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Journal of Arid Land
Journal of Arid Land  2020, Vol. 12 Issue (4): 561-579    DOI: 10.1007/s40333-020-0066-x
Research article     
Spatial-temporal characteristics of drought detected from meteorological data with high resolution in Shaanxi Province, China
Yudan WANG1,2,3, Yunfeng KONG1,2,*(), Hao CHEN3, Yongjian DING4
1 College of Environment and Planning, Henan University, Kaifeng 475004, China
2 Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China
3 School of Geography and Environment, Baoji University of Arts and Sciences, Baoji 721013, China
4 Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
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Abstract  

The spatial pattern of meteorological factors cannot be accurately simulated by using observations from meteorological stations (OMS) that are distributed sparsely in complex terrain. It is expected that the spatial-temporal characteristics of drought in regions with complex terrain can be better represented by meteorological data with the high spatial-temporal resolution and accuracy. In this study, Standard Precipitation Evapotranspiration Index (SPEI) calculated with meteorological factors extracted from ITPCAS (China Meteorological Forcing Dataset produced by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences) was applied to identify the spatial-temporal characteristics of drought in Shaanxi Province of China, during the period of 1979-2016. Drought areas detected by SPEI calculated with data from ITPCAS (SPEI-ITPCAS) on the seasonal scale were validated by historical drought records from the Chinese Meteorological Disaster Canon-Shaanxi, and compared with drought areas detected by SPEI calculated with data from OMS (SPEI-OMS). Drought intensity, trend and temporal ranges for mutations of SPEI-ITPCAS were analyzed by using the cumulative drought intensity (CDI) index and the Mann-Kendall test. The results indicated that drought areas detected from SPEI-ITPCAS were closer to the historical drought records than those detected from SPEI-OMS. Severe and exceptional drought events with SPEI-ITPCAS lower than -1.0 occurred most frequently in summer, followed by spring. There was a general drying trend in spring and summer in Shaanxi Province and a significant wetting trend in autumn and winter in northern Shaanxi Province. On seasonal and annual scales, the regional and temporal ranges for mutations of SPEI-ITPCAS were different and most mutations occurred before the year 1990 in most regions of Shaanxi Province. The results reflect the response of different regions of Shaanxi Province to climate change, which will help to manage regional water resources.

Key words： SPEI      drought areas      meteorological data      cumulative drought intensity      drying trend      wetting trend     
Received: 03 July 2019      Published: 10 July 2020
Corresponding Authors:
About author: *Corresponding author: KONG Yunfeng (E-mail: yfkong@henu.edu.cn)
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Yudan WANG
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WANG Yudan, KONG Yunfeng, CHEN Hao, DING Yongjian. Spatial-temporal characteristics of drought detected from meteorological data with high resolution in Shaanxi Province, China. Journal of Arid Land, 2020, 12(4): 561-579.

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http://jal.xjegi.com/10.1007/s40333-020-0066-x     OR     http://jal.xjegi.com/Y2020/V12/I4/561

Fig. 1 Topography, administrative areas and distribution of standard meteorological stations of Shaanxi Province. N, northern Shaanxi (the Loess Plateau in the northern part of Shaanxi Province); G, Guanzhong (Guanzhong Plain in the middle of Shaanxi Province); S, southern Shaanxi (the Qinba Mountainous region in the southern part of Shaanxi Province). The two blue lines are the northern and southern boundaries of Guanzhong.
