Assessing Spatiotemporal Drought Dynamics and Its Related Environmental Issues in the Mekong River Delta
![Thumbnail](/xmlui/bitstream/handle/10234/186986/69022.pdf.jpg?sequence=5&isAllowed=y)
View/ Open
Impact
![Google Scholar](/xmlui/themes/Mirage2/images/uji/logo_google.png)
![Microsoft Academico](/xmlui/themes/Mirage2/images/uji/logo_microsoft.png)
Metadata
Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/8634
comunitat-uji-handle4:
INVESTIGACIONMetadata
Title
Assessing Spatiotemporal Drought Dynamics and Its Related Environmental Issues in the Mekong River DeltaAuthor (s)
Date
2019Publisher
MDPIISSN
2072-4292Bibliographic citation
TRAN, Thuong V., et al. Assessing Spatiotemporal Drought Dynamics and Its Related Environmental Issues in the Mekong River Delta. Remote Sensing, 2019, vol. 11, núm. 23, p. 2742Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/2072-4292/11/23/2742Version
info:eu-repo/semantics/publishedVersionAbstract
Drought is a major natural disaster that creates a negative impact on socio-economic development and environment. Drought indices are typically applied to characterize drought events in a meaningful way. This study ... [+]
Drought is a major natural disaster that creates a negative impact on socio-economic development and environment. Drought indices are typically applied to characterize drought events in a meaningful way. This study aims at examining variations in agricultural drought severity based on the relationship between standardized ratio of actual and potential evapotranspiration (ET and PET), enhanced vegetation index (EVI), and land surface temperature (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. A new drought index, called the enhanced drought severity index (EDSI), was developed by applying spatiotemporal regression methods and time-series biophysical data derived from remote sensing. In addition, time-series trend analysis in the 2001–2018 period, along with the Mann–Kendal (MK) significance test and the Theil Sen (TS) slope, were used to examine the spatiotemporal dynamics of environmental parameters (i.e., LST, EVI, ET, and PET), and geographically weighted regression (GWR) was subsequently applied in order to analyze the local correlations among them. Results showed that a significant correlation was discovered among LST, EVI, ET, and PET, as well as their standardized ratios (|r| > 0.8, p < 0.01). Additionally, a high performance of the new developed drought index, showing a strong correlation between EDSI and meteorological drought indices (i.e., standardized precipitation index (SPI) or the reconnaissance drought index (RDI)), measured at meteorological stations, giving r > 0.7 and a statistical significance p < 0.01. Besides, it was found that the temporal tendency of this phenomenon was the increase in intensity of drought, and that coastal areas in the study area were more vulnerable to this phenomenon. This study demonstrates the effectiveness of EDSI and the potential application of integrating spatial regression and time-series data for assessing regional drought conditions. [-]
Is part of
Remote Sensing, 2019, vol. 11, núm. 23, p. 2742Investigation project
This study was funded by the Ministry of Education and Training (5652/QĐ-BGDĐT) in Vietnam under the grant number B2019 –SPH - 03. P.H.T was supported by Vietnam Academy of Science and Technology (VAST) under grant number VAST05.04/16-17.Rights
info:eu-repo/semantics/openAccess
This item appears in the folowing collection(s)
- INIT_Articles [753]
- LSI_Articles [362]
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).