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Journal articles on the topic 'Standardized precipitation index'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 June 2025

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1

Kim. "A Study on Target Standardized Precipitation Index in Korea." Journal of the Korean Society of Civil Engineers 34, no. 4 (2014): 1117. http://dx.doi.org/10.12652/ksce.2014.34.4.1117.

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2

Mega, Nabil, and Abderrahmane Medjerab. "Statistical comparison between the standardized precipitation index and the standardized precipitation drought index." Modeling Earth Systems and Environment 7, no. 1 (2021): 373–88. http://dx.doi.org/10.1007/s40808-021-01098-4.

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3

Vinothkanna, S., V. Emayavaramban, A. P. Ramaraj, and K. Senthilraja. "Exploring the Drought Scenario of Namakkal through Standardized Precipitation Index." Geo-Eye 10, no. 1 (2021): 13–21. https://doi.org/10.53989/bu.ge.v10i1.3.

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Drought has long been recognized as one of the major causes of human distress and is a natural disaster that claims so many fatalities annually. Droughts are a series of climate events that often hit South Asia, causing significant water shortages, economic losses and adverse social consequences. Water scarcity can be said as the cause and effect of drought. It is not possible to avoid droughts. But drought preparedness can be developed and drought impacts can be managed. The success of both depends, amongst the others, on how well the droughts are defined and drought characteristics quantifie

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4

Oh, Bu-yeong, Jeong-woo Son, Seon-ah Hwang, and Seung-oh Hur. "Drought Assessment Using Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index and Soil Available Water Content." Korean Journal of Soil Science and Fertilizer 55, no. 4 (2022): 497–510. http://dx.doi.org/10.7745/kjssf.2022.55.4.497.

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5

Isia, Ismallianto, Tony Hadibarata, Muhammad Noor Hazwan Jusoh, et al. "Drought Analysis Based on Standardized Precipitation Evapotranspiration Index and Standardized Precipitation Index in Sarawak, Malaysia." Sustainability 15, no. 1 (2022): 734. http://dx.doi.org/10.3390/su15010734.

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Drought analysis via the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) is necessary for effective water resource management in Sarawak, Malaysia. Rainfall is the best indicator of a drought, but the temperature is also significant because it controls evaporation and condensation. This study examined drought periods in the state of Sarawak using the SPI and SPEI based on monthly precipitation and temperature data from thirty-three rainfall stations during a forty-year period (1981–2020). This analysis of drought conditions revealed tha

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6

Ünal, Ayça. "Drought and Trend Analysis of Rize Station with Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index Methods." Journal of Nature, Science & Technology 2, no. 3 (2023): 1–5. http://dx.doi.org/10.36937/janset.2022.6774.

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Since ancient times, drought has been one of the worst natural disasters that humanity has experienced. Drought, which is likely to occur locally or regionally can be defined as the lack of precipitation in a certain period of time. Objectively determining long-term droughts in advance enables taking measures against drought. Estimation of drought is of great importance in order to reduce the socio-economic, agricultural, and environmental negative effects that drought may cause. One method used in determining drought is the drought indices, which are found with the help of precipitation value

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7

Manullang, Fanly Parhimpunan, Kerista Tarigan, Marhaposan Situmorang, Syahrul Humaidi, Deassy Eirene Diana Doloksaribu, and Yahya Darmawan. "Characterization of Meteorological Drought Using Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index Methods in North Sumatera." Prisma Sains : Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram 11, no. 4 (2023): 1084. http://dx.doi.org/10.33394/j-ps.v11i4.9961.

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Climate variability in Indonesia is influenced by several global factors including El Niño Southern Oscillation and Indian Ocean Dipole, one consequence of climate variability is drought. The drought index is used to identify and describe the level of drought in an area, the methods used in this study are the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index which are calculated based on climate data with a span of 24 years as many as 67 rain observation posts in North Sumatra using R Studio software. The purpose of this study is to determine the fact

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8

He, Liupeng, Liang Tong, Zhaoqiang Zhou, et al. "A Drought Index: The Standardized Precipitation Evapotranspiration Irrigation Index." Water 14, no. 13 (2022): 2133. http://dx.doi.org/10.3390/w14132133.