Year Season Drought areas
1991 Summer South of northern Shaanxi, Guanzhong and southern Shaanxi (especially in Shangluo)
1994 Winter North of northern Shaanxi and Shangluo
1995 Summer South of northern Shaanxi and Guanzhong
1995 Autumn All regions*
1997 Spring All regions*
1997 Summer All regions*
1998 Autumn All regions*
1998 Winter All regions*
1999 Summer All regions*
2000 Summer Northern Shaanxi, northern Guanzhong and east of southern Shaanxi
2001 Spring All regions*
2001 Summer Northern Shaanxi, Guanzhong and east of southern Shaanxi
2002 Summer All regions of Shaanxi Province except for Tongchuan and south of Yan'an
2008 Winter All regions*
2010 Autumn All regions*
2011 Summer Part of northern Shaanxi and Guanzhong
Table 1 Historical records of typical drought events occurred in Shaanxi Province from the Chinese Meteorological Disaster Canon-Shaanxi
Drought Normal Waterlogging
Exceptional Severe Moderate Normal Moderate Severe Exceptional
SPEI ≤ -2.0 -2.0- -1.0 -1.0- -0.5 -0.5-0.5 0.5-1.0 1.0-2.0 ≥0.0
Table 2 Categories of drought and waterlogging classified by SPEI (Standard Precipitation Evapotranspiration Index)
Fig. 2 Spatial distributions of drought and non-drought areas in Shaanxi Province detected from SPEI-ITPCAS (Standard Precipitation Evapotranspiration Index calculated with data from China Meteorological Forcing Dataset produced by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences). Drought areas were detected as SPEI-ITPCAS lower than -0.5 (Table 2). The two blue lines are the northern and southern boundaries of Guanzhong.
Fig. 3 Spatial distributions of drought and non-drought areas in Shaanxi Province detected from SPEI-OMS (Standard Precipitation Evapotranspiration Index calculated with data from observations of meteorological stations). Drought areas were detected as SPEI-OMS lower than -0.5 (Table 2). The two blue lines are the northern and southern boundaries of Guanzhong.
Year Season Discrepancy of drought areas
1991 Summer North of northern Shaanxi
1994 Winter East of Ankang
2000 Summer North of Guanzhong
2002 Summer Tongchuan and south of Yan'an
Table 3 Discrepancies of drought areas detected from historical drought records of Chinese Meteorological Disaster Canon-Shaanxi and SPEI-ITPCAS
Year Season Discrepancy of drought areas
1991 Summer North of northern Shaanxi
1994 Winter Part of Weinan
1995 Summer South of northern Shaanxi and north of Guanzhong
1999 Summer North of Guanzhong
2000 Summer North of Guanzhong
2001 Summer Yulin
2002 Summer Tongchuan, south of Yan'an and Yulin
2008 Winter Tongchuan, Xianyang and Weinan
2011 Summer Guanzhong and parts of northern Shaanxi
Table 4 Discrepancies of drought areas detected from historical drought records of Chinese Meteorological Disaster Canon-Shaanxi and SPEI-OMS
Fig. 4 Spatial distributions of cumulative drought intensity (CDI) in spring (a), summer (b), autumn (c) and winter (d), and on an annual scale (e) in Shaanxi Province from 1979 to 2016. A1 and A2 represent regions with high CDI values in spring; B1 and B2 represent regions with high CDI values in summer; C1 and C2 represent regions with high CDI values in autumn; E1 and E2 represent regions with high CDI values on an annual scale. The two blue lines are the northern and southern boundaries of Guanzhong.
Season/annual scale Severe and exceptional drought (times) Regions with high CDI values
Spring 12,331 Part of Hanzhong (A1), with an area of about 500 km2; part of Shangluo, Weinan, Ankang and Xi'an (A2), with an area of about 2000 km2
Summer 12,937 Part of Yulin (B1), with an area of about 820 km2; part of Shangluo, Weinan and Xi'an (B2), with an area of about 780 km2
Autumn 11,860 Part of Yan'an (C1), with an area of about 1000 km2; part of Hanzhong (C2), with an area of about 700 km2
Annual 12,250 Part of Yulin (E1), with an area of about 440 km2; part of Shangluo (E2), with an area of about 490 km2
Table 5 Frequencies of severe and exceptional drought (SPEI-ITPCAS lower than -1.0) and regions with high cumulative drought intensity (CDI) values on seasonal and annual scales in Shaanxi Province
Fig. 5 Spatial distributions of variable Z of Mann-Kendall (MK) test for precipitation, temperature and SPEI-ITPCAS in spring (a1-a3), summer (b1-b3), autumn (c1-c3) and winter (d1-d3) in Shaanxi Province. The two blue lines are the northern and southern boundaries of Guanzhong.
