Drought Monitoring in Tehran Province Using TRMM Satellite Data

Document Type : Research Article

Authors

1 PhD Student, Department of Geography and Urban Planning, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran

2 Associate Professor, Department of Geography and Urban Planning, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran (Corresponding Author)

Abstract

Drought is a climatic phenomenon that affects different parts the environment during its continuation. Most drought assessment systems are mainly based on rainfall data. short statistical period of many data, insufficient density of stations and poor quality of ground rainfall data, reduces the ability show the spatial pattern of drought. the current paper aims at monitoring drought in Tehran province using rainfall network data. Thus, monthly precipitation data six synoptic stations in Tehran province and monthly precipitation data of TRMM satellite with spatial resolution of.25 × .25 degrees during the period (1998-2019) have been used. The results show that output of the 12-month SPI index for TRMM points is in good agreement with synoptic stations and the drought characteristics at different stations are consistent with different points of the TRMM network. In 36% of the study period, the rainfall in the province is in normal range and in 64% the rainfall is not normal. In all parts of the province, frequency dry and wet periods is equal and each of which with 31.8%. In terms of severity, most precipitation anomalies in Tehran province are mild and moderate, so that the frequency of mild drought is 18%, moderate drought is 9% and severe drought is about 4.5%. Extremely severe drought has not occurred in any part of the province in the last 22 years. Also, 2001, 2008, 2013 and 2014 are the most severe periods of widespread severe drought in the province, with most areas suffering from moderate to severe drought.

