Advanced Search
  • Included in CSCD
  • Chinese Core Journals
  • Included in WJCI Report
  • Included in Scopus, CA, DOAJ, EBSCO, JST
  • The Key Magazine of China Technology
Volume 42 Issue 5
Oct.  2023
Turn off MathJax
Article Contents
Article Navigation >  CARSOLOGICA SINICA  > 2023  >  42(5): 995-1004
LIU Chunwei, QI Huan, LIN Guangqi, LIU Haoran, PANG Wei, YU Lingqin, MA Hekuan. Study on the influencing factors of spring water in Jinan City based on wavelet transform method[J]. CARSOLOGICA SINICA, 2023, 42(5): 995-1004. doi: 10.11932/karst20230510
Citation: LIU Chunwei, QI Huan, LIN Guangqi, LIU Haoran, PANG Wei, YU Lingqin, MA Hekuan. Study on the influencing factors of spring water in Jinan City based on wavelet transform method[J]. CARSOLOGICA SINICA, 2023, 42(5): 995-1004. doi: 10.11932/karst20230510
shu

Study on the influencing factors of spring water in Jinan City based on wavelet transform method

doi: 10.11932/karst20230510
  • 1.

    801 Institute of Hydrogeology and Engineering Geology, Shandong Provincial Bureau of Geology & Mineral Resources (Shandong Provincial Geo-mineral Engineering Exploration Institute), Jinan, Shandong 250014, China

  • 2.

    Shandong Engineering Research Center for EnvironmentalProtection and Remediation on Groundwater, Jinan, Shandong 250014, China

  • Received Date: 2023-04-20
  • Accepted Date: 2023-07-25
  • Rev Recd Date: 2023-07-21
    • Available Online: 2023-10-20
    Abstract
  • In order to find out the influence of two main factors—precipitation and groundwater exploitation—on the gushing of spring in Jinan urban area, we selected the exploitation data of the western suburb in Jinan (the water source area of Emei Mountain, Dayangzhuang and Lashan), Jinan urban area (the water source area of Quancheng road, Jiefangqiao, Yinhuchi, and Linan) and the eastern suburb in Jinan (the water source area of Huaneng road). We also selected dynamic observation data of urban spring water level and precipitation during the same period. Based on cross wavelet change, wavelet coherence spectrum and multiple wavelet coherence spectrum, we analyzed the time-lag relationship, comprehensive impact and impact degree between atmospheric precipitation, groundwater exploitation and spring water in Jinan City, in order to provide a basis for the optimal allocation of groundwater development and utilization and the promotion of spring protection in this city.The following conclusions are drawn in this study. (1) By cross wavelet transform, we analyzed the resonance period, significant period and phase relationship between the spring level and the influencing factors in the time-frequency domain. It is found that during the research period, there was a frequency domain period of about 1 year between spring water level, precipitation and exploitation quantity of groundwater. The urban spring level and precipitation passed the 95% red noise test and there was a frequency domain period of 0.69-1.16 a outside COI. In a hydrological year, the urban spring level lagged behind the precipitation for 133.22 days. When the urban spring level and groundwater exploitation passed the 95% red noise test and there was a frequency domain period of 0.82-1.23 a outside COI, the response time lag between the urban spring level and the western suburb and the eastern suburb of Jinan was 125.43 days and 83.85 days, respectively. There existed a hydraulic relationship between spring water in Jinan urban area and groundwater in the western suburb and the eastern suburb of this city. The cross wavelet transforms between urban spring level and the exploitation quantity in the western suburb of Jinan, and between the urban spring level and the exploitation quantity in the urban area also showed a dispersed low energy region of 0.39-0.58 a, and the 95% red noise test reflected the seasonal characteristics of the exploitation of Jinan water source. (2) We carried out the wavelet coherence analysis of urban spring water level, precipitation and exploitation quantity of groundwater to explore the change characteristics of urban spring water level and influencing factors in the whole period. The wavelet coherence average value (AWC) between the urban spring level and precipitation was 0.58. The AWC value between the urban spring level and the respective exploitation quantity in the western suburb, in the city area and in the eastern suburb is 0.47, 0.40 and 0.32. PASC was 13.90%, 16.81% and 10.09%, respectively. During the research period, both precipitation and karst groundwater exploitation exerted obvious effects on urban spring levels. In terms of groundwater exploitation in different locations, the urban exploitation exerted the greatest influence on the urban spring level, followed by the western suburb. The eastern suburb of Jinan was influenced least. (3) According to exploitation conditions during the research period, the combination of precipitation and exploitation quantity in the western suburb of Jinan, and its combination in the urban area were regarded as the biggest influencing factors for the change of spring water level. Under the influence of the three factors, MWC produced by the combination of precipitation and exploitation quantities in the western suburb and the urban area reached 0.91, and PASC increased by more than 5%. Under the combined action of the four influencing factors, MWC reached the maximum value of 0.94, while PASC decreased. One reason was that the PASC threshold with statistical significance increased after additional factors were added, and the other reason was that the overlapping effect caused by collinearity among influencing factors reduced the variance contribution of some factors. Therefore, the multivariate wavelet coherence spectrum showed that the combination of precipitation and the exploitation quantities in the western suburb and the urban area is the most influential factor for the change of urban spring water level under the exploitation conditions during the research period.

