ارزیابی مدل WetSpass-M در برآورد پاسخ هیدرولوژیکی حوضه نیشابور-رخ به تغییراقلیم سال‌های آتی

نوع مقاله : مقالات پژوهشی

نویسندگان

• سپیده دولت آبادی ¹
• مهدی امیرآبادی زاده ¹
• مهدی زارعی ²

¹ دانشگاه بیرجند

² مرکز پژوهشی علوم جغرافیایی و مطالعات اجتماعی، دانشگاه حکیم سبزواری

https://doi.org/10.22067/jsw.2022.78598.1199

چکیده

در سال­های اخیر، آشکار شدن اثرات تغییراقلیم بر بخش­های مختلف از جمله منابع آب سبب شده مشکلات ناشی از آن به یکی از بحران­های اساسی مدیریت منابع آب کشور تبدیل شود. بنابراین کسب دانش کافی در خصوص اثرات تغییراقلیم بر فرآیندهای هیدرولوژیکی ضرورت دارد. این تحقیق، به مطالعه اثرات تغییراقلیم بر مؤلفه­های منابع آب حوضه نیشابور- رخ می­پردازد. در این راستا، شبیه­سازی هیدرولوژیکی حوضه در بازه زمانی 2017-1991 با استفاده از مدل WetSpass-M انجام شد. در گام بعد، پارامترهای اقلیمی شش مدل گردش کلی تحت سناریو RCP4.5 در دوره پایه توسط روش اصلاح اریبی چارک­ها ریزمقیاس و با روش اعتبارسنجی متقابل leave one out واسنجی و اعتبارسنجی گردید. با انجام رتبه­بندی و وزن‌دهی شش مدل اقلیمی انتخاب شده و جهت ارزیابی پاسخ هیدرولوژیکی حوضه به تغییراقلیم بازه زمانی 2052-2026، خروجی­های شش مدل گزارش پنجم گردش کلی تحت سناریو انتشار RCP4.5 و ریزمقیاس شده توسط روش اصلاح اریبی چارک­ها به صورت گروهی به مدل WetSpass-M وارد و پیش­نگری در آینده نزدیک انجام گرفت. نتایج نشان داد بارش و متوسط دمای سالانه حوضه در آینده نزدیک به ترتیب 66/4 درصد و 21/1 درجه سانتیگراد افزایش می­یابد. تحلیل مؤلفه­های منابع آب در آینده نزدیک نشان می­دهد رواناب کل، تغذیه آب زیرزمینی، تبخیرتعرق واقعی سالانه به ترتیب 9/5، 85/14، 42/1 درصد نسبت به دوره پایه افزایش و رواناب مستقیم و برگاب سالانه به ترتیب 15/15 و 54/3 درصد نسبت به دوره پایه کاهش خواهند داشت. با توجه به اهمیت و نقش عمده حوضه نیشابور در اقتصاد محصولات کشاورزی استان خراسان رضوی، نتایج پژوهش حاضر کمک شایان توجهی به مدیران و سیاست­گذاران مدیریت منابع آب کشور در جهت اتخاذ تصمیمات مناسب با هدف تقلیل اثرات تغییراقلیم بر منابع آب حوضه نیشابور-رخ خواهد نمود.

کلیدواژه‌ها

• تغذیه آب زیرزمینی
• تغییراقلیم
• رواناب
• مدل WetSpass-M
• نیشابور

20.1001.1.20084757.1401.36.5.7.7

موضوعات

• هواشناسی کشاورزی

عنوان مقاله [English]

Evaluation of WetSpass-M Model for Estimation of Hydrological Response of Neyshabur-Rookh Watershed to Climate Change of Future Years

نویسندگان [English]

• Sepideh Dowlatabadi ¹
• Mahdi Amirabadizadeh ¹
• Mahdi Zarei ²

¹ Water Science and Engineering, Water Resources, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran

² Research Centre of Social Studies & Geographical Sciences, Hakim Sabzevari University, Iran

چکیده [English]

