Identification of Seasonal Sub-Regions of the Drought in the North China Plain
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data Source
2.2. Standardized Precipitation Evapotranspiration Index
2.3. Empirical Orthogonal Function Analysis
3. Results
3.1. Seasonal rEOFs
3.1.1. Spring (March/April/May)
3.1.2. Summer (June/July/August)
3.1.3. Fall (September/October/November)
3.1.4. Winter (December/January/February)
3.2. Seasonal Trends
3.3. Correlation of Variation in Subregions
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Dai, A. Drought under global warming: A review. WIREs Clim. Chang. 2011, 2, 45–65. [Google Scholar] [CrossRef] [Green Version]
- Sönmez, F.K.; Kömüscü, A.L.I.Ü.; Erkan, A.; Turgu, E. An Analysis of Spatial and Temporal Dimension of Drought Vulnerability in Turkey Using the Standardized Precipitation Index. Nat. Hazards 2005, 35, 243–264. [Google Scholar] [CrossRef]
- AghaKouchak, A.; Farahmand, A.; Melton, F.S.; Teixeira, J.; Anderson, M.C.; Wardlow, B.D.; Hain, C.R. Remote sensing of drought: Progress, challenges and opportunities. Rev. Geophys. 2015, 53, 452–480. [Google Scholar] [CrossRef] [Green Version]
- Hao, Z.; Singh, V.P. Drought characterization from a multivariate perspective: A review. J. Hydrol. 2015, 527, 668–678. [Google Scholar] [CrossRef]
- Liu, X.; Zhu, X.; Pan, Y.; Zhao, A.; Li, Y. Spatiotemporal changes of cold surges in Inner Mongolia between 1960 and 2012. J. Geogr. Sci. 2015, 25, 259–273. [Google Scholar] [CrossRef]
- Salinger, M.J.; Stigter, C.J.; Das, H.P. Agrometeorological adaptation strategies to increasing climate variability and climate change. Agric. For. Meteorol. 2000, 103, 167–184. [Google Scholar] [CrossRef]
- Wu, J.; Zhou, L.; Mo, X.; Zhou, H.; Zhang, J.; Jia, R. Drought monitoring and analysis in China based on the Integrated Surface Drought Index (ISDI). Int. J. Appl. Earth Obs. 2015, 41, 23–33. [Google Scholar] [CrossRef]
- Bonaccorso, B.; Bordi, I.; Cancellire, A.; Rossi, G.; Sutera, A. Spatial variability of drought-an analysis of the SPI in sicily. Water Resour. Manag. 2003, 17, 273–296. [Google Scholar] [CrossRef]
- Omondi, P.; Ogallo, L.A.; Anyah, R.; Muthama, J.M.; Ininda, J. Linkages between global sea surface temperatures and decadal rainfall variability over Eastern Africa region. Int. J. Climatol. 2013, 33, 2082–2104. [Google Scholar] [CrossRef]
- Piao, S.; Ciais, P.; Huang, Y.; Shen, Z.; Peng, S.; Li, J.; Zhou, L.; Liu, H.; Ma, Y.; Ding, Y.; et al. The impacts of climate change on water resources and agriculture in China. Nature 2010, 467, 43–51. [Google Scholar] [CrossRef]
- Wang, Q.; Wu, J.; Lei, T.; He, B.; Wu, Z.; Liu, M.; Mo, X.; Geng, G.; Li, X.; Zhou, H.; et al. Temporal-spatial characteristics of severe drought events and their impact on agriculture on a global scale. Quat. Int. 2014, 349, 10–21. [Google Scholar] [CrossRef]
- Shi, W.; Tao, F.; Liu, J. Regional temperature change over the Huang-Huai-Hai Plain of China: The roles of irrigation versus urbanization. Int. J. Climatol. 2014, 34, 1181–1195. [Google Scholar] [CrossRef]
- Guo, R.; Lin, Z.; Mo, X.; Yang, C. Responses of crop yield and water use efficiency to climate change in the North China Plain. Agric. Water Manag. 2010, 97, 1185–1194. [Google Scholar] [CrossRef]
