ارزیابی ارتباط بین خشک‌سالی هواشناسی و پوشش گیاهی زمین‌های دیم در استان لرستان

نوع مقاله : پژوهشی

نویسندگان

1 دانش‌آموخته‌ی گروه تخصصی عمران آب، دانشکده عمران، معماری و هنر، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران

2 عضو هیأت علمی پژوهشکده حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران

3 عضو هیأت علمی دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، گروه عمران آب، تهران، ایران

چکیده

تأثیرپذیری پوشش گیاهی از خشک‌سالی هواشناسی و ارتباط آن‌ها با هم در استان لرستان با کاربرد شاخص خشک‌سالی هواشناسی (بارش بمعیار) برای 28 ایستگاه باران‌سنجی در سال­های 1366-1396 بررسی شد. با کاربرد روش سنجش‌ازدور و سنجنده­ی مودیس شاخص اختلاف بهنجارشده‌ی پوشش گیاهی در سال­های 2000-2017 استخراج، و شاخص وضعیت پوشش گیاهی محاسبه شد. با کاربرد نتیجه‌های شاخص بارش بمعیار، سال­های خشک، بهنجار، و مرطوب محاسبه و سال شاخص برای آن‌ها انتخاب شد. همبستگی بین بارش بمعیار و وضعیت پوشش گیاهی با وایازی خطی بررسی‌شد. نتیجه‌ها نشان داد که بیش‌ترین ضریب همبستگی پیرسون میان وضعیت پوشش گیاهی اسفند با بارش بمعیار آبان برای دوره‌ی 9 ماهه است (0/64)، و مقدار ضریب همبستگی میان وایازی خطی شش‌متغیره بین شش ماه بارش بمعیار با وضعیت پوشش گیاهی خرداد 0/7 به‌دست آمد. نتیجه‌های وایازی خطی چندمتغیره نشان داد که بارش بمعیار در بازه­ی زمانی 9 و12 ماهه با وضعیت پوشش گیاهی همبستگی معناداری در تراز 5% دارد. برای بررسی تطابق رده‌­های خشک‌سالی شاخص بارش بمعیار با وضعیت پوشش گیاهی چهارچوب درهمی به‌کار برده شد. نتیجه‌ها نشان داد که بیش‌ترین تطابق وضعیت پوشش گیاهی با شاخص بارش بمعیار در رده‌ی خشک‌سالی متوسط است. به‌طور کلی نتیجه‌ها نشان‌دهنده‌ی تاخیر زمانی نه‌ماهه‌ی خشک‌سالی هواشناسی با خشک‌سالی ماهواره‌یی وضعیت پوشش گیاهی و معناداری در تراز 5% شاخص بارش بمعیار با وضعیت پوشش گیاهی است، که نشان می­دهد در نبود شاخص­های هواشناسی ممکن است وضعیت پوشش گیاهی برای بررسی خشک‌سالی منطقه به‌کار برده شود.

کلیدواژه‌ها

عنوان مقاله [English]

An Assessment of the Relationships between Meteorological Drought Index and Vegetation Condition in Dry Farming in the Province of Lorestan

نویسندگان [English]

  • Tahereh Sadat Mirmohammadhosseini 1
  • Bagher Ghermezcheshmeh 2
  • Seyed Abbas Hosseini 3
  • Ahmad Sharafati 3
1 Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Soil Conservation and Watershed Management Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
3 Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
چکیده [English]

Effect of meteorological drought on vegetation conditions and their relationships with each other was investigated in the Province of Lorestan. The standard precipitation index (SPI) as a meteorological drought index was used for 28 rain gauging stations during the years 1987-2017 in that province. Benefiting from the remote sensing and MODIS images, the normalized difference vegetation index (NDVI) was extracted for the years 2000-2017 and the vegetation condition index (VCI) was calculated. Using the SPI results, the dry, normal and wet years were identified and the index year was selected for them. The correlation between the SPI and VCI was investigated using linear regression. The results indicated that the highest correlation coefficient of Pearson was related to the VCI in March with a 9-month SPI in November was equal to 0.64; the correlation coefficient between the multivariate linear regressions of the SPI with VCI in June was 0.7. The results of multivariate linear regression indicated that the SPI had a significant correlation with the VCI at the five percent level over a period of 9 and 12 months. A confusion matrix was used to evaluate the compatibility of the SPI drought classes with the VCI; the results also indicated that the highest compliance of the VCI with the SPI was in the moderate drought class. Furthermore, the results of this study indicated a 9-month delay in the meteorological drought index with satellite drought index at the 5 % level significance of the SPI with the VCI, which indicates that the VCI may be used in the absence of meteorological indicators for the study area.

