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

2019 ◽  
Vol 11 (23) ◽  
pp. 2742 ◽  
Author(s):  
Tran ◽  
Tran ◽  
Myint ◽  
Latorre-Carmona ◽  
Ho ◽  
...  

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.

2021 ◽  
Author(s):  
Javad Bazrafshan ◽  
Zahra Azhdari

Abstract In arid and semi-arid regions, precipitation and seasonal streamflow are the two major sources of water for vegetation. The scarcity of these water sources has a detrimental effect on vegetation cover degradation. The purpose of this research is to study the effect of meteorological and hydrological droughts, and also their combined effects, on vegetation changes in seven coastal sub-basins in southern Iran (part of the Bandar-Sedij and Kol-Mehran catchment). To track meteorological and hydrological droughts, the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) were used. The copula function and the entropy approach (which is developed in this research) were used to blend individual meteorological and hydrological drought indices, yielding hybrid indices called the Copula-based Drought Index and the Entropy-based Drought Index (EnDI). The single (i.e., SPI and SDI) and hybrid drought indices (CoDI and EnDI) were compared in terms of temporal behavior, drought severity and duration characteristics, drought frequency, and a bivariate analysis of the drought severity-duration return period. The results indicated that the rank correlation (\({r}_{s}\)) between SPI and SDI ranged between 0.327 and 0.726 in the studied sub-basins. However, the two hybrid indices CoDI and EnDI had extremely high correlations (\({r}_{s}\ge 0.9\)). Despite the fact that meteorological droughts benefited both hybrid drought indices more than hydrological droughts, the contribution of meteorological droughts to EnDI was greater than that of CoDI. Over the study region, CoDI reported droughts that were both longer and more severe than those recorded by EnDI. EnDI showed stronger associations with the Normalized Vegetation Difference Index (NDVI) in nearly all the sub-basins, possibly because precipitation has a greater effect on EnDI than it does on CoDI. EnDI was therefore recommended as a superior index for estimating vegetation droughts throughout the research region.


2021 ◽  
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su

&lt;p&gt;Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982&amp;#8211;2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI&lt;sub&gt;&lt;/sub&gt;= 0.34, SSI&lt;sub&gt;&lt;/sub&gt;= 0.24, scPDSI&lt;sub&gt;&lt;/sub&gt;= 0.23, SPI&lt;sub&gt;&lt;/sub&gt;= 0.20, SPEI&lt;sub&gt;&lt;/sub&gt;= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982&amp;#8211;1986, 1990&amp;#8211;1996, and 2005&amp;#8211;2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.&lt;/p&gt;


2019 ◽  
Vol 43 (5) ◽  
pp. 627-642 ◽  
Author(s):  
Luis Eduardo Quesada-Hernández ◽  
Oscar David Calvo-Solano ◽  
Hugo G Hidalgo ◽  
Paula M Pérez-Briceño ◽  
Eric J Alfaro

The Central American Dry Corridor (CADC) is a sub-region in the isthmus that is relatively drier than the rest of the territory. Traditional delineations of the CADC’s boundaries start at the Pacific coast of southern Mexico, stretching south through Central America’s Pacific coast down to northwestern Costa Rica (Guanacaste province). Using drought indices (Standardized Precipitation Index, Modified Rainfall Anomaly Index, Palmer Drought Severity Index, Palmer Hydrological Drought Index, Palmer Drought Z-Index and the Reconnaissance Drought Index) along with a definition of aridity as the ratio of potential evapotranspiration (representing demand of water from the atmosphere) over precipitation (representing the supply of water), we proposed a CADC delineation that changes for normal, dry and wet years. The identification of areas that change their classification during extremely dry conditions is important because these areas may indicate the location of future expansion of aridity associated with climate change. In the same way, the delineation of the CADC during wet extremes allows the identification of locations that remain part of the CADC even during the wettest years and that may require special attention from the authorities.


2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.


2020 ◽  
Author(s):  
Song Youngseok ◽  
Kim Jinbok ◽  
Park Jongun ◽  
Park Moojong

&lt;p&gt;Unlike natural disasters such as typhoons, torrential rains and floods, drought is a disaster caused by long-term effects as well as short-term effects. The effect of drought is caused by damage from a short period of weeks to a long period of years, which causes extensive and enormous damage to agriculture, life, society and economy. In addition, the recent climate change has affected the frequency and scale of rainfall in the global temperature, so it is necessary to prepare measures against it.&lt;/p&gt;&lt;p&gt;The past studies on drought have been conducted using drought indexes such as agricultural, meteorological, and hydrological methods to evaluate drought. The representative drought indexes for each drought are Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Agricultural drought is Crop Moisture Index (CMI), Crop Specific Drought Index (CSDI), Hydrological drought is Surface Drought Water Supply Index (SWSI), Reclamation Drought Index (RDI) and so on are used. However, these drought indices are only used as a method of predicting the depth of drought, and do not give the actual number of drought occurrences.&lt;/p&gt;&lt;p&gt;In this study, we want to determine the frequency of Mega-drought occurrences in consideration of the drought damage characteristics that occurred worldwide from 1900 to 2018. The drought damages in the world were used by EM-DAT (the Emergency Events Database) which manages disaster data in CRED (Centre for Research on the Epidemiology of Disasters). Drought damages occurred in the world from 1900 to 2018 occurred more than once/years in 146 countries. The duration of drought persistence occurred in the country continuously for at least one to 17 years. The purpose of this study is to propose the criteria for mega drought by using the past victim data in connection with the incidence frequency.&lt;/p&gt;&lt;p&gt;Acknowledges : This research was supported by a grant(2019-MOIS31-010) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety(MOIS).&lt;/p&gt;&lt;div&gt;&amp;#160;&lt;/div&gt;


