Assessing Spatiotemporal Drought Dynamics and Its Related Environmental Issues in the Mekong River Delta

Remote Sensing

Thuong V. Tran¹  Hung N. Dao²  Phuong H. Tran³  Duan D. Ho³  Pedro Latorre-Carmona⁴  Duy X. Tran⁵  Soe W. Myint⁶ 

[1] Centre for Climate Changes Studies, University of Social Sciences and Humanities, VNU-HCM, HCMC 70000, Vietnam;Faculty of Geography, Hanoi National University of Education, Hanoi 10000, Vietnam;Ho Chi Minh City Institute of Resources Geography, Vietnam Academy of Science and Technology, HCMC 70000, Vietnam;Institute of New Imaging Technologies, Universitat Jaume, I 12071 Castelló de la Plana, Spain;School of Agriculture and Environment, Massey University, Palmerston North 4442, New Zealand;School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287-0104, USA;

关键词: drought index;    lst;    evi;    et;    pet;    mekong;   

DOI  :  10.3390/rs11232742

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown