سامانه پشتیبانی خدمات اطلاعات

  اخبار و اعلانات

 آمار

تعداد نشریات158
تعداد شماره‌ها6,230
تعداد مقالات67,764
تعداد مشاهده مقاله115,147,382
تعداد دریافت فایل اصل مقاله89,908,174
بهزادی, فرهاد, جوادی, سامان, یوسفی, حسین, مریدی, علی. (1401). بررسی و تحلیل اثر خشکسالی بر سفره‌های آب زیرزمینی در ایران (مطالعه موردی دشت شهرکرد). , 12(2), 327-348. doi: 10.22059/jwim.2022.341590.982
فرهاد بهزادی; سامان جوادی; حسین یوسفی; علی مریدی. "بررسی و تحلیل اثر خشکسالی بر سفره‌های آب زیرزمینی در ایران (مطالعه موردی دشت شهرکرد)". , 12, 2, 1401, 327-348. doi: 10.22059/jwim.2022.341590.982
بهزادی, فرهاد, جوادی, سامان, یوسفی, حسین, مریدی, علی. (1401). 'بررسی و تحلیل اثر خشکسالی بر سفره‌های آب زیرزمینی در ایران (مطالعه موردی دشت شهرکرد)', , 12(2), pp. 327-348. doi: 10.22059/jwim.2022.341590.982
بهزادی, فرهاد, جوادی, سامان, یوسفی, حسین, مریدی, علی. بررسی و تحلیل اثر خشکسالی بر سفره‌های آب زیرزمینی در ایران (مطالعه موردی دشت شهرکرد). , 1401; 12(2): 327-348. doi: 10.22059/jwim.2022.341590.982

بررسی و تحلیل اثر خشکسالی بر سفره‌های آب زیرزمینی در ایران (مطالعه موردی دشت شهرکرد)

مدیریت آب و آبیاری
دوره 12، شماره 2، تیر 1401، صفحه 327-348    اصل مقاله (5.26 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22059/jwim.2022.341590.982
نویسندگان
فرهاد بهزادی1؛ سامان جوادی* 2؛ حسین یوسفی3؛ علی مریدی4
1دانشجوی کارشناسی ارشد منابع آب، گروه مهندسی آب، دانشکدگان ابوریحان، دانشگاه تهران، تهران، ایران.
2دانشیار، گروه مهندسی آب، دانشکدگان ابوریحان، دانشگاه تهران، تهران، ایران.
3دانشجوی دکتری منابع آب، گروه مهندسی منابع آب، دانشکده عمران، آب و محیط زیست، دانشگاه شهید بهشتی، تهران، ایران.
4استادیار، گروه مهندسی منابع آب، دانشکده عمران، آب و محیط زیست، دانشگاه شهید بهشتی، تهران، ایران.
چکیده
آب زیرزمینی همواره یکی از باارزش‌ترین منابع آبی در هر منطقه به‌شمار می‌رود و در بسیاری از مناطق خشک و نیمه‌خشک جهان نظیر کشور ایران، اصلی‌ترین منبع جهت تأمین نیازهای شرب و کشاورزی محسوب می‌شود. در سالیان اخیر، با افزایش جمعیت و در نتیجه افزایش برداشت از آبخوان‌ها و تغییرات اقلیمی، تراز آب زیرزمینی در بسیاری از آبخوان‌های ایران همواره نزولی بوده و بسیاری از آبخوان‌های کشور در شرایط وخیم قرار دارند و این شرایط در بسیاری از آبخوان‌های کشور ادامه‌دار بوده یا شرایط در حال بدترشدن است. در همین راستا همواره پایش منظم وضعیت آبخوان‌ها از اهمیت بالایی برخوردار است و با اتخاذ تصمیم‌های مدیریتی مناسب می‌توان از آسیب‌دیدن هرچه بیش‌تر آبخوان‌ها جلوگیری کرد و همواره خسارت را کاهش داد. هدف این پژوهش تعیین خشک‌سالی‌های دوره آتی و تعیین تأثیر آن بر آبخوان دشت شهرکرد می‌باشد. در این پژوهش با استفاده از برونداد مدل‌های CMIP6 در ابتدا متغیرهای اقلیمی نظیر بارندگی و دما برای دوره آتی شبیه‌سازی شده و وضعیت بارندگی در منطقه تا سال 2100 تعیین شده است. در ادامه با استفاده از مدل ANFIS، عمق آب زیرزمینی در پنج پیزومتر منتخب در سطح دشت تا سال 2050 پیش‌بینی شده است. با توجه به نتایج این پژوهش، وضعیت آبخوان دشت شهرکرد تا سال 2050 تعیین شده و مشخص شده است در برخی از نقاط دشت شهرکرد، عمق آب زیرزمینی تا 26 متر افزایش پیدا خواهد کرد. از این‌رو، با توجه به تغییرات محتمل در آینده‌ای نه چندان دور و به‌منظور جلوگیری از وخیم‌ترشدن شرایط و افزایش خسارت‌ها، باید تصمیم‌های مدیریتی مناسبی در این منطقه اتخاذ شود.
