To identify the response of groundwater level variation to global climate change in Northwest China’s inland basins,the Golmud River Catchment was chosen as a case in this paper.Approaches of time series analysis and...To identify the response of groundwater level variation to global climate change in Northwest China’s inland basins,the Golmud River Catchment was chosen as a case in this paper.Approaches of time series analysis and correlation analysis were adopted to investigate the variation of groundwater level influenced by global climate change from 1977 to 2017.Results show that the temperature in the Golmud River Catchment rose 0.57℃ every 10 years.It is highly positive correlated with global climate temperature,with a correlation coefficient,0.87.The frequency and intensity of extreme precipitation were both increased.Generally,groundwater levels increased from 1977 to 2017 in all phreatic and confined aquifers and the fluctuation became more violent.Most importantly,extreme precipitation led to the fact that groundwater level rises sharply,which induced city waterlogging.However,no direct evidence shows that normal precipitation triggered groundwater level rise,and the correlation coefficients between precipitation data from Golmud meteorological station located in the Gobi Desert and groundwater level data of five observation wells are 0.13,0.02,−0.11,0.04,and−0.03,respectively.This phenomenon could be explained as that the main recharge source of groundwater is river leakage in the alluvial-pluvial Gobi plain because of the high total head of river water and goodness hydraulic conductivity of the vadose zone.Data analysis shows that glacier melting aggravated because of local temperature increased.As a result,runoff caused groundwater levels to ascend from 1977 to 2017.Correlation coefficients of two groundwater wells observation data and runoff of Golmud River are 0.80 and 0.68.The research results will contribute to handling the negative effects of climate change on groundwater for Northwestern China.展开更多
基金This research was supported by the National Natural Science Foundation of China(41672250,42177076)the Key R&D Projects of Shaanxi Province(2021ZDLSF05-09)the Natural Science Foundation of Shaanxi Province(2019JLZ-03).
文摘To identify the response of groundwater level variation to global climate change in Northwest China’s inland basins,the Golmud River Catchment was chosen as a case in this paper.Approaches of time series analysis and correlation analysis were adopted to investigate the variation of groundwater level influenced by global climate change from 1977 to 2017.Results show that the temperature in the Golmud River Catchment rose 0.57℃ every 10 years.It is highly positive correlated with global climate temperature,with a correlation coefficient,0.87.The frequency and intensity of extreme precipitation were both increased.Generally,groundwater levels increased from 1977 to 2017 in all phreatic and confined aquifers and the fluctuation became more violent.Most importantly,extreme precipitation led to the fact that groundwater level rises sharply,which induced city waterlogging.However,no direct evidence shows that normal precipitation triggered groundwater level rise,and the correlation coefficients between precipitation data from Golmud meteorological station located in the Gobi Desert and groundwater level data of five observation wells are 0.13,0.02,−0.11,0.04,and−0.03,respectively.This phenomenon could be explained as that the main recharge source of groundwater is river leakage in the alluvial-pluvial Gobi plain because of the high total head of river water and goodness hydraulic conductivity of the vadose zone.Data analysis shows that glacier melting aggravated because of local temperature increased.As a result,runoff caused groundwater levels to ascend from 1977 to 2017.Correlation coefficients of two groundwater wells observation data and runoff of Golmud River are 0.80 and 0.68.The research results will contribute to handling the negative effects of climate change on groundwater for Northwestern China.