Fig. 6 Spatial distributions of variable Z of MK test for precipitation (a), temperature (b) and SPEI-ITPCAS (c) on an annual scale in Shaanxi Province. The two blue lines are the northern and southern boundaries of Guanzhong.
Season/annual scale Z value Trend Regions
Spring Z≥0.00 Upward All of Shaanxi Province except for Xi'an and Weinan
Z≥1.28 Upward* Parts of Yulin and Ankang
Z≤0.00 Downward Xi'an and Weinan
Z≤ -1.28 Downward* Parts of Xi'an and Weinan
Summer Z≥0.00 Upward Tongchuan and parts of Yulin and Yan'an
Z≥1.28 Upward*
Z≤0.00 Downward Parts of northern Shaanxi, Guanzhong (except for Tongchuan) and southern Shaanxi
Z≤ -1.28 Downward* Parts of Baoji, Hanzhong and Weinan
Autumn Z≥0.00 Upward All of Shaanxi Province except for parts of Weinan, Xi'an, Shangluo and Ankang
Z≥1.28 Upward* Yulin and Yan'an
Z≤0.00 Downward Parts of Weinan, Xi'an, Shangluo and Ankang
Z≤ -1.28 Downward* Parts of Xi'an and Ankang
Winter Z≥0.00 Upward All of Shaanxi Province except for parts of Weinan, Xi'an, Ankang and Hanzhong
Z≥1.28 Upward* Yulin, Yan'an, and parts of Tongchuan, Xianyang and Baoji
Z≤0.00 Downward Parts of Weinan, Xi'an, Ankang and Hanzhong
Z≤ -1.28 Downward* Parts of Xi'an and Ankang
Annual Z≥0.00 Upward Northern Shaanxi, parts of Guanzhong and southern Shaanxi
Z≥1.28 Upward* Parts of Yulin, Yan'an and Tongchuan
Z≤0.00 Downward Parts of Guanzhong and southern Shaanxi
Z≤ -1.28 Downward* Parts of Baoji, Xi'an and Weinan
Table 6 Significance and trend of precipitation in Mann-Kendall (MK) test on seasonal and annual scales in Shaanxi Province
Season/annual scale Z value Trend Regions
Spring Z≥0.00 Wetting Parts of southern Shaanxi and Baoji
Z≥1.28 Wetting* Parts of Ankang
Z≤0.00 Drying All of Shaanxi Province except for parts of southern Shaanxi and Baoji
Z≤ -1.28 Drying* Part of Yulin, Yan'an, and middle and east of Guanzhong
Summer Z≥0.00 Wetting Parts of Tongchuan and south of Yan'an
Z≥1.28 Wetting*
Z≤0.00 Drying All of Shaanxi Province except for parts of Tongchuan and south of Yan'an
Z≤ -1.28 Drying* West of southern Shaanxi, and parts of Yan'an and Guanzhong
Autumn Z≥0.00 Wetting Northern Shaanxi, west and north of Guanzhong, and east of Hanzhong
Z≥1.28 Wetting* Yulin and north of Yan'an
Z≤0.00 Drying Middle and eastern parts of Guanzhong and southern Shaanxi
Z≤ -1.28 Drying* Parts of Xi'an and Ankang
Winter Z≥0.00 Wetting Northern Shaanxi, and parts of Gaunzhong and southern Shaanxi
Z≥1.28 Wetting* Northern Shaanxi, and parts of Gaunzhong and southern Shaanxi
Z≤0.00 Drying Parts of Xi'an, Weinan, Hanzhong and Ankang
Z≤ -1.28 Drying* Parts of Xi’an, Weinan, Hanzhong and Ankang
Annual Z≥0.00 Wetting Yulin, and parts of Yan'an, Tongchuan and Xianyang
Z≥1.28 Wetting*
Z≤0.00 Drying All of Shaanxi Province except for Yulin, and parts of Yan'an, Tongchuan and Xianyang
Z≤ -1.28 Drying* Parts of Guanzhong, Hanzhong and Ankang
Table 7 Significance and trend of SPEI-ITPCAS in MK test on seasonal and annual scales in Shaanxi Province
Fig. 7 Temporal ranges for mutations of SPEI-ITPCAS in spring (a), summer (b), autumn (c) and winter (d), and on an annual scale (e) in Shaanxi Province. The two blue lines are the northern and southern boundaries of Guanzhong.
