Abstract
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.
Highlights
Drought originates from precipitation shortage in a region over an extended period of time and it can be considered as an abnormal climatic event aligned with water resource deficits [1,2]
The Mekong River Delta (MRD), which covers an area of approximately 40,000 km2, is a major agricultural region in the Lower Mekong River Delta (LMRD) (Figure 1)
It was found that the changes in potential evapotranspiration (PET) and land surface temperature (LST) are coherent with the enhanced vegetation index (EVI) change in the study area
Summary
Drought originates from precipitation shortage in a region over an extended period of time and it can be considered as an abnormal climatic event aligned with water resource deficits [1,2]. Meteorological drought is mainly affected by the reduction of precipitation and high temperature, while agricultural drought is caused by soil moisture deficit [8,9]. The hydrological drought occurs as a consequence of stream flow shortage and groundwater reduction and socioeconomic drought takes place when water demand for socioeconomic activities cannot be fulfilled by water supply [9]. Most drought studies were conducted using data from hydro-meteorological stations [10,11,12]. It is necessary to conduct a space and time analysis of this issue
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