SCIENCE CHINA Earth Sciences, Volume 60, Issue 4: 745-760(2017) https://doi.org/10.1007/s11430-016-5133-5

Regional applicability of seven meteorological drought indices in China

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  • ReceivedNov 22, 2016
  • AcceptedJan 3, 2017
  • PublishedMar 9, 2017


The definition of a drought index is the foundation of drought research. However, because of the complexity of drought, there is no a unified drought index appropriate for different drought types and objects at the same time. Therefore, it is crucial to determine the regional applicability of various drought indices. Using terrestrial water storage obtained from the Gravity Recovery And Climate Experiment, and the observed soil moisture and streamflow in China, we evaluated the regional applicability of seven meteorological drought indices: the Palmer Drought Severity Index (PDSI), modified PDSI (PDSI_CN) based on observations in China, self-calibrating PDSI (scPDSI), Surface Wetness Index (SWI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and soil moisture simulations conducted using the community land model driven by observed atmospheric forcing (CLM3.5/ObsFC). The results showed that the scPDSI is most appropriate for China. However, it should be noted that the scPDSI reduces the value range slightly compared with the PDSI and PDSI_CN; thus, the classification of dry and wet conditions should be adjusted accordingly. Some problems might exist when using the PDSI and PDSI_CN in humid and arid areas because of the unsuitability of empiricalparameters. The SPI and SPEI are more appropriate for humid areas than arid and semiarid areas. This is because contributions of temperature variation to drought are neglected in the SPI, but overestimated in the SPEI, when potential evapotranspiration is estimated by the Thornthwaite method in these areas. Consequently, the SPI and SPEI tend to induce wetter and drier results, respectively. The CLM3.5/ObsFC is suitable for China before 2000, but not for arid and semiarid areas after 2000. Consistent with other drought indices, the SWI shows similar interannual and decadal change characteristics in detecting annual dry/wet variations. Although the long-term trends of drought areas in China detected by these seven drought indices during 1961–2013 are consistent, obvious differences exist among the values of drought areas, which might be attributable to the definitions of the drought indices in addition to climatic change.

Funded by

National Basic Research Program of China(2012CB956201)

National Natural Science Foundation of China(41275085,41530532 ,&, 41305062)

National Key Technology R&D Program of China(2013BAC10B02,China Special Fund for Meteorological Research in the Public Interest (Grant No. GYHY201506001-1)


This research was supported by the National Basic Research Program of China (Grant No. 2012CB956201), the National Natural Science Foundation of China (Grant Nos. 41275085, 41530532 & 41305062), the National Key Technology R&D Program of China (Grant No. 2013BAC10B02) and China Special Fund for Meteorological Research in the Public Interest (Grant No. GYHY201506001-1).


[1] Adam D. Gravity measurement: Amazing grace. Nature, 2002, 416: 10-11 CrossRef PubMed Google Scholar

[2] Allen R G, Pereira L S, Raes D, Smith M. 1998. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Rome, 300: D05109. Google Scholar

[3] An S Q, Xing J X. 1986. A modified Palmer’s Drought Index (in Chinese). J Acad Meteorol Sci China, 1: 75–82. Google Scholar

[4] Cao Y P, Nan Z T, Cheng G D. 2015. GRACE gravity satellite monitoring of drought characteristics in Xinjiang (in Chinese). J Arid Land Resour Environ, 29: 87–92. Google Scholar

[5] Dai A. Characteristics and trends in various forms of the Palmer drought severity index during 1900–2008. J Geophys Res, 2011a, 116: D12115 CrossRef ADS Google Scholar

[6] Dai A. Drought under global warming: A review. WIREs Clim Change, 2011b, 2: 45-65 CrossRef Google Scholar

[7] Dai A. Increasing drought under global warming in observations and models. Nat Clim Change, 2012, 3: 52-58 CrossRef ADS Google Scholar

[8] Dai A, Trenberth K E, Karl T R. Global variations in droughts and wet spells: 1900–1995. Geophys Res Lett, 1998, 25: 3367-3370 CrossRef ADS Google Scholar

