Meteorological Drought Analysis in the Lower Mekong Basin Using Satellite-Based Long-Term CHIRPS Product

Guo, Hao; Bao, Anming; Li, Shipeng; Ndayisaba, Felix; He, Daming; Kurban, Alishir; Maeyer, Philippe De

doi:10.3390/su9060901

Cited by 139 publications

(92 citation statements)

References 57 publications

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“…In this sense, Quesada-Montano et al [59] highlighted that the selection of the precipitation database was more important than the selection of the drought index. e use of CHIRPS precipitation estimates for drought monitoring based on the SPI has gained attraction nowadays, as shown by studies performed in Indonesia [60], China [1,28], Nepal [11], Morocco [54], Southeast Asia [27], Central America [59], and Chile [12].…”

Section: Discussionmentioning

confidence: 99%

“…Based on a comparison among six precipitation-based drought indices, the SPI was selected as the most adequate for analysing meteorological droughts along southern South America [44]. For the calculation of the SPI, time series of 1-month, 3-month, and 6month accumulations were generated and tted to a twoparameter gamma distribution function, following previous recommendations for the study area [22] and in other regions [12,13,27]. Finally, an equiprobability transformation from the cumulative density functions to the standard normal distribution with the mean of 0 and the variance of 1 were performed to obtain the SPI.…”

Section: Methodsmentioning

confidence: 99%

“…Besides the efforts for the use of the CHIRPS database as a tool for regional precipitation monitoring, few validation studies evaluated its suitability for the assessment of dry and wet conditions. Guo et al [27] found that CHIRPS can properly capture the drought characteristics at various timescales with the best performance at the three-month timescale. Zambrano et al [12] concluded that, in order to use the CHIRPS dataset to monitor drought intensity conditions, the product should be calibrated to adjust for the overestimation/underestimation of rainfall geographically.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Rivera

Hinrichs

Marianetti

2019

Advances in Meteorology

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e Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987-2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. e large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. e frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. is bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. e results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Rivera

Hinrichs

Marianetti

2019

Advances in Meteorology

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“…In every drought monitoring practice more emphasis is given to meteorological drought (simple absence/deficit of rainfall from the normal) as it is the first to occur and other droughts are consequent to it (Goshu et al, 2017). If the precipitation deficit continues for a longer period, all the other drought happens one after the other (Hao et al, 2017). Many countries consider that drought monitoring system is one of most effective ways for reducing drought damages by early drought detection and issuing warnings (Boken et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

Drought Monitoring in the Dry Zone of Myanmar using MODIS Derived NDVI and Satellite Derived CHIRPS Precipitation Data

Dutta¹

2018

SAR

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Drought has become an increasingly frequent phenomena around the globe causing negative impacts on ecosystems, agriculture, and socio-economic conditions. While efforts have been underway for developing effective monitoring and risk management measures, it still remains a challenge in countries like Myanmar where access to observed and near real time data is a constraint. This study therefore, tries to derive correlations between MODIS Normalized Difference Vegetation Index (NDVI) and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data to see if some empirical relationships can be established. Statistical analysis showed that strong correlation (R² = 0.74 and 0.82) exist between NDVI and CHIRPS data indicating that vegetation stress conditions observed in the Dry Zone of Myanmar is due to insufficient precipitation conditions. The analysis also showed that the region had faced with three extreme conditions during the period from 1981-2015 with 2014 and 2015 being the extreme event. It further concluded that NDVI and CHIRPS could provide near real time information on vegetation stress situations of the Dry Zone of Myanmar.

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“…Extreme drought events were recorded in the study area in 1992, 1993, 1998, and 1999 [47]. The recently extreme drought occurrences had taken place in 2003, 2006, and 2017 [48].…”

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confidence: 99%

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

Tran

Myint

et al. 2019

Remote Sensing

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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.

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Meteorological Drought Analysis in the Lower Mekong Basin Using Satellite-Based Long-Term CHIRPS Product

Cited by 139 publications

References 57 publications

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Drought Monitoring in the Dry Zone of Myanmar using MODIS Derived NDVI and Satellite Derived CHIRPS Precipitation Data

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

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