SPI-Based Analyses of Drought Changes over the Past 60 Years in China’s Major Crop-Growing Areas

Xia, Lang; Zhao, Fen; Mao, Kebiao; Yuan, Zijin; Zuo, Zhiyan; Xu, Tongren

doi:10.3390/rs10020171

Cited by 33 publications

(22 citation statements)

References 33 publications

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“…Drought is a complex and recurring natural disaster that occurs throughout the world and often has negative impacts on many sectors of society [1,2]. Droughts are increasing in frequency and severity, and their impact on human lives and the economy is accelerating due to growing levels of urbanization and an increasing number of extreme weather events [3][4][5]. The effective assessment of drought is an essential means towards achieving sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Capability of Remotely Sensed Drought Indices for Representing the Spatio–Temporal Variations of the Meteorological Droughts in the Yellow River Basin

Wang

Yang

et al. 2018

Remote Sensing

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Due to the advantages of wide coverage and continuity, remotely sensed data are widely used for large-scale drought monitoring to compensate for the deficiency and discontinuity of meteorological data. However, few studies have focused on the capability of various remotely sensed drought indices (RSDIs) to represent the spatio–temporal variations of meteorological droughts. In this study, five RSDIs, namely the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Modified Temperature Vegetation Dryness Index (MTVDI), and Normalized Vegetation Supply Water Index (NVSWI), were calculated using monthly Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS). The monthly NDVI and LST data were filtered by the Savitzky–Golay (S-G) filtering method. A meteorological station-based drought index represented by the Standardized Precipitation Evapotranspiration Index (SPEI) was compared with the RSDIs. Additionally, the dimensionless Skill Score (SS) method was adopted to identify the spatiotemporally optimal RSDIs for presenting meteorological droughts in the Yellow River basin (YRB) from 2000 to 2015. The results indicated that: (1) RSDIs revealed a decreasing drought trend in the overall YRB consistent with the SPEI except for in winter, and different variations of seasonal trends spatially; (2) the optimal RSDIs in spring, summer, autumn, and winter were VHI, TCI, MTVDI, and VCI, respectively, and the average correlation coefficient between the RSDIs and the SPEI was 0.577 (α = 0.05); and (3) different RSDIs have time lags of zero–three months compared with the meteorological drought index.

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Section: Introductionmentioning

confidence: 99%

Capability of Remotely Sensed Drought Indices for Representing the Spatio–Temporal Variations of the Meteorological Droughts in the Yellow River Basin

Wang

Yang

et al. 2018

Remote Sensing

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“…Significant efforts have been made to develop drought indices. Indeed, hundreds of drought indices, broadly based on meteorological and satellite data, have been developed [15,16]. The use of meteorological data-based drought indices, such as the Standardized Precipitation Index (SPI [17]) and the Palmer Drought Severity Index (PDSI [18]) are common in the literature [15].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Method for Identifying Present Status and Risk of Drought in Bangladesh

et al. 2020

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The occurrence and severity of agricultural droughts may not be dependent upon climatic variables alone. Rather increasingly, drought is affected by human interventions such as irrigation. Anthropogenic activity has introduced uncertainty in the assessment of current drought and future drought risk in many parts of the world; neither climatic nor remote sensing data alone are able to assess drought conditions effectively. In response, we present a simple approach to assess drought by combining a remote sensing-based drought index, the Temperature Vegetation Dryness Index (TVDI), climate data (i.e., rainfall and temperature), and field observations to evaluate recent drought conditions in northwestern Bangladesh (NWB). Applying this approach, we gained five insights: (i) the TVDI successfully indicated the drought conditions of NWB and agrees with field observations, (ii) the integrated use of TVDI and climate data (such as rainfall and temperature) provides the best understanding of the difference between meteorological drought and droughts resulting from surface moisture conditions, (iii) the TVDI results agree with rainfall data (r2 = 0.40 in March and r2 = 46 in April) in a part of the study area (NWB) where irrigation is not available, (iv) the TVDI can be used along with climate data to predict the potential risk of drought, and (v) while meteorological drought exists due to low rainfall and high temperature in this NWB in pre-monsoon season, because of widespread irrigation practices, meteorological drought is unable to trigger agricultural drought over most parts of the study area. The findings imply that there is a potential risk of drought in NWB, since any disruption of irrigation water supply could trigger a severe agricultural drought over the whole region. This is similar to what is currently observed over a small part of NWB.

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“…There are now many distinct satellite-based precipitation products available, with some of them being widely used and having large-scale coverage with high spatial and temporal resolutions, such as the National Aeronautics and Space Administration (NASA) tropical rainfall measuring mission (TRMM) multi-satellite precipitation analysis (TMPA) [15], the climate prediction center morphing (CMORPH) technique [16] and integrated multi-satellite retrievals for global precipitation measurement (IMERG) [17]. The TRMM precipitation datasets have been available since November 1997 and many researchers have proved its ability for drought monitoring [18][19][20][21][22][23][24]. For example, Zeng et al [18] evaluated the TRMM multi-satellite precipitation analysis (TMPA) in drought monitoring in Lancang River Basin.…”

Section: Introductionmentioning

confidence: 99%

Drought Monitoring Utility using Satellite-Based Precipitation Products over the Xiang River Basin in China

et al. 2019

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Drought is a natural hazard disaster that can deeply affect environments, economies, and societies around the world. Therefore, accurate monitoring of patterns in drought is important. Precipitation is the key variable to define the drought index. However, the spare and uneven distribution of rain gauges limit the access of long-term and reliable in situ observations. Remote sensing techniques enrich the precipitation data at different temporal–spatial resolutions. In this study, the climate prediction center morphing (CMORPH) technique (CMORPH-CRT), the tropical rainfall measuring mission (TRMM) multi-satellite precipitation analysis (TRMM 3B42V7), and the integrated multi-satellite retrievals for global precipitation measurement (IMERG V05) were evaluated and compared with in situ observations for the drought monitoring in the Xiang River Basin, a humid region in China. A widely-used drought index, the standardized precipitation index (SPI), was chosen to evaluate the drought monitoring utility. The atmospheric water deficit (AWD) was used for comparison of the drought estimation with SPI. The results were as follows: (1) IMERG V05 precipitation products showed the highest accuracy against grid-based precipitation, followed by CMORPH-CRT, which performed better than TRMM 3B42V7; (2) IMERG V05 showed the best performance in SPI-1 (one-month SPI) estimations compared with CMORPH-CRT and TRMM 3B42V7; (3) SPI-1 was more suitable for drought monitoring than AWD in the Xiang River Basin, because its high R-values and low root mean square error (RMSE) compared with the corresponding index based on in situ observations; (4) drought conditions in 2015 were apparently more severe than that in 2016 and 2017, with the driest area mainly distributed in the southwest part of the Xiang River Basin.

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SPI-Based Analyses of Drought Changes over the Past 60 Years in China’s Major Crop-Growing Areas

Cited by 33 publications

References 33 publications

Capability of Remotely Sensed Drought Indices for Representing the Spatio–Temporal Variations of the Meteorological Droughts in the Yellow River Basin

Capability of Remotely Sensed Drought Indices for Representing the Spatio–Temporal Variations of the Meteorological Droughts in the Yellow River Basin

An Integrated Method for Identifying Present Status and Risk of Drought in Bangladesh

Drought Monitoring Utility using Satellite-Based Precipitation Products over the Xiang River Basin in China

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