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Drought has had an increasingly serious impact on humans with global climate change. The drought index is an important indicator used to understand and assess different types of droughts. At present, many drought indexes do not sufficiently consider human activity factors. This study presents a modified drought index and the standardized precipitation evapotranspiration irrigation index (SPEII), considering the human activity of irrigation that is based on the theory of the standardized precipitation evapotranspiration index (SPEI). This study aims to compare the modified drought index (SPEII)

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9

Wang, Long, Hang Yu, Maoling Yang, Rui Yang, Rui Gao, and Ying Wang. "A drought index: The standardized precipitation evapotranspiration runoff index." Journal of Hydrology 571 (April 2019): 651–68. http://dx.doi.org/10.1016/j.jhydrol.2019.02.023.

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10

Pandya, Parthsarthi, Rohit Kumarkhaniya, Ravina Parmar, and Piyush Ajani. "Meteorological Drought Analysis Using Standardized Precipitation Index." Current World Environment 15, no. 3 (2020): 477–86. http://dx.doi.org/10.12944/cwe.15.3.12.

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Drought is a natural hazard which is challenging to quantify in terms of severity, duration, areal extent and impact. The present study was aimed to assess the meteorological drought for Junagadh (Gujarat), India using Standardized Precipitation Index (SPI) and evaluate its correlation with the productivity of Groundnut and Cotton. The SPI was computed for eight durations including monthly (June to August each), 3 monthly (June to August and July to September) and 6 monthly (June to November) time scales for the year1988 to 2018. The results revealed that 54% to 67% of years suffered from drou

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11

Cancelliere, A., G. Di Mauro, B. Bonaccorso, and G. Rossi. "Drought forecasting using the Standardized Precipitation Index." Water Resources Management 21, no. 5 (2006): 801–19. http://dx.doi.org/10.1007/s11269-006-9062-y.

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12

Tegos, Aristoteles, Stefanos Stefanidis, John Cody, and Demetris Koutsoyiannis. "On the Sensitivity of Standardized-Precipitation-Evapotranspiration and Aridity Indexes Using Alternative Potential Evapotranspiration Models." Hydrology 10, no. 3 (2023): 64. http://dx.doi.org/10.3390/hydrology10030064.

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This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration index combines precipitation and temperature data, quantifying the severity of a drought as the difference in a timestep as the difference between precipitation and PET. The standardized precipitation-evapotranspiration index

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13

Wen-Ping and ZHOU Guang-Sheng, YUAN, and $author.xingMing_EN. "COMPARISON BETWEEN STANDARDIZED PRECIPITATION INDEX AND Z-INDEX IN CHINA." Chinese Journal of Plant Ecology 28, no. 4 (2004): 523–29. http://dx.doi.org/10.17521/cjpe.2004.0071.

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14

Guttman, Nathaniel B. "COMPARING THE PALMER DROUGHT INDEX AND THE STANDARDIZED PRECIPITATION INDEX." Journal of the American Water Resources Association 34, no. 1 (1998): 113–21. http://dx.doi.org/10.1111/j.1752-1688.1998.tb05964.x.

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15

Łabędzki, Leszek. "Categorical Forecast of Precipitation Anomaly Using the Standardized Precipitation Index SPI." Water 9, no. 1 (2017): 8. http://dx.doi.org/10.3390/w9010008.

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16

Lucas, Matthew P., Clay Trauernicht, Abby G. Frazier, and Tomoaki Miura. "Long-Term, Gridded Standardized Precipitation Index for Hawai‘i." Data 5, no. 4 (2020): 109. http://dx.doi.org/10.3390/data5040109.

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Spatially explicit, wall-to-wall rainfall data provide foundational climatic information but alone are inadequate for characterizing meteorological, hydrological, agricultural, or ecological drought. The Standardized Precipitation Index (SPI) is one of the most widely used indicators of drought and defines localized conditions of both drought and excess rainfall based on period-specific (e.g., 1-month, 6-month, 12-month) accumulated precipitation relative to multi-year averages. A 93-year (1920–2012), high-resolution (250 m) gridded dataset of monthly rainfall available for the State of Hawai‘

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17

Tatli, Hasan. "Downscaling standardized precipitation index via model output statistics." Atmósfera 28, no. 2 (2015): 83–98. http://dx.doi.org/10.20937/atm.2015.28.02.02.