Introduction
The sustainable availability of water resources and the qualitative and quantitative status of these resources are threatened by many natural and antropogenic factors, among which climate change plays an important role. Climate change can have profound effects on the hydrological cycle through changes in the amount and intensity of precipitation, evapotranspiration, soil moisture, and increasing temperature. On the other hand, the distribution of rainfall in different parts of the world will be uneven. So that some parts of the world may face a significant decrease in the amount and intensity of precipitation, as well as major changes in the timing of wet and dry seasons. Therefore, sufficient knowledge about the effects of climate change on hydrological processes and water resources will be of particular importance. In this research, as the first comprehensive study, the effect of future climate change on the water resources components of Neyshabur-Rookh watershed was investigated by a set of one hydrological model and six General Circulation Models under the RCP4.5 scenario.
Materials and Methods
The Neyshabur-Rookh watershed with an area of 9449 square kilometers is a sub-basin of Kavir-e Markazi-e Iran and a part of the Kalshoor Neyshabur watershed, which is located between of 58 degrees and 13 minutes and 59 degrees and 30 minutes and east longitude and 35 degrees and 40 minutes and 36 degrees and 39 minutes north latitude. The study area with an average altitude of 1549.6 m above sea level and average annual precipitation of 246.83 mm, a mean annual temperature of 13.3 Celsius has an arid to semi-arid climate. For hydrological simulation of the watershed using WetSpass-M model, maps of Digital Elevation Model (DEM), land-use, soil texture, slope, and distribution map of groundwater depth, Leaf Area Index (LAI), and climate data (rainfall, mean temperature, potential evapotranspiration, wind speed and the number of rainy days) per month in 1991-2017 period were used. Then the prepared model was calibrated and validated. The climatic data of six General Circulation Models (GCMs) under the RCP4.5 scenario (Representative Concentration Pathways) were downscaled using the Quantile Mapping Bias-Corrected method. The downscaled GCM models were ranked and weighted in each station according to results of the Leave one out cross validation method and utilized as an ensemble for projecting the near-future climatic conditions of the water resources components of the watershed. By importing the monthly maps of precipitation, average temperature and evapotranspiration in the period of 2026-2052 into the calibrated hydrological model, the hydrological response of watershed to near future climate change was determined and evaluated.
Results and Discussion
WetSpass-M was calibrated by changing the calibration parameters in five hydrometric stations and the compared measured and simulated streamflow. The values of four evaluation criteria NS, R2, MB, and RMSE indicated the good performance of the model during the calibration and validation process. By predicting climatic parameters in near future and preparing and importing maps of monthly precipitation, mean temperature, and evapotranspiration to WetSpass-M, the hydrologic simulation of the watershed was done in the 2026-2052 period. The results indicated that the mean annual temperature and precipitation would be respectively increased by 4.66% and 1.21°C under RCP4.5 in the near-future period compared to the baseline period. The average temperature will increase in all months so that the most changes will occur in September and the least changes will occur in March. The rainfall of the watershed will increase in March, April, May, October, and December and will decrease in the rest of the months. The highest and lowest rainfall changes will happen in April and August, respectively. The analysis of the components of water resources in the near future shows that annual total runoff, groundwater recharge, and actual evapotranspiration will increase by 5.9%, 14.85%, and 1.42% compared to the base period, and annual direct runoff and interception will decrease by 15.15% and 3.54%, respectively.
Conclusion
Considering the importance and major role of the Neyshabur watershed in the economy of agricultural products of Razavi Khorasan province, the results of this research will be of great help to the managers and policymakers of the country's water resources management in order to make appropriate decisions with the aim of reducing the effects of climate change on the water resources of the Neyshabur-Rookh Basin.

کلیدواژه‌ها [English]

