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Authors: Arpakorn Wongsit
อาภากร วงศ์สิทธิ์
Burapha University. Faculty of Geoinformatics
Keywords: Drought
Drought index
Remote Sensing
Issue Date:  15
Publisher: Burapha University
Abstract: Drought over Thailand is a recurring natural phenomenon in different regions. Drought typically remains the crucial problem in Thailand that is merely not a recent issue but a severe recurring difficulty. Thailand experiences droughts every year throughout the dry season, although to wildly differing degrees of persistent intensity. Droughts can be produced by a variety of factors, the most common of which is an imbalanced and insufficient rainfall distribution to some areas. When insufficient rainfall is distributed unevenly, certain areas lack a sufficient water supply, causing problems for people and agriculture on a local level, as well as economic, social, and environmental consequences. The primary goal of this study is to use main indices to analyze and investigate the evolution of the spatio-temporal pattern from drought indices that contributed to affecting transition flood and drought over Thailand from 1991 to 2020, as well as to analyze and investigate the relationship between meteorological drought, vegetation drought, soil moisture drought, and hydrological drought. The Standardized Precipitation Index (SPI) is a meteorological index that uses data from rainfall gauge sites to calculate precipitation. The Standardized Runoff Index (SRI) is the hydrological data obtained from the runoff, whereas the Standardized Soil Moisture Index (SSI) is soil moisture data collected from root zone soil moisture both of which were derived from the MERRA-2. The Vegetation Condition Index (VCI), derived from NDVI obtained from the NOAA Climate Data Record (CDR) of AVHRR Normalized Difference Vegetation Index, was also used. Assessment of drought using a common factor from remote sensing data. This can be easily monitored and can analyze drought-prone areas according to time series, which can generate the best correlation-anticipation relationship for early signs of drought impacts and drought monitoring purposes. This study analyzes and investigates the spatio-temporal dynamics of drought in Thailand, with four drought indicators analyzed from 1991 to 2020. The results of this study, the SPI index found that the years with the most severe droughts were 1992, 2004, 2012, 2016, and 2020, with the droughts starting in March to May and November to December on average. SSI, SRI, and VCI experienced the same drought in 1992, 2004, 2016, and 2020. The wetness and dryness of drought occurrences may now be easily noticed as a result of this research. In addition, the worst drought was in 2004, while the wetness year was 2017. The mean of each index is consistent with changes in rainfall but affects a distinct time connection, according to the results of the four indices analysis.  The SPI index using meteorological data is useful for monitoring accumulated drought, but visual inspection only is insufficient to tell if the study area has become drier or wetter. This is likely to be beneficial, but it should be combined with other indices and data. As a result, indices derived from satellite data represent an alternate method for evaluating and analyzing temporal and spatial drought that might be combined with meteorological data. It is simple and quick, and the results can be used on a regular basis. Drought is evaluated using indices obtained from satellite imagery on the different land use and land cover are also given the drought’s effect differently. Therefore, each area's drought database should be evaluated. In the meantime, data from other factors that influence drought occurrence should be incorporated to demonstrate the drought's decision-making.
Description: Master Degree of Science (M.Sc.)
วิทยาศาสตรมหาบัณฑิต (วท.ม.)
Appears in Collections:Faculty of Geoinformatics

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