The best-fitting distribution of water balance and the spatiotemporal characteristics of drought in Guizhou Province, China

Abstract

Drought is one of the most severe natural hazards with a significant impact on water resources. Droughts affect the sustainability of water resources and may result in environmental degradation of a region. The appropriate drought index is playing an important role on drought assessment. This paper addresses the best-fitting distribution of monthly water balance (WB), and the spatiotemporal characteristics of drought in Guizhou Province, China, during 1960–2017. The best-fitting distribution of monthly WB calculated using three potential evapotranspiration (PET) estimation methods was determined based on the goodness-of-fit test. The Standardized Precipitation Evapotranspiration Index (SPEI) at various timescales was computed based on the optimal distribution. The modified Mann-Kendall method, run theory, and inverse distance weight (IDW) interpolation method were used to investigate spatiotemporal evolution of drought. Over result revealed that the common log-logistic distribution was not the most suitable distribution for WB in Guizhou Province and the gen. extreme value distribution is optimum fit for the WB series calculated based on different methods for 76.47% of the stations. Moreover, different calculation methods seem to have little influence on the fitting results. The drought shows an upward trend in spring and autumn and a downward trend in summer and winter during 1960–2017; the increasing magnitude of summer and autumn drought was greater in the northeastern and northwestern Guizhou Province. The annual droughts are significantly increasing (p = 0.05) at Anshun and Panxian. The drought frequency showed a decreasing trend from light drought to severe drought in Guizhou Province, and the drought intensity was relatively more severe during 2010–2017 than other periods. These findings are helpful for water resource management in Guizhou Province and indicate that we should pay more attention to the drought mitigation of the higher-elevation regions.

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References

  1. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspi-ration. Guidelines for computing crop water requirements. FAO Irrigation and Drainage, Rome

    Google Scholar 

  2. Angelidis P, Maris F, Kotsovinos N, Hrissanthou V (2012) Computation of drought index SPI with alternative distribution functions. Water Resour Manag 26(9):2453–2473

    Article  Google Scholar 

  3. Ayantobo OO, Li Y, Song S, Yao N (2017) Spatial comparability of drought characteristics and related return periods in mainland China over 1961-2013. J Hydrol 550:549–567

    Article  Google Scholar 

  4. Belayneh A, Adamowski J, Khalil B, Ozga-Zielinski B (2014) Long-term SPI drought forecasting in the Awash River basin in Ethiopia using wavelet neural network and wavelet support vector regression models. J Hydrol 508:418–429

    Article  Google Scholar 

  5. Cao X, Wang Y, Wu P, Zhao X, Wang J (2015) An evaluation of the water utilization and grain production of irrigated and rain-fed croplands in China. Sci Total Environ 529:10–20

    Article  Google Scholar 

  6. Chen HP, Sun JQ (2015) Changes in drought characteristics over China using the standardized precipitation evapotranspiration index. J Clim 28(13):5430–5447

    Article  Google Scholar 

  7. Cheng QP, Gao L, Chen Y, Liu MB, Deng HJ, Chen XW (2018) Temporal-spatial characteristics of drought in Guizhou Province, China, based on multiple drought indices and historical disaster records. Adv Meteorol 2018:1–22

    Google Scholar 

  8. Dai AG (2011) Drought under global warming: a review. Climate Change 2(1):45–65

    Google Scholar 

  9. Donohue RJ, McVicar TR, Roderick ML (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. J Hydrol 386(1–4):186–197

    Article  Google Scholar 

  10. Droogers P, Allen RG (2002) Estimating reference evapotranspiration under inaccurate data conditions. Irrig Drain Syst 16(1):33–45

    Article  Google Scholar 

  11. Feng L, Li T, Yu WD (2014) Cause of severe droughts in Southwest China during 1951–2010. Clim Dyn 43(7–8):2033–2042

    Article  Google Scholar 

  12. Feng K, Su XL, Zhang GX, Javed T, Zhang ZZ (2020) Development of a new integrated hydrological drought index (SRGI) and its application in the Heihe River basin, China[J]. Theor Appl Climatol 141:43–59