- Fu, C.; Wen, G. Research on the Characteristics of Interdecadal Variability of Summer Climate in China and its Possible Cause. Clim. Environ. Res. 2002, 7, 22–29. [Google Scholar]
- Liu, X.; Pan, Y.; Zhu, X.; Yang, T.; Bai, J.; Sun, Z. Drought evolution and its impact on the crop yield in the North China Plain. J. Hydrol. 2018, 564, 984–996. [Google Scholar] [CrossRef]
- Ma, Z. 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. [Google Scholar] [CrossRef]
- Shi, Y.; Yao, X.; Yang, X.; Li, Z. Characteristic analysis of unusual summer precipitation in North China. Sci. Meteorol. Sin. 2008, 28, 377–383. [Google Scholar]
- Li, X.; Ju, H.; Liu, Q.; Li, Y.; Qin, X. Analysis of drought characters based on the SPEI-PM index in Huang-Huai-Hai Plain. Acta Ecol. Sin. 2017, 37, 2054–2066. [Google Scholar] [CrossRef] [Green Version]
- Sun, H.; Zhang, X.; Liu, X.; Liu, X.; Shao, L.; Chen, S.; Wang, J.; Dong, X. Impact of different cropping systems and irrigation schedules on evapotranspiration, grain yield and groundwater level in the North China Plain. Agric. Water Manag. 2019, 211, 202–209. [Google Scholar] [CrossRef]
- Zhao, Q.; Zhang, B.; Yao, Y.; Wu, W.; Meng, G.; Chen, Q. Geodetic and hydrological measurements reveal the recent acceleration of groundwater depletion in North China Plain. J. Hydrol. 2019, 575, 1065–1072. [Google Scholar] [CrossRef]
- Zhong, R.; Chen, X.; Lai, C.; Wang, Z.; Lian, Y.; Yu, H.; Wu, X. Drought monitoring utility of satellite-based precipitation products across mainland China. J. Hydrol. 2018, 568, 343–359. [Google Scholar] [CrossRef]
- Liu, Q.; Zhang, G.; Shahzad, A.; Wang, X.; Wang, G.; Pan, Z.; Zhang, J. SPI-based drought simulation and prediction using Arma-Garch model. Appl. Math. Comput. 2019, 355, 96–107. [Google Scholar] [CrossRef]
- Wu, J.; Zhou, L.; Liu, M.; Zhang, J.; Leng, S.; Diao, C. Establishing and assessing the Integrated Surface Drought Index (ISDI) for agricultural drought monitoring in mid-eastern China. Int. J. Appl. Earth Obs. 2013, 23, 397–410. [Google Scholar] [CrossRef]
- Yang, X.; Xie, Q.; Zhu, Y.; Sun, X.; Guo, Y. Decadal-to-interdecadal variability of precipitation in North China and associated atmospheric and oceanic anomaly patterns. Chin. J. Geophys. 2005, 48, 789–797. [Google Scholar]
- Chen, Q.; Liu, Y.; Ge, Q.; Pan, T. Impacts of historic climate variability and land use change on winter wheat climatic productivity in the North China Plain during 1980–2010. Land Use Policy 2018, 76, 1–9. [Google Scholar] [CrossRef]
- Li, P.; Ren, L. Evaluating the effects of limited irrigation on crop water productivity and reducing deep groundwater exploitation in the North China Plain using an agro-hydrological model: II. Scenario simulation and analysis. J. Hydrol. 2019, 574, 715–732. [Google Scholar] [CrossRef]
- Xiao, D.; Qi, Y.; Li, Z.; Wang, R.; Moiwo, J.P.; Liu, F. Impact of thermal time shift on wheat phenology and yield under warming climate in the Huang-Huai-Hai Plain, China. Front. Earth Sci. 2017, 11, 148–155. [Google Scholar] [CrossRef]
- Hannachi, A.; Jolliffe, I.T.; Stephenson, D.B. Empirical orthogonal functions and related techniques in atmospheric science (A review). Int. J. Climatol. 2007, 27, 1119–1152. [Google Scholar] [CrossRef]
