Application of radon dynamics in analyzing karst spring flood processes: A case study of the Yaji Experimental Site, Guilin
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摘要: 对岩溶水系统降雨的响应过程进行解析是理解其非均质结构及调蓄机制的重要途径。峰丛洼地含水系统具有以管道为主和裂隙相结合的结构特征，水文过程对降雨响应迅速，容易引发洪水。为深入探究这一复杂系统的洪水形成机制，以桂林丫吉试验场为例，选择三场典型降雨事件进行解析。对泉水的水文、电导率、氢稳定同位素（δ2H）和氡放射性同位素（222Rn）进行高分辨率监测，获取降雨补给激发的岩溶泉洪水过程，分析径流组成并计算事件水比例。结果发现：（1）三场降雨事件中岩溶泉流量峰值滞后降雨峰值5~12 h；（2）电导率在流量峰值后显著下降，而222Rn活度的峰值滞后电导率峰值十余小时，反映了事件水通过不同路径进入系统。电导率的变化归因于坡面地表径流迅速补给，而222Rn滞后是因为其主要通过土壤和表层岩溶带补给，δ2H的波动则表明事件水与其他来源水的复杂补给过程；（3）不同示踪剂对事件水的响应存在差异，这种差异受到降雨强度的影响，并反映了入渗路径的不同所导致的水文响应结果的变化。Abstract:
This study utilized the naturally occurring tracer radon (222Rn) to analyze the hydrological responses of a karst spring system, aiming to elucidate variations in flow composition and recharge pathways within the karst aquifer. Three typical flood events were investigated at the Yaji Experimental Site in Guilin to understand the response mechanisms of this karst aquifer, which exhibits high heterogeneity due to its conduit-fracture system. This heterogeneity leads to rapid responses to rainfall, frequently resulting in flash floods. High-resolution monitoring of spring discharge, electrical conductivity, stable hydrogen isotope (δ2H), and 222Rn activity during these events captured the dynamic response of the system to rainfall-induced recharge, allowing for an assessment of contributions from different water sources to spring discharge. These sensitive hydrological indicators, including 222Rn and other hydrochemical parameters, revealed the complexities of aquifer recharge processes, thereby enriching our understanding of karst system responses to intense precipitation. The response time and tracer variations in the karst spring exhibited significant dependence on rainfall intensity and duration, showing a notable lag effect. Peak spring discharge lagged behind rainfall peaks by 5 to 12 hours, depending on specific rainfall characteristics. A decrease in electrical conductivity after peak discharge suggested a rapid influx of surface runoff; conversely, the peak in ²²²Rn activity was delayed by approximately 10 hours relative to the conductivity peak, indicating multi-pathway recharge into the aquifer. While conductivity primarily reflected the rapid influx of surface runoff, the delayed 222Rn peak indicated slower percolation through the soil and epikarst zone. Variations in hydrogen isotopes further illustrated the mixing between event water and pre-event water, highlighting complex recharge dynamics under varying rainfall conditions. Under the influence of rainfall intensity and recharge pathways, the responses of various tracers to rainfall events showed significant differences. During high-intensity rainfall, rapid surface runoff infiltrated the system, significantly altering spring hydrochemistry. In contrast, recharge from the soil and epikarst zone, characterized by slow infiltration, gradually increased 222Rn activity. End-member analysis, based on tracer concentrations, differentiated pre-event water (stored water prior to rainfall) from newly introduced event water. Modeling indicated that changes in conductivity and 222Rn activity corresponded to rapid surface input and slower subsurface recharge, capturing the effects of diverse recharge sources and pathways. Post-rainfall increases in 222Rn activity suggested prolonged recharge from the soil and epikarst zone, a feature not fully captured by conductivity and δ2H data. The delayed 222Rn response highlighted the sustained recharge from the epikarst zone, thereby enhancing the understanding of recharge timing and pathways in karst systems. 222Rn has been validated as an effective tracer in groundwater recharge processes, providing valuable insights for water resource management in karst regions. By distinguishing the contributions of surface runoff and groundwater flow, this method offers significant implications for flood risk prediction and groundwater recharge management, providing essential support for water resource planning and risk management in karst landscapes. -
Key words:
- karst spring /
- peak-cluster depression /
- flood process /
- radon /
- runoff separation
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图 1 丫吉试验场水文地质图与剖面示意图
（A为丫吉试验场平面水文地质图 B、C分别为B-B’、C-C’剖面示意图）
Figure 1. Hydrogeological map and cross-sectional diagrams of the experimental site
(A represents the hydrogeological map of the field experimental site, while B and C are the cross-sectional diagrams along sections B-B' and C-C', respectively)
图 2 S31泉水全年电导率、水位与降雨的关系
Figure 2. Annual variations in conductivity, water level, and rainfall at Spring S31
图 3 三次洪水过程中S31号泉的水文和水化学变化
Figure 3. Hydrological and geochemical changes at Spring S31 during three flood events
图 4 场雨二和场雨三中S31岩溶泉径流识别结果
Figure 4. Runoff identification results for Spring S31 during rainfall events 2 and 3
图 5 岩溶系统水文过程概念模型图
Figure 5. Conceptual model of the hydrological process in a karst system
表 1 场雨特征统计
Table 1. Statistical summary of rainfall characteristics during the monitoring period
场雨 时间 持续时间
/h降雨量
/mm最大雨强
/mm·h−1流量最大值
/L·s−1一 2022/4/25 4:00 93 73 32 1246 二 2022/5/9 10:00 124 97 19 631 三 2022/6/4 5:00 135 235 45 2185 
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