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18

Salmin, A. S., I. F. Asaulyak, and A. I. Belolyubtsev. "ANALYSING TIME SERIES OF STANDARDIZED PRECIPITATION INDEX (SPI)." Успехи современного естествознания (Advances in Current Natural Sciences), no. 5 2021 (2021): 101–9. http://dx.doi.org/10.17513/use.37630.

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19

Almedeij, Jaber. "Drought Analysis for Kuwait Using Standardized Precipitation Index." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/451841.

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Implementation of adequate measures to assess and monitor droughts is recognized as a major matter challenging researchers involved in water resources management. The objective of this study is to assess the hydrologic drought characteristics from the historical rainfall records of Kuwait with arid environment by employing the criterion of Standardized Precipitation Index (SPI). A wide range of monthly total precipitation data from January 1967 to December 2009 is used for the assessment. The computation of the SPI series is performed for intermediate- and long-time scales of 3, 6, 12, and 24

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20

Magallanes-Quintanar, Rafael, Carlos Eric Galván-Tejada, Jorge Isaac Galván-Tejada, Hamurabi Gamboa-Rosales, Santiago de Jesús Méndez-Gallegos, and Antonio García-Domínguez. "Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting." Atmosphere 15, no. 8 (2024): 912. http://dx.doi.org/10.3390/atmos15080912.

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In the context of climate change, studying changes in rainfall patterns is a crucial area of research, remarkably so in arid and semi-arid regions due to the susceptibility of human activities to extreme events such as droughts. Employing predictive models to calculate drought indices can be a useful method for the effective characterization of drought conditions. This study applies two type of machine learning methods—long short-term memory (LSTM) and Neural Hierarchical Interpolation for Time Series Forecasting (N-HiTS)—to develop and deploy artificial neural network models with the aim of p

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21

Guttman, Nathaniel B. "ACCEPTING THE STANDARDIZED PRECIPITATION INDEX: A CALCULATION ALGORITHM1." JAWRA Journal of the American Water Resources Association 35, no. 2 (1999): 311–22. http://dx.doi.org/10.1111/j.1752-1688.1999.tb03592.x.

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22

Carbone, Gregory J., Junyu Lu, and Michele Brunetti. "Estimating uncertainty associated with the standardized precipitation index." International Journal of Climatology 38 (January 3, 2018): e607-e616. http://dx.doi.org/10.1002/joc.5393.

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23

Ariyanto, Dwi Priyo, Abdul Aziz, Komariah Komariah, Sumani Sumani, and Magarsa Abara. "Comparing the accuracy of estimating soil moisture using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI)." SAINS TANAH - Journal of Soil Science and Agroclimatology 17, no. 1 (2020): 23. http://dx.doi.org/10.20961/stjssa.v17i1.41396.

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<span>The Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are used to monitor and identify different types of drought, including meteorological, hydrological, and agricultural droughts. This study evaluates the accuracy of estimating soil moisture levels using the two indexes. The analysis correlated the SPI and the SPEI over three years (November 2016–October 2019) using <em>Rstudio</em>, with average monthly soil moisture taken using a Soil Moisture Sensor; 3-, 6- and 12-months SPI and SPEI showed a positive correlat

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24

Aye, Aye Thant. "Drought Assessment Using Standard Precipitation Index." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 1814–19. https://doi.org/10.31142/ijtsrd18181.

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Drought is one of the extreme climatic events among the most relevant natural disasters. This paper presents drought assessment using Standardized Precipitation Index SPI to overview the respective drought hot spots. Monthly rainfall data during the previous 36 years 1982 - 2017 are applied to generate Standardized Precipitation Index SPI with 3 month and 9 month scale on the basis of Gamma distribution for the areas in the central dry zone of Myanmar namely Mandalay, Nyaung U, Myingyan, Natogyi, Meikhtila, Kyaukpadaung, Wundwin, Sagaing, Monywa, Shwebo, Myinmu, Magway, Minbu, Chauk and Pakokk

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25

Ziese, M., U. Schneider, A. Meyer-Christoffer, et al. "GPCC Drought Index – a new, combined, and gridded global drought index." Earth System Science Data Discussions 7, no. 1 (2014): 243–70. http://dx.doi.org/10.5194/essdd-7-243-2014.

