity Solutions: 1st National Salinity Engineering Conference 2004. Engineers Australia, pp. 37–342. Croke BM, Andrews W, Spate F, Cuddy J. 2005. IHACRES user guide. Technical Report 2005/19. Second ed. ICAM, School of Resources. Environment and Society. The Australian National University. Canberra. pp. 35–38. Dutta D, Welsh W, Vaze J, Kim Sh, Nicholls D. 2012. A comparative evaluation of short-term stream flow forecasting using time series analysis and rainfall-runoff models in eWater Source. Water Resources Management, 26 (2): 4397–4415. Dutta D, Wilson K, Welsh W, Nicholls D, Kim Sh, Lydia C. 2013. A new river system modelling tool for sustainable operational management of water resources. Journal of Environmental Management, 121 (4): 13–28. Ewater group. 2019. [Online]. Available at https://ewater.org.au/products/ewater-source. Harlan D, Wangsadipura M, Munajat CM. 2010. Rainfall-runoff modeling of Citarum Hulu River Basin by using GR4J. in proc. World Congress on Engineering, pp. 1607–1611. Harun S, Ahmat N, Kassim A. 2002. Artificial neural network model for rainfall-runoff relationship. Journal Technology, 37(2): 1–12. Hughes JD, Dutta D, Vaze J, Kim S, Podger G. 2014. An automated multi-step calibration procedure for a river system model. Environmental Modelling & Software, 51 (2): 173–183. Hughes JD, Silberstein RP, Grigg A. 2013. Extending rainfall–runoff models for use in environments with long–term catchment storage and forest cover changes. In MODSIM2013, 20th International Congress on Modelling and Simulation, pp. 231–243. Huo Z, Feng S, Kang S, Huang G, Wang F, Guo P. 2012. Integrated neural networks for monthly river flow estimation in arid inland basin of northwest China. Journal of Hydrology, 420 (2): 159–170. Kunnath-Poovakka A, Eldho TI. 2019. A comparative study of conceptual rainfall-runoff models GR4J, AWBM and Sacramento at catchments in the upper Godavari river basin, India. Journal of Earth System Science, 128 (2): 21–33. Mouelhi S, Madani K, Lebdi F. 2013. A structural overview through GR (s) models characteristics for better yearly runoff simulation. Open Journal of Modern Hydrology, 3 (2): 14–27. Mouelhi S, Michel C, Perrin C, Andréassian V. 2006. Linking stream flow to rainfall at the annual time step: The Manabe bucket model revisited. Journal of Hydrology, 328 (1): 283–296. Nguyen H, Recknagel F, Meyer W, Frizenschaf J, Ying H, Gibbsd M. 2019. Comparison of the alternative models SOURCE and SWAT for predicting catchment streamflow, sediment and nutrient loads under the effect of land use changes. Science of the Total Environment, 662 (3): 254–265. Nohegar A, Motamednia M, Malekian A. 2016. Daily river flood modeling using genetic programming and artificial neural network (Case study: Amameh representative watershed). Physical Geography Research, 48 (3): 367–383. (In Persian). Rassam D, Peeters L, Pickett T, Jolly J, Linda H. 2013. Accounting for surface groundwater interactions and their uncertainty in river and groundwater models: A case study in the Namoi River, Australia. Environmental Modelling & Software, 50 (3): 108–119. Rassam DW, Jolly I, Pickett T. 2012. Guidelines for modeling groundwater surface water interactions in eWater source, Toward Best Practice Model Application, ISBN 978-1-921543-59-3. Rassam DW. 2011. A conceptual framework for incorporating surface groundwater interactions into a river operation-planning model. Environmental Modelling & Software, 26 (2):1554–1567. Rwasoka DT, Madamombe CE, Gumindoga W, Kabobah A. 2013. Calibration, validation, parameter indentifiability and uncertainty analysis of a 2–parameter parsimonious monthly rainfall-runoff model in two catchments in Zimbabwe. Physics and Chemistry of the Earth, 67 (3): 36–46. Traore Vb, Sambou S, Tamba S, Fall S, Diaw At, Cisse M. 2014. Calibrating the rainfall-runoff model GR4J and GR2M on the Koulountou river basin, a tributary of the Gambia River, American Journal of Environmental Protection, 3 (4): 36–4. Welsh WD, Dutta D, Wilson K, Nicholls D, Kim S, Cetin L. 2012. Improvements in river operations forecasting using Source IMS. In: Proceedings of Water and Climate: Policy Implementation Challenges. Engineers Australia, Canberra, Australia, pp. 280–296. Welsh WD, Vaze J, Dutta D, Rassam D, Rahman JM, Jolly ID, Wallbrink P, Podger GM, Bethune M, Hardy MJ, Teng J, Lerat J. 2013. An integrated modelling framework for regulated river systems. Environmental Modelling & Software, 39 (3): 81–102. Zandi Dareh Gharibi F, Khorsandi Z, Mozayan M, Arman N. 2017. Technical Note: Evaluating the proficiency of GR2M and GR4J rainfall-runoff models in Darehtakht Basin runoff simulation. Watershed Engineering and Management, 9 (3):360–370. (In Persian). Zhang X, Waters D, Ellis R. 2013. Evaluation of sighed, Sacramento and GR4J rainfall runoff models in two contrasting Great Barrier Reef catchments. 20th International Congress on Modelling and Simulation, Adelaide, Australia, pp. 3260–3266. | ||
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