[9] Dai Y J, Zeng X B, Dickinson R E, Baker I, Bonan G B, Bosilovich M G, Denning A S, Dirmeyer P A, Houser P R, Niu G Y, Oleson K W, Schlosser C A, Yang Z L. The common land model. Bull Amer Meteorol Soc, 2003, 84: 1013-1023 CrossRef ADS Google Scholar

[10] Diaz H F. Drought in the united states. J Clim Appl Meteorol, 1983, 22: 3-16 CrossRef Google Scholar

[11] Fei Y H, Miao J X, Zhang Z J, Chen Z Y, Song H B, Yang M. 2009. Analysis on evolution of groudwater depression cones and its leading factors in North China Plain (in Chinese). Resour Sci, 31: 394–399. Google Scholar

[12] Friedl M A, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang X. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sens Environ, 2010, 114: 168-182 CrossRef Google Scholar

[13] Getirana A. Extreme water deficit in Brazil detected from space. J Hydrometeorol, 2016, 17: 591-599 CrossRef ADS Google Scholar

[14] Grayson M. Agriculture and drought. Nature, 2013, 501: S1 CrossRef PubMed ADS Google Scholar

[15] Heim R R. 2002. A review of twentieth-century drought indices used in the United States. Bull Amer Meteorol Soc, 83: 1149–1165. Google Scholar

[16] Hulme M, Marsh R, Jones P. Global changes in a humidity index between 1931–60 and 1961–90. Clim Res, 1992, 2: 1-22 CrossRef Google Scholar

[17] Karl T R, Koscielny A J. Drought in the United States: 1895–1981. J Climatol, 1982, 2: 313-329 CrossRef ADS Google Scholar

[18] Kerr Y H. Soil moisture from space: Where are we?. Hydrogeol J, 2007, 15: 117-120 CrossRef ADS Google Scholar

[19] Keyantash J, Dracup J A. 2002. The quantification of drought: An evaluation of drought indices. Bull Amer Meteorol Soc, 83: 1167–1180. Google Scholar

[20] Li M X, Ma Z G. Comparisons of simulations of soil moisture variations in the Yellow River basin driven by various atmospheric forcing data sets. Adv Atmos Sci, 2010, 27: 1289-1302 CrossRef ADS Google Scholar

[21] Li M X, Ma Z G. Soil moisture-based study of the variability of dry-wet climate and climate zones in China. Chin Sci Bull, 2013, 58: 531-544 CrossRef Google Scholar

[22] Li M X, Ma Z G. Soil moisture drought detection and multi-temporal variability across China. Sci China Earth Sci, 2015, 58: 1798-1813 CrossRef Google Scholar

[23] Liu W W, An S Q, Liu G S, Guo A H. 2004. The farther modification of Palmer drought severity model (in Chinese). J Appl Meteorol Sci, 15: 207–216. Google Scholar

[24] Lloyd-Hughes B, Saunders M A. A drought climatology for Europe. Int J Climatol, 2002, 22: 1571-1592 CrossRef ADS Google Scholar

[25] Ma Z G. 2005. Dry/wet variation and its relationship with regional warming in arid-regions of norther China (in Chinese). Chin J Geophys, 48: 1011–1018. Google Scholar

[26] Ma Z G. The interdecadal trend and shift of dry/wet over the central part of North China and their relationship to the Pacific Decadal Oscillation (PDO). Chin Sci Bull, 2007, 52: 2130-2139 CrossRef Google Scholar

[27] Ma Z G, Fu C B. Some evidence of drying trend over northern China from 1951 to 2004. Chin Sci Bull, 2006, 51: 2913-2925 CrossRef Google Scholar

[28] Ma Z G, Fu C B. Global aridification in the second half of the 20th century and its relationship to large-scale climate background. Sci China Ser D-Earth Sci, 2007, 50: 776-788 CrossRef Google Scholar

[29] Ma Z G, Hua L J, Ren X B. 2003. The extreme dry/wet events in Northern China during recent 100 years (in Chinese). Acta Geogr Sin, 58: 69–74. Google Scholar

[30] Mao F, Sun H, Yang H L. 2011. Research progress in dry/wet climate Zoning (in Chinese). Progr Geoger, 30: 17–26. Google Scholar

