Li-qiong Wei; Fang Guo; Guang-hui Jiang; Tian-wang Pan; Fan Liu

doi:10.26599/JGSE.2026.9280109

doi: 10.26599/JGSE.2026.9280109

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^{1, 3, 5},
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出版历程
- 收稿日期: 2026-04-03
- 录用日期: 2026-07-16
- 网络出版日期: 2026-10-29

Unraveling the drivers of fecal indicator bacteria dynamics in karst spring hyporheic zones: The role of external loading, hydrodynamics, and environmental forcing

Li-qiong Wei¹,
Fang Guo^{1, 3, 4, 5
, ,},
Guang-hui Jiang^{2
, ,},
Tian-wang Pan^{1, 3, 5},
Fan Liu^{1, 3, 4, 5}

1.
Key Laboratory of Karst Dynamics, MNR/GZAR, Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin, Guangxi, China
2.
College of Civil Engineering and Architecture, Guangxi University, Nanning, China
3.
International Research Centre on Karst under the Auspices of UNESCO, National Center for International Research on Karst Dynamic System and Global Change, Guilin, Guangxi, China
4.
Guilin Karst Geology Observation and Research Station of Guangxi, Guilin, Guangxi, China
5.
Pingguo Guangxi, Karst Ecosystem, National Observation and Research Station, Pingguo, Guangxi, China

More Information

Corresponding author: gfkarst@126.com; bmnxz@126.com

摘要

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Abstract: Fecal Indicator Bacteria (FIB) are widely used to assess microbial safety in drinking water sources; however, their dynamics in karst springs hydraulically connected to rivers remain insufficiently understood due to strong hydrodynamic disturbances. This study investigated a large karst spring and its confluent river in South China to examine FIB contamination and the controls on FIB spatiotemporal patterns in the spring outlet hyporheic zone. Most hyporheic-zone and aquifer samples exceeded the relevant limits for Total Coliforms (TC) specified in the Chinese Standard for Groundwater Quality (GB/T 14848–2017) and Standards for Drinking Water Quality (GB 5749–2006), and Fecal Coliforms (FC) were detected in nearly half of the samples. During non-backflow periods, FIB abundances were significantly higher in summer and autumn than in spring and winter. Spatially, FIB generally increased downstream within the hyporheic zone, with high levels confined downstream at low water levels but extending upstream at medium and high water levels. Potential contamination sources included river backflow, aquifer discharge, sewage leakage, and rainfall-induced runoff. FIB were not clearly related to most physicochemical parameters, but were associated with organic matter and water temperature. River backflow strongly influenced FIB dynamics by altering water exchange and the physicochemical environment. During the two observed river backflow events, strong backflow mainly caused sharp FIB increases in the hyporheic zone and aquifer through intensified hydrodynamic transport and particle-associated migration, whereas weak backflow, despite not reaching the aquifer, still increased FIB within the hyporheic zone under reduced dilution and favorable nutritional and microecological conditions. High FIB concentrations and detection frequencies, together with elevated chemical indicators, indicate poorer microbial and chemical water quality in the hyporheic zone. These findings clarify the factors and processes shaping FIB dynamics in karst spring hyporheic zones and support drinking water source protection and microbial water quality management in vulnerable karst regions.
- Hyporheic zone /
- Fecal indicator bacteria /
- Hydrodynamics /
- Drinking water safety /
- Water environment

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Figure 1. Study area

Notes: (a) Geographic location of the study area in Guangxi, China. (b) Schematic plan of LingShui Spring and adjacent Wuming River, showing the locations of three river sampling sites (MXY, MXDZ, and LB) and surrounding residential areas. (c) Aerial view of the LingShui Spring area, illustrating the sampling points from aquifer (Y1, Y2), spring outlets (S1-S3), lake water (L1-L6), and their spatial distribution within the spring system. (d) Spring outlet (S2) on May 31, 2021 (before backflow). (e) Spring outlet (S2) on June 2, 2021 (during the flooding). (f) Spring outlet (S2) on September 6, 2024 (before backflow). (g) Spring outlet (S2) on September 8, 2024 (during the flooding).

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Figure 2. Spatial variations in TC (a) and FC (b) during non-backflow periods, and their concentrations in the aquifer (c).

