基于小波分析与Mann-Kendall法的岩溶大泉动态研究
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摘要
研究地下水动态是认识地下水资源的有效手段。根据1956-2013年济南岩溶泉域大气降水及地下水水位动态监测资料,采用小波分析法、Mann-Kendall趋势检验、突变检验法研究了58个水文年泉水位对大气降水的响应,可以看出:(1)大气降水和泉水位呈现出多尺度的变化特征,长时间尺度上两者的变化周期基本相同,变化周期为16年和12年,说明大气降水对泉水位有直接影响;(2)在1956—2013年,济南泉域地下水水位具有0.65m·(10a)~(-1)的年际显著下降趋势,但降水具有12.65mm·(10a)~(-1)的不显著上升趋势,说明在人为因素影响下泉水动态的影响因素的权重发生了变化;(3)大气降水在1999年发生突变,1999年之后年降水为增加趋势;而地下水水位突变年份为1967年,1967年以后水位持续降低,2004年以后水位快速上升,泉水位未来趋势应与降水保持一致,呈上升趋势,说明大气降水并非泉水动态的唯一影响因素;(4)通过建立不同时段的多元回归模型,表明近58年来地下水水位的主要影响因素由大气降水到人工开采之间的转换,同时验证了小波分析和Mann-Kendall法研究地下水动态的适宜性和可靠性,也为济南市的保泉提供了参考依据。
The study of groundwater dynamics is one of the most effective ways to understand the nature of groundwater resources.According to the monitoring data of precipitation and groundwater level in the Jinan karst spring area from 1956to 2013,this work studies the spring water level response to atmospheric precipitation during these 58years using the wavelet analysis,Mann-Kendall trend test and mutation test.The results show that,(1)the precipitation and spring water level show a feature of multi-scale variation,and the change cycle is basically the same on a long-term scale,which are 16years and 12years,respectively.It means that atmospheric precipitation has a direct impact on the spring water level.(2)From 1956to 2013,the groundwater level in the Jinan spring area had a significant downward trend of 0.65m·(10a)~(-1),while the precipitation had an upward trend of 12.65mm·(10a)~(-1),which is not significant,indicating that the weight of the influencing factors of spring dynamic has changed under the influence of human factors.(3)Furthermore,there has been a mutation of atmospheric precipitation which occurred in 1999,and the annual precipitation increased after 1999.However,the groundwater level mutation appeared in 1967,while the water level continued to decrease after 1967and then increased rapidly after 2004.The future trend of the spring water level should be kept consistent with the precipitation and show an upward trend,indicating that atmospheric precipitation is not the sole factor affecting the dynamics of the spring.(4)The results from multivariable regressions for different periods of time suggest that the main influencing factors of groundwater level in the past 58years are the transition from precipitation to artificial mining;at the same time,it validates the suitability and reliability of wavelet analysis and the Mann-Kendall method to study groundwater dynamics,and also provides a reference for the protection of the spring in Jinan City.
The study of groundwater dynamics is one of the most effective ways to understand the nature of groundwater resources.According to the monitoring data of precipitation and groundwater level in the Jinan karst spring area from 1956to 2013,this work studies the spring water level response to atmospheric precipitation during these 58years using the wavelet analysis,Mann-Kendall trend test and mutation test.The results show that,(1)the precipitation and spring water level show a feature of multi-scale variation,and the change cycle is basically the same on a long-term scale,which are 16years and 12years,respectively.It means that atmospheric precipitation has a direct impact on the spring water level.(2)From 1956to 2013,the groundwater level in the Jinan spring area had a significant downward trend of 0.65m·(10a)~(-1),while the precipitation had an upward trend of 12.65mm·(10a)~(-1),which is not significant,indicating that the weight of the influencing factors of spring dynamic has changed under the influence of human factors.(3)Furthermore,there has been a mutation of atmospheric precipitation which occurred in 1999,and the annual precipitation increased after 1999.However,the groundwater level mutation appeared in 1967,while the water level continued to decrease after 1967and then increased rapidly after 2004.The future trend of the spring water level should be kept consistent with the precipitation and show an upward trend,indicating that atmospheric precipitation is not the sole factor affecting the dynamics of the spring.(4)The results from multivariable regressions for different periods of time suggest that the main influencing factors of groundwater level in the past 58years are the transition from precipitation to artificial mining;at the same time,it validates the suitability and reliability of wavelet analysis and the Mann-Kendall method to study groundwater dynamics,and also provides a reference for the protection of the spring in Jinan City.