کلیدواژه‌ها
بارندگی؛ دما؛ ANFIS؛ GRI؛ SPI
عنوان مقاله [English]
Investigation and analysis the effect of drought on groundwater aquifers in Iran (Case study: Shahrekord plain)
نویسندگان [English]
Farhad Behzadi1؛ saman Javadi2؛ Hossein Yousefi3؛ Ali Moridi4
1M.Sc. Student of Water Resources, Department of Water Engineering, College of Aburaihan, University of Tehran, Tehran, Iran.
2Associate Professor, Department of Water Engineering, College of Aburaihan, University of Tehran, Tehran, Iran.
3Ph.D. Student of Water Resources Engineering, Department of Water Resources Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
4Assistant Professor, Department of Environmental Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
چکیده [English]
Groundwater is the most valuable water resources in any region and in many arid and semi-arid regions of the world, such as Iran, is the main source for drinking and agricultural needs. In recent years, with the increase in population and as a result of increasing withdrawals from aquifers and climate change, many of aquifers are in poor condition, and these conditions continue or are deteriorating. In this regard, regular monitoring of aquifers is always very important and by making appropriate management decisions, it is possible to prevent more damage to aquifers and reduce the damage. The purpose of this study is to determine the droughts of the future and to determine its impact on the aquifer of Shahrekord plain. In this study, using the output of CMIP6 models, climatic variables such as rainfall and temperature for the next period are simulated and the rainfall situation in the region until 2100 has been determined. Then, using the ANFIS model, groundwater depth in five selected piezometers in the plain is predicted by 2050. According to the results of this study, the aquifer condiotion of Shahrekord plain has been determined by 2050 and it has been determined that in some parts of Shahrekord plain, the groundwater depth will increase to 26 meters. Due to possible changes in the future in order to prevent the situation from deteriorating and increasing the damage, appropriate management decisions must be made in this regard.
کلیدواژه‌ها [English]
ANFIS, GRI, Precipitation, SPI, Temperature
مراجع
  1. Akinsanola, A. A., Ongoma, V., & Kooperman, G. J. (2021). Evaluation of CMIP6 models in simulating the statistics of extreme precipitation over Eastern Africa. Atmospheric Research, 254, 105509.
  2. Ahmadi Akhormeh, M., Nohegar, A., Soleimani Motlagh, M., & Taie Samiromi, M. (2015). Groundwater Drought Investigating using SWI and GRI Indices) Case Study: Marvdasht Kharameh Aquifer). Iranian Journal of Irrigation and Water Engineering, 6(1), 105-118. (In Persian)
  3. Klutse, N. A. B., Quagraine, K. A., Nkrumah, F., Quagraine, K. T., Berkoh-Oforiwaa, R., Dzrobi, J. F., & Sylla, M. B. (2021). The climatic analysis of summer monsoon extreme precipitation events over West Africa in CMIP6 simulations. Earth Systems and Environment, 5(1), 25-41.
  4. Ashraf, S., AghaKouchak, A., Nazemi, A., Mirchi, A., Sadegh, M., Moftakhari, H. R., ... & Mallakpour, I. (2019). Compounding effects of human activities and climatic changes on surface water availability in Iran. Climatic Change, 152(3), 379-391.
  5. Auer, C., Kriegler, E., Carlsen, H., Kok, K., Pedde, S., Krey, V., & Müller, B. (2021). Climate change scenario services: From science to facilitating action. One Earth, 4(8), 1074-1082.
  6. Bağçaci, S. Ç., Yucel, I., Duzenli, E., & Yilmaz, M. T. (2021). Intercomparison of the expected change in the temperature and the precipitation retrieved from CMIP6 and CMIP5 climate projections: A Mediterranean hot spot case, Turkey. Atmospheric Research, 256, 105576.
