织金洞CO<sub>2</sub>浓度对旅游活动响应机制的小波变换分析

张弘智; 吴克华; 罗书文

doi:10.11932/karst20250607

织金洞CO₂浓度对旅游活动响应机制的小波变换分析

doi: 10.11932/karst20250607

张弘智^{1, 2,},
吴克华^{1, 2, ,},
罗书文^{1, 3}

1.
贵州省山地资源研究所, 贵州贵阳 550001
2.
贵州省洞穴工程中心有限公司, 贵州贵阳 550001
3.
贵州省喀斯特洞穴（旅游）资源开发利用工程技术研究中心, 贵州贵阳 550001

基金项目: 贵州省科技计划项目（黔科合支撑[2021]一般379）；贵州省自然科学基金项目（黔科合基础-ZK[2024]一般632）

详细信息

作者简介:
张弘智（1992－），男，助理研究员，主要从事岩溶地质与环境研究。E-mail：1187065677@qq.com

通讯作者:
吴克华（1979－），男，研究员，主要从事喀斯特洞穴与旅游地理研究。E-mail：kehuakarst@163.com。

中图分类号: X144；P593
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出版历程
- 收稿日期: 2024-09-27
- 录用日期: 2025-05-09
- 修回日期: 2025-02-24
- 刊出日期: 2025-12-25

Wavelet transform analysis of the response mechanism of CO₂ concentration to tourist activities in Zhijin Cave

ZHANG Hongzhi^{1, 2
,},
WU Kehua^{1, 2
, ,},
LUO Shuwen^{1, 3}

1.
Guizhou Institute of Mountain Resources, Guiyang, Guizhou 550001, China
2.
Guizhou Cave Engineering Center Co., Ltd., Guiyang,Guizhou 550001, China
3.
Guizhou Engineering and Technology Research Center for Karst Cave(Tourism) Resources Development and Utilization, Guiyang, Guizhou 550001, China

摘要

摘要: 旅游活动将导致洞穴环境发生改变，特别是对于洞穴CO₂浓度短时间内变化影响，多时间尺度下两者间的关联性研究较少。为准确探讨旅游活动对洞内CO₂浓度的影响及其响应机制，本文基于织金洞封控期和运营期洞内温度、CO₂浓度和游客量监测数据，利用小波变换进行多时间尺度下时频和时滞性分析。结果表明：织金洞内部环境受旅游活动扰动，洞内平均温度提升0.2~0.9 ℃，但各监测点间变幅存在差异；与封控期相比，运营期旅游高峰时段洞内CO₂浓度明显升高，高峰时段后，3#和4#下降过程较为缓慢，5#至7#呈快速下降特征；织金洞运营期洞内CO₂浓度长周期短于封控期，存在与客流日间差异特征显著关联的短周期变化；节假日期间洞内CO₂浓度与游客量存在显著的正相关性，昼夜尺度上洞内CO₂浓度对旅游活动的响应具有滞后性。研究结果为旅游活动对洞穴内部微环境的扰动程度及其影响过程提供重要的数据支撑，为指导洞穴开发、利用、管理提供科学理论依据。
- 小波变换 /
- 洞穴环境 /
- CO₂浓度 /
- 旅游活动 /
- 响应机制 /
- 织金洞
Abstract: Karst caves are among the most frequented visited geological sites worldwide. However, their stable environments are vulnerable to changes caused by tourist activities, including variations in temperature, CO₂ concentrations, humidity, airflow, microbial communities, and groundwater chemistry. Therefore, it is imperative to investigate the impact of tourist on cave ecosystems and to implement strategies aimed at enhancing the overall environmental quality of these caves. These efforts are crucial for ensuring the sustainable development of tourist caves.As a principal driver of karst processes, CO₂ has garnered considerable attention in the fields of regional carbon cycling, weathering of cave sedimentary landscapes, and the analysis of cave ecological capacity. Prior research primarily focused on the characteristics of CO₂ concentration variations, their sources, and influencing factors within tourist caves. Observations of diurnal and nocturnal fluctuations in CO₂ concentrations clearly indicate that tourist activities exert a significant influence on these variations. However, monitoring of CO₂ concentrations prior to development has not been conducted in most tourist caves, which limits the ability to accurately assess the extent of tourist impact on CO₂ dynamics. The closure of tourist caves during the COVID-19 pandemic has provided a unique opportunity for comparative analyses. Currently, statistical analyses of CO₂ concentrations in tourist caves predominantly rely on line graphs and scatter plots, which illustrate magnitude and variability but fail to accurately capture frequency variations across multiple temporal scales. Moreover, the depth of data exploration remains limited. Additionally, studies exploring the temporal variations of CO₂ concentrations in relation to tourist volume often involve a degree of subjectivity. While, wavelet transform techniques can effectively reveal the periodic temporal-frequency characteristics of time series data across various scales, while precisely depicting the lag between dynamic changes in time series and their influencing factors. This methodological approach effectively addresses the existing gaps in research concerning CO₂ levels in tourist caves. This study utilizes monitoring data on temperature, CO₂ concentrations, and tourist volume from Zhijin Cave during both the lockdown and operation period. By employing wavelet transform for comprehensive time-frequency and lag analysis across multiple temporal scales, this research aims to provide an accurate assessment of the impact of tourist activities on CO₂ concentrations within the cave, ultimately offering a scientific foundation to enhance predictive capabilities regarding CO₂ levels in Zhijin Cave.The results reveal that following disturbances caused by tourist activities, the average temperature within Zhijin Cave increased by 0.23 to 0.86 °C, with notable variations observed among different monitoring sites. Compared to the lockdown period, CO₂ concentrations within the cave exhibited a marked increase during peak tourist hours of the operation period. Subsequently, the decline in CO₂ levels at monitoring points 3 and 4 was relatively gradual, whereas points 5 through 7 demonstrated a rapid decrease. During the operation period, the long-term periodicity of CO₂ concentrations in Zhijin Cave was shorter than that recorded during the lockdown, with significant short-term fluctuations closely associated with variations in daytime visitor flows. During the holiday period (September 30 to October 4), a significant positive correlation was identified between CO₂ concentrations and tourist volume within the cave. The response of CO₂ concentrations to tourist activities displayed a distinct lag effect across both diurnal and nocturnal time scales. Overall, it was found that larger cave volumes were associated with longer lag times for CO₂ concentrations in response to changes in tourist volume. These findings provide valuable insights for analyzing the changes in CO₂ concentrations within tourist caves under relatively natural conditions and offer a scientific foundation for effective cave management. However, it is important to note that this study did not include monitoring of CO₂ concentrations in the overlying soil, which limits the availability of direct data to characterize soil CO₂ variations during the lockdown period. Additionally, the elevated visitor numbers during peak holiday periods influenced the correlation between CO₂ concentrations and visitor counts during non-holiday intervals. Therefore, a comprehensive consideration of data comparisons during non-holiday periods is warranted. Furthermore, the analysis was conducted over a limited timeframe, which restricts its broader applicability. It is suggested that future research should adopt innovative analytical methodologies to investigate the response of CO₂ concentrations in the cave to tourist volume across seasonal and interannual scales.
- wavelet transform /
- cave environment /
- CO₂concentration /
- tourist activities /
- response mechanism /
- Zhijin Cave