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Abstract. The Global Precipitation Climatology Centre Drought Index (GPCC-DI) provides estimations of precipitation anomalies with respect to long term statistics. It is a combination of the Standardized Precipitation Index with adaptations from Deutscher Wetterdienst (SPI-DWD) and the Standardized Precipitation Evapotranspiration Index (SPEI). Precipitation data were taken from the Global Precipitation Climatology Centre (GPCC) and temperature data from NOAA's Climate Prediction Center (CPC). The GPCC-DI is available with several averaging periods of 1, 3, 6, 9, 12, 24 and 48 months for diffe

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26

Patel, cNikita C. "Correlation between Standardized Precipitation Index and Standardized Runoff Index : A Case Study of AJI Basin." International Journal for Research in Applied Science and Engineering Technology 6, no. 6 (2018): 775–86. http://dx.doi.org/10.22214/ijraset.2018.6120.

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27

Ziese, M., U. Schneider, A. Meyer-Christoffer, et al. "The GPCC Drought Index – a new, combined and gridded global drought index." Earth System Science Data 6, no. 2 (2014): 285–95. http://dx.doi.org/10.5194/essd-6-285-2014.

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Abstract. The Global Precipitation Climatology Centre Drought Index (GPCC-DI) provides estimations of water supply anomalies with respect to long-term statistics. It is a combination of the Standardized Precipitation Index with adaptations from Deutscher Wetterdienst (SPI-DWD) and the Standardized Precipitation Evapotranspiration Index (SPEI). Precipitation data were taken from the Global Precipitation Climatology Centre (GPCC) and temperature data from NOAA's Climate Prediction Center (CPC). The GPCC-DI is available with several accumulation periods of 1, 3, 6, 9, 12, 24 and 48 months for dif

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28

Panda, Aishwarya, Narayan Sahoo, Balram Panigrahi, and Dwarika Mohan Das. "Drought Assessment using Standardized Precipitation Index and Normalized Difference Vegetation Index." International Journal of Current Microbiology and Applied Sciences 9, no. 7 (2020): 1125–36. http://dx.doi.org/10.20546/ijcmas.2020.907.132.

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29

Yu, Hang, Long Wang, Jianlong Zhang, and Yuanfang Chen. "A global drought-aridity index: The spatiotemporal standardized precipitation evapotranspiration index." Ecological Indicators 153 (September 2023): 110484. http://dx.doi.org/10.1016/j.ecolind.2023.110484.

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30

Ángeles Clemente, Víctor Antonio, Del Piero Raphael Arana Ruedas, Steve Dann Camargo Hinostroza, and Onafuje Oketta. "Comparison between Standardized Precipitation Index (SPI) and Standardized Evapotranspiration Index (SPEI) for agricultural drought over Mantaro Valley, Peru." Manglar 21, no. 3 (2024): 337–45. http://dx.doi.org/10.57188/manglar.2024.037.

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Drought is one of the main events associated to climate change that affects water supply and food productions at different locations and time (spatio-temporal) in the Peruvian Tropical Andes (PTA). Furthermore, studies evidenced that drought are causing an enormous damage to social, economic and environmental spheres. Hence, The World Meteorological Organization (WMO) has published a handbook of drought indicators and indices with the most representative methods used in the world to assess drought events, but each index has a different advantage since the requested variable and scope are diffe

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31

Pavlova, Anna Illarionovna. "Estimation of meteorological drought based on a Standardized Precipitation Evapotranspiration Index." Agrarian Bulletin of the 24, no. 05 (2024): 605–16. http://dx.doi.org/10.32417/1997-4868-2024-24-05-605-616.

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Abstract. Various climatic indices are used to monitor meteorological drought, among which the best known are the standardized precipitation index and the standardized precipitation evapotranspiration index (SPEI). The purpose of the research is to assess the conditions of moisture content of the growing season of grain crops in agrolandscapes of the Novosibirsk region on the basis of standardised precipitation and evapotranspiration index. Methods. Methods of big data processing, statistical analysis were used in the study. The scientific novelty consists in assessing the humidity and intensi

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32

Gocic, Milan, Danilo Misic, Slavisa Trajkovic, and Mladen Milanovic. "Using GIS tool for presenting spatial distribution of drought." Facta universitatis - series: Architecture and Civil Engineering 18, no. 1 (2020): 77–84. http://dx.doi.org/10.2298/fuace200409006g.

