Assessment and Monitoring of Drought Using Satellite and Meteorological Time Series Data (Case Study: Zanjan Province)

Shojaee Shiri, Hossein; Arzani, Hossein; Keshtkar, Hamidreza; Bagheri, Setareh; Kavoosi, Omid

doi:10.22059/ije.2025.380086.1841

Assessment and Monitoring of Drought Using Satellite and Meteorological Time Series Data (Case Study: Zanjan Province)

Document Type : Research Article

Authors

¹ Department of Reclamation of Arid and Mountainous Regions, Faculty of Natural Resources, University College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

² International Desert Research Center, University College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

10.22059/ije.2025.380086.1841

Abstract

Objective: This study aims to conduct a comparative analysis of drought indices by integrating meteorological and satellite-based indices to enhance the spatial and temporal monitoring of drought in Zanjan Province.
Method: Two meteorological drought indices, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), were calculated for different time scales (1, 3, 6, 9, and 12 months) from 2004 to 2022. Additionally, five satellite-based drought indices—Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI)—were extracted for the same period. The results of these indices were compared to evaluate their effectiveness in drought monitoring.
Results: The SPI and SPEI indices indicated that most of the studied years were in a normal condition, with excessive rainfall in 2019. SPEI identified drought conditions in 2008, 2011, and 2022, while SPI recorded drought in 2007 and 2022. Among the satellite-based indices, NDVI showed the highest correlation with meteorological indices (R² = 0.82), whereas VHI exhibited the lowest correlation (R² = 0.57).
Conclusions: The study highlights the effectiveness of NDVI in monitoring drought compared to other satellite-based indices. The findings provide a basis for informed decision-making in utilizing remote sensing data for rapid drought assessment.

Keywords

Main Subjects

Climate Change

References

Aghajanlou, F., Ghorbani, A., Zare Chahoki, M. A., Mostafazadeh, R., & Hashemi Majd, K. (2018). Ecological survey of the presence and absence of Ferula ovina (Boiss.) Boiss and Ferula persica willd. in north-western rangelands of Iran (case dtudy: Zanjan province). J Rangel Sci, 8(4), 352-62.

Avazpour, N., Faramarzi, M., Omidipour, R., & Mehdizadeh, H. (2021). Monitoring the drought effects on vegetation changes using satellite imagery (Case study: Ilam catchment). Geography and Environmental Sustainability, 11(4), 125-143. [In Persian]

Bhuiyan, C., Singh, R. P., & Kogan, F. N. (2006). Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 8(4), 289-302.

Dastorani, M., Vali, A., Sepehr, A., & Komaki, C. B. (2022). The effect of drought on vegetation using MODIS satellite Khorasan Razavi. Desert Ecosystem Engineering, 4(7), 1-8. [In Persian]

Dayal, K. S., Deo, R. C., & Apan, A. A. (2018). Investigating drought duration-severity-intensity characteristics using the Standardized Precipitation-Evapotranspiration Index: case studies in drought-prone Southeast Queensland. Journal of Hydrologic Engineering, 23(1), 05017029.

De Jong, R., Verbesselt, J., Schaepman, M. E., & De Bruin, S. (2012). Trend changes in global greening and browning: contribution of short‐term trends to longer‐term change. Global Change Biology, 18(2), 642-655.

Dutta, D., Kundu, A., Patel, N. R., Saha, S. K., & Siddiqui, A. R. (2015). Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI). The Egyptian Journal of Remote Sensing and Space Science, 18(1), 53-63.

Firouzi, F., Tavosi, T., & Mahmoudi, P. (2019). Investigating the sensitivity of NDVI and EVI vegetation indices to dry and wet years in arid and semi-arid regions (Case study: Sistan plain, Iran). Scientific-Research Quarterly of Geographical Data (SEPEHR), 28(110), 163-179. [In Persian]

Gebrehiwot, T., Van der Veen, A., & Maathuis, B. (2011). Spatial and temporal assessment of drought in the Northern highlands of Ethiopia. International Journal of Applied Earth Observation and Geoinformation, 13(3), 309-321.