HTML

图 1 织金洞地理位置、监测点分布和无人机航拍图

Figure 1. Geographical location of Zhijin Cave, distribution of monitoring points, and aerial photography of UAV

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图 2 运营期间游客量变化特征

Figure 2. Characteristics of tourist volume changes during the operation period

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图 3 织金洞各监测点气温变化（蓝线为2022年封控期，红线为2023年运营期，绿线为均值线）

Figure 3. The temperature changes of each monitoring point in Zhijin Cave (blue line:lockdown period in 2022; red line: operation period in 2023; green line: mean line)

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图 4 织金洞洞内CO₂浓度变化（蓝线2022年封控期，红线2023年运营期）

Figure 4. Changes in CO₂ concentration in Zhijin Cave (blue line: lockdown period in 2022; red line: operation period in 2023)

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图 5 织金洞临时封控和正常运营状况下洞穴CO₂小波系数实部

注：a₁~a₈为2022年临时封控期；b₁~b₈为2023年正常运营期。

Figure 5. Real part of CO₂ wavelet coefficients in Zhijin Cave under temporary lockdown and normal operation conditions

Note: a₁~a₈ represent the temporary lockdown period in 2022; while b₁~b₈ denote the normal operation period in 2023.

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图 6 2023年织金洞各监测站点CO₂浓度与游客量小波相干谱

注：图例表示交叉小波相关性（无量纲），黑弧线为小波影响锥边界，弧线以内表示通过α=0.05的红色噪音标准谱显著性检验，箭头方向反映了洞内CO₂浓度与游客量的相位关系：箭头水平向右，表示两者同步变换；水平向左，表示洞内CO₂浓度滞后游客量1/2周期；箭头垂直向上，表示洞内CO₂浓度滞后游客量1/4周期；向下则提前1/4周期。

Figure 6. Coherence spectrum of CO₂ concentration and tourist volume wavelet in each monitoring point of the Zhijin Cave in 2023

Note: The legend indicates the cross-wavelet coherence (dimensionless). The black arcs represent the boundaries of the wavelet cone of influence. Regions within the arcs denote areas that pass the red noise standard spectral significance test at α=0.05. The arrow directions reflect the phase relationship between cave CO₂ concentration and tourist numbers:right-pointing arrows indicate in-phase synchronization between the two variables；left-pointing arrows signify that cave CO₂ concentration lags behind tourist volume by half a period (1/2 period)；upward-pointing arrows denote cave CO₂ concentration lagging tourist numbers by a quarter period (1/4 period)；and downward-pointing arrows suggest cave CO₂ concentration leads tourist volumns by a quarter period (1/4 period).

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图 7 洞腔体积与相位差的关系

Figure 7. Cave volume and phase difference

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图 8 织金洞游客量呈小波变化特征

Figure 8. Characteristics of wavelet transform of tourist volume in Zhijin Cave (a) wavelet analysis of tourist volume in Zhijin Cave; (b) fluctuation characteristics of wavelet coefficient with the main period a=37h

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表 1 织金洞监测点洞腔主要参数

Table 1. Main cavity indexes of Zhijin Cave

监测站点	景点名称	长度/m	高度		宽度		面积/ m²	体积/ m³	测点海拔/ m	到旅游步道距离/m
监测站点	景点名称	长度/m	最大/m	最小/m	最大/m	最小/m	面积/ m²	体积/ m³	测点海拔/ m	到旅游步道距离/m
1#	迎宾厅	105	26	8	70	20	4700	106218	1267	20
2#	塔林宫	91	29	12	38	5	2900	45895	1264	4
3#	苗岭大厅	281	38	19	85	50	18000	426384	1244	14
4#	苗岭大厅	281	38	19	85	50	18000	426384	1249	6
5#	灵霄殿	180	42	14	95	38	11600	362114	1306	3
6#	银雨宫	190	66	40	115	90	18600	825472	1329	25
7#	掌上明珠	120	58	21	125	39	12500	372191	1339	19
8#	雷子洞	58	14	6	23	6	800	6512	1309	4

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