[1]   Ahmad I, Tang D S, Wang T F, et al. 2015. Precipitation trends over time using Mann-Kendall and spearman's rho tests in Swat River Basin, Pakistan. Advances in Meteorology, 2015: 431860, doi: https://doi.org/10.1155/2015/431860.
[2]   Allen K J, Ogden J, Buckley B M, et al. 2011. The potential to reconstruct broadscale climate indices associated with southeast Australian droughts from Athrotaxis species, Tasmania. Climate Dynamics, 37(9-10): 1799-1821.
doi: 10.1007/s00382-011-1011-7
[3]   Allen R, Smith M, Perrier A, et al. 1994. An update for the definition of reference evapotranspiration. ICID bulletin, 43(2): 1-34.
[4]   Beguería S, Vicente-Serrano S M, Reig F, et al. 2014. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology, 34(10): 3001-3023.
doi: 10.1002/joc.3887
[5]   Changnon S A, Easterling W E. 1989. Measuring drought impacts: the illinois case. Jawra Journal of the American Water Resources Association, 25(1): 27-42.
doi: 10.1111/jawr.1989.25.issue-1
[6]   Chen Y Y, Yang K, He J, et al. 2011. Improving land surface temperature modeling for dry land of China. Journal of Geophysical Research-Atmospheres, 116(D20): 12-20.
[7]   Dai A G. 2011. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900-2008. Journal of Geophysical Research-Atmospheres, 116(D12): 1248-1256.
[8]   Duan Y, Wang W, Cai X J. 2013. Applied analyses on Palmer, SPEI and CI indices of Drought Process in Yangtze-Huaihe River Basins during Winter of 2010/Spring of 2011. Plateau Meterology, 32(4): 1126-1139. (in Chinese)
[9]   Gobena A K, Gan T Y. 2013. Assessment of trends and possible climate change impacts on summer moisture availability in western Canada based on metrics of the Palmer Drought Severity Index. Journal of Climate, 26(13): 4583-4595.
doi: 10.1175/JCLI-D-12-00421.1
[10]   Goovaerts P. 2000. Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228(1-2): 113-129.
doi: 10.1016/S0022-1694(00)00144-X
[11]   Guo D L, Wang H J. 2013. Simulation of permafrost and seasonally frozen ground conditions on the Tibetan Plateau, 1981-2010 . Journal of Geophysical Research-Atmospheres, 118(11): 5216-5230.
doi: 10.1002/jgrd.50457
[12]   Hannaford J, Lloyd-Hughes B, Keef C, et al. 2011. Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit. Hydrological Processes, 25(7): 1146-1162.
doi: 10.1002/hyp.v25.7
[13]   He B, Lü A F, Wu J J, et al. 2011. Drought hazard assessment and spatial characteristics analysis in China. Journal of Geographical Sciences, 21(2): 235-249.