Notes: Sampling locations are categorized along the hydrological flow path from the spring outlet (SP: S1–S3) to the central lake (ML: L1–L5), and then to the downstream lake (DL: L6). Log₁₀ (TC+1) and Log₁₀ (FC+1) represent the base-10 logarithmic transformation of TC and FC concentrations, respectively, with 1 added to avoid undefined values when concentrations are zero.

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Figure 3. Seasonal variations in TC (a) and FC (b) in the hyporheic zone during non-backflow periods.

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Figure 4. TC (a) and FC (b) count at the spring outlet (S2) and downstream lake (L6) under non-backflow and backflow conditions.

Notes: The area to the left of the dashed line represents the non-backflow period, and the area to the right represents the backflow period during the 2024 backflow event.

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Figure 5. Response of TC (a) and FC (b) in the aquifer to lake water level fluctuations during the 2021 backflow event.

Notes: The area between the two dashed lines indicates the period during which both total coliforms and fecal coliform concentrations exceeded 10⁴ CFU/100 mL.

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Figure 6. Variations in physicochemical parameters in response to lake water level fluctuations during backflow events.

Notes: (a) Water Temperature (WT) and Specific Electrical Conductivity (SEC) during the 2024 backflow event. (b) pH and Dissolved Oxygen (DO) during the 2024 backflow event. (c) Turbidity (Turb.), Specific Electrical Conductivity (SEC), and Water Temperature (WT) during the 2021 backflow event.

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Figure 7. Chl-a (a) and DOC (b) levels at the spring outlet (S2) during the two backflow events and normal periods.

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Figure 8. Seasonal dynamics of spring discharge at the Lingshui Spring.

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Figure 9. Conceptual model of the FIB sources and dynamics in the karst spring outlet hyporheic zone under contrasting hydrodynamic conditions.

Notes: The model illustrates FIB dynamics under three hydrodynamic scenarios: (a) the non-backflow period, (b) a strong backflow event, and (c) a weak backflow event. FIB mainly originated from the aquifer, river backflow, surrounding domestic sewage, and rainfall-induced runoff. During the non-backflow period, FIB concentrations were higher in summer and autumn than in spring and winter. Generally, they increased from the spring outlet to the central lake, lake tail, and river-affected zone. Both river backflow events led to marked increases in FIB concentrations at LS. The strong backflow event was associated with an approximately 8 m rise in water level, with effects extending to both the hyporheic zone and the connected aquifer. In contrast, the weak backflow event involved a water-level rise of only approximately 2.5 m, and its influence was mainly restricted to the hyporheic zone.

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Figure 10. TC concentration and FC detection frequency in the hyporheic zone under different water-level conditions.

Notes: (a) TC concentration by sampling zone and water level; (b) FC detection frequency by sampling zone; and (c) overall FC detection frequency by water level.

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Table 1. Seasonal variation of integrated environmental factors in the hyporheic zone (mean ± SD).

	Spring (N=17)	Summer (N=19)	Autumn (N=23)	Winter (N=23)
pH	7.32±0.13	7.18±0.10	7.23±0.18	7.38±0.17
WT (°C)	24.21±0.39	24.46±0.23	24.40±0.23	24.01±0.34
DO (mg/L)	4.31±0.54	4.06±0.75	3.88±0.51	5.11±1.13
SEC (μS/cm)	378.9±15.1	380.4±18.2	383.6±16.0	381.4±14.2
Chl-a (μg/L)	0.22±0.20	0.18±0.16	0.20±0.30	0.09±0.08
CDOM (μg/L)	0.02±0.07	0.81±1.13	0.84±0.90	0.15±0.23
ORP (mV)	331.6±13.7	332.4±85.6	336.3±43.0	339.5±44.2

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Table 2. Measured physicochemical parameters in hyporheic zone and river.