  7. Bhardwaj, K., & Mishra, V. (2021). Drought detection and declaration in India. Water Security, 14, 100104.
  8. Bloomfield, J. P., & Marchant, B. P. (2013). Analysis of groundwater drought building on the standardised precipitation index approach. Hydrology and Earth System Sciences, 17(12), 4769-4787.
  9. Bloomfield, J. P., Marchant, B. P., Bricker, S. H., & Morgan, R. B. (2015). Regional analysis of groundwater droughts using hydrograph classification. Hydrology and Earth System Sciences, 19(10), 4327-4344.
  10. Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., ... & Vuichard, N. (2020). Presentation and evaluation of the IPSL‐CM6A‐LR climate model. Journal of Advances in Modeling Earth Systems, 12(7), e2019MS002010.
  11. Brêda, J. P. L. F., de Paiva, R. C. D., Collischon, W., Bravo, J. M., Siqueira, V. A., & Steinke, E. B. (2020). Climate change impacts on South American water balance from a continental-scale hydrological model driven by CMIP5 projections. Climatic Change, 159(4), 503-522.
  12. Costa, D., Zhang, H., & Levison, J. (2021). Impacts of climate change on groundwater in the Great Lakes Basin: A review. Journal of Great Lakes Research, 47(6), 1613-1625.
  13. Dell, M., Jones, B. F., & Olken, B. A. (2012). Temperature shocks and economic growth: Evidence from the last half century. American Economic Journal: Macroeconomics, 4(3), 66-95.
  14. Ekrami, M., Fathimarj, A., Barkhordaeu, J. (2015). Assessment Agricultural Drought Vulnerability In Arid and S-arid climates using GIS and AHP, A Case Study for Taft Township, Yazd province, Iran. Iranian Journal of Irrigation and Water Engineering, 5(4), 107-117. (In Persian)
  15. Emamgholizadeh, S., Moslemi, K., & Karami, G. (2014). Prediction the groundwater level of bastam plain (Iran) by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Iranian Journal of Water Resources Management, 28(15), 5433-5446. (In Persian)
  16. Gerten, D., Rost, S., von Bloh, W., & Lucht, W. (2008). Causes of change in 20th century global river discharge. Geophysical Research Letters, 35(20).
  17. Guenang, G. M., & Mkankam Kamga, F. (2014). Computation of the standardized precipitation index (SPI) and its use to assess drought occurrences in Cameroon over recent decades. Journal of Applied Meteorology and Climatology, 53(10), 2310-2324.
  18. Hassan, W. H. (2020). Climate change impact on groundwater recharge of Umm er Radhuma unconfined aquifer Western Desert, Iraq. International Journal of Hydrology Science and Technology, 10(4), 392-412.
  19. Lloyd‐Hughes, B., & Saunders, M. A. (2002). A drought climatology for Europe. International Journal of Climatology, 22(13), 1571-1592.
  20. Hong, J., Javan, K., Shin, Y., & Park, J. S. (2021). Future Projections and Uncertainty Assessment of Precipitation Extremes in Iran from the CMIP6 Ensemble. Atmosphere, 12(8), 1052.
  21. Hosseinzadeh, M. M., & Nohegar, A. (2011). Studying the Effect of Drought on Water Resources over Two Decades and Occurrences of the Sinking Phenomenon in Minab Plain. Iranian Journal of Environmental Science, 9(1), 75-98. (In persian)
  22. Huang, J., Cao, L., Yu, F., Liu, X., & Wang, L. (2021). Groundwater drought and cycles in Xuchang City, China. Frontiers in Earth Science, 9, 831.
  23. Javadinejad, S., Dara, R., & Jafary, F. (2020). Evaluation of hydro-meteorological drought indices for characterizing historical and future droughts and their impact on groundwater. Resources Environment and Information Engineering, 2(1), 71-83.
  24. Kamworapan, S., Thao, P. T. B., Gheewala, S. H., Pimonsree, S., & Prueksakorn, K. (2021). Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century. Heliyon, 7(11), e08263.
  25. Kaur, N., Kaur, S., Kaur, P., & Aggarwal, R. (2021). Impact of climate change on groundwater levels in Sirhind Canal Tract of Punjab, India. Groundwater for Sustainable Development, 15, 100670.
