Hydrological drought monitoring in the shoor river catchment area using the streamflow drought index (SDI)

Document Type : Applied Article

Authors

1 Ph.D Student of Climatology, Department of Geography, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

2 Assistant Professor, Department of Urban Planning, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran

3 Associate Professor, Department of Geography, Science and Research Branch, Islamic Azad University, Tehran, Iran

4 Assistant Professor, Department of Geography, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

10.22059/jhsci.2025.399292.888

Abstract

Objective: Hydrological drought is a part of the natural flow regime, but severe and prolonged events can lead to reduced river flows, limiting human uses and diminishing environmental flow availability. the aim of this study is to assess hydrological drought in the shoor river catchment area using the streamflow drought index (SDI).
Method: In this study, the status of hydrological drought in the shoor river catchment area was assessed using the streamflow drought index (SDI) on monthly and annual scales during the statistical period 1983–2023. for this purpose, annual precipitation data from the Masjedsoleyman synoptic station and annual discharge data from the dasht bozorg hydrometric station in the shoor river catchment area were used. the Mann–Kendall test was also used to determine the trend of discharge variations.
Results: The results of the streamflow trend analysis using the Mann–Kendall test indicated a decreasing trend in basin discharge at a 95% confidence level. the results of the streamflow drought index (SDI) indicate that during the early years of the statistical study period (1983–1999), the dasht bozorg hydrometric station generally experienced either no drought or intermittent mild droughts, and from the year 2000 to the end of the statistical period, the severity of droughts has increased. in general, the final years of the study period were associated with more severe drought conditions.
Conclusions: The results indicate that severe and extreme droughts did not occur at this station during the study period, and in most cases mild drought or no drought conditions prevailed.