[31] McKee T B, Doesken N J, Kleist J. 1993. The relationship of drought frequency and duration to time scales. In: 8th Conference on Applied Climatology. Anaheim. 179–184. Google Scholar

[32] McRoberts D B, Nielsen-Gammon J W. The use of a high-resolution standardized precipitation index for drought monitoring and assessment. J Appl Meteorol Climatol, 2012, 51: 68-83 CrossRef Google Scholar

[33] Palmer W C. 1965. Meteorological Drought Research Paper 45. Washington D C: US Weather Bureau. Google Scholar

[34] Sheffield J, Goteti G, Wood E F. Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J Clim, 2006, 19: 3088-3111 CrossRef ADS Google Scholar

[35] Sheffield J, Wood E F, Roderick M L. Little change in global drought over the past 60 years. Nature, 2012, 491: 435-438 CrossRef PubMed ADS Google Scholar

[36] Shi Y F, Shen Y P, Hu R J. 2002. Preliminary study on signal, impact and foreground of climatic shift from warm-dry to warm-humid in Northwest China (in Chinese). J Glaciol Geocryol, 24: 219–226. Google Scholar

[37] Shi Y F, Shen Y P, Li D L, Zhang G W. 2003. Discussion on the present climate change from warm-dry to warm-wet in Northwest China (in Chinese). Quat Sci, 23: 152–164. Google Scholar

[38] Sims A P, Niyogi D S, Raman S. Adopting drought indices for estimating soil moisture: A North Carolina case study. Geophys Res Lett, 2002, 29: 24-1-24-4 CrossRef ADS Google Scholar

[39] Sternberg T. Regional drought has a global impact. Nature, 2011, 472: 169-169 CrossRef PubMed Google Scholar

[40] Su X L, Ping J S, Ye Q X. Terrestrial water variations in the North China Plain revealed by the GRACE mission. Sci China Earth Sci, 2011, 54: 1965-1970 CrossRef Google Scholar

[41] The Ministry of Water Resources of the People’s Republic of China. 2007. Chinese Water Resources Bulletin 2006 (in Chinese). Beijing: Chian water Conservancy and Hydropower Press. Google Scholar

[42] Thornthwaite C W. An approach toward a rational classification of climate. Geographical Rev, 1948, 38: 55-94 CrossRef Google Scholar

[43] United Nations. 1994. Elaboration of an International Convention to Combat Desertification in Countries Experiencing Serious Drought and/or Desertification particularly in Africa. Environmental Policy and Law, A/RES/51/180, 5. Google Scholar

[44] van der Schrier G, Jones P D, Briffa K R. The sensitivity of the PDSI to the Thornthwaite and Penman-Monteith parameterizations for potential evapotranspiration. J Geophys Res, 2011, 116: D03106 CrossRef ADS Google Scholar

[45] Vicente-Serrano S M, Beguería S, López-Moreno J I, Angulo M, El Kenawy A. A new global 0.5° gridded dataset (1901–2006) of a multiscalar drought index: Comparison with current drought index datasets based on the Palmer drought severity index. J Hydrometeorol, 2010, 11: 1033-1043 CrossRef ADS Google Scholar

[46] Vicente-Serrano S M, Beguería S, Lorenzo-Lacruz J, Camarero J J, López-Moreno J I, Azorin-Molina C, Revuelto J, Morán-Tejeda E, Sanchez-Lorenzo A. Performance of drought indices for ecological, agricultural, and hydrological applications. Earth Interact, 2012, 16: 1-27 CrossRef ADS Google Scholar

[47] Wang C H, Wang Z L, Guo Y P. 2012. Application and verification of drought index in meteorology drought monitor and prediction (in Chinese). Adv Earth Sci, 27: 957–968. Google Scholar

[48] Wang J S, Guo J Y, Zhou Y W, Yang L F. 2007. Progress and prospect on drought indices research (in Chinese). Arid Land Geogr, 30: 60–65. Google Scholar

[49] Wang L, Chen W. 2012. Characteristics of multi-timescale variabilities of the drought over last 100 years in Southwest China (in Chinese). Adv Meteorol Sci Technol, 4: 21–26. Google Scholar