2008 ◽  
Vol 9 (2) ◽  
pp. 292-299 ◽  
Author(s):  
Eleanor J. Burke ◽  
Simon J. Brown

Abstract The uncertainty in the projection of future drought occurrence was explored for four different drought indices using two model ensembles. The first ensemble expresses uncertainty in the parameter space of the third Hadley Centre climate model, and the second is a multimodel ensemble that additionally expresses structural uncertainty in the climate modeling process. The standardized precipitation index (SPI), the precipitation and potential evaporation anomaly (PPEA), the Palmer drought severity index (PDSI), and the soil moisture anomaly (SMA) were derived for both a single CO2 (1×CO2) and a double CO2 (2×CO2) climate. The change in moderate drought, defined by the 20th percentile of the relevant 1×CO2 distribution, was calculated. SPI, based solely on precipitation, shows little change in the proportion of the land surface in drought. All the other indices, which include a measure of the atmospheric demand for moisture, show a significant increase with an additional 5%–45% of the land surface in drought. There are large uncertainties in regional changes in drought. Regions where the precipitation decreases show a reproducible increase in drought across ensemble members and indices. In other regions the sign and magnitude of the change in drought is dependent on index definition and ensemble member, suggesting that the selection of appropriate drought indices is important for impact studies.


Author(s):  
G. J. Perez ◽  
M. Macapagal ◽  
R. Olivares ◽  
E. M. Macapagal ◽  
J. C. Comiso

A monitoring and forecasting sytem is developed to assess the extent and severity of agricultural droughts in the Philippines at various spacial scales and across different time periods. Using Earth observation satellite data, drought index, hazard and vulnerability maps are created. The drought index, called Standardized Vegetation-Temperature Ratio (SVTR), is derived using the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). SVTR is evaluated by correlating its values with existing agricultural drought index, particulary Evaporative Stress Index (ESI). Moreover, the performance of SVTR in detecting drought occurrences was assessed for the 2015-2016 drought event. This period is a strong El Niño year and a large portion of the country was affected by drought at varying degrees, making it a good case study for evaluating drought indices. Satellitederived SVTR was validated through several field visits and surveys across different major agricultural areas in the country, and was found to be 73% accurate. The drought hazard and vulnerability maps are produced by utilizing the evapotranspration product of MODIS, rainfall climatology from the Tropical Rainfall Microwave Mission (TRMM) and ancillary data, including irrigation, water holding capacity and land use. Finally, we used statistical techniques to determine trends in NDVI and LST and generate a sixmonth forecast of drought index. Outputs of this study are being assessed by the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) and the Department of Agriculture Bureau of Soils and Water Management (DABSWM) for future integration in their operations.


2021 ◽  
Author(s):  
Oualid HAKAM ◽  
◽  
Abdennasser BAALI ◽  
Touria EL KAMEL ◽  
Ahouach Youssra ◽  
...  

Due to the lack of studies on drought in the Lower Sebou basin (LSB), the complexity of drought event and the difference in climate conditions. The identification of the most appropriate drought indices (DIs) to assess drought conditions has become a priority. Therefore, assessing the performance of different drought indices was considered in order to identify the universal drought indices that are well adapted to the LSB. Based on data availability, five DIs were used: Standardized Precipitation Index (SPI), Standardized Precipitation and Evapotranspiration Index (SPEI), Reconnaissance Drought Index (RDI), self-calibrated Palmer Drought Severity Index (sc-PDSI) and Streamflow Drought Index (SDI). The DIs were calculated on an annual scale using monthly time series of precipitation, temperature and river flow from 1984-2016. Thornthwaite's method was used to calculate potential evapotranspiration (PET). Pearson's correlation (r) were analyzed. Furthermore, five decision criteria namely robustness, traceability, transparency, sophistication and scalability were used to evaluate the performance of these indices. The results proved the fact that SPI is suitable to detect the drought duration and intensity compared to other indices with high correlation coefficients especially in sub humid regions, knowing that it tends to give more results that are humid in stations with semi-arid climates. SPI, SPEI and RDI follow the same trend during the period studied. However, sc-PDSI appears to be the most sensitive to temperature and precipitation by overestimating the drought conditions. Eventually, the results of the performance evaluation criteria revealed that SPEI classified first (total score = 137) among other meteorological drought indices, followed by SPI, RDI and sc-PDSI.


Author(s):  
A. Dare ◽  
E. J. Zakka ◽  
Maikano Samson ◽  
A. O. Afolabi ◽  
S. O. Okechalu ◽  
...  

Drought is defined as the lack of adequate precipitation, either rain or snow that causes reduced soil moisture or groundwater, diminished streamflow, crop damage and a general water shortage. The objective of this study focuses on meteorological and hydrological drought monitoring in river Kaduna catchment area. Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) drought indices were used to characterize meteorological drought while Streamflow Drought Index (SDI) was used for hydrological drought monitoring for a period of 34 years (1967 – 2001). DrinC software, a drought indices calculator, was used for the calculation of SPI, RDI, and SDI respectively. The drought severity classification based on meteorological and hydrological drought indices gave 33% and 37% drought conditions period with the year 1967 – 2001. Based on these indexes, the drought characteristics of the catchment area were investigated by analyzing meteorological data from 1967 to 2001. The results of this analysis show that more non-drought/normal conditions were predominant than drought conditions. During the period under study (34 years), only one-year return period of extreme drought condition.


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