	Spring outlet		Lake		River
	Range	Mean	Range	Mean	Range	Mean
pH	6.82–7.45	7.24	7.01–7.93	7.31	7.35–8.43	7.75
WT (°C)	23.93–24.72	24.27	23.53–24.95	24.27	14.71–31.32	24.85
DO (mg/L)	3.10–7.44	4.13	3.38–7.15	4.52	4.35–9.12	7.32
SEC (μS/cm)	336.3–413.9	378.51	363.8–398.2	383.02	222.7–414	294.5
Chl-a (μg/L)	0.00–0.91	0.11	0.03–0.91	0.21	0.55–9.75	2.15
CDOM (μg/L)	0.00–2.31	0.25	0.00–4.46	0.67	4.26–19.86	11.19
DOC (mg/L)	0.25–4	1.07	0.23–5.06	1.31	1.05–15.76	7.77
Turb. (NTU)	0.01–0.86	0.43	0.01–1.38	0.57	3.36–11.40	7.62
Cl⁻ (mg/L)	5.09–6.89	6.14	5.00–6.77	5.94	6.04–33.96	9.92
SO₄²⁻ (mg/L)	0.96–8.54	4.09	1.88–5.48	3.81	6.01–15.42	10.07
PO₄³⁻ (mg/L)	0–0.12	0.05	0–0.08	0.03	0–0.64	0.101
NO₃⁻ (mg/L)	0–23.56	9.10	0–11.68	6.50	0–13.14	2.77
NO₂⁻ (mg/L)	0–0.018	0.005	0–4.82	0.788	0–3.18	0.439
NH₄⁺ (mg/L)	0–0.02	0.005	0–0.062	0.011	0–0.2	0.034

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Table 3. Changes in major pollutants in the hyporheic zone before and after river backflow

Period	Date	Site	Cl⁻ (mg/L)	SO₄²⁻ (mg/L)	NH₄⁺ (mg/L)	NO₂⁻ (mg/L)	NO₃⁻ (mg/L)	PO₄³⁻ (mg/L)
Normal period	2021/1/13	L6	5.84	5.48	–	–	8.94	–
Normal period	2021/4/7	L6	5.96	3.36	0	0.003	8.94	0.08
Backflow period	2021/6/2 12:00	Y2	6.54	7.49	0	3.54	0.36	0
	2021/6/3 8:00	Y2	6.54	9.68	1.35	0.003	9.55	0.08
	2021/6/4 10:30	Y2	6.30	6.05	0	5.62	0	0
Normal period	2021/9/16	L6	5.00	2.8	–	–	–	–
	2021/12/22	L6	5.57	3.77	–	–	9.92	0.05
	2022/4/19	L6	6.40	3.54	0	3.57	–	0.03
	2023/5/31	L6	6.68	4.01	0	4.82	0.80	0
	2023/9/6	L6	6.37	3.25	0	0	–	0
	2024/7/15	L6	6.26	3.54	0.02	0	10.49	0
Backflow period	2024/9/8 7:09	L6	8.18	11.42	0.08	0	0	0
	2024/9/8 9:00	L6	7.83	4.22	0.12	0	0	0
	2024/9/8 14:00	L6	10.10	15.46	1.27	0	0	0.071
	2024/9/8 22:00	L6	8.07	10.66	0	0	0	0
	2024/9/8 22:00	S2	7.69	10.74	0	0	0	0
Notes: – indicates missing data

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Table 4. Correlation coefficients for environmental factors with FIB.

	Log₁₀ (TC +1)	Log₁₀ (FC + 1)
Log₁₀ (NO₃⁻ + 1)	−0.579**	−0.439**
Log₁₀ (NO₂⁻ + 1)	0.409*	0.432*
Log₁₀ (NH₄⁺ + 1)	−0.007	−0.311
Log₁₀ (PO₄³⁻ + 1)	−0.308	0.003
Log₁₀ (Turb. + 1)	0.436	0.157
Log₁₀ (DOC + 1)	0.392^*	0.274
Log₁₀ (Chla + 1)	0.329**	0.453**
Log₁₀ (CDOM + 1)	0.418**	0.314*
Log₁₀ (WT + 1)	0.423**	0.202
Log₁₀ (pH + 1)	0.142	0.096
Log₁₀ (ORP + 1)	0.130	0.073
Log₁₀ (SEC + 1)	−0.043	0.100
Log₁₀ (DO + 1)	0.002	−0.051
Notes: Values represent Pearson correlation coefficients. "*" indicates significance at p < 0.01; "" indicates significance at p < 0.05. Log₁₀ (TC + 1) and Log₁₀ (FC + 1) represent the base-10 logarithmic transformation of TC and FC concentrations, respectively, with 1 added to avoid undefined values when concentrations are zero.