He, C., Zhang, Q., Li, Y., Li, X., & Shi, P. (2005). Zoning grassland protection area using remote sensing and cellular automata modeling—a case study in Xilingol steppe grassland in northern China. Journal of Arid Environments, 63(4), 814-826.

Homdee, T., Pongput, K., & Kanae, S. (2016). A comparative performance analysis of three standardized climatic drought indices in the Chi River basin, Thailand. Agriculture and Natural Resources, 50(3), 211-219.

Huho, J. M., & Kosonei, R. C. (2014). Understanding extreme climatic events for economic development in Kenya. IOSR Journal of Environmental Science, Toxicology and Food Technology, 8(2), 14-24.

Jain, S. K., Keshri, R., Goswami, A., & Sarkar, A. (2010). Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India. Natural hazards, 54, 643-656.

Ji, L., & Peters, A. J. (2003). Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote sensing of Environment, 87(1), 85-98.

Jiang, W., Wang, L., Feng, L., Zhang, M., & Yao, R. (2020). Drought characteristics and its impact on changes in surface vegetation from 1981 to 2015 in the Yangtze River Basin, China. International Journal of Climatology, 40(7), 3380-3397.

Kogan, F. (2002). World droughts in the new millennium from AVHRR‐based vegetation health indices. Eos, Transactions American Geophysical Union, 83(48), 557-563.

Kogan, F. N. (1990). Remote sensing of weather impacts on vegetation in non-homogeneous areas. International Journal of remote sensing, 11(8), 1405-1419.

Kogan, F. N. (1995). Application of vegetation index and brightness temperature for drought detection. Advances in space research, 15(11), 91-100.

Kogan, F., Gitelson, A., Zakarin, E., Spivak, L., & Lebed, L. (2003). AVHRR-based spectral vegetation index for quantitative assessment of vegetation state and productivity. Photogrammetric Engineering & Remote Sensing, 69(8), 899-906.

Kreibich, H., Di Baldassarre, G., Vorogushyn, S., Aerts, J. C., Apel, H., Aronica, G. T., & Merz, B. (2017). Adaptation to flood risk: Results of international paired flood event studies. Earth's Future, 5(10), 953-965.

Masud, M. B., Qian, B., & Faramarzi, M. (2020). Performance of multivariate and multiscalar drought indices in identifying impacts on crop production. International Journal of Climatology, 40(1), 292-307.

McKee, T. B., Doesken, N. J., & Kleist, J. (1993, January). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, No. 22, pp. 179-183).

Mirmosavei, S., & Kareimei, H. (2013). Effect of drought on vegetation cover using MODIS sensing images case: Kurdistan Province. Geography and Development, 11(31), 57-76. [In Persian]

Moazami, N., Keshtkar, A., Hamzeh, S., Mirzaei, S., Keshtkar, H., & Afzali, A. (2022). Remote sensing-based monitoring of the spatiotemporal characteristics of drought using hydro-meteorological indices. Desert, 27(2), 343-358.

Mostafazadeh, R., & Zabihi, M. (2016). Comparison of SPI and SPEI indices to meteorological drought assessment using R programming (Case study: Kurdistan Province). Journal of the Earth and Space Physics, 42(3), 633-643. [In Persian]

Myneni, R. B., Hall, F. G., Sellers, P. J., & Marshak, A. L. (1995). The interpretation of spectral vegetation indexes. IEEE Transactions on Geoscience and remote Sensing, 33(2), 481-486.

Nasir, J., Assefa, E., Zeleke, T., & Gidey, E. (2021). Meteorological Drought in Northwestern Escarpment of Ethiopian Rift Valley: detection seasonal and spatial trends. Environmental Systems Research, 10, 1-20.

Noorbakhsh, M., & Nazari Nejad A. (2022). Investigation of the relationship between NDVI and EVI vegetation indices and land surface temperature in Tehran. Geography and Human Relationships, 1(17), 225-236. [InPersian]

Ozelkan, E., Chen, G., & Ustundag, B. B. (2016). Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery. International Journal of Applied Earth Observation and Geoinformation, 44, 159-170.