[50] Wang S P, Wang J S, Zhang Q, Li Y P, Wang Z L. 2015. Applicability evaluation of drought indices in monthly scale drought monitoring in Southwestern and Southern China (in Chinese). Plateau Meteorol, 34: 1616–1624. Google Scholar

[51] Wang Y, Jiang Z H, Zhang Q, Li K, Liu M, Xue C F. 2008. Evaluating aridity and wetness of the wheat with Palmer moisture anomaly index in the east of Northwest China (in Chinese). J Appl Meteorol Sci, 19: 342–349. Google Scholar

[52] Wang Z L, Wang J S, Li Y H, Wang C H. 2013. Comparision of application between generalized extreme value index and Standardized Precipitation Index in Northwest China (in Chinese). Plateau Meteorol, 32: 839–847. Google Scholar

[53] Wei J, Tao S Y, Zhang Q Y. 2003. Analysis of drought in Northern China based on the palmer severity drought index (in Chinese). Acta Geogr Sin, 58: 91–99. Google Scholar

[54] Wells N, Goddard S, Hayes M J. A Self-Calibrating Palmer drought severity index. J Clim, 2004, 17: 2335-2351 CrossRef Google Scholar

[55] Wilhite D A. 2000. Drought as a natural hazard: Concepts and definitions. In: Drought—National Drought Mitigation Center. Vol. 1. London: Routledge. 3–18. Google Scholar

[56] Wilhite D A. 2002. Drought in the US great plains. In: Handbook of Weather, Climate, and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts. Hoboken: John Wiley & Sons. 743–758. Google Scholar

[57] Wilhite D A, Glantz M H. Understanding: The drought phenomenon: The role of definitions. Water Int, 1985, 10: 111-120 CrossRef Google Scholar

[58] Yao Y B, Zhang C J, Deng Z Y, Dong A X, Zhang X Y, Wei F, Yang J H. 2007. Overview of meteorological and agricultural drought indices (in Chinese). Agric Rese Arid Areas, 25: 185–211. Google Scholar

[59] Yuan W P, Zhou G S. 2004a. Theoratical study and research prospect on drought indices (in Chinese). Adv Earth Sci, 19: 982–991. Google Scholar

[60] Yuan W P, Zhou G S. 2004b. Comparison between Standardized Precipitaiton Index and Z_index in China (in Chinese). Acta Phytoecol Sin, 28: 523–529. Google Scholar

[61] Zhai J, Su B, Krysanova V, Vetter T, Gao C, Jiang T. Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of China. J Clim, 2010, 23: 649-663 CrossRef Google Scholar

[62] Zhang Q, Zhang L, Cui X C, Zeng J. 2011. Progresses and challenges in drought assessment and monitoring (in Chinese). Adv Earth Sci, 26: 763–778. Google Scholar

[63] Zhao J, Yang D H, Yang Z Y, Hu Y, Weng B S, Gong B Y. 2015. Improvement and adaptability evaluation of Standardized Precipitation Evapotranspiration Index (in Chinese). Acta Phys Sin, 64: 049202. Google Scholar

[64] Zhao Y L, Ren F M, Li D L, Liu J Y. 2013. Study on improvement of drought index base on effective precipitation (in Chinese). Meteorol Monthly, 39: 600–607. Google Scholar

[65] Zhou T, Shi P J, Fan Y D. 2002. The change trend of soil mositure in northern China and the influences of human being on them (in Chinese). J Beijing Normal Univ-Natural Sci, 38: 131–137. Google Scholar

[66] Zhu C H, Zhang Q, Chen Y. 2003. Ten Extreme Meteorological Events in 2002 in China (in Chinese). J Catastrophol, 16: 74–78. Google Scholar

[67] Zou X K, Ren G Y, Zhang Q. 2010. Droughts variations in China based on a compound index of meteorological drought (in Chinese). Clim Environ Res, 15: 371–378. Google Scholar

  • Figure 1

    Distribution of meteorological (753) and agrometeorological (59) stations. Red points indicate agrometeorological stations with high correlation coefficients (R>0.85) between the two observed soil moisture datasets during 1991–2002. Blue lines show Yangtze and Yellow Rivers.

  • Figure 2

    Correlations between observed warm seasons (April–October) mean 10-cm relative soil moisture and (a) SPI12, (b) SPEI12, (c) PDSI, (d) scPDSI, (e) PDSI-CN, and (f) CLM3.5/ObsFC during 1991–2013.

  • Figure 3

    Evolution of warm seasons mean 10-cm relative soil moisture (standardized, Obs), SPI12, SPEI12, scPDSI, and CLM3.5/ObsFC over the west of northwestern China. The PDSI and PDSI-CN are omitted because they were consistent with the scPDSI (correlation coefficients R>0.85).

  • Figure 4

    Evolution of standardized warm seasons mean 10-cm soil moisture, SPI12, SPEI12, scPDSI, and CLM3.5/ObsFC for four stations during 1981–2013. The PDSI and PDSI-CN are omitted because they were consistent with the scPDSI (correlation coefficients R>0.97).

  • Figure 5

    (a) Stations located in the Yellow River valley (green) and Yangtze River valley (orange); evolution of the SPI12, SPEI12, scPDSI, SWI, CLM3.5/ObsFC, and streamflow over (b) the Yellow River valley and (c) the Yangtze River valley during 1961–2013. The PDSI and PDSI-CN are omitted because they were consistent with the scPDSI (correlation coefficients R>0.95).

  • Figure 6

    Correlations between terrestrial water storage with (a) SPI12, (b) SPEI12, (c) PDSI, (d) scPDSI, (e) PDSI-CN, and (f) CLM3.5/ObsFC during 2002.04–2013.12.

  • Figure 7

    (a) Distribution of cropland in China based on 2010 Moderate Resolution Imaging Spectroradiometer LULC and agrometeorological stations (31) over North China; (b) evolution of terrestrial water storage (GRACE), SPI12, SPEI12, scPDSI, and CLM3.5/ObsFC, observed 50-cm relative soil moisture and monthly precipitation anomalies (unit: mm). Values in parentheses indicate correlation coefficients between terrestrial water storage with other variables, passing the 0.05 significant test. The PDSI and PDSI-CN are omitted because they were consistent with the scPDSI (correlation coefficients R>0.96).

  • Figure 8

    Correlations between (a) PDSI and PDSI-CN, (b) PDSI and scPDSI, (c) PDSI-CN and scPDSI during 1961–2013. Correlation coefficients passing the 0.05 significant test are shaded.

  • Figure 9

    Spatial patterns of severe drought frequency in China during 1961–2013. The threshold for severe drought is –3 in (a)‒(c), and the tenth percentile in (d)‒(f).

  • Figure 10

    RMSEs between SPEI12 and PDSI, SPEI12 and SPI12. Scatters and solid lines represent 753 meteorological stations and fitting equations, respectively.

  • Figure 11

    Evolution of (a) drought areas (unit: %) detected by the seven meteorological drought indices, (b) regional averaged annual precipitation and annual mean temperature anomalies in China during 1961–2013. The PDSI and PDSI-CN are omitted in (a) because they were consistent with the scPDSI (correlation coefficients R > 0.97).

  • Table 1   Wet/dry classification for PDSI, PDSI_CN, scPDSI, SPI, and SPEI




    Extreme wet



    Severe wet



    Moderate wet



    Slightly wet





    Slightly drought



    Moderate drought



    Severe drought



    Extreme drought



  • Table 2   Information for the seven meteorological drought indices

    Drought indices




    Time scale


    Palmer Drought Severity Index


    T, P, AWC



    Revised PDSI


    T, P, AWC



    Self-calibrating PDSI


    T, P, AWC



    Surface Wetness Index


    T, P



    Standardized Precipitation Index





    Standardized Precipitation Evapotranspiration Index


    T, P



    Simulated soil moisture


    observation-based atmospheric forcing


    T, monthly mean air temperature; P, monthly accumulated precipitation; AWC, available water capacity

  • Table 3   Correlation coefficients, passing the 0.05 significant test, between warm seasons mean 10-cm soil moisture and SPI12, SPEI12, scPDSI, and CLM3.5/ObsFC (the SWI was unavailable) for four stations during 1981–2013




































  • Table 4   Tendencies of drought areas detected by the seven meteorological drought indices



























    Tendencies passing the 0.05 significant test, unit: % yr–1

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