• Climate change
• Recharge groundwater
• Runoff
• Neyshabur
• WetSpass-M model

مراجع

1. Abbaspour, K.C., Faramarzi, M., Seyed Ghasemi, S., & Yang, H. (2009). Assessing the impact of climate change on water resources in Iran. Water Resources Research 45(10). https://doi.org/10.1029/2008WR007615.
2. Abdollahi, K., Bashir, I., & Batelaan, O. (2012). WetSpass Graphical User Interface. Brussels: Vrije Universiteit Brussels Department of Hydrology and Hydraulic Engineering.
3. Abdollahi, K., Bashir, I., Verbeiren, B., Harouna, M.R., Griensven, A.V., Huysmans, M., & Batelaan, O. (2017). A distributed monthly water balance model: formulation and application on Black Volta Basin, Environmental Earth Sciences 76(198): 1-18. https://doi.org/10.1007/s12665-017-6512-1.
4. Almasi, P., Soltani, S., Goodarzi, M., & Modarres, R. (2017). Assessment the Impacts of Climate Change on Surface Runoff in Bazoft Watershed. Journal of Water and Soil Science 20(78): 39-52. http://jstnar.iut.ac.ir/article-1-3434-fa.html
5. Ansari, S., Massah Bavani, A., & Roozbahani, A. (2016). Effects of climate change on groundwater recharge (Case study: Sefid Dasht plain). Journal of Water and Soil 30(2): 416-431. (In Persian with English abstract)
6. Dakhlaoui, H., Ruelland, D., Tramblay, Y., & Bargaoui, Z. (2017). Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia. Journal of Hydrology 550: 201-217. https://doi.org/10.1016/j.jhydrol.2017.04.032.
7. Fereidoon, M., & Koch, M. (2018). SWAT-MODSIM-PSO optimization of multi-crop planning in the Karkheh River Basin, Iran, under the impacts of climate change. Science of The Total Environment 630: 502-516. http://doi.org/10.1016/j.scitotenv.2018.02.234.
8. Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, SC., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., & Rummukainen, M. (2013). Evaluation of climate models. in: climate change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
9. Gebremeskel, G., & Kebede, A. (2018). Estimating the effect of climate change on water resources: Integrated use of climate and hydrological models in the Werii watershed of the Tekeze river basin, Northern Ethiopia. Agriculture and Natural Resources 52(2): 195-207. https://doi.org/10.1016/j.anres.2018.06.010.
10. Gudmundsson, L., Bremnes, J.B., Haugen, J.E., & Engen-Skaugen, T. (2012). Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations- a comparison of methods. Hydrology and Earth System Sciences 16: 3383-3390. https://doi.org/10.5194/hess-16-3383-2012.
11. Hargreaves, G.H., & Samani, Z.A. (1985). Reference crop evapotranspiration from ambient air temperature, American Society of Agricultural and Biological Engineers. https://doi.org/10.13031/2013.26773.
12. Hashemi, H., Uvo C, B., & Berndtsson, R. (2015). Coupled modeling approach to assess climate change impacts on groundwater recharge and adaptation in arid areas. Hydrology and Earth System Sciences 19(10): 4165–4181. https://doi.org/10.5194/hess-19-4165-2015.
13. Hastie, T., Tibshirani, R., & Freidman, J.H. (2008). The Elements of Statistical Learning. Springer Series in Statistics.
14. Kahsay, K.D., Pingale, S.M., & Hatiye, S.D. (2018). Impact of climate change on groundwater recharge and base flow in the sub-catchment of Tekeze basin, Ethiopia. Groundwater for Sustainable Development 6: 121-133. https://doi.org/10.1016/j.gsd.2017.12.002.
15. Lawrence Livermore National Laboratory - Green Data Oasis Available athttp://gdo-dcp.ucllnl.org/downscaled_cmip_projections/dcpInterface.html.
16. Mengistu, D., Bewket, W., Dosio, A., & Pantiz, H.J. (2021). Climate change impacts on water resources in the Upper Blue Nile (Abay) River Basin, Ethiopia. Journal of Hydrology https://doi.org/10.1016/j.jhydrol.2020.125614.
17. 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. American Society of Agricultural and Biological Engineers 50(3): 885-900. https://doi.org/10.13031/2013.23153.
18. Ougahi, J.H., Cutler, ME.J., & Cook. SJ. (2022). Modelling climate change impact on water resources of the Upper Indus Basin. Journal of Water & Climate Change 13(2): 482-504. https://doi.org/10.2166/wcc.2021.233.
19. Safari Shad, M., Habibnejad Roshan, M., Solaimani, K., Ildoromi, A., & Zeinivand, H. (2017). The potential effects of the climate change on the river flow in Hamadan watershed-Bahar. Hydrogeomorphology 4(10): 81-98. (In Persian with English abstract)
20. Sharafati, A., Haji Seyed Asadollahi, S.B., & Shahbazi, A. (2021). Assessing the impact of climate change on urban water demand and related uncertainties: a case study of Neyshabur, Iran. Theoretical and Applied Climatology 145: 473-487. https://doi.org/10.1007/s00704-021-03638-5
21. Shrestha, S., Bach, T.V., & Pandey, V.P. (2016). Climate change impacts on groundwater resources in Mekong Delta under representative concentration pathways (RCPs) scenarios. Environmental Science & Policy 6: 1-13. https://doi.org/10.1016/j.envsci.2016.03.010.
22. Tan, M.L., Ibrahim, A.L., Yusop, Z., Chua, V.P., & Chan, N.W. (2017). Climate change impacts under CMIP5 RCP scenarios on water resources of Kelantan River Basin, Malaysia. Atmospheric Research 189: 1-10. https://doi.org/10.1016/g.atmosres.2017.01.008.
23. Wang, Y., Liao, W., Ding, Y., Wang, X., Jiang, Y., Song, X., & Lei, X. (2015). Water resources spatiotemporal pattern evaluation of the upstream Yangtze River corresponding to climate changes. Quaternary International 380: 187-196. https://doi.org/10.1016/j.quaint.2015.02.023.
24. Wang, Y., Sivandran, G., & Bielicki, J.M. (2017). The stationarity of two statistical downscaling methods for precipitation under different choices of cross-validation periods. International Journal of Climatology 38(5): 330-348. https://doi.org/10.1002/joc.5375.
25. Zhang, J., Wang, G., He, R., & Liu, C. (2009). Variation trends of runoffs in the Middle Yellow River basin and its response to climate change. Advances in Water Science 20(2): 153-158.