Drought characteristics in Nanxiaohegou basin
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DOI:10.7606/j.issn.1000-7601.2017.05.42
Key Words: drought  standardized precipitation index (SPI)  change characteristics  model validation  Mann-Kendall test
Author NameAffiliation
LI Lan-jun State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi'an University of Technology, Xi'an, Shaanxi 710048, China 
SONG Xiao-yu State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi'an University of Technology, Xi'an, Shaanxi 710048, China 
WANG Guang-she Shaanxi Province Institute of Water Resources and Electric Power Investigation and Design, Xi'an, Shaanxi 710001, China 
LI Huai-you Xifeng Experiment Station of Soil and Water Conservation, Yellow River Conservancy Committee, Xifeng, Gansu 745000, China 
LI Yao-lin Xifeng Experiment Station of Soil and Water Conservation, Yellow River Conservancy Committee, Xifeng, Gansu 745000, China 
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Abstract:
      The ecological environment is fragile in the Loess Plateau, and the occurrence of the drought can seriously affect the agricultural production and economic development in the region. The rainfall data of 1970—2012 years in the Nanxiaohegou basin were selected, and the drought level was described by the standardized precipitation index (SPI). Mann-Kendall test was performed on the annual and seasonal scale SPI sequence and the seasonal cross multiply trend model was used to verify the drought on annual and seasonal scale. The results are as follows:the frequency of drought in the basin was 48.84%, the annual variation of SPI was severe, and in a direction towards the development of drought. Spring drought had obvious stage characteristics, the degree of summer drought was not significant, the trend of drought in autumn was not significant except for the year of 1975 and the degree of drought in winter was relatively stable, mainly concentrated in the non-drought and light-drought levels. The seasonal cross multiply trend model had good effect in annual, autumn and winter drought assessment, the pass rate all reached 71.43% and it also had a strong tendency to estimate the other drought level to the moderate level when a prediction error occured.