doi: 10.1007/s11442-011-0841-x
[14]   He S W, Nan Z T, Zhang L, et al. 2015. Spatial-temporal distribution of water and energy fluxes in the upper reaches of the Heihe River simulated with VIC model. Journal of Glaciology and Geocryology, 37(1): 211-225. (in Chinese)
doi: 10.7522/j.issn.1000-0240.2015.0024
[15]   Jia J, Wang Q, Li L H. 2016. Long-term oscillation of drought conditions in the western China: an analysis of PDSI on a decadal scale. Journal of Arid Land, 8(6): 819-831.
doi: 10.1007/s40333-016-0089-5
[16]   Jiang R G, Xie J C, He H L, et al. 2015. Use of four drought indices for evaluating drought characteristics under climate change in Shaanxi, China: 1951-2012. Natural Hazards, 75(3): 2885-2903.
doi: 10.1007/s11069-014-1468-x
[17]   Kan B Y, Su F G, Tong K, et al. 2013. Analysis of the applicability of four precipitation datasets in the upper reaches of the Yarkant River, the Karakorum. Journal of Glaciology and Geocryology, 35(3): 710-722. (in Chinese)
doi: 10.7522/j.issn.1000-0240.2013.0081
[18]   Kendall M G. 1975. Rank Correlation Methods. London: Charles Griffin, 200-202.
[19]   Kim T W, Valdés J B, Aparicio J. 2002. Frequency and spatial characteristics of droughts in the Conchos River Basin, Mexico. Water International, 27(3): 420-430
doi: 10.1080/02508060208687021
[20]   Kogan F, Adamenko T, Guo W. 2013. Global and regional drought dynamics in the climate warming era. Remote Sensing Letters, 4(4): 364-372.
doi: 10.1080/2150704X.2012.736033
[21]   Liu C R, Chen H, Ning C, et al. 2018. Analysis of drought characteristics in Shaanxi Province during 1961-2016 based on SPI. Acta Agriculturae Jiangxi, 30(4): 117-122. (in Chinese)
[22]   Liu W L, Zhang M J, Wang S J, et al. 2013. Changes in precipitation extremes over Shaanxi Province, northwestern China, during 1960-2011. Quaternary International, 313-314: 118-129.
[23]   Liu Y, Yang X L, Ren L L, et al. 2015. A new physically based self-calibrating palmer drought severity index and its performance evaluation. Water Resources Management, 29(13): 4833-4847.
doi: 10.1007/s11269-015-1093-9
[24]   Liu Y F, Yuan Z H, Feng J M, et al. 2016. Dry-wet condition of Shaanxi Province in recent 56 years based on surface humidity index. Arid Land Geography, 39(6): 1186-1196. (in Chinese)
[25]   Loukas A, Vasiliades L, Tzabiras J. 2008. Climate change effects on drought severity. Advances in Geosciences, 17: 23-29.
doi: 10.5194/adgeo-17-23-2008
[26]   Lu J, Jia L, Menenti M, et al. 2018. Performance of the standardized precipitation index based on the TMPA and CMORPH precipitation products for drought monitoring in China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(5): 1387-1396.
doi: 10.1109/JSTARS.2018.2810163
[27]   Ma M W, Ren L Y, Singh V P, et al. 2015. Evaluation and application of the SPDI-JDI for droughts in Texas, USA. Journal of Hydrology, 521: 34-45.
doi: 10.1016/j.jhydrol.2014.11.074
[28]   Mann H B. 1945. Nonparametric tests against trend. Econometrico, 13(3): 245-259.
doi: 10.2307/1907187
[29]   Meza F J. 2013. Recent trends and ENSO influence on droughts in Northern Chile: An application of the Standardized Precipitation Evapotranspiration Index. Weather & Climate Extremes, 1(1): 51-58.