  26. Kaur, N., Tech, M., Kaur, S., Kaur, P., Ph, D., & Aggarwal, R. (2021). Groundwater for Sustainable Development Impact of climate change on groundwater levels in Sirhind Canal Tract of. Groundwater for Sustainable Development, 15(August 2020), 100670.
  27. Khosravi, A., Mirabbasi, R., Samadi Boroujeni, H., & Ghasemi Dastgerdi, A. R. (2019). Monitoring and Forecasting of Groundwater Drought Using Groundwater Resource Index (GRI) and First to Third-Order Markov Chain Models (Case study: Boroujen Plain). Iranian Journal of Water and Soil Conservation, 26(2), 117-136. (In Persian)
  28. Kumar, R., Musuuza, J. L., Van Loon, A. F., Teuling, A. J., Barthel, R., Ten Broek, J., ... & Attinger, S. (2016). Multiscale evaluation of the Standardized Precipitation Index as a groundwater drought indicator. Hydrology and Earth System Sciences, 20(3), 1117-1131.
  29. Lloyd‐Hughes, B., & Saunders, M. A. (2002). A drought climatology for Europe. International Journal of Climatology, 22(13), 1571-1592.
  30. McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology, 17(22), 179-183. Boston.
  31. Mechoso, C. R., Arakawa, A., & Angeles, L. (2015). General Circulation Models. In Encyclopedia of Atmospheric Sciences 2nd Edition (Second Edition, Vol. 4). Elsevier.
  32. Mendicino, G., Senatore, A., & Versace, P. (2008). A Groundwater Resource Index (GRI) for drought monitoring and forecasting in a Mediterranean climate. Journal of Hydrology, 357(3-4), 282-302.
  33. Mesbah Zadeh, T., & Soleymani Sardoo, F. (2018). Assessment of the temporal and spatial pattern of meteorology and hydrogeology drought in arid and desert regions (Case study: Bam plain). Iranian Journal of Rangeland and Desert Research, 25(2), 366-377. (In Persian)
  34. Mishra, A. K., & Singh, V. P. (2010). Review paper A review of drought concepts. Journal of Hydrology, 391(1-2), 202-216.
  35. Nashwan, M. S., & Shahid, S. (2022). Future precipitation changes in Egypt under the 1.5 and 2.0°C global warming goals using CMIP6 multimodel ensemble. Atmospheric Research, 265, 105908.
  36. Nayyeri, M., Hosseini, S. A., Javadi, S., & Sharafati, A. (2021). Spatial differentiation characteristics of groundwater stress index and its relation to land use and subsidence in the Varamin Plain, Iran. Natural Resources Research, 30(1), 339-357.
  37. Ritchie, M., Frazier, T., Johansen, H., & Wood, E. (2021). Early climate change indicators in the Arctic: A geographical perspective. Applied Geography, 135, 102562.
  38. Roshun, S. H., & Habibnejad Roshan, M. (2018). Monitoring of temporal and spatial variation of groundwater drought using GRI and SWI indices (Case study: Sari-Neka plain). Iranian Journal of Watershed Management Research, 9(17), 269-279. (In Persian)
  39. Saeedi Razavi, B., & Arab, A. (2019). Groundwater Level Prediction of Ajabshir Plain using Fuzzy Logic, Neural Network Models and Time Series. Iranian Journal of Hydrogeology, 3(2), 69-81. (In Persian)
  40. Sanginabadi, H., Saghafian, B., & Delavar, M. (2019). Monitoring and assessing the characteristics of groundwater drought in aquifers with negative balance. Iranian Journal of Iran-Water Resources Research, 15(3), 155-166. (In Persian)
  41. Schreiner-McGraw, A. P., & Ajami, H. (2021). Delayed response of groundwater to multi-year meteorological droughts in the absence of anthropogenic management. Journal of Hydrology, 603, 126917.
  42. Sharafi, L., Zarafshani, K., Keshavarz, M., Azadi, H., & Van Passel, S. (2020). Drought risk assessment: Towards drought early warning system and sustainable environment in western Iran. Ecological Indicators, 114, 106276.
  43. Seidenfaden, I. K., Jensen, K. H., & Sonnenborg, T. O. (2021). Climate change impacts and uncertainty on spatiotemporal variations of drought indices for an irrigated catchment. Journal of Hydrology, 601, 126814.