کلیدواژه‌ها [English]

  • Lorestan
  • Normalized Difference Vegetation Index (NDVI)
  • Vegetation Condition Index (VCI)
  • Standardized Precipitation Index (SPI)

مراجع

Aghakouchak , Farahmand F, Melton J, Teixeira M, Anderson B, Hain R. 2015. Reviews of geophysics remote sensing of drought: Progress, Challenges. Reviews of Geophysics, 53: 1–29.
Allison EW, Brown RJ, Press HE, Gairns JG.1989. Monitoring drought affected vegetation with AVHRR. In 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium, 4(1):1965–1967.
Dehkordi L, Sohrabi T, Ghanavizbaf M, Ghazavi R. 2016. Drought monitoring by using of MODIS satellite images in dry lands (Case study: Isfahan Rangelands). Journal of Geography and Environmental Planning, 27(3): 177–190. (In Persian).
Dutta D, Arnab K, Patel N, Saha K, Siddiqui A. 2015. Assessment of agricultural drought in Rajasthan (India) using remote sensing derived vegetation condition index (VCI) and standardized precipitation index (SPI). Egyptian Journal of Remote Sensing and Space Science, 18 (1): 53–63.
Ebrahimzadeh S, Bazrafshan J, Ghorbani KH. 2013. Study of the identification of the variations in plant vegetation using remote sensing and ground-based drought indices (Case study: Kermanshah Province). Journal of Agricultural Meteorology, 1 (1): 37–48. (In Persian).
Farrokhzadeh B, Mansouri S, Sepehri A. 2018. Determining the correlation between NDVI and evi vegetation indices and SPI drought index (Case study: Golestan Rangelands). Journal of Agricultural Meteorology, 5 (2): 56–65. (In Persian).
Ganesh S, Quiring M. 2010. Evaluating the utility of the vegetation condition index (VCI) for monitoring meteorological drought in Texas. Agricultural and Forest Meteorology, 150(3): 330–339.
Hamzeh S, Farahani Z, Mahdavi S, Chatrobgoun O, Gholamnia M. 2017. Spatio-temporal monitoring of agricultural drought using remotely sensed data (Case study of Markazi Province of Iran). Journal of Spatial Analysis Environmental Hazarts, 4 (3):53–70. (In Persian).
Jafari M, Janfaza E, Nematolahi M, Alavipanah SK, Zehtabian Gh, Matinfar HR. 2012. Assessment of ASTER data for soils investigation using field data and GIS in Damghan Playa. Desert, 17 (3): 241–48.
Kogan FN. 1995. Application of vegetation index and brightness temperature for drought detection. Advances in Space Research, 15 (11): 91–100.
Liu Q, Zhang S, Zhang H, Yun B, Jiahua Z. 2020. Monitoring drought using composite drought indices based on remote sensing. Science of the Total Environment 711(1): 134–585.
Lloyd‐Hughes B, Saunders MA. 2002. A drought climatology for europe. International Journal of Climatology: A Journal of the Royal Meteorological Society, 22(13): 1571–1592.
Malaksabet M, Zare M, Hosari M, Mokhtari M. 2015. Evaluation of meteorological indices of draught versus remote sensing indices: A case study of Yazd Province. Journal of Geographical Research on Desert Areas, 3 (1): 101–18. (In Persian).
McKee TB, Doesken NG, Kleist J. 1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, 17(1):179–184.
Mirahsani M, Mahini S, Soffianian S, Moddares R, Jafari R, Mohammadi J. 2018. Regional drought monitoring in Zayandeh-Rud Basin based on time series variations of the SPI and satellite-based VCI indices. Geoghraphy and Environmental Hazards, 6 (24): 1–22. (In Persian).
Mishra AK, SinghV, Desai R. 2009. Drought characterization: A probabilistic approach. Stochastic Environmental Research and Risk Assessment, 23 (1): 41–55.
Moazzenzadeh R, Arshad S, Ghahraman B, Davari K. 2012. Drought monitoring in unirrigated lands based on the remote sensing technique. Water and Irrigation Management, 2 (2): 39–52. (In Persian).
Obasi G. 1994. WMO’s role in the international decade for natural disaster reduction, Bulletin of the American Meteorological Society, 75(9): 1655–1662.
Potop V, Možný M, Soukup J. 2012. Drought evolution at various time scales in the lowland regions and their impact on vegetable crops in the Czech republic. Agricultural and Forest Meteorology, 156(1): 121–33.
Rahimzadeh P, Darvishsefat A, Khalili A, Makhdom A. 2008. Using AVHRR-based vegetation indices for drought monitoring in the northwest of Iran. Journal of Arid Environments, 72 (6): 1086–1096.
Safarishad M, Ildoromi A, Akhzari D. 2017. Drought monitoring using vegetation indices and MODIS data (Case study: Isfahan Province, Iran). Journal of Rangeland Science, 7 (2): 148–159.
Shamsipour AA, AlaviPanah SK, Mohammadi H. 2010. Efficiency of vegetation and thermal indices of NOAA-AVHRR satellite in ecological drought analysis of Kashan Region. Iranian journal of Range and Desert Reseach, 17 (3): 445–65. (In Persian).
Singh RP, Roy S, Kogan F. 2003. Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India. International Journal of Remote Sensing, 24 (22):4393–4402.
Zambrano F, Saavedra M, Verbist K, Lagos O. 2016. Sixteen years of agricultural drought assessment of the BioBío Region in chile using a 250 m resolution vegetation condition index (VCI). Remote Sensing, 8 (6): 530–550.
Zargar A, Sadiq R, Naser B, Faisal IK. 2011. A review of drought indices. Environmental Reviews, 19 (1): 333–49.

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سابقه مقاله

  • تاریخ دریافت: 31 اردیبهشت 1399
  • تاریخ بازنگری: 02 مرداد 1399
  • تاریخ پذیرش: 30 شهریور 1399

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