Abstract
This study investigates the linkage between agricultural drought and meteorological drought, using normalization different vegetation index (NDVI) and land surface temperature (LST) for the whole of Iran in four periods of 16 days of late March, April, May, and June between 2000 and 2017. LST and NDVI were obtained from the production of MODIS MOD13A2 and MOD11A2. In the next step, the basic time synchronization of LST and NDVI was performed by the mean of two 8-day LST images and their conversion to 16-day LST for each year. The vegetation health index (VHI) was calculated from the combination of temperature condition index (TCI) and vegetation condition index (VCI). Then, Iran’s map of standardized precipitation-evapotranspiration index (SPEI) was calculated on a 12-month timescale for 68 meteorological stations with the inverse distance weighted (IDW) method. By using ArcGIS 10.5, the Pearson correlation coefficient and the slope of linear regression were calculated between 12-month SPEI and VHI for all four periods in different climates: hyper dry, dry, semi-dry, semi-humid, and humid. Results showed that the correlation increased when the temperature increased. This increase occurred in dry and hyper-dry climates. As the temperature rose, the slope of the linear regression for 12-month standardized precipitation-evapotranspiration index (SPEI) on vegetation health index (VHI) increased. The highest and lowest average effects of the slope were observed in dry and climatic class, respectively. With increasing temperature, the need for water in plants will increase. Hence, there is a direct relation or a positive correlation between temperature and correlation strength and slope effect. Therefore, plants more seriously will face drought stress during the drought period, and this drought stress has a positive correlation with drought intensity. From this study, it was concluded that the highest correlation and the highest slope effect between the 12-month SPEI and VHI happened in the dry climatic class in June.
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References
AghaKouchak A, Farahmand A, Melton FS, Teixeira J, Anderson MC, Wardlow BD, Hain CR (2015) Remote sensing of drought: progress, challenges and opportunities. Rev Geophys 53(2):452–480. https://doi.org/10.1002/2014RG000456
Ahmad MI, Sinclair CD, Werritty A (1988) Log-logistic flood frequency analysis. J Hydrol 98:205–224. https://doi.org/10.1016/0022-1694(88)90015-7
Amirkhani S, Chizari M (2010) Factors influencing drought management in varamin township, third congress of agricultural extension and natural resources, Mashhad, Iran
Araste M, Kaboli SH, Yazdani M (2017) Assessing the impacts of meteorological drought on the yield of rain fed wheat and barley (case study: Khorasan Razavi province). J Agric Meteorol 5(1):15–25
Bachmair S, Tanguy M, Hannaford J, Stahl K (2018) How well do meteorological indicators represent agricultural and forest drought across Europe? Environ Res Lett 13(3):034–042. https://doi.org/10.1088/1748-9326/aaafda
Bokal S, Grobicki A, Kindler J, Thalmeinerova D (2014) From national to regional plans—the integrated drought management programme of the global water partnership for Central and Eastern Europe. Weather Clim Extrem 3:37–46. https://doi.org/10.1016/j.wace.2014.03.006
Chatfield C (2016) The analysis of time series: an introduction. CRC press
Cong D, Zhao S, Chen C, Duan Z (2017) Characterization of droughts during 2001– 2014 based on remote sensing: a case study of Northeast China. Eco Inform 39:56–67. https://doi.org/10.1016/j.ecoinf.2017.03.005
Dai A (2013) Increasing drought under global warming in observations and models. Nat Clim Chang 3:52–58. https://doi.org/10.1038/nclimate1633
Dogan S, Berktay A, Singh VP (2012) Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey. J Hydrol 470:255–268. https://doi.org/10.1016/j.jhydrol.2012.09.003
Dracup JA, Lee KS, Paulson EG (1980) On the statistical characteristics of drought events. Water Resour Res 16:289–296. https://doi.org/10.1029/WR016i002p00289
