Identification of Preferential Runoff Belts in Jinan Spring Basin Based on Hydrological Time-Series Correlation

被引:15
作者
Niu, Shuyao [1 ,2 ]
Shu, Longcang [1 ,2 ]
Li, Hu [3 ]
Xiang, Hua [4 ]
Wang, Xin [3 ]
Opoku, Portia Annabelle [1 ,2 ]
Li, Yuxi [1 ,2 ]
机构
[1] Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Peoples R China
[2] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
[3] Jinan Rail Transit Grp Co Ltd, Jinan 250101, Peoples R China
[4] Hydrol Ctr Shandong, Jinan 250002, Peoples R China
关键词
Jinan Spring Basin; preferential runoff belt; hydrological time-series analysis; wavelet analysis; time-lag; correlation coefficient; FLOW; PRECIPITATION; SIMULATION;
D O I
10.3390/w13223255
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Jinan karst system is one of the typical karst systems in North China. The karst springs in Jinan are important historical heritage in China. However, in recent years, due to urbanization and the excessive exploitation of groundwater resources in Jinan City, the rate of spring flow has decreased tremendously. Preferential runoff belts are channels of karst aquifers where fractures and conduits are well-developed and serve as the main pathways for groundwater movement and solute transport. In view of this, a study was conducted in the Jinan Spring Basin to identify preferential runoff belts based on hydrological time-series correlation. Firstly, through cross wavelet transform and Pearson correlation coefficient, the time-lag and correlation of spring water level and precipitation were analyzed, the result show that the precipitation in the areas of Xinglong, Donghongmiao, Qiujiazhuang, Xiying, Yanzishan and Liubu stations has a greater impact on spring water level. In addition, combined with the hydrogeological conditions of the Jinan Spring Basin, the above stations meet the characteristics of the preferential runoff belt. In conclusion, the above stations are most likely to be located on the preferential runoff belt. The results of this study can serve as great reference points for building a correct hydrogeological conceptual model, and for the future planning of spring protection measures.
引用
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页数:15
相关论文
共 41 条
[1]   Utilizing Precipitation and Spring Discharge Data to Identify Groundwater Quick Flow Belts in a Karst Spring Catchment [J].
An, Lixing ;
Ren, Xingyuan ;
Hao, Yonghong ;
Yeh, Tian-Chyi Jim ;
Zhang, Baoju .
JOURNAL OF HYDROMETEOROLOGY, 2019, 20 (10) :2057-2068
[2]   DIFFUSE FLOW AND CONDUIT FLOW IN LIMESTONE TERRAIN IN MENDIP HILLS, SOMERSET (GREAT-BRITAIN) [J].
ATKINSON, TC .
JOURNAL OF HYDROLOGY, 1977, 35 (1-2) :93-110
[3]   Daily Runoff Forecasting Using a Cascade Long Short-Term Memory Model that Considers Different Variables [J].
Bai, Yun ;
Bezak, Nejc ;
Zeng, Bo ;
Li, Chuan ;
Sapac, Klaudija ;
Zhang, Jin .
WATER RESOURCES MANAGEMENT, 2021, 35 (04) :1167-1181
[4]   When is a correlation between non-independent variables "spurious"? [J].
Brett, MT .
OIKOS, 2004, 105 (03) :647-656
[5]   A novel two-dimensional correlation coefficient for assessing associations in time series data [J].
Dikbas, Fatih .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2017, 37 (11) :4065-4076
[6]   Analyzing multi-scale hydrodynamic processes in karst with a coupled conceptual modeling and signal decomposition approach [J].
Duran, Lea ;
Massei, Nicolas ;
Lecoq, Nicolas ;
Fournier, Matthieu ;
Labat, David .
JOURNAL OF HYDROLOGY, 2020, 583
[7]   Karst Spring Discharges Analysis in Relation to Drought Periods, Using the SPI [J].
Fiorillo, Francesco ;
Guadagno, Francesco M. .
WATER RESOURCES MANAGEMENT, 2010, 24 (09) :1867-1884
[8]  
[高宗军 Gao Zongjun], 2014, [地学前缘, Earth Science Frontiers], V21, P135
[9]   Application of the cross wavelet transform and wavelet coherence to geophysical time series [J].
Grinsted, A ;
Moore, JC ;
Jevrejeva, S .
NONLINEAR PROCESSES IN GEOPHYSICS, 2004, 11 (5-6) :561-566
[10]   A Complicated Karst Spring System: Identified by Karst Springs Using Water Level, Hydrogeochemical, and Isotopic Data in Jinan, China [J].
Guo, Yi ;
Qin, Dajun ;
Li, Lu ;
Sun, Jie ;
Li, Fulin ;
Huang, Jiwen .
WATER, 2019, 11 (05)