  44. Sobhani, B., Eslahi, M., & Babaeian, I. (2017). Comparison of statistical downscaling in climate change models to simulate climate elements in Northwest Iran. Iranian Journal of Physical Geography Research Quarterly, 49(2), 301-325. (In Persian)
  45. Song, Z., Xia, J., She, D., Li, L., Hu, C., & Hong, S. (2021). Assessment of meteorological drought change in the 21st century based on CMIP6 multi-model ensemble projections over mainland China. Journal of Hydrology, 601, 126643.
  46. Swart, N. C., Cole, J. N., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., ... & Winter, B. (2019). The Canadian earth system model version 5 (CanESM5. 0.3). Geoscientific Model Development, 12(11), 4823-4873.
  47. Trambauer, P., Maskey, S., Werner, M., Pappenberger, F., Van Beek, L. P. H., & Uhlenbrook, S. (2014). Identification and simulation of space–time variability of past hydrological drought events in the Limpopo River basin, southern Africa. Hydrology and Earth System Sciences, 18(8), 2925-2942.
  48. Tramblay, Y., Koutroulis, A., Samaniego, L., Vicente-Serrano, S. M., Volaire, F., Boone, A., ... & Polcher, J. (2020). Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth-Science Reviews, 210, 103348.Vaghefi, S. A., Keykhai, M., Jahanbakhshi, F., & Sheikholeslami, J. (2019). The future of extreme climate in. Scientific Reports, December 2018, 1-11. https://doi.org/10.1038/s41598-018-38071-8
  49. Van Lanen, H. A. (2006). Drought propagation through the hydrological cycle. IAHS publication, 308, 122.
  50. Venturini, A. (2022). Climate change, risk factors and stock returns: A review of the literature. International Review of Financial Analysis, 79, 101934.
  51. Wanders, N., van Lanen, H. A., & van Loon, A. F. (2010). Indicators for drought characterization on a global scale(No. 24). Wageningen Universiteit.
  52. Wang, D., Liu, J., Shao, W., Mei, C., Su, X., & Wang, H. (2021). Comparison of CMIP5 and CMIP6 Multi-Model Ensemble for Precipitation Downscaling Results and Observational Data: The Case of Hanjiang River Basin. Atmosphere, 12(7), 867.
  53. Wang, T., Tu, X., Singh, V. P., Chen, X., & Lin, K. (2021). Global data assessment and analysis of drought characteristics based on CMIP6. Journal of Hydrology, 596, 126091.
  54. Wen, X., Feng, Q., Yu, H., Wu, J., Si, J., Chang, Z., & Xi, H. (2015). Wavelet and adaptive neuro-fuzzy inference system conjunction model for groundwater level predicting in a coastal aquifer. Neural Computing and Applications, 26(5), 1203-1215.
  55. Wilhite, D. A., & Glantz, M. H. (1985). Understanding: the drought phenomenon: the role of definitions. Water International, 10(3), 111-120.
  56. Xu, Y., Zhang, X., Hao, Z., Hao, F., & Li, C. (2021). Projections of future meteorological droughts in China under CMIP6 from a three‐dimensional perspective. Agricultural Water Management, 252, 106849.
  57. Zandifar, S., Fijani, E., Naeimi, M., & Khosroshahi, M. (2020). Spatiotemporal variations of groundwater drought indices, Case study: Zohreh-Jarrahi watershed. Iranian Journal of Hydrogeology, 4(2), 108-130. (In Persian)
  58. Zarrin, A., & Dadashi-Roudbari, A. (2021). Projection of future extreme precipitation in Iran based on CMIP6 multi-model ensemble. Theoretical and Applied Climatology, 144(1), 643-660.
  59. Zhang, G., Su, X., Singh, V. P., & Ayantobo, O. O. (2021). Appraising standardized moisture anomaly index (SZI) in drought projection across China under CMIP6 forcing scenarios. Journal of Hydrology: Regional Studies, 37, 100898.
  60. Zhao, X., Huang, G., Li, Y., Lin, Q., Jin, J., Lu, C., & Guo, J. (2021). Projections of meteorological drought based on CMIP6 multi-model ensemble: A case study of Henan Province, China. Journal of Contaminant Hydrology, 243, 103887.
آمار
تعداد مشاهده مقاله: 508
تعداد دریافت فایل اصل مقاله: 376


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب