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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

Abstract

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)


Acknowledgment

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).


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  • 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

    Classes

    PDSI, PDSI_CN, scPDSI

    SPI, SPEI

    Extreme wet

    ≥4.00

    ≥2.00

    Severe wet

    3.00–4.00

    1.50–2

    Moderate wet

    2.00–3.00

    1.00–1.5

    Slightly wet

    1.00–2.00

    0–1

    Normal

    −1–1

    Slightly drought

    −2–−1

    −1–0

    Moderate drought

    −3–−2

    −1.5–−1

    Severe drought

    −4–−3

    −2–−1.50

    Extreme drought

    ≤−4.00

    ≤−2.00

  • Table 2   Information for the seven meteorological drought indices

    Drought indices

    Name

    Definition

    Variables

    Time scale

    PDSI

    Palmer Drought Severity Index

    1965

    T, P, AWC

    month

    PDSI_CN

    Revised PDSI

    2004

    T, P, AWC

    month

    scPDSI

    Self-calibrating PDSI

    2004

    T, P, AWC

    month

    SWI

    Surface Wetness Index

    1992

    T, P

    annual

    SPI

    Standardized Precipitation Index

    1993

    P

    month

    SPEI

    Standardized Precipitation Evapotranspiration Index

    2010

    T, P

    month

    CLM3.5/ObsFC

    Simulated soil moisture

    2010

    observation-based atmospheric forcing

    month

    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

    Stations

    SPI12

    SPEI12

    PDSI

    scPDSI

    PDSI-CN

    CLM3.5/Obs

    54049

    0.78

    0.78

    0.79

    0.77

    0.79

    0.44

    53923

    0.54

    0.72

    0.82

    0.78

    0.75

    0.86

    57290

    0.39

    0.37

    0.47

    0.43

    0.43

    0.44

    58158

    0.49

    0.55

    0.74

    0.68

    0.70

    0.55

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

    SPI12

    SPEI12

    PDSI

    scPDSI

    PDSI_CN

    SWI

    CLM3.5/Obs

    Mean

    1962–1990

    –0.69

    –0.34

    –0.74

    –0.73

    –0.66

    –0.54

    –0.46

    –0.59

    1991–2007

    0.52

    2.03

    1.33

    1.53

    1.48

    0.60

    0.90

    1.25

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

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