Evans JD (1996) Straightforward statistics for the behavioral sciences. Brooks/Cole Publishing, Pacific Grove
Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups I and II of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Toulmin C (2010) Food security: the challenge of feeding 9 billion people. Science 327(5967):812–818. https://doi.org/10.1126/science.1185383
Gohari A, Mirchi A, Madani K (2017) System dynamics evaluation of climate change adaptation strategies for water resources management in central Iran. Water Resour Manag 31(5):1413–1434. https://doi.org/10.1007/s11269-017-1575-z
Gomes ACC, Bernardo N, Alcântara E (2017) Accessing the southeastern Brazil 2014 drought severity on the vegetation health by satellite image. Nat Hazards 89(3):1401–1420. https://doi.org/10.1007/s11069-017-3029-6
Heydari Alamdarloo E, Behrang Manesh M, Khosravi H (2018) Probability assessment of vegetation vulnerability to drought based on remote sensing data. Environ Monit Assess 190(702):702. https://doi.org/10.1007/s10661-018-7089-1
Jiang L, Jiapaer G, Bao A, Guo H, Ndayisaba F (2017) Vegetation dynamics and responses to climate change and human activities in Central Asia. Sci Total Environ 599–600:967–980. https://doi.org/10.1016/j.scitotenv.2017.05.012
Kaptué AT, Prihodko L, Hanan N (2015) On regrinding and degradation in Sahelian watersheds. Proc Natl Acad Sci U S A 112(39):12133–12138
Kogan FN (1990) Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int J Remote Sens 11:1405–1419. https://doi.org/10.1080/01431169008955102
Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15(11):91–100. https://doi.org/10.1016/0273-1177(95)00079-T
Lee Rodgers J, Nicewander WA (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42(1):59–66
Ma’rufah U, Hidayat R, Prasasti I (2017) Analysis of the relationship between meteorological and agricultural drought using standardized precipitation index and vegetation health index. IOP Conference Series:Environ Earth Sci 54(1):012008 IOP Publishing
Mafi-Gholami D, Zenner EK, Jaafari A, Ward RD (2019) Modeling multi-decadal mangrove leaf area index in response to drought along the semi-arid southern coasts of Iran. Sci Total Environ 656:1326–1336. https://doi.org/10.1016/j.scitotenv.2018.11.462
Masud MB, Khaliq MN, Wheater HS (2015) Analysis of meteorological droughts for the Saskatchewan River Basin using univariate and bivariate approaches. J Hydrol 522:452–466. https://doi.org/10.1016/j.jhydrol.2014.12.058
McKee TB, Doesken NJ, Kliest J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th conference on applied climatology, 17–22 January, Anaheim, CA (Boston: American Meteorological Society), pp 179–184
Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391(1–2):202–216. https://doi.org/10.1016/j.jhydrol.2010.07.012
Nemani R, Hashimoto H, Votava P, Melton F, Wang W, Michaelis A, White M (2009) Monitoring and forecasting ecosystem dynamics using the Terrestrial Observation and Prediction System (TOPS). Remote Sens Environ 13(7):1497–1509. https://doi.org/10.1016/j.rse.2008.06.017
Nichol JE, Abbas S (2015) Integration of remote sensing datasets for local scale assessment and prediction of drought. Sci Total Environ 505:503–507. https://doi.org/10.1016/j.scitotenv.2014.09.099
Orville H (1990) AMS statement on meteorological drought. Amer Meteorological Soc 45 Beacon St, Boston, MA. 2108–3693
Pei F, Wu C, Liu X, Li X, Yang K, Zhou Y, Xia G (2018) Monitoring the vegetation activity in China using vegetation health indices. Agric For Meteorol 248:215–227. https://doi.org/10.1016/j.agrformet.2017.10.001
Qian X, Liang L, Shen Q, Sun Q, Zhang L, Liu Z, Qin Z (2016) Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010. Environ Monit Assess 188(11):639. https://doi.org/10.1007/s10661-016-5657-9
Samadi Neghab S (2007) Drought prediction with GCM pattern outflow. J Geogr Develop 8(1):193–212
Shahi A (2019) Drought: the Achilles heel of the Islamic Republic of Iran. Asia Aff 50(1):18–39. https://doi.org/10.1080/03068374.2019.1567100