     

    • FullText(HTML)
  • loading
    • References(27)
  • [1]
    Zhang Z X, Wang W P, Qu S S, Huang Q, Liu S, Xu Q Y, Ni L D. A new perspective to explore the hydraulic connectivity of karst aquifer system in Jinan spring catchment, China[J]. Water, 2018, 10(10):1368. doi: 10.3390/w10101368
    [2]
    郭艺, 秦大军, 王枫, 甘甫平, 闫柏琨. 基于时间序列分析法的岩溶泉水位预测[J]. 中国岩溶, 2021, 40(4):689-697.

    GUO Yi, QIN Dajun, WANG Feng, GAN Fuping, YAN Baikun. Karst spring location prediction based on time series analysis[J]. Carsologica Sinica, 2021, 40(4):689-697.
    [3]
    Xing L T, Huang L X, Chi G Y, Yang L Z, Li C S, Hou X Y. A dynamic study of a karst spring based on wavelet analysis and the Mann-Kendall trend test[J]. Water, 2018, 10(6):698. doi: 10.3390/w10060698
    [4]
    唐春雷, 晋华, 梁永平, 赵春红, 申豪勇, 潘尧云, 景泽. 娘子关泉域岩溶地下水位变化特征及成因[J]. 中国岩溶, 2020, 39(6):810-816.

    TANG Chunlei, JIN Hua, LIANG Yongping, ZHAO Chunhong, SHEN Haoyong, PAN Yaoyun, JING Ze. Characteristics and causes of karst groundwater level change in Niangziguan spring basin[J]. Carsologica Sinica, 2020, 39(6):810-816.
    [5]
    杨晓俊. 基于时间序列分析的柳林泉流量预测[J]. 人民黄河, 2017, 39(11): 99-102.

    YANG Xiaojun. Flow prediction of Liulin spring based on time series analysis[J]. Yellow River, 2017, 39(11): 99-102.
    [6]
    孙才志, 王金生, 林学钰. 山西晋祠泉在引水条件下的可再生性研究[J]. 中国岩溶, 2001, 20(1):11-16.

    SUN Caizhi, WANG Jinsheng, LIN Xueyu. Research on the renewability of Jinci spring in Shanxi Province under water diversion[J]. Carsologica Sinica, 2001, 20(1):11-16.
    [7]
    徐源, 齐欢, 李传磊, 赵有美, 李常锁. 近60年济南市降水量变化特征分析[J]. 山东国土资源, 2021, 37(2): 44-49.

    XU Yuan, QI Huan, LI Chuanlei, ZHAO Youmei, LI Changsuo. Analysis on the characteristics of precipitation changes in recent 60 years in Jinan city[J]. Shandong Land and Resources, 2021, 37(2): 44-49.
    [8]
    祁晓凡, 李文鹏, 李传生, 杨丽芝, 马瑜宏. 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.

    QI Xiaofan, LI Wenpeng, LI Chuansheng, YANG Lizhi, MA Yuhong. Trends and persistence of groundwater table and precipitation of Jinan karst springs watershed[J]. Journal of Irrigation and Drainage, 2015, 34(11):98-104.
    [9]
    秦品瑞. 济南岩溶水系统数值模拟与保泉供水开采方案[J]. 水资源保护, 2018, 34(3):30-36, 103.

    QIN Pinrui. Numerical simulation of Jinan karst water system and groundwater exploitation scheme of keeping spring spurting and water supply[J]. Water Resources Protection, 2018, 34(3):30-36, 103.
    [10]
    Niu Shuyao, Shu Longcang, Li Hu, Xiang Hua, Wang Xin, Portia Annabelle Opoku, Li Yuxi. Identification of preferential runoff belts in Jinan spring basin based on hydrological time-series correlation[J]. Water, 2021, 13(22):3255. doi: 10.3390/w13223255
    [11]
    Hu Wei, Si Bingcheng. Multiple wavelet coherence for untangling scale-specific and localized multivariate relationships in geosciences[J]. Hydrology and Earth System Sciences, 2016, 20(8):3183-3191. doi: 10.5194/hess-20-3183-2016
    [12]
    Si Bingcheng. Spatial scaling analyses of soil physical properties: A review of spectral and wavelet methods[J]. Vadose Zone Journal, 2008, 7(2):547-562. doi: 10.2136/vzj2007.0040
    [13]
    Rehman N, Mandic D P. Multivariate empirical mode decomposition[J]. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2010, 466(2117):1291-1302. doi: 10.1098/rspa.2009.0502
    [14]
    Li S, Liu N, Tang L, Zhang F, Liu J, Liu J. Mutation test and multiple-wavelet coherence of PM2.5 concentration in Guiyang, China[J]. Air Quality, Atmosphere & Health, 2021, 14(7):955-966.
    [15]
    Wu Tsungpao, Wu Hungche, Liu Shubing, Hsueh Shunjen, Chen Junyan. A partial and multiple wavelet analysis of tourism and house prices[J]. Journal of China Tourism Research, 2022, 18(2):419-432. doi: 10.1080/19388160.2020.1866728
    [16]
    Gu Xiufen, Sun Hongguang, Zhang Yong, Yu Zhongbo, Zhu Jianting. Multiple wavelet coherence to evaluate local multivariate relationships in a groundwater system[J]. Groundwater, 2021, 59(3):443-452. doi: 10.1111/gwat.13068
    [17]
    孙斌, 彭玉明. 济南泉域边界条件、水循环特征及水环境问题[J]. 中国岩溶, 2014, 33(3): 272-279.