Keywords


  • احراری، سعیده؛ و رجا، امید (1404). بررسی شاخص‌های خشکسالی هواشناسی، کشاورزی و هیدرولوژیکی در دشت مهاباد. مدیریت آب در کشاورزی، 12(1)، 29-48.
  • پرچمی، ناهیده؛ مصطفی‌زاده، رئوف؛ اسمعلی، اباذر؛ و ایمانی، رسول (1401). تغییرات مکانی خشکسالی هیدرولوژیک جریان در مقیاس‌های مختلف زمانی در رودخانه‌های استان اردبیل. هیدروژئومورفولوژی، 9(33)، 21-36.https://doi:10.2203 4/hyd.2022.51550.1637
  • جهانگیر، محمدحسین؛ بابایی، سحر؛ و نوروزی، اقبال (1398). ارزیابی وضعیت خشکسالی استان کرمانشاه با استفاده از شاخص خشکسالی جریان رودخانه (SDI). آبیاری و زهکشی ایران، 13(1)، 190-202. https://doi.org/20.1001.1.2 0087942.1398.13.1.17.3
  • حیدری مطلق، آرین؛ سبزواری، یاسر؛ و نصرالهی، علی (1397). تحلیل روند خشکسالی هیدرولوژیکی با استفاده از شاخص SDI در حوضۀ آبریز رودخانۀ الشتر. هفتمین همایش ملی سامانه‌های سطوح آبگیر باران با محوریت استحصال آب باران و مدیریت بحران آب، خشکسالی و گردوغبار، پژوهشکدۀ حفاظت خاک و آبخیزداری- انجمن سیستم‌های سطوح آبگیر باران، تهران.
  • سهیلی، اسماعیل؛ ملکی‌نژاد، حسین؛ و اختصاصی، محمدرضا (1396). تحلیل روند خشکسالی‌های هواشناسی و هیدرولوژیکی در مناطق نیمه‌خشک ایران (مطالعۀ موردی: حوزۀ آبخیز سد درودزن). مدیریت بیابان. 5(9)، 31-45. https://doi.org/ 10.22034/jdmal.2017.27914
  • صلاحی، برومند؛ و وطن‌پرست قلعه‌جوق، فاطمه (1403). پایش خشکسالی کشاورزی در حوضۀ آبریز رودخانۀ ارس با استفاده از شاخص‌های ماهواره‌ای و هواشناسی. مدیریت مخاطرات محیطی، (3)، 193-212. https://doi.org/10.22059/jhsci.20 24.384523.847
  • Amini, H., Esmali-Ouri, A., Mostafazadeh, R., Sharari, M., & Zabihi, M. (2019). Hydrological drought response of regulated river flow under the influence of dam reservoir in Ardabil Province. Earth and Space Physics, 45(2):473-486. https://doi.org/10.22059/jesphys.2019.272671.1007078 (In Persian)
  • Araghinejad, S. (2013). Data-driven modeling: using MATLAB® in water resources and environmental engineering 67. Springer Science & Business Media. https://link.springer.com/ book/10.1007/978-94-007-7506-0
  • Eroğluer, T. A., & Apaydin, H. (2022). Estimation of drought by Streamflow Drought Index (SDI) and Artificial Neural Networks (ANNs) in Ankara-Nallihan region. Turkish Journal of Agriculture- Food Science and Technology, 8(2):348. https://doi.org/10.24925/turjaf.v8i2.348-357.3045
  • Faraji Amoqein, A., Kanooni, A., & Hasanpour Kashani, M. (2024). Investigating meteorological and hydrological drought characteristics and their propagation relationship under the influence of human activities in Ardabil plain. Journal of Water and Irrigation Management. https://doi.org/10. 22059/jwim.2024.371936.1141 (In Persian)
  • Guhathakurta, P., Menon, P., Mazumdar, A. B., & Sreejith, O. P. (2010). Changes in extreme rainfall events and flood risk in India during the last century. National Climatic Centre, RR (3).
  • Hasan, H. H., Mohd Razali, S. F., Muhammad, N. S., & Ahmad, A. (2021). Hydrological drought across Peninsular Malaysia: implication of drought index. Natural Hazards and Earth System Sciences. https://doi.org/10.5194/nhess-2021-249
  • Khorooshi, S., Mostafazadeh, R., Esmali Ouri, A., & Raoof, M. (2017). ‌Spatiotemporal assessment of the hydrologic river health index variations in Ardabil Province Watersheds. Journal of Ecohydrology, 4(2):379-393. https://doi.org/10.22059/ije.2017.61475 (In Persian)
  • Ma, M., Ren, L., Singh, V. P., Yuan, F., Chen, L., Yang, X., & Liu, Y. (2016). Hydrologic model-based Palmer indices for drought characterization in the Yellow River basin, China. Stochastic Environmental Research and Risk Assessment, 30(5):1401–1420. https://doi.org/10.1007/s00477-015-1136-z
  • Mesbahzadeh, T., & Soleimani Sardoo, F. (2018). Temporal Trend Study of Hydrological and Meteorological Drought in Karkheh Watershed. Iran-Watershed Management Science and Engineering, 12(40):105-114. https://doi.org/20.1001.1.20089554.1397.12.40.12.9 (In Persian)
  • Minh, H. V. T., Kumar, P., Van Toan, N., Nguyen, P. C., Van Ty, T., Lavane, K., & Downes, N. K. (2024). Deciphering the relationship between meteorological and hydrological drought in Ben Tre province, Vietnam. Natural Hazards.120(6):5869-5894.https://doi.org/10.1007/s11069-024-06437-z
  • Mishra, A. K., & Desai, V. R. (2005). Drought forecasting using stochastic models. Stochastic Environment Research Risk Assessment, 19:326-339. https://doi.org/10.1007/s00477-005-0238-4
  • Moghimi Ebrahim,(2021) River Ecogeomorphology and their lows, University of Tehran press,
  • Nalbantis, I., & Sakiris, G. T. (2009). Assessment of hydrological drought revisited:Water Resources Management, 23(5):881-897. https://doi.org/10.1007/s11269-008-9305-1
  • Pandhumas, T., Kuntiyawichai, K., Jothityangkoon, C., & Suryadi, F. X. (2020). Assessment of climate change impacts on drought severity using SPI and SDI over the Lower Nam Phong River Basin, Thailand. Engineering and Applied Science Research, 47(3):326–338. https://ph01.tci-thaijo. org/index.php/easr/article/view/234800
  • Sarwar‚ A. N., Waseem‚ M., Azam‚ M., Abbas‚ A., Ahmad‚ I., Lee‚ J. E., & Haq‚ F. U. (2022). Shifting of Meteorological to Hydrological Drought Risk at Regional Scale. Applied Sciences12(11):5560. https://doi.org/10.3390/app12115560
  • Tabari, H., Nikbakht, J., & Hosseinzadeh Talaee, P. H. (2013). Hydrological drought assessment in northwestern Iran based on Streamflow Drought Index (SDI). Water Resources Management 27:137–151. https://doi.org/10.1007/s11269-012-0173-3 (In Persian)
  • Wang, M., Jiang, Sh., Ren, L., Xu, Ch., Menzel, L., Yuan, F., Xu, Q., Liu, Y., & Yang, X. (2021). Separating the effects of climate change and human activities on drought propagation via a natural and human-impacted catchment comparison method. Journal of Hydrology, 603, Part A, 126913. https://doi.org/10.1016/j.jhydrol.2021.126913
  • Yao, N., Zhao, H., Li, Y., Biswas, A., Feng, H., Liu, F., & Pulatov, B. (2020). National-scale variation and propagation characteristics of meteorological, agricultural, and hydrological droughts in China. Remote Sensing, 12(20):3407. https://doi.org/10.3390/rs12203407