The hydrological variations of Ganjiang River Basin have significant influence on the ecological environment of Poyang Lake, which is one of the largest freshwater lake and wetland in the world. This study analyzed the spatial and temporal characteristics of rainfall across Ganjiang River Basin. The analyses include annual total rainfall amount (ATRA), annual total rainy day (ATRD) and annual mean daily rainfall intensity (AMDRI). To detect changes in the hydrological trends, data from 19 rainfall stations from 1953 to 2013 were used in the analyses. First, quality control and homogeneity detection was carried out to examine the annual rainfall series. Second, the spatial correlation analysis was used to identify the spatial relationship among the measurements from different stations. Finally, the statistics of coefficient of variation (CV) and average were used to analyze the interannual variation trend. The modified Mann–Kendall (MMK) trend test method was used to detect the temporal characteristics of rainfall. The results include: (1) Some outliers were detected and corrected. (2) The correlation of ATRA and ATRD series of all the stations had lower spatial variability while the AMDRI series of all the stations had higher spatial variability. On the other hand, the ATRA, ATRD and AMDRI series of single stations show similar spatial variability and the influencing radius of the rainfall events was less than 50 km. (3) the rainfall at the northern and southern parts of the basin had smaller CV. Further, by applying the MMK test method to the ATRA, ATRD, and AMDRI series, the ATRA series has an increasing trend which is opposite to that of the ATRD series. The increasing trend in the ATRA series also led to the increasing trend in the AMDRI series. These stations are mainly in central and northern parts of the basin which are more likely to experience droughts and floods. Thus, for the central and northern parts of the basin, they should receive particular attention on the prevention and treatment of droughts and floods.
Rainfall Station Poyang Lake Candidate Station Rainfall Series Negative Exponential Model
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.
Compliance with ethical standards
This study was supported by the National Natural Science Foundation of China (NO.51279143) and the Collaborative Innovation Center for Major Ecological Security Issues of Jiangxi Province and Monitoring Implementation (No.JXS-EW-00).
Conflict of interest
The authors declare that they have no conflict of interest.
This study does not involve human participants and animals.
Deng X, Zhao Y, Wu F, Lin Y, Lu Q, Dai J (2011) Analysis of the trade-off between economic growth and the reduction of nitrogen and phosphorus emissions in the Poyang Lake Watershed, China. Ecol Model 222(2):330–336CrossRefGoogle Scholar
Deng Z, Zhang X, Luo W, Xiao Y, Pan G, Chen L (2014) Response of Poyang Lake wetland carex to the water level change. J Basic Sci Eng 22(5):865–876Google Scholar
Kao SC, Kume T, Komatsu H, Liang WL (2013) Spatial and temporal variations in rainfall characteristics in mountainous and lowland areas in Taiwan. Hydrol Process 27(18):2651–2658. doi:10.1002/hyp.9416CrossRefGoogle Scholar
Luo W, Zhang X, Deng Z (2013) Variation of the total runoff into Poyang Lake and drought-flood abrupt alternation during the past 50 years. J Basic Sci Eng 21(5):845–856Google Scholar
Ngongondo C, Xu C, Gottschalk L, Alemaw B (2011) Evaluation of spatial and temporal characteristics of rainfall in Malawi: a case of data scarce region. Theoret Appl Climatol 106(1):79–93. doi:10.1007/s00704-011-0413-0CrossRefGoogle Scholar
Sinokrot BA, Stefan HG, Mccormick JH, Eaton JG (1995) Numerical modeling of the response of alluvial rivers to Quaternary climate change. Global Planet Change 30(2):181–200. doi:10.1016/S0921-8181(01)00064-9Google Scholar
Štěpánek, P (2008): AnClim - software for time series analysis: Dept. of Geography, Fac. of Natural Sciences, MU, Brno. 1.47 MB. http://www.climahom.eu/AnClim.html. Accessed 10 Dec 2014
Štěpánek P, Zahradníček P, Skalák P (2009) Data quality control and homogenization of air temperature and precipitation series in the area of the Czech Republic in the period 1961–2007. Adv Sci Res 3:23–26. doi:10.5194/asr-3-23-2009CrossRefGoogle Scholar
Vicente-serrano SM, Beguería S, López-moreno JI, García-vera MA, Stepanek P (2010) A complete daily precipitation database for northeast Spain: reconstruction, quality control, and homogeneity. Int J Climatol 30(8):1146–1163. doi:10.1002/joc.1850CrossRefGoogle Scholar
Wang H, Chen Y, Chen Z (2013) Spatial distribution and temporal trends of mean precipitation and extremes in the arid region, northwest of China, during 1960–2010. Hydrol Process 27(12):1807–1818. doi:10.1002/hyp.9339CrossRefGoogle Scholar
Xu X, Zhang Q, Li Y, Li X, Wang X (2014) Inner-annual variation of soil water content and groundwater level in a typical islet wetland of Lake Poyang. J Lake Sci 26(02):260–268CrossRefGoogle Scholar