Silleos NG, Alexandridis TK, Gitas IZ, Perakis K (2006) Vegetation indices: advances made in biomass estimation and vegetation monitoring in the last 30 years. Geocarto Int 21(4):21–28
Singh VP, Guo H, Yu FX (1993) Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome. Stoch Hydrol Hydraul 7:163–177. https://doi.org/10.1080/10106040608542399
Sun B, Zhao H, Wang X (2016) Effects of drought on net primary productivity: roles of temperature, drought intensity, and duration. Chin Geogr Sci 26(2):270–282. https://doi.org/10.1007/s11769-016-0804-3
Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94. https://doi.org/10.2307/210739
Tran HT, Campbell JB, Tran TD, Tran HT (2017) Monitoring drought vulnerability using multispectral indices observed from sequential remote sensing (case study: Tuy Phong, Binh Thuan, Vietnam). Gisci Remote Sens 54(2):167–184. https://doi.org/10.1080/15481603.2017.1287838
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) a multiscalar Drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718. https://doi.org/10.1175/2009JCLI2909.1
Vicente-Serrano SM, Gouveia C, Camarero JJ, Begueria S, Trigo R, Lopez-Moreno JI, Azorin Molina C, Pasho E, Lorenzo-Lacruz J, Revuelto J, Moran-Tejeda E, Sanchez-Lorenzo A (2013) Response of vegetation to drought time-scales across global land biomes. Proc Natl Acad Sci U S A 110(1):52–57. https://doi.org/10.1073/pnas.1207068110
Wu Z, Mao Y, Li X, Lu G, Lin Q, Xu H (2016) Exploring spatiotemporal relationships among meteorological, agricultural, and hydrological droughts in Southwest China. Stoch Env Res Risk A 30(3):1033–1044
Xu HJ, Wang XP, Zhao CHY, Yang XM (2018) Diverse responses of vegetation growth to meteorological drought across climate zones and land biomes in northern China from 1981 to 2014. Agric For Meteorol 262:1–13. https://doi.org/10.1016/j.agrformet.2018.06.027
Zarch MAA, Malekinezhad H, Mobin MH, Dastorani MT, Kousari MR (2011) Drought monitoring by reconnaissance drought index (RDI) in Iran. Water Resour Manag 25(13):3485–3504. https://doi.org/10.1007/s11269-011-9867-1
Zarei AR, Moghimi MM, Mahmoudi MR (2016) Analysis of changes in spatial pattern of drought using RDI index in south of Iran. Water Resour Manag 30(11):3723–3743. https://doi.org/10.1007/s11269-016-1380-0
Zhang A, Jia G (2013) Monitoring meteorological drought in semiarid regions using multisensor microwave remote sensing data. Remote Sens Environ 134:12–23
Zhang X, Goldberg M, Tarpley D, Friedl MA, Morisette J, Kogan F, Yu Y (2010) Drought-induced vegetation stress in southwestern North America. Environ Res Lett 5(2):024008. https://doi.org/10.1088/1748-9326/5/2/024008
Zhang L, Jiao W, Zhang H, Huang C, Tong Q (2017) Studying drought phenomena in the Continental United States in 2011 and 2012 using various drought indices. Remote Sens Environ 190:96–106. https://doi.org/10.1016/j.rse.2013.02.023
Zhao A, Zhang A, Cao S, Liu X, Liu J, Cheng D (2018) Responses of vegetation productivity to multi-scale drought in Loess Plateau, China. CATENA 163:165–171. https://doi.org/10.1016/j.catena.2017.12.016
Zheng Y, Han J, Huang H, Fassnacht SR, Xie S, Lv E, Chen M (2018) Vegetation response to climate conditions based on NDVI simulations using stepwise cluster analysis for the Three-River Headwaters region of China. Ecol Indic 92:18–29. https://doi.org/10.1016/j.ecolind.2017.06.040
Zhongbao X, JiongXin X, Wie Z (2008) Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau. (1981–2006): impacts of climate changes and human activities. Sci China Ser D Earth Sci 51(1):67–78. https://doi.org/10.1007/s11430-007-0137-2
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Behrang Manesh, M., Khosravi, H., Heydari Alamdarloo, E. et al. Linkage of agricultural drought with meteorological drought in different climates of Iran. Theor Appl Climatol 138, 1025–1033 (2019). https://doi.org/10.1007/s00704-019-02878-w
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DOI: https://doi.org/10.1007/s00704-019-02878-w