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[1]. Subash N, Mohan HR, Banukumar K. Comparing water-vegetative indices for rice (Oryza sativa L.) –wheat (Triticum aestivum L.) drought assessment. Computers and electronics in agriculture. 2011 Jul 1;77(2):175-87.
[2]. Azizi Gh, Safarrad T. Evaluation of conventional kriging methods and weight inverse distance in estimating drought and wetland values of Iran, The first national conference on geomatics in natural resources and environment 2016. [in Persian].
[3]. Rossi G, Vega T, Bonaccorso B, editors. Methods and tools for drought analysis and management. Springer Science & Business Media; 2007 Jul 26.
[4]. Kogan FN. Global drought watch from space. Bulletin of the American Meteorological Society. 1997 Apr;78(4):621-36.
[5]. Wilhite DA. Drought and water crises: science, technology, and management issues. Crc Press; 2005 Mar 22.
[6]. Zarrin A, Salehabadi N, Drought risk prediction in Tehran based on the output of CMIP6 models, Sixth Regional Conference on Climate Change. 2019. [in Persian].
[7]. Asong ZE, Wheater HS, Bonsal B, Razavi S, Kurkute S. Historical drought patterns over Canada and their teleconnections with large-scale climate signals. Hydrology and Earth System Sciences. 2018 Jun 4;22(6):3105-24.
[8]. Cheng Q, Gao L, Chen Y, Liu M, Deng H, Chen X. Temporal-spatial characteristics of drought in Guizhou Province, China, based on multiple drought indices and historical disaster records. Advances in Meteorology. 2018 Jan 1;2018.
[9]. Rahimi M, Statistical Analysis - Synonymy of Droughts in Southwest Iran, Master Thesis, Faculty of Geography, University of Tehran. 2011. [in Persian].
[10]. Lukamba MT. Natural disasters in African countries: What can we learn about them?. TD: The Journal for Transdisciplinary Research in Southern Africa. 2010 Dec 1;6(2):478-95.
[11]. McKee TB, Doesken NJ, Kleist J. The relationship of drought frequency and duration to time scales. InProceedings of the 8th Conference on Applied Climatology 1993 Jan 17 (Vol. 17, No. 22, pp. 179-183).
[12]. Peters E, Bier G, Van Lanen HA, Torfs PJ. Propagation and spatial distribution of drought in a groundwater catchment. Journal of Hydrology. 2006 Apr 30;321(1-4):257-75.
[13]. Edossa DC, Babel MS, Gupta AD. Drought analysis in the Awash river basin, Ethiopia. Water resources management. 2010 May;24(7):1441-60.
[14]. Akbari H, Rakhshandehroo G, Sharifloo AH, Ostadzadeh E. Drought analysis based on standardized precipitation index (SPI) and streamflow drought index (SDI) in Chenar Rahdar river basin, Southern Iran. Southern Iran, American Society of Civil Engineers. 2015 Aug 5:11-22.
[15]. Sobral BS, de Oliveira-Junior JF, de Gois G, Pereira-Júnior ER, de Bodas Terassi PM, Muniz-Júnior JG, Lyra GB, Zeri M. Drought characterization for the state of Rio de Janeiro based on the annual SPI index: trends, statistical tests and its relation with ENSO. Atmospheric research. 2019 May 15;220:141-54.
[16]. Yerdelen C, Abdelkader M, Eri E. Assessment of drought in SPI series using continuous wavelet analysis for GEDIZ basin, Turkey. Atmospheric Research. 2021 May 25:105687.
[17]. Farajzade M, Ahmadian K. Temporal and spatial analysis of drought using SPI index in Iran, natural hazards. 2014. 4:1-16. [in Persian].
[18]. Madanchi P, Shahedi K, Habibnejad M, Soleymani K, Fatehi A. Zoning of climatic droughts and the magnitude of drought using SPI index in Kerman province. Irrigation and Water Engineering of Iran. 2019. 38: 205-228. [in Persian].
[19]. Mazidi A, Omidvar K. Investigation of drought and wetness of Isfahan meteorological station using SPI index. Geography and human relations. 2021. 13:657-672
[20]. Hatmoko W, Seizarwati W, Vernimmen R. Comparison of TRMM satellite rainfall and APHRODITE for drought analysis in the Pemali-comal River Basin. Procedia Environmental Sciences. 2016 Jan 1;33:187-95.
[21]. Miri M, Rahimi M,Norouzi A. Assessing the accuracy of estimating daily precipitation of TRMM and GPM databases versus observational data in Iran, watershed engineering and management. 2019. 4: 978-983. [in Persian].
[22]. Erfnian M, vafaee N, Rezaeean M. Presenting a new method for drought risk assessment in Fars province by combining monthly rainfall data of TRMM satellite and NDVI vegetation index data of Terra / MODIS sensor, Natural geography researches. 2014. 87:93-108. [in Persian].
[23]. Naumann G, Barbosa P, Carrao H, Singleton A, Vogt J. Monitoring drought conditions and their uncertainties in Africa using TRMM data. Journal of Applied meteorology and Climatology. 2012 Oct;51(10):1867-74.
[24]. Du L, Tian Q, Yu T, Meng Q, Jancso T, Udvardy P, Huang Y. A comprehensive drought monitoring method integrating MODIS and TRMM data. International Journal of Applied Earth Observation and Geoinformation. 2013 Aug 1;23:245-53.
[25]. Yan N, Wu B, Chang S, Bao X. Evaluation of TRMM Precipitation Product for Meteorological Drought Monitoring in Hai Basin. InIOP Conference Series: Earth and Environmental Science 2014 Mar 18 (Vol. 17, No. 1, p. 012093). IOP Publishing.
[25]. Ghafourian H, Sanayeenejad H, Davari K. Investigation of determining suitable areas for drought monitoring using TRMM satellite data (Case study: Khorasan Razavi province), Water and soil. 2014. 28: 639-648. [in Persian].
[26]. Ahmadi M, Houshmand A, Zamani F. Drought monitoring in the northwest of the country using MODIS and TRMM data, 24th National Geomatics Conference. 2017. [in Persian].
[27]. Miri M, Razi T, Rahimi M. Statistical evaluation and comparison of TRMM and GPCC precipitation data with observational data in Iran, Earth and space physics. 2016. 3: 657-672. [in Persian].
[28]. Jahangir Mh, Mousavi M. A Comparative Study of Meteorological (SPI) and Hydrological Drought Index (SSI) Based on the Best Cumulative Distribution Function in Tehran Province. Iranian Journal of Watershed Management Science & Engineering. 2020. 14(48): 1-10. [in Persian].