Evaluation of the capability of the SWAT model in simulating water balance components of the Aras basin

Document Type : Research Paper

Authors

1 Post-doctoral researcher of Climatology at University of Mohaghegh Ardabili, Ardabil, Iran

2 Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

3 Post-doctoral researcher of Climatology, University of Mohaghegh Ardabili, Ardabil, Iran

10.22034/gp.2024.61336.3253

Abstract

In this research, the water balance components of the Aras basin area were simulated in the SWAT model for a period of 28 years (1987-2014). For this purpose, the efficiency and capability of the SWAT model by SWAT CUP using the SUFI2 algorithm and based on the observed discharge data in the selected hydrometric station of Aras basin (Bdoy) with 70% of the data (1987-2006) and 30% of the rest (2007-2014) was validated. Based on the raster data input to the model, this basin was divided into 68 subbasins with 1264 hydrological response units (HRUs) and calculations were performed on their level. SWAT model calibration was done by using 14 important parameters that were selected from several parameters based on the comparison of sensitivity analysis results. In the sensitivity analysis stage of the model, parameters related to monthly temperature, air temperature, and soil evaporation factor from.bsn,.wgn, and.hru files were identified as the most effective parameters in simulating the flow discharge of the selected hydrometric station of Aras Basin. By running 300 times of calibration, finally, the best round of simulation based on the target criteria was identified and the output data was evaluated. The efficiency and accuracy of the model in the calibration period (1987-2006) based on the evaluation criteria of NS, P-Factor, R-Factor, and R2 were calculated as 0.64, 0.71, 0.27, and 0.79 respectively, which show the satisfactory performance of the model. In the water balance simulation, it is Aras Basin. The values of these criteria in the validation period were calculated as 0.7, 0.78, 0.3, and 0.68 respectively.

Keywords

Main Subjects

Full Text

در این پژوهش مؤلفه‌های بیلان آب حوضه آبریز ارس برای دوره 28 ساله (1987-2014) در مدل SWAT شبیه‌سازی گردید. بدین منظور کارایی و قابلیت مدل SWAT توسط SWAT CUP با استفاده از الگوریتم SUFI2 و بر اساس داده دبی مشاهداتی در ایستگاه هیدرومتری منتخب حوضه ارس (بدوی) با 70 درصد از داده‌ها (1987-2006) واسنجی و با 30 درصد بقیه (2007-2014) اعتبارسنجی شد. بر مبنای داده‌های رستری ورودی به مدل، این حوضه به 68 زیرحوضه با 1264 واحد پاسخ هیدرولوژیکی تقسیم و محاسبات در سطح آن‌ها انجام شد. با استفاده از 14 پارامتر مهم که بر اساس مقایسه نتایج تحلیل حساسیت از بین چندین پارامتر انتخاب شده بودند، کالیبره کردن مدل SWAT انجام شد. در مرحله تحلیل حساسیت مدل، پارامترهای مربوط به دمای ماهانه و دمای هوا و فاکتور تبخیر از خاک از فایل‌های .bsn و .wgn و .hru به‌عنوان مؤثرترین پارامترها در شبیه‌سازی دبی جریان ایستگاه هیدرومتری منتخب حوضه ارس شناسایی شدند. با اجرای 300 باره کالیبراسیون، در نهایت بهترین دور شبیه‌سازی بر اساس معیار هدف شناسایی شده و داده‌های خروجی مورد ارزیابی قرار گرفت. کارایی و دقت مدل در دوره واسنجی (1987-2006) بر اساس معیارهای ارزیابی NS، P-Factor، R-Factor و R2 به‌ترتیب 64/0، 71/0، 27/0 و 79/0 محاسبه گردید که نشان‌دهنده رضایت‌بخش بودن کارایی مدل در شبیه‌سازی بیلان آب حوضه ارس است. مقدار این معیارها در دوره اعتبارسنجی به‌ترتیب 7/0، 78/0، 3/ و 68/0 محاسبه شد.