- Richman, M.B. Rotation of principal components. J. Climatol. 1986, 6, 293–335. [Google Scholar] [CrossRef]
- Cai, W.; Zhang, Y.; Chen, Q.; Yao, Y. Spatial Patterns and Temporal Variability of Drought in Beijing-Tianjin-Hebei Metropolitan Areas in China. Adv. Meteorol. 2015, 2015, 289471. [Google Scholar] [CrossRef]
- Zambreski, Z.T.; Lin, X.; Aiken, R.M.; Kluitenberg, G.J.; Pielke, R.A.S. Identification of hydroclimate subregions for seasonal drought monitoring in the U.S. Great Plains. J. Hydrol. 2018, 567, 370–381. [Google Scholar] [CrossRef]
- Cheval, S.; Busuioc, A.; Dumitrescu, A.; Birsan, M.V. Spatiotemporal variability of meteorological drought in Romania using the standardized precipitation index (SPI). Clim. Res. 2014, 60, 235–248. [Google Scholar] [CrossRef]
- Martins, D.S.; Raziei, T.; Paulo, A.A.; Pereira, L.S. Spatial and temporal variability of precipitation and drought in Portugal. Nat. Hazards Earth Syst. Sci. 2012, 12, 1493–1501. [Google Scholar] [CrossRef] [Green Version]
- Vicente-Serrano, S.M.; Begueri’a, S.; Pez-Moreno, J.I.L. A multiscalar drought index sensitive to global warming-the standardized precipitation evapotranspiration index. J. Clim. 2010, 23, 1696–1718. [Google Scholar] [CrossRef] [Green Version]
- Jia, Y.; Zhang, B. Spatial-temporal Variability Characteristics of Extreme Drought Events Based on Daily SPEI in the Southwest China in Recent 55 Years. Sci. Geogr. Sin. 2018, 38, 474–483. [Google Scholar] [CrossRef]
- Lu, E.; Cai, W.; Jiang, Z.; Zhang, Q.; Zhang, C.; Higgins, R.W.; Halpert, M.S. The day-to-day monitoring of the 2011 severe drought in China. Clim. Dyn. 2013, 43, 1–9. [Google Scholar] [CrossRef]
- Wang, Q.; Shi, P.; Lei, T.; Geng, G.; Liu, J.; Mo, X.; Li, X.; Zhou, H.; Wu, J. The alleviating trend of drought in the Huang-Huai-Hai Plain of China based on the daily SPEI. Int. J. Climatol. 2015, 35, 3760–3769. [Google Scholar] [CrossRef]
- Ma, B.; Zhang, B.; Jia, L.; Huang, H. Conditional distribution selection for SPEI-daily and its revealed meteorological drought characteristics in China from 1961 to 2017. Atmos. Res. 2020, 246, 105108. [Google Scholar] [CrossRef]
- Hamed, K.H.; Rao, A.R. The modified Mann-Kendall trend test for autocorrelated data. J. Hydrol. 1998, 204, 182–196. [Google Scholar] [CrossRef]
- Sun, H.; Shen, Y.; Yu, Q.; Flerchinger, G.N.; Zhang, Y.; Liu, C.; Zhang, X. Effect of precipitation change on water balance and WUE of the winter wheat–summer maize rotation in the North China Plain. Agric. Water Manag. 2010, 97, 1139–1145. [Google Scholar] [CrossRef]
- Wang, X.L.; Wen, Q.H.; Wu, Y. Penalized maximal t test for detecting undocumented mean change in climate data series. J. Appl. Meteorol. Climatol. 2007, 46, 916–931. [Google Scholar] [CrossRef]
- Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; FAO Irrigation and Drainage Paper No. 56; FAO: Rome, Italy, 1998; pp. 1–15. [Google Scholar]
- Ahmad, M.I.; Sinclair, C.D.; Werritty, A. Log-logistic flood frequency analysis. J. Hydrol. 1988, 98, 205–224. [Google Scholar] [CrossRef]
- Singh, V.P.; Guo, H.; Yu, F.X. Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome. Stoch. Hydrol. Hydraul. 1993, 7, 163–177. [Google Scholar] [CrossRef]