[30]   Naumann G, Dutra E, Barbosa P, et al. 2014. Comparison of drought indicators derived from multiple data sets over Africa. Hydrology and Earth System Sciences, 18(18): 1625-1640.
doi: 10.5194/hess-18-1625-2014
[31]   Pandey R P, Ramasastri K S. 2010. Relationship between the common climatic parameters and average drought frequency. Hydrological Processes, 15(6): 1019-1032.
doi: 10.1002/(ISSN)1099-1085
[32]   Parsons D J, Rey D, Tanguy M, et al. 2019. Regional variations in the link between drought indices and reported agricultural impacts of drought. Agricultural Systems, 173: 119-129.
doi: 10.1016/j.agsy.2019.02.015
[33]   Paulo A A, Rosa R D, Pereira L S. 2012. Climate trends and behaviour of drought indices based on precipitation and evapotranspiration in Portugal. Natural Hazards and Earth System Sciences, 12(5): 1481-1491.
[34]   Qiao L, Cheng K, Wu L R, et al. 2012. Spatial and temporal distribution of meteorological drought disasters in Shaanxi Province over past 30 year. Bulletin of Soil and Water Conservation, 46(1): 253-256. (in Chinese)
[35]   Rhee J, Im J. 2017. Meteorological drought forecasting for ungauged areas based on machine learning: Using long-range climate forecast and remote sensing data. Agricultural and Forest Meteorology, 237-238: 105-122.
doi: 10.1016/j.agrformet.2017.02.011
[36]   Salehnia N, Zare H, Kolsoumi S, et al. 2017a. Predictive value of Keetch-Byram Drought Index for cereal yields in a semi-arid environment. Theoretical & Applied Climatology, 134(3-4): 1005-1014.
[37]   Salehnia N, Alizadeh A, Sanaeinejad H, et al. 2017b. Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data. Journal of Arid Land, 9(6): 797-809.
doi: 10.1007/s40333-017-0070-y
[38]   Spinoni J, Barbosa P, de Jager A, et al. 2019. A new global database of meteorological drought events from 1951 to 2016. Journal of Hydrology: Regional Studies, 22(4): 100593-100616.
doi: 10.1016/j.ejrh.2019.100593
[39]   Szcześniak M, Piniewski M. 2015. Improvement of hydrological simulations by applying daily precipitation interpolation schemes in meso-scale catchments. Water, 7(2): 747-779.
doi: 10.3390/w7020747
[40]   Thornthwaite C W. 1937. Microclimatic studies in Oklahoma and Ohio. Science, 86(2222): 100-101.
doi: 10.1126/science.86.2222.100 pmid: 17733943
[41]   Tian M, Li W G. 2015. Analysis of spatial and temporal characteristics of drought and flood based on TRMM remote sensing data. Transactions of the Chinese Society for Agricultural Machinery, 46(5): 252-257. (in Chinese)
[42]   Tsakiris G, Pangalou D, Vangelis H. 2007. Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resources Management, 21(5): 821-833.
doi: 10.1007/s11269-006-9105-4
[43]   Vasiliades L, Loukas A. 2009. Hydrological response to meteorological drought using the Palmer drought indices in Thessaly, Greece. Desalination, 237(1-3): 3-21.
doi: 10.1016/j.desal.2007.12.019
[44]   Vicente-Serrano S M, Beguería S, López-Moreno J I. 2010a. A multiscalar drought index sensitive to global warming: the Standardized Precipitation Evapotranspiration Index. Journal of Climate, 23(7): 1696-1718.
doi: 10.1175/2009JCLI2909.1
[45]   Vicente-Serrano S M, Begueria S, López-Moreno J I, et al. 2010b. A new global 0.5 degrees gridded dataset (1901-2006) of a multiscalar drought index: comparison with current drought index datasets based on the Palmer Drought Severity Index. Journal of Hydrometeorology, 11(4): 1033-1043.
doi: 10.1175/2010JHM1224.1
[46]   Vicente-Serrano S M, Beguería S, López-Moreno J I. 2011. Comment on "characteristics and trends in various forms of the Palmer Drought Severity Index (PDSI) during 1900-2008" by Aiguo Dai. Journal of Geophysical Research-Atmospheres, 116(D19): 4-13.