References

Abbaspour, K., Faramarzi, M., Ghasemi, S., Yang, H. (2009). Assessing the impact of climate change on water resources in Iran, Water Resour. Res., 45(10).
Alansi, A. W., Amin, M. S. M., Abdul Halim, G., Shafri, H. Z. M., Aimrun, W. (2009). Validation of SWAT model for stream flow simulation and forecasting in Upper Bernam humid tropical river basin, Malaysia, Hydrology and Earth System Sciences, 6: 7581–7609.
Arnold, J. G., Srinivasan, R., Muttiah, R. S., Williams, J. R. (1998). Large area hydrologic modeling and assessment Part I: Model development, JAWRA J. Am. Water Resour. Assoc., 34: 73–89.
Arnold, J. G., Williams, J. R., Maidment, D. R. (1995). Continuous-Time Water and Sediment-Routing Model for Large Basins. J. Hydraul. Eng., 121: 171–183.
Bekiaris, I. G., Panagopoulos, I. N., Mimikou, N. A. (2005). Application of the SWAT model in the Ronnea catchment of Sweden. Global NEST Journal, 3(7): 252-257.
Bieger, K., Hormann, G., Fohrer, N. (2015). Detailed spatial analysis of SWAT-simulated surface runoff and sediment yield in a mountainous watershed in China, Hydrological Sciences, 60: 784-800.
Chu, T. W., Shirmohammadi, A. (2004). Evaluation of the SWAT model’s hydrology component in the piedmont physiographic region of Maryland, American Society of Agricultural and Biological Engineers (ASABE), 47(4): 1057-1073.
Dobler, C., Bürger, G., Stötter, J. (2012). Assessment of climate change impacts on flood hazard potential in the Alpine Lech watershed, J. Hydrol, 460-461: 29-39.
Eum, H., Simonovic, S. P. (2012). Assessment on variability of extreme climate events for the Upper Thames River basin in Canada, Hydrol. Process, 26(4): 485-499.
Feyereisen, G. W., Strickland, T. C., Bosch, D. D., Sullivan, D. G. (2007). Evaluation of SWAT manual calibration and input parameter sensitivity in the little river watershed, American Society of Agricultural and Biological Engineers, 50: 843−855.
Hasheminasab, S., Rahimi, D., Zakerinejad, R., Kropáček, J. (2022). Assessment of climate change impact on surface water: a case study—Karoun River Basin, Iran, Arabian Journal of Geosciences, 15:904. https://doi.org/10.1007/s12517-022-09969-5
Kalcic, M., Chaubey, I., Frankenberger, J. (2015). Defining Soil and Water Assessment Tool (SWAT) hydrologic response units (HRUs) by field boundaries, Agricultural and Biological Engineering, 8: 1 -12.
Kim, J. H., Sung, J. H., Chung, E. S., Kim, S. U., Son, M., Shiru, M. S. (2021). Comparison of projection in meteorological and hydrological droughts in the Cheongmicheon Watershed for RCP4. 5 and SSP2-4.5, Sustainability, 13(4): 2066
Li, K. Y., Coe, M. T., Ramankutty, N., De Jong, R. (2007). Modeling the hydrological impact of landchange in West Africa, J. of Hydro., 337: 258-268.
Lu, Z., Zou, S., Xiao, H., Zheng, C., Yin, Z., Wang, W. (2015). Comprehensive hydrologic calibration of SWAT and water balance analysis in mountainous watersheds in northwest China, Physics and Chemistry of the Earth, Parts A/B/C 79: 76-85.
Nash, J. E. Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I- A discussion of principles, Journal of Hydrology, 10(3): 282-290.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R. Willams, J. R. (2005). Soil and Water Assessment Tool theoretical documentation. Blackland Research Center, Texas Agricultural Experiment Station, 494 p. from www.brc.tamus.edu.
Rahimi, D., Hasheminasab, S., Abdollahi, K., (2019). Assessment of temperature and rainfall changes in the Karoun River basin, Theoretical and Applied Climatology, 137(6). DOI: 10.1007/s00704-019-02771-6
Santhi, C., Muttiah, R. S., Arnold, J. G., Srinivasan, R. (2005). A GIS-based regional planning tool for irrigation demand assessment and savings using SWAT, Transactions of the ASAE 48(1):137-147.
Wang, D., Hejazi, M., Cai, X., Valocchi, A. J. (2011). Climate change impact on meteorological, agricultural, and hydrological drought in central Illinois, Water Resour. Res., 47(9).
Wilby, R., Haris, I. (2006). A frame work for assessing uncertainties in Climate change impacts: low flow scenarios for the River Thames, U. K. water resources research.
Wolock, D., McCabe, G. (1999). Estimates of Runoff Using Water-Balance and Atmospheric, journal of the American water resources association. 35, 6: 1341-1350.
Zuo, D., Xu, Z., Zhao, J., Abbaspour, K. C., Yang, H. (2015). Response of runoff to climate change in the Wei River basin, China. Hydrological Sciences Journal, 60(3):1-15.

Files

Share

How to cite

Statistics