引文
[1]祁晓凡,杨丽芝,韩晔,等.济南泉域地下水位动态及其对降水响应的交叉小波分析[J].地球科学进展,2012,27(9):969-978.
[2]祁晓凡,蒋忠诚,罗为群.典型表层岩溶水系统降水量与泉流量的交叉小波分析[J].地球与环境,2012,40(4):561-567.
[3]郭琳,宫辉力,朱锋,等.基于小波分析的地下水水位与降水的周期性特征研究[J].地理与地理信息科学,2014,30(2):35-38,127.
[4] Tremblay L,Larocque M,Anctil F,et al.Teleconnections and interannual variability in Canadian groundwater levels[J].Journal of Hydrology,2011,410(3):178-188.
[5] Nakken M.Wavelet analysis of rainfall-runoff variability isolating climatic from anthropogenic patterns[J].Environmental Modelling&Software,1999,14(4):283-295.
[6]张建芝,邢立亭.回归分析法在地下水动态分析中的应用[J].地下水,2010,32(4):88-90.
[7]迟光耀,邢立亭,主恒祥,等.大气降水与济南泉水动态变化的定量关系研究[J].地下水,2017,39(1):8-11.
[8] Lu W X,Zhao Y,Chu H B,et al.The analysis of groundwater levels influenced by dual factors in western Jilin Province by using time series analysis method[J].Applied Water Science,2014,3(4):251-260.
[9] Jan C D,Chen T H,Huang H M.Analysis of rainfall-induced quick groundwater-level response by using a Kernel function[J].Paddy Water Environment,2013(11):135-144.
[10] Chang F J,Chen P A,Liu C W,et al.Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling[J].Journal of Hydrology,2013,499:265-274.
[11]胡克祯,张建芝,邢立亭.基于时间序列分析的地下水动态研究[J].水科学与工程技术,2011(5):32-34.
[12] Mao X M,Shang S H,Liu X.Groundwater level predictions using artificial neural networks[J].Tsinghua Science and Technology,2002,7(6):574-579.
[13] Schulze-Makuch D,Douglas A,Carlson,D Scherkauer,etal.Scale dependency of hydraulic conductivity in hetero-geneous media[J].GroundWater,1999,37(6):904-919.
[14] Eric K,Webb and Mary P,Anderson.Simulation of preferential flow in three-dimensional heterogeneous conductivity fields with realistic internal architecture[J].Water Resources Research,1996,32(3):533-545.
[15]孙晨,束龙仓,鲁程鹏,等.裂隙-管道介质泉流量衰减过程试验研究及数值模拟[J],水利学报,2014,45(1):50-57,64.
[16] Faulkner J,Hu B,Kish S,et al.Laboratory analog and numerical study of groundwater flow and solute transport in a karst aquifer with conduit and matrix domains[J].Journal of Contaminant Hydrology,2009,110(1-2):34-44.
[17]宫辉力,赵文吉,诸云强.裂隙-岩溶介质空间水流数值仿真与流场优化[J].系统仿真学报,2002,14(2):186-188.
[18] Gallegos J J.Modeling groundwater flow in karst aquifers:an evaluation of MODFLOW-CFP at the laboratory and sub-regional scales[D].Tallahassee:Florida State University,2011.
[19] Shoemaker B W,Kuniansky E L,Steffen B.Documentation of a conduit flow process(CFP)for MODFLOW-2005[M].Virginia:U S GeologicalSur vey,2007:1-50.
[20]祁晓凡,李文鹏,李传生,等.济南岩溶泉域地下水位与降水的趋势性与持续性[J].灌溉排水学报,2015,34(11):98-104.
[21]吴小玲,张斌,艾南山,等.基于小波变换的上海市近10年SO2污染指数的变化[J].环境科学,2009,30(8):2193-2198.
[22] Torrence C,Compo G.A practical guide to wavelet analysis[J].Bulletin of the American Meteorological Society,1998,79(1):61-78.
[23] Orhan Gunduz,Celalettin Simsek.Influence of Climate Change on Shallow Groundwater Resources:The Link Between Precipitation and Groundwater Levels in Alluvial Systems[J].Climate Change and its Effects on Water Resources,2011,3:225-233.
[24]董婕,周淑艳,卢斌.富平县地下水位与降水量变化动态分析[J].西北师范大学学报(自然科学版),2008,44(6):98-101.
[25] Noam Zach Dvory,Yakov Livshitz,Eilon Adar,et al.The effect of hydrogeological conditions on variability and dynamic of groundwater recharge in a carbonate aquifer at local scale[J].Journal of Hydrology,2016,535:480-494.