    Article  Google Scholar 

  13. Gao CJ, Chen HS, Sun SL, Ongoma V, Hua WJ, Ma HD, Xu B, Li Y (2017) A potential predictor of multi-season droughts in Southwest China: soil moisture and its memory. Nat Hazards 91(2):553–566

    Article  Google Scholar 

  14. George HH, Zohrab AS (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1(2):96–99

    Article  Google Scholar 

  15. Guo H, Bao AM, Liu T, Jiapaer GL, Ndayisaba F, Jiang LL, Kurban A, Maeye PD (2018) Spatial and temporal characteristics of droughts in Central Asia during 1966–2015. Sci Total Environ 624:1523–1538

    Article  Google Scholar 

  16. Guo Y, Huang SZ, Huang Q, Wang H, Fang W, Yang YY, Wang L (2019) Assessing socioeconomic drought based on an improved multivariate standardized reliability and resilience index. J Hydrol 568:904–918

    Article  Google Scholar 

  17. Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204(1–4):182–196

    Article  Google Scholar 

  18. Hargreaves GH, Allen RG (2004) History and evaluation of Hargreaves evapotranspiration equation. J Irrig Drain Eng 130:448–449

    Article  Google Scholar 

  19. Hernandez EA, Uddameri V (2014) Standardized precipitation evaporation index (spei)-based drought assessment in semi-arid South Texas. Environ Earth Sci 71(6):2491–2501

    Article  Google Scholar 

  20. Javed T, Yao N, Chen XG, Suon S, Li Y (2020) Drought evolution indicated by meteorological and remote-sensing drought indices under different land cover types in China. Environ Sci Pollut Res 27(4):4258–4274

    Article  Google Scholar 

  21. Lana X, Burgue OA (2000) Some statistical characteristics of monthly and annual pluviometric irregularity for the spanish mediterranean coast. Theor Appl Climatol 65(1–2):79–97

    Article  Google Scholar 

  22. Li Z, Zheng FL, Liu WZ (2012) Spatiotemporal characteristics of reference evapotranspiration during 1961–2009 and its projected changes during 2011–2099 on the loess plateau of China. Agric For Meteorol 154-155:147–155

    Article  Google Scholar 

  23. Li YJ, Ren FM, Li YP (2014) Characteristics of the regional meteorological drought events in Southwest China during 1960–2010. J Meteorol Res 28(3):381–392

    Article  Google Scholar 

  24. Li SE, Kang SZ, Zhang L, Zhang JH, Du TS, Tong L, Ding RS (2016) Evaluation of six potential evapotranspiration models for estimating crop potential and actual evapotranspiration in arid regions. J Hydrol 543:450–461

    Article  Google Scholar 

  25. Li Z, Xu X, Xu C, Liu M, Wang K (2018) Dam construction impacts on multiscale characterization of sediment discharge in two typical karst watersheds of Southwest China. J Hydrol 558:42–54

    Article  Google Scholar 

  26. Liu B, Chen C, Lian Y, Chen J, Chen X (2015) Long-term change of wet and dry climatic conditions in the southwest karst area of China. Glob Planet Chang 127:1–11

    Article  Google Scholar 

  27. Mazhuvanchery AS, Subhankar K, Terence C, Christian R (2016) Design rainfall framework using multivariate parametric-nonparametric approach. J Hydrol Eng 21(1):04015041–04015017

    Google Scholar 

  28. McKee T, Doesken N, Kleist J (1999) Drought monitoring of climate. Geogr Rev 38:55–94

    Google Scholar 

  29. Palmer WC (1965) Meteorological Drought Research. Washington DC: US Weather Bureau. No. 45

  30. Penman HL (1948) Natural evaporation from open water, bare soil and grass (Vol. 193). Proceedings of the Royal Society of London: The Royal Society