[47]   Wan X J, Ren Z Y, Zhang C. 2013. Research on spatial-temporal distribution of temperature and precipitation changes in Shaanxi. Journal of Arid Land Resources and Environment, 27(6): 140-147. (in Chinese)
[48]   Wang F, Wang Z M, Yang H B, et al. 2018. Study of the temporal and spatial patterns of drought in the Yellow River basin based on SPEI. Science China Earth Sciences, 61(8): 1098-1111.
doi: 10.1007/s11430-017-9198-2
[49]   Wang X Y, Zhuo L, Li C, et al. 2019. Temporal and spatial evolution trends of drought in northern Shaanxi of China: 1960-2100. Theoretical and Applied Climatology, 139(3-4): 965-979.
doi: 10.1007/s00704-019-03024-2
[50]   Wang Y D, Chen H, Liu C R, et al. 2018. Applicability of ITPCAS and CMORPH precipitation datasets over Shaanxi Province. Arid Zone Research, 35(3): 579-588. (in Chinese)
[51]   Wang Z, Guan K Y, Sheffield J, et al. 2016. Depiction of drought over sub-Saharan Africa using reanalyses precipitation data sets. Journal of Geophysical Research Atmospheres, 121(18): 10555-10574.
doi: 10.1002/jgrd.v121.18
[52]   Wells N, Goddard S, Hayes M J. 2004. A self-calibrating Palmer Drought Severity Index. Journal of Climate, 17(12): 2335-2351.
doi: 10.1175/1520-0442(2004)017<2335:ASPDSI>2.0.CO;2
[53]   Xue B L, Wang L, Yang K, et al. 2013. Modeling the land surface water and energy cycles of a mesoscale watershed in the central Tibetan Plateau during summer with a distributed hydrological model. Journal of Geophysical Research-Atmospheres, 118(16): 8857-8868.
doi: 10.1002/jgrd.50696
[54]   Yang M J, Yan D H, Yu Y D, et al. 2016. SPEI-based spatiotemporal analysis of drought in Haihe River Basin from 1961 to 2010. Advances in Meteorology, 2016: 7658015, doi: 10.1155/2016/7658015.
[55]   Yang Q, Li M X, Zheng Z Y, et al. 2017. Regional applicability of seven meteorological drought indices in China. Science China Earth Sciences. 60(4): 745-760.
doi: 10.1007/s11430-016-5133-5
[56]   Yu F K, Huang X H, Liang Q B, et al. 2015. Ecological water demand of regional vegetation: the example of the 2010 severe drought in southwest China. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology, 149(1): 100-110.
doi: 10.1080/11263504.2013.817488
[57]   Yu M X, Li Q F, Hayes M J, et al. 2014. Are droughts becoming more frequent or severe in China based on the Standardized Precipitation Evapotranspiration Index: 1951-2010? International Journal of Climatology, 34(3): 545-558.
doi: 10.1002/joc.3701
[58]   Yuan F, Ma M W, Ren L L, et al. 2015. Possible future climate change impacts on the hydrological drought events in the Weihe River Basin, China. Advances in Meteorology, 2016: 2905198, doi: https://doi.org/10.1155/2016/2905198.
[59]   Zhai Y A. 2005. China Meteorological Disaster Canon-Shaanxi Volume. Beijing: Meteorological Press, 30-41. (in Chinese)
[60]   Zhang R, Chen Z Y, Xu L J, et al. 2019. Meteorological drought forecasting based on a statistical model with machine learning techniques in Shaanxi Province, China. Science of the Total Environment, 665: 338-346.
doi: 10.1016/j.scitotenv.2019.01.431 pmid: 30772564
[61]   Zhang X S, Srinivasan R. 2009. GIS-Based spatial precipitation estimation: A comparison of geostatistical approaches. Journal of the American Water Resources Association, 45(4): 894-906.
doi: 10.1111/jawr.2009.45.issue-4
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