[26]徐建华,现代地理学中的数学方法[M].北京:高等教育出版社,2002.
[27]桑燕芳,王栋.水文序列小波分析中小波函数选择方法[J].水利学报,2008,39(3):295-300,306.
[28]姜晓艳,刘树华,马明敏,等.东北地区近百年降水时间序列变化规律的小波分析[J].地理研究,2009,28(2):354-362.
[29] Xu J H,Chen Y N,Lu F,et al.The nonlinear trend of runoff and its response to climate change in the Aksu River,western China[J].International Journal of Climatology,2011,31(5):687-695.
[30]申倩倩,束炯,王行恒.上海地区近136年气温和降水量变化的多尺度分析[J].自然资源学报,2011,26(4):644-654.
[31]刘宇峰,孙虎,原志华.基于小波分析的汾河河津站径流与输沙的多时间尺度特征[J].地理科学,2012,32(6):764-770.
[32] Van B G,Hughes J P.Nonparametric tests for trends in water quality[J].Water Resources Research,1984,20(1):127-136.
[33] HAMED K.Exact distribution of the mann-kendall trend test statistic for persistent data[J].Journal of Hydrology,2009,365(1):86-94.
[34] Zhang Q,Xu C Y,Tao H,et al.Climate changes and their impacts on water resources in the arid Regions:A case study of the tarim river basin,China[J].Stochastic Environmental Research and Risk Assessment,2010,24(3):349-358.
[35]于延胜,陈兴伟.基于Mann-Kendall法的水文序列趋势成分比重研究[J].自然资源学报,2011,26(9):1585-1591.
[36]刘叶玲,翟晓丽,郑爱勤.关中盆地降水量变化趋势的MannKendall分析[J].人民黄河,2012,34(2):28-30+33.
[37]祁晓凡,王雨山,杨丽芝,等.近50年济南岩溶泉域地下水位对降水响应的时滞差异[J].中国岩溶,2016,35(4):384-393.
[38]王珺瑜,王家乐,靳孟贵.济南泉域岩溶水水化学特征及其成因[J],地球科学,2017,42(5):821-831.
[39]周娟,邢立亭,滕朝霞,等.制约济南岩溶大泉持续喷涌的主因素阈值研究[J].华东师范大学学报(自然科学版),2015(3):146-156.
[2]祁晓凡,蒋忠诚,罗为群.典型表层岩溶水系统降水量与泉流量的交叉小波分析[J].地球与环境,2012,40(4):561-567.
[3]郭琳,宫辉力,朱锋,等.基于小波分析的地下水水位与降水的周期性特征研究[J].地理与地理信息科学,2014,30(2):35-38,127.
[4] Tremblay L,Larocque M,Anctil F,et al.Teleconnections and interannual variability in Canadian groundwater levels[J].Journal of Hydrology,2011,410(3):178-188.
[5] Nakken M.Wavelet analysis of rainfall-runoff variability isolating climatic from anthropogenic patterns[J].Environmental Modelling&Software,1999,14(4):283-295.
[6]张建芝,邢立亭.回归分析法在地下水动态分析中的应用[J].地下水,2010,32(4):88-90.
[7]迟光耀,邢立亭,主恒祥,等.大气降水与济南泉水动态变化的定量关系研究[J].地下水,2017,39(1):8-11.
[8] Lu W X,Zhao Y,Chu H B,et al.The analysis of groundwater levels influenced by dual factors in western Jilin Province by using time series analysis method[J].Applied Water Science,2014,3(4):251-260.
[9] Jan C D,Chen T H,Huang H M.Analysis of rainfall-induced quick groundwater-level response by using a Kernel function[J].Paddy Water Environment,2013(11):135-144.
[10] Chang F J,Chen P A,Liu C W,et al.Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling[J].Journal of Hydrology,2013,499:265-274.
[11]胡克祯,张建芝,邢立亭.基于时间序列分析的地下水动态研究[J].水科学与工程技术,2011(5):32-34.
[12] Mao X M,Shang S H,Liu X.Groundwater level predictions using artificial neural networks[J].Tsinghua Science and Technology,2002,7(6):574-579.
[13] Schulze-Makuch D,Douglas A,Carlson,D Scherkauer,etal.Scale dependency of hydraulic conductivity in hetero-geneous media[J].GroundWater,1999,37(6):904-919.
[14] Eric K,Webb and Mary P,Anderson.Simulation of preferential flow in three-dimensional heterogeneous conductivity fields with realistic internal architecture[J].Water Resources Research,1996,32(3):533-545.