  31. Sanjib G, Manindra KR, Soma CB (2016) Determination of the best fit probability distribution for monthly rainfall data in Bangladesh. Am J Math Stat 6(4):170–174

    Google Scholar 

  32. Santiago B, Sergio MVS, Fergus R, Borja L (2014) Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int J Climatol 34(10):3001–3023

    Article  Google Scholar 

  33. Sharma MA, Singh JB (2010) Use of probability distribution in rainfall analysis. N Y Sci J 3(9):40–49

    Google Scholar 

  34. Shen XJ, Wu X, Xie XM, Ma ZZ, Yang MJ (2017) Spatiotemporal analysis of drought characteristics in Song-Liao River basin in China. Adv Meteorol 2017:1–13

    Google Scholar 

  35. Sienz F, Bothe O, Fraedrich K (2012) Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias. Hydrol Earth Syst Sci 16(7):2143–2157

    Article  Google Scholar 

  36. Stagge JH, Tallaksen LM, Gudmundsson L, Van Loon AF, Stahl K (2015) Candidate distributions for climatological drought indices (SPI and SPEI). Int J Climatol 35(13):4027–4040

    Article  Google Scholar 

  37. Sun SL, Chen HS, Ju WM, Wang GJ, Sun G, Huang J, Ma HD, Gao CJ, Hua WJ, Yan GX (2016) On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China. Clim Dyn 48(11–12):3779–3797

    Google Scholar 

  38. Tan CP, Yang JP, Li MJ (2015) Temporal-spatial variation of drought indicated by SPI and SPEI in Ningxia Hui autonomous region, China. Atmosphere 6:1399–1421

    Article  Google Scholar 

  39. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94

    Article  Google Scholar 

  40. Tong S, Lai Q, Zhang J, Bao Y, Lusi A, Ma Q, Li X, Zhang F (2018) Spatiotemporal drought variability on the Mongolian plateau from 1980-2014 based on the SPEI-PM, intensity analysis and Hurst exponent. Sci Total Environ 615:1557–1565

    Article  Google Scholar 

  41. Van DSG, Jones PD, Briffa KR (2011) The sensitivity of the pdsi to the thornthwaite and penman-monteith parameterizations for potential evapotranspiration. J Geophys Res 116(D3):D03106

    Google Scholar 

  42. Vanderplas JT, Connolly AJ, Ivezic Z, Gray A (2012) Introduction to astroML: machine learning for astrophysics. Paper presented at the Conference on Intelligent Data Understanding

  43. Vangelis H, Tigkas D, Tsakiris G (2013) The effect of PET method on reconnaissance drought index (RDI) calculation. J Arid Environ 88:130–140

    Article  Google Scholar 

  44. Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23(7):1696–1718

    Article  Google Scholar 

  45. Vicente-Serrano SM, López-Moreno JI, Beguería S, Lorenzo-Lacruz J, Azorin-Molina C, Morán-Tejeda E (2012) Accurate computation of a streamflow drought index. J Hydrol Eng 17(2):318–332

    Article  Google Scholar 

  46. Wang F, Wang Z, Yang H, Di D, Liang Q (2020) A new copula-based standardized precipitation evapotranspiration streamflow index for drought monitoring. J Hydrol 585:124793. https://doi.org/10.1016/j.jhydrol.2020.124793

    Article  Google Scholar 

  47. Wu L, Wang S, Bai X, Luo W, Tian Y (2017) Quantitative assessment of the impacts of climate change and human activities on runoff change in a typical karst watershed, sw China. Sci Total Environ 601-602:1449–1465

    Article  Google Scholar 

  48. Xu XF, Yu Y, Wang CZ (2008) China meteorological disaster yearbook. China Meteorological Press, Beijing (in Chinese)

    Google Scholar 

  49. Xu K, Yang D, Yang H, Li Z, Qin Y, Shen Y (2015) Spatio-temporal variation of drought in China during 1961–2012: a climatic perspective. J Hydrol 526:253–264