    SUN Bin, PENG Yuming. Boundary condition, water cycle and water environment changes in Jinan spring region[J]. Carsologica Sinica, 2014, 33(3): 272-279.
    [18]
    孟庆斌, 邢立亭, 滕朝霞. 济南泉域“三水”转化与泉水恢复关系研究[J]. 山东大学学报(工学版), 2008, 38(5):82-87.

    MENG Qingbin, XING Liting, TENG Zhaoxia. The relationship of spring protection and transformation pattern between precipitation groundwater and surface water in the Jinan spring region[J]. Journal of Shandong University (Engineering Science), 2008, 38(5):82-87.
    [19]
    王涛, 霍彦峰, 罗艳. 近300a来天山中西部降水与太阳活动的小波分析[J]. 干旱区研究, 2016, 33(4):708-717.

    WANG Tao, HUO Yanfeng, LUO Yan. Precipitation and sunspots in the central-west Tianshan Mountains in recent 300 years[J]. Arid Zone Research, 2016, 33(4):708-717.
    [20]
    Torrence C, Compo G P. A practical guide to wavelet analysis[J]. Bulletin of the American Meteorological Society, 1998, 79(1):61-78. doi: 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
    [21]
    Grinsted A, Moore J C, Jevrejeva S. Application of the cross wavelet transform and wavelet coherence to geophysical time series[J]. Nonlinear Processes in Geophysics, 2004, 11:561-566. doi: 10.5194/npg-11-561-2004
    [22]
    Wang Junjie, Shi Bing, Zhao Enjin, Chen Xuguang, Yang Shaopeng. Synergistic effects of multiple driving factors on the runoff variations in the Yellow River Basin, China[J]. Journal of Arid Land, 2021, 13(8):835-857. doi: 10.1007/s40333-021-0078-1
    [23]
    祁晓凡, 杨丽芝, 韩晔, 尚浩, 邢立亭. 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.

    QI Xiaofan, YANG Lizhi, HAN Ye, SHANG Hao, XING Liting. Cross wavelet analysis of groundwater level regimes and precipitation-groundwater level regime in Jinan spring region[J]. Advances in Earth Science, 2012, 27(9): 969-978.
    [24]
    赵增文. 济南市保泉供水研究[D]. 西安: 西安建筑科技大学, 2004.

    ZHAO Zengwen. Research on springs protection and water supply in Jinan City[D]. Xi'an: Xi'an University of Architecture and Technology, 2004.
    [25]
    李铁锡, 李岚, 刘业筠. 济南泉水特征及影响因素系统分析[J]. 山东国土资源, 2003, 19(3):48-51.

    LI Tiexi, LI Lan, LIU Yeyun. Systematic analysis of characteristics and effected elements of spring in Jinan City[J]. Shandong Land and Resources, 2003, 19(3):48-51.
    [26]
    Hu Wei, Si Bingcheng, Biswas Asim, Chau Henry Wai. Temporally stable patterns but seasonal dependent controls of soil water content: Evidence from wavelet analyses[J]. Hydrological Processes, 2017, 31(21):3697-3707. doi: 10.1002/hyp.11289
    [27]
    Ng E K W, Chan J C L. Geophysical applications of partial wavelet coherence and multiple wavelet coherence[J]. Journal of Atmospheric and Oceanic Technology, 2012, 29(12):1845-1853. doi: 10.1175/JTECH-D-12-00056.1
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF(2075.0KB)
    XML

    Article Metrics

    Article views (47) PDF downloads(38) Cited by()
    Proportional views
    Related

    Website Copyright © CARSOLOGICA SINICA 桂ICP备05009877号-1

    Sponsor: Chinese Academy of Geological Sciences Sponsored by: Institute of Karst Geology, Chinese Academy of Geological Sciences Address: No.50, Qixing Road, Guilin, Guangxi

    Post Code: 541004 Tel: 0773-5812949 7796657 Email: zgyr@mail.cgs.gov.cn; zgyrbjb@163.com

    Supported by: Beijing Renhe Information Technology Co., Ltd.    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return