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By using GIS tools, it is possible to improve the preview of hydrological processes such as evapotranspiration, precipitation, flood and drought. In order to quantify drought, different type of drought indicators have been developed such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Standardized Precipitation Evapotranspiration Index (SPEI) or Water Surplus Variability Index (WSVI). In this paper the precipitation-based SPI indicator was applied to the monthly precipitation data from Serbia during the period 1948-2012. The data were processed in the QuantumGIS

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33

Blain, Gabriel Constantino. "Standardized precipitation index based on pearson type III distribution." Revista Brasileira de Meteorologia 26, no. 2 (2011): 167–80. http://dx.doi.org/10.1590/s0102-77862011000200001.

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The initial step in calculating the Standardized Precipitation Index (SPI) is to determine a probability density function (pdf) that describes the precipitation series under analysis. Once this pdf is determined, the cumulative probability of an observed precipitation amount is computed. The inverse normal function is then applied to the cumulative probability. The result is the SPI. This article assessed the changes in SPI final values, when computed based on Gamma 2-parameters (Gam) and Pearson Type III (PE3) distributions (SPIGam and SPIPE3, respectively). Monthly rainfall series, available

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34

Fedhasa, Benti. "Spatiotemporal Attribution and Trends of Climate Variables in Iluababora Zone, Oromia National Regional State, Ethiopia." Journal of Science and Sustainable Development 7, no. 2 (2019): 52–64. https://doi.org/10.20372/au.jssd.7.2.2019.0137.

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The environmental diversity associated climatic variables in the micro environments are anticipated to change over times. This study aimed to examine precipitation concentration and anomaly indices, and trends of climatic variables over micro-environments of Iluabbabora zone. Climatic data were obtained from NASA’s dataset, recorded from 1981–2018. Precipitation concentration indices were estimated and interpolated using an inverse distance weighting. The frequency and percentile of drier and wetter periods was analyzed using standardized precipitation anomaly index model. The Mann

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35

LI, Wei-Guang, Xue YI, Mei-Ting HOU, Hui-Lin CHEN, and Zhen-Li CHEN. "Standardized precipitation evapotranspiration index shows drought trends in China." Chinese Journal of Eco-Agriculture 20, no. 5 (2012): 643–49. http://dx.doi.org/10.3724/sp.j.1011.2012.00643.

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36

Ryoo, So-Ra, and Chul-Sang Yoo. "A Modified Standardized Precipitation Index (MSPI) and Its Application." Journal of Korea Water Resources Association 37, no. 7 (2004): 553–67. http://dx.doi.org/10.3741/jkwra.2004.37.7.553.

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37

Karavitis, Christos A., Stavros Alexandris, Demetrios E. Tsesmelis, and George Athanasopoulos. "Application of the Standardized Precipitation Index (SPI) in Greece." Water 3, no. 3 (2011): 787–805. http://dx.doi.org/10.3390/w3030787.

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38

Zhao Jing, Yan Deng-Hua, Yang Zhi-Yong, Hu Yong, Weng Bai-Sha, and Gong Bo-Ya. "Improvement and adaptability evaluation of standardized precipitation evapotranspiration index." Acta Physica Sinica 64, no. 4 (2015): 049202. http://dx.doi.org/10.7498/aps.64.049202.

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Popovych, Victor Fedorovych, and Ielizaveta Andreevna Dunaieva. "STANDARDIZED PRECIPITATION INDEX USAGE FOR RESERVOIRS OPERATION REGIME ANALYSIS." Water and Ecology 23, no. 3 (2018): 39–47. http://dx.doi.org/10.23968/2305-3488.2018.20.3.39-47.

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Ebrahimpour, Meisam, Jaber Rahimi, Armin Nikkhah, and Javad Bazrafshan. "Monitoring Agricultural Drought Using the Standardized Effective Precipitation Index." Journal of Irrigation and Drainage Engineering 141, no. 1 (2015): 04014044. http://dx.doi.org/10.1061/(asce)ir.1943-4774.0000771.

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Hayes, Michael J., Mark D. Svoboda, Donald A. Wilhite, and Olga V. Vanyarkho. "Monitoring the 1996 Drought Using the Standardized Precipitation Index." Bulletin of the American Meteorological Society 80, no. 3 (1999): 429–38. http://dx.doi.org/10.1175/1520-0477(1999)080<0429:mtduts>2.0.co;2.