    Article  Google Scholar 

  50. Yang MJ, Yan DH, Yu YD, Yang ZY (2016) SPEI-based spatiotemporal analysis of drought in Haihe River basin from 1961 to 2010. Adv Meteorol 2016(1):1–10

    Google Scholar 

  51. Yang Y, Chen RS, Han CT, Liu ZW (2021) Evaluation of 18 models for calculating potential evapotranspiration in different climatic zones of China. Agric Water Manag 244:106545

    Article  Google Scholar 

  52. Yao N, Li Y, Lei T, Peng L (2018) Drought evolution, severity and trends in mainland China over 1961-2013. Sci Total Environ 616-617:73–89

    Article  Google Scholar 

  53. Ye XC, Singh VP (2001) Evaluation and generalization of temperature-based methods for calculating evaporation. Hydrol Process 15(2):305–319

    Article  Google Scholar 

  54. Yevjevich V, Ingenieur J (1967) An objective approach to definitions and investigations of continental hydrologic droughts. J Hydrol 7(3):353

    Google Scholar 

  55. Yu MX, Li QF, Hayes MJ, Svoboda MD, Heim RR (2014) Are droughts becoming more frequent or severe in China based on the standardized precipitation evapotranspiration index: 1951-2010? Int J Climatol 34(3):545–558

    Article  Google Scholar 

  56. Zarei AR, Mahmoudi MR (2017) Evaluation of changes in RDIst index effected by different potential evapotranspiration calculation methods. Water Resour Manag 31(15):4981–4999

    Article  Google Scholar 

  57. Zhang Q, Xu CY, Zhang ZX, Chen X, Han ZQ (2009) Precipitation extremes in a karst region: a case study in the Guizhou province, Southwest China. Theor Appl Climatol 101(1–2):53–65

    Article  Google Scholar 

  58. Zhang WJ, Jin FF, Zhao JX, Qi L, Ren HL (2013) The possible influence of a nonconventional El Niño on the severe autumn drought of 2009 in Southwest China. J Clim 26(21):8392–8405

    Article  Google Scholar 

  59. Zhang BQ, Wang ZK, Chen G (2016) A sensitivity study of applying a two-source potential evapotranspiration model in the standardized precipitation evapotranspiration index for drought monitoring. Land Degrad Dev 28(2):783–793

    Article  Google Scholar 

  60. Zhao PW, Guo P, Li LY, Shu J (2017) Comparision of SPEI and SPI index on account of the droughts of the Southwest Yunnan area. Resour Env Yangtze Basin 26(01):142–149 (in Chinese)

    Google Scholar 

  61. Zhou L, Wu J, Mo X, Zhou H, Zhang F (2017) Quantitative and detailed spatiotemporal patterns of drought in China during 2001–2013. Sci Total Environ 589:136–145

    Article  Google Scholar 

  62. Zuo D, Cai S, Xu Z, Li F, Sun W, Yang X (2016) Spatiotemporal patterns of drought at various time scales in Shandong province of eastern China. Theor Appl Climatol 131:1–14

    Google Scholar 

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Acknowledgments

We thank the editor and anonymous reviewers for their critical and insightful comments and suggestions that improved this paper.

Funding

This research is financially supported by the Science and Technology Project of Guizhou Province Water Resources Department (grant number KT201705).

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Yingying Wang: methodology, software, formal analysis, writing—original draft. Zhiliang Wang: writing—review and editing. Zezhong Zhang: review and editing, project administration. Dongfang Shen: writing and editing. Ling Zhang: writing and editing.

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Correspondence to Zhiliang Wang.

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Wang, Y., Wang, Z., Zhang, Z. et al. The best-fitting distribution of water balance and the spatiotemporal characteristics of drought in Guizhou Province, China. Theor Appl Climatol 143, 1097–1112 (2021). https://doi.org/10.1007/s00704-020-03469-w

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