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[6]	Yu Chu, Wu Li-jie, Zhang Yi-long, Wang Xiu-ya, Wang Zhan-chuan, Zhang Zhou2022: Effect of groundwater on the ecological water environment of typical inland lakes in the Inner Mongolian Plateau, Journal of Groundwater Science and Engineering, 10, 353-366. doi: 10.19637/j.cnki.2305-7068.2022.04.004
[7]	MA Li-sha, HAN Zhan-tao, WANG Yan-yan2021: Dispersion performance of nanoparticles in water, Journal of Groundwater Science and Engineering, 9, 37-44. doi: 10.19637/j.cnki.2305-7068.2021.01.004
[8]	YIN Xiao-lin, GAO Yuan-yuan, WU Hai-ping, ZHAO Xue-ming2020: Water-saving potential evaluation of water-receiving regions in Shandong province on the East Route of the South-to-North Water Transfer Project of China, Journal of Groundwater Science and Engineering, 8, 287-297. doi: 10.19637/j.cnki.2305-7068.2020.03.009
[9]	Ahmed Mohammad Tofayal, Monir Minhaj Uddin, Hasan Md Yeasir, Rahman Md Mominur, Rifat Md Shamiul Islam, Islam Md Naim, Khan Abu Shamim, Rahman Md Mizanur, Islam Md Shajidul2020: Hydro-geochemical evaluation of groundwater with studies on water quality index and suitability for drinking in Sagardari, Jashore, Journal of Groundwater Science and Engineering, 8, 259-273. doi: 10.19637/j.cnki.2305-7068.2020.03.006
[10]	MIAO Qing-zhuang, ZHOU Xiao-ni, WANG Gui-ling, ZHANG Wei, LIU Feng, XING Lin-xiao2019: Research on changes of hydrodynamics and ion-exchange adsorption in Brackish-Water Interface, Journal of Groundwater Science and Engineering, 7, 94-105. doi: 10.19637/j.cnki.2305-7068.2019.02.001
[11]	WANG Ying, CHEN Zong-yu2016: Responses of groundwater system to water development in northern China, Journal of Groundwater Science and Engineering, 4, 69-80.
[12]	GONG Xiao-ping, JIANG Guang-hui, CHEN Chang-jie, GUO Xiao-jiao, ZHANG Hua-sheng2015: Specific yield of phreatic variation zone in karst aquifer with the method of water level analysis, Journal of Groundwater Science and Engineering, 3, 192-201.
[13]	LIU Kai, SUN Ying, LI Yu, LIU Jiu-rong, LIU Ying-chao2014: Zonation for exploitation and utilization of geothermal water in Beijing, Journal of Groundwater Science and Engineering, 2, 94-104.
[14]	Le SONG, Yan-pei CHENG2014: Optimization Research of Water-Soil Resources in Huanghua, Journal of Groundwater Science and Engineering, 2, 86-94.
[15]	GE Li-qiang, CHENG Yan-pei, YUE Chen2014: Study of water resources for crop utilization in China from the perspective of Virtual Water, Journal of Groundwater Science and Engineering, 2, 67-75.
[16]	HAN Mei, JIA Na, LI Ke, ZHAO Guo-xing, LIU Bing-bing, LIU Sheng-hua, LIU Jie2014: Analysis of bromate and bromide in drinking water by ion chromatography-inductively coupled plasma mass spectrometry, Journal of Groundwater Science and Engineering, 2, 48-53.
[17]	HE Hong, GUO Hong-bin, LIU Hong-yun2014: Analysis of effect of water construction in different phases on groundwater environment, Journal of Groundwater Science and Engineering, 2, 54-59.
[18]	Cheng Yanpei, Ma Renhui2013: Analysis of Water Resource Demands: Based on the Hydrological Unit, Journal of Groundwater Science and Engineering, 1, 48-59.
[19]	Do Van Binh2013: Source and Formation of the Arsenic in Ground Water in Hanoi , Vietnam, Journal of Groundwater Science and Engineering, 1, 102-108.
[20]	Meng-jie Wu, Hui-zhen Hen2013: Brief Talk of Groundwater Resources in Role of Rural Drinking Water Safety and Construction of City Emergency Water Source, Journal of Groundwater Science and Engineering, 1, 40-52.