[15]孙晨,束龙仓,鲁程鹏,等.裂隙-管道介质泉流量衰减过程试验研究及数值模拟[J],水利学报,2014,45(1):50-57,64.
[16] Faulkner J,Hu B,Kish S,et al.Laboratory analog and numerical study of groundwater flow and solute transport in a karst aquifer with conduit and matrix domains[J].Journal of Contaminant Hydrology,2009,110(1-2):34-44.
[17]宫辉力,赵文吉,诸云强.裂隙-岩溶介质空间水流数值仿真与流场优化[J].系统仿真学报,2002,14(2):186-188.
[18] Gallegos J J.Modeling groundwater flow in karst aquifers:an evaluation of MODFLOW-CFP at the laboratory and sub-regional scales[D].Tallahassee:Florida State University,2011.
[19] Shoemaker B W,Kuniansky E L,Steffen B.Documentation of a conduit flow process(CFP)for MODFLOW-2005[M].Virginia:U S GeologicalSur vey,2007:1-50.
[20]祁晓凡,李文鹏,李传生,等.济南岩溶泉域地下水位与降水的趋势性与持续性[J].灌溉排水学报,2015,34(11):98-104.
[21]吴小玲,张斌,艾南山,等.基于小波变换的上海市近10年SO2污染指数的变化[J].环境科学,2009,30(8):2193-2198.
[22] Torrence C,Compo G.A practical guide to wavelet analysis[J].Bulletin of the American Meteorological Society,1998,79(1):61-78.
[23] Orhan Gunduz,Celalettin Simsek.Influence of Climate Change on Shallow Groundwater Resources:The Link Between Precipitation and Groundwater Levels in Alluvial Systems[J].Climate Change and its Effects on Water Resources,2011,3:225-233.
[24]董婕,周淑艳,卢斌.富平县地下水位与降水量变化动态分析[J].西北师范大学学报(自然科学版),2008,44(6):98-101.
[25] Noam Zach Dvory,Yakov Livshitz,Eilon Adar,et al.The effect of hydrogeological conditions on variability and dynamic of groundwater recharge in a carbonate aquifer at local scale[J].Journal of Hydrology,2016,535:480-494.
[26]徐建华,现代地理学中的数学方法[M].北京:高等教育出版社,2002.
[27]桑燕芳,王栋.水文序列小波分析中小波函数选择方法[J].水利学报,2008,39(3):295-300,306.
[28]姜晓艳,刘树华,马明敏,等.东北地区近百年降水时间序列变化规律的小波分析[J].地理研究,2009,28(2):354-362.
[29] Xu J H,Chen Y N,Lu F,et al.The nonlinear trend of runoff and its response to climate change in the Aksu River,western China[J].International Journal of Climatology,2011,31(5):687-695.
[30]申倩倩,束炯,王行恒.上海地区近136年气温和降水量变化的多尺度分析[J].自然资源学报,2011,26(4):644-654.
[31]刘宇峰,孙虎,原志华.基于小波分析的汾河河津站径流与输沙的多时间尺度特征[J].地理科学,2012,32(6):764-770.
[32] Van B G,Hughes J P.Nonparametric tests for trends in water quality[J].Water Resources Research,1984,20(1):127-136.
[33] HAMED K.Exact distribution of the mann-kendall trend test statistic for persistent data[J].Journal of Hydrology,2009,365(1):86-94.
[34] Zhang Q,Xu C Y,Tao H,et al.Climate changes and their impacts on water resources in the arid Regions:A case study of the tarim river basin,China[J].Stochastic Environmental Research and Risk Assessment,2010,24(3):349-358.
[35]于延胜,陈兴伟.基于Mann-Kendall法的水文序列趋势成分比重研究[J].自然资源学报,2011,26(9):1585-1591.
[36]刘叶玲,翟晓丽,郑爱勤.关中盆地降水量变化趋势的MannKendall分析[J].人民黄河,2012,34(2):28-30+33.
[37]祁晓凡,王雨山,杨丽芝,等.近50年济南岩溶泉域地下水位对降水响应的时滞差异[J].中国岩溶,2016,35(4):384-393.
[38]王珺瑜,王家乐,靳孟贵.济南泉域岩溶水水化学特征及其成因[J],地球科学,2017,42(5):821-831.
[39]周娟,邢立亭,滕朝霞,等.制约济南岩溶大泉持续喷涌的主因素阈值研究[J].华东师范大学学报(自然科学版),2015(3):146-156.