Paltsyn, M. Y., Gibbs, J. P., Iegorova, L. V., & Mountrakis, G. (2017). Estimation and prediction of grassland cover in western Mongolia using MODIS-derived vegetation indices. Rangeland ecology & management, 70(6), 723-729.

Quiring, S. M., & Ganesh, S. (2010). Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas. Agricultural and forest meteorology, 150(3), 330-339.

Rafiei Sardooi, E., Azareh, A., Eskandari Damaneh, H., & Skandari Damaneh, H. (2021). Drought monitoring using MODIS land surface temperature and normalized difference vegetation index products in semi-arid areas of Iran. Journal of Rangeland Science, 11(4), 402-418. [In Persian]

Rimkus, E., Stonevicius, E., Kilpys, J., Maciulyte, V., & Valiukas, D. (2017). Drought identification in the eastern Baltic region using NDVI. Earth system dynamics, 8(3), 627-637.

Saberi, A. , Soltani-Gerdefaramarzi, S. and Miryaghoubzadeh, M. (2018). Study of drought using meteorological and remote sensing data (Azarbaijan province). Journal of the Earth and Space Physics, 44(2), 439-461. [In Persian]

Saberi, A., Gholami, L., Kavian, E.A. & Qheysoori, M. (2019) Evaluation of meteorological drought in Urmia Lake basin using meteorological indicators and remote sensing technique. 4th Conference on Watershed Science and Engineering. [In Persian]

Scasta, J. D., Lalman, D. L., & Henderson, L. (2016). Drought mitigation for grazing operations: matching the animal to the environment. Rangelands, 38(4), 204-210.

Singh, R. P., 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.

Şorman, A. Ü., Mehr, A. D., & Hadi, S. J. (2018). Study on spatial-temporal variations of Meteorological-Agricultural droughts in Turkey. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 483-490.

Su, Z., He, Y., Dong, X., & Wang, L. (2017). Drought monitoring and assessment using remote sensing. Remote sensing of hydrological extremes, 151-172.

Tesfamariam, B. G., Melgani, F., & Gessesse, B. (2019). Rainfall retrieval and drought monitoring skill of satellite rainfall estimates in the Ethiopian Rift Valley Lakes Basin. Journal of Applied Remote Sensing, 13(1), 014522-014522.

Tian, L., Yuan, S., & Quiring, S. M. (2018). Evaluation of six indices for monitoring agricultural drought in the south-central United States. Agricultural and forest meteorology, 249, 107-119.

Ugwu, E. B. I., Ugbor, D. O., Agbo, J. U., & Alfa, A. (2023). Analyzing rainfall trend and drought occurences in Sudan Savanna of Nigeria. Scientific African, 20, e01670.

Usman, U., Yelwa, S. A., Gulumbe, S. U., Danbaba, A., & Nir, R. (2013). Modelling relationship between NDVI and climatic variables using geographically weighted regression. Journal of Mathematical Sciences and Applications, 1(2), 24-28.

Vali, A. A., Mousavi, S. H., & Zamani, E. (2019). Statistical analysis of occurrence frequency of dust storms in Yazd province and its modeling based on climatic elements and vegetation cover. Journal of Spatial Analysis Environmental hazarts, 6(3), 121-142. [In Persian]

Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of climate, 23(7), 1696-1718.

Wilhite, D. A. (2005). Drought and water crises: science, technology, and management issues. Crc Press.

Zambrano, F., Wardlow, B., Tadesse, T., Lillo-Saavedra, M., & Lagos, O. (2017). Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile. Atmospheric Research, 186, 26-42.

Zhao, C., Brissette, F., Chen, J., & Martel, J. L. (2020). Frequency change of future extreme summer meteorological and hydrological droughts over North America. Journal of Hydrology, 584, 124316.

Zuo, D., Hou, W., Wu, H., Yan, P., & Zhang, Q. (2021). Feasibility of calculating standardized precipitation index with short-term precipitation data in China. Atmosphere, 12(5), 603.