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洪, 兴骏. "Applicability of Standardized Precipitation Index with Alternative Distribution Functions." Journal of Water Resources Research 02, no. 01 (2013): 33–41. http://dx.doi.org/10.12677/jwrr.2013.21006.

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43

Bazrafshan, Javad, Somayeh Hejabi, and Jaber Rahimi. "Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)." Water Resources Management 28, no. 4 (2014): 1045–60. http://dx.doi.org/10.1007/s11269-014-0533-2.

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44

Seiler, R. A., M. Hayes, and L. Bressan. "Using the standardized precipitation index for flood risk monitoring." International Journal of Climatology 22, no. 11 (2002): 1365–76. http://dx.doi.org/10.1002/joc.799.

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45

Touchan, Ramzi, Gary Funkhouser, Malcolm K. Hughes, and Nesat Erkan. "Standardized Precipitation Index Reconstructed from Turkish Tree-Ring Widths." Climatic Change 72, no. 3 (2005): 339–53. http://dx.doi.org/10.1007/s10584-005-5358-9.

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46

da Silva, Antonio Samuel Alves, Tatijana Stosic, Ilija Arsenić, Rômulo Simões Cezar Menezes, and Borko Stosic. "Multifractal analysis of standardized precipitation index in Northeast Brazil." Chaos, Solitons & Fractals 172 (July 2023): 113600. http://dx.doi.org/10.1016/j.chaos.2023.113600.

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47

Sinha, Manish Kumar, Preeti Rajput, and Mukesh Kumar Verma. "Validation of Standardized Precipitation Index (SPI) for Meteorological Drought Risk in Central India." Disaster Advances 11, no. 7 (2018): 1–12. https://doi.org/10.5281/zenodo.4670999.

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This study materialized an approach to drought risk (DR) mapping in an agricultural basin. The risks of drought have potential to cause damage, their occurrences are matter of concern to the agricultural society and economy. This study mainly dealt with droughts during the southwest monsoon season (June– September) in central India. The risk associated with drought was assessed by a combination of the regional exposure associated with natural events and the vulnerability of anthropogenic events. DR is the abstraction of the product of drought hazard (DH) and drought vulnerability (DV). T

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48

Kartika, Fitria Dewi, and Pipit Wijayanti. "Drought disaster modeling using drought index: a systematic literature review." IOP Conference Series: Earth and Environmental Science 1190, no. 1 (2023): 012026. http://dx.doi.org/10.1088/1755-1315/1190/1/012026.

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Abstract A prolonged absence of rainfall that results in a temporary reduction or deficit in the amount of natural water available is known as drought. The goal of this article is to examine how drought indices from various nations might be used to simulate the features of drought. Understanding the various drought indexes, as well as their benefits and drawbacks, is crucial. The literature review methodology is employed in this investigation. The Standardized Precipitation Index, or SPI, is the output of the most used modeling technique. Because this technique solely uses the rainfall series,

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49

Behifar, M., A. A. Kakroodi, M. Kiavarz, and F. Amiraslani. "COMBINATION OF METEOROLOGICAL INDICES AND SATELLITE DATA FOR DROUGHT MONITORING IN TWO DIFFERENT ENVIRONMENTS IN IRAN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 197–200. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-197-2019.

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Abstract. The main problem using meteorological drought indices include inappropriate distribution of meteorological stations. Satellite data have reliable spatial and temporal resolution and provide valuable information used in many different applications. The Standardized precipitation index has several advantages. The SPI is based on rainfall data alone and has a variable time scale and is thus conducive to describing drought conditions for different application.This study aims to calculate SPI using satellite precipitation data and compare the results with traditional methods. To do this,

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Vicente-Serrano, Sergio M., Santiago Beguería, and Juan I. López-Moreno. "A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index." Journal of Climate 23, no. 7 (2010): 1696–718. http://dx.doi.org/10.1175/2009jcli2909.1.

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Abstract The authors propose a new climatic drought index: the standardized precipitation evapotranspiration index (SPEI). The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. The procedure to calculate the index is detailed and involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution. Mathematically, the SPEI is similar to the standardized prec

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