- Hosking, J.R.M. The Theory of Probability Weighted Moments; RC12210; IBM Research Division: Yorktown Heights, NY, USA, 1986. [Google Scholar]
- Beguería, S.; Vicente-Serrano, S.M.; Reig, F.; Latorre, B. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int. J. Climatol. 2014, 34, 3001–3023. [Google Scholar] [CrossRef] [Green Version]
- Wen, K.; Ding, Y. China Disaster Canon-Comprehensive; China Meteorological Press: Beijing, China, 2008; pp. 157–229. [Google Scholar]
- North, G.R.; Bell, T.L.; Cahalan, R.F.; Moeng, F.J. Sampling errors in the estimation of empirical orthogonal functions. Mon. Weather Rev. 1982, 110, 699–706. [Google Scholar] [CrossRef]
- Daly, C. Guidelines for assessing the suitability of spatial climate data sets. Int. J. Climatol. 2006, 26, 707–721. [Google Scholar] [CrossRef]
- Yang, Q.; Li, M.; Zheng, Z.; Ma, Z. Regional applicability of seven meteorological drought indices in China. Sci. China Earth Sci. 2017, 60, 745–760. [Google Scholar] [CrossRef]
- Wang, L.; Chen, W. Applicability Analysis of Standardized Precipitation Evapotranspiration Index in Drought Monitoring in China. Plateau Meteorol. 2014, 33, 423–431. [Google Scholar]
- Chen, L.; Duan, J.; Ma, Z. Objective analysis on large-scale circulation type and its links to precipitation over China. Adv. Earth Sci. 2018, 33, 396–403. [Google Scholar] [CrossRef]
- Huang, H.; Cao, M.; Song, J.; Han, Y.; Chen, S. Temporal and spatial changes of potential evapotranspiration and its influencing factors in China from 1957 to 2012. J. Nat. Resour. 2015, 30, 315–326. [Google Scholar] [CrossRef]
- Jiang, D.; Wang, H. Natural interdecadal weakening of East Asian summer monsoon in the late 20th century. Chin. Sci. Bull. 2005, 50, 2256–2262. [Google Scholar] [CrossRef]
- Rashid, M.A.; Jabloun, M.; Andersen, M.N.; Zhang, X.; Olesen, J.E. Climate change is expected to increase yield and water use efficiency of wheat in the North China Plain. Agric. Water Manag. 2019, 222, 193–203. [Google Scholar] [CrossRef]
- Lu, H.; Mo, X.; Hu, S. Spatiotemporal variation characteristics of meteorological droughts in North China Plain during 1960–2009. J. Nat. Disaster 2012, 21, 72–82. [Google Scholar] [CrossRef]
- Wu, S.; Pan, T.; Liu, Y.; Deng, H.; Jiao, K.; Lu, Q.; Feng, A.; Yue, X.; Yin, Y.; Zhao, D.; et al. Comprehensive climate change risk regionalization of China. Acta Geogr. Sin. 2017, 72, 3–17. [Google Scholar] [CrossRef]
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Cui, Y.; Zhang, B.; Huang, H.; Wang, X.; Zeng, J.; Jiao, W.; Yao, R. Identification of Seasonal Sub-Regions of the Drought in the North China Plain. Water 2020, 12, 3447. https://doi.org/10.3390/w12123447
Cui Y, Zhang B, Huang H, Wang X, Zeng J, Jiao W, Yao R. Identification of Seasonal Sub-Regions of the Drought in the North China Plain. Water. 2020; 12(12):3447. https://doi.org/10.3390/w12123447
Chicago/Turabian StyleCui, Yanqiang, Bo Zhang, Hao Huang, Xiaodan Wang, Jianjun Zeng, Wenhui Jiao, and Rongpeng Yao. 2020. "Identification of Seasonal Sub-Regions of the Drought in the North China Plain" Water 12, no. 12: 3447. https://doi.org/10.3390/w12123447