喀斯特小流域管道-裂隙流对降雨的非线性响应特征研究

罗梦瑶; 王发; 陈洪松; 张君; 连晋姣

doi:10.11932/karst2026y003

喀斯特小流域管道-裂隙流对降雨的非线性响应特征研究

doi: 10.11932/karst2026y003

罗梦瑶^{1, 2, 3,},
王发^{1, 2, ,},
陈洪松^{1, 2},
张君^{1, 2},
连晋姣^{1, 2}

1.
中国科学院亚热带农业生态研究所, 湖南长沙 410125
2.
中国科学院环江喀斯特生态系统观测研究站, 广西喀斯特生态过程与服务重点实验室, 广西环江 547100
3.
中国科学院大学, 北京 100049

基金项目: 国家自然科学基金项目（U2344201，42207096，42171048）。

详细信息

作者简介:
罗梦瑶（2002－），女，硕士研究生，主要从事生态水文研究。E-mail：lmy_0225@163.com

通讯作者:
王发（1989－），男，博士，助理研究员，主要从事土壤物理和生态水文研究。E-mail：wangfa@isa.ac.cn。

中图分类号: X143
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- 被引次数: 0
出版历程
- 收稿日期: 2025-05-16
- 录用日期: 2026-01-21
- 修回日期: 2026-01-20
- 网络出版日期: 2026-06-23

Study on the nonlinear response characteristics of conduit-fracture flow to rainfall in a karst small watershed

LUO Mengyao^{1, 2, 3
,},
WANG Fa^{1, 2
, ,},
CHEN Hongsong^{1, 2},
ZHANG Jun^{1, 2},
LIAN Jinjiao^{1, 2}

1.
Institute of Subtropical Agriculture , Chinese Academy of Sciences, Changsha, Hunan 410125, China
2.
Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Guangxi Key laboratory of Karst Ecological Processes and Services, Huanjiang, Guangxi 547100, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China

摘要

摘要: 全球气候变化背景下，西南喀斯特区洪涝灾害频繁。由于二元结构发育，管道-裂隙在降雨过程中发挥快速导水作用，是径流对降雨响应的重要驱动因子，尤其是洪水过程。但受限于地下结构不可见和复杂性，管道-裂隙流对径流的贡献及其作用机制仍缺乏定量解析。本研究以典型白云岩峰丛洼地小流域为对象，通过流域出口溪流水高频电导率监测，结合电导率频率分布法识别管道流与裂隙流组分，采用增强回归树与分段回归模型揭示其日尺度贡献特征及阈值响应机制。结果表明:（1）管道流与裂隙流年均贡献率分别为4.1%和6.6%，但日最大贡献可达39.2%和61.8%，其中日降雨量为主导控制因子；（2）管道-裂隙流对降雨呈现"S型"非线性响应，具有双重阈值特征：初始响应阈值相近（12mm和11mm），饱和阈值分别为49mm和32.5mm；（3）超过饱和阈值后，受管道-裂隙空间结构限制，贡献率趋于稳定，表明含水层进入相对饱和状态。该研究量化了喀斯特含水层管道-裂隙流对降雨响应的双阈值特征，为喀斯特地区水文过程的认识及径流预测提供了科学依据。
- 喀斯特小流域 /
- 管道-裂隙流 /
- 阈值效应 /
- 电导率动态变化
Abstract: The intensification of global climate change has led to a widespread increase in both the frequency and magnitude of extreme precipitation events. This trend poses a serious threat to the karst regions of southwestern China, which are characterized by ecological fragility and hydrological complexity. Karst aquifers are highly developed with conduit and fracture networks that act as preferential flow paths during rainfall events. These pathways allow groundwater and surface water to rapidly converge into streams, substantially shortening runoff response times and amplifying flood peaks. As a result, the increasing occurrence of flood hazards has greatly complicated local water resources management and disaster mitigation efforts. However, the quantitative contributions of conduit flow and fracture flow to total runoff, as well as their activation mechanisms, remain poorly understood. This knowledge gap primarily arises from the concealed and highly heterogeneous nature of subsurface karst structures, which are difficult to characterize using conventional hydrological monitoring techniques. Consequently, existing hydrological models often underestimate peak discharges during extreme events in karst catchments.To address these challenges, we deployed a high-frequency electrical conductivity (EC) monitoring system with a 5-minute sampling interval at the outlet of a typical dolomite peak-cluster depression catchment in Huanjiang County, Guangxi Zhuang Autonomous Region, China. Such high temporal resolution is essential for tracking rapid hydrochemical dynamics during intense rainfall events. We applied a conductivity frequency distributions (CFDs) approach to decompose streamflow into different runoff components. This method is based on the principle that water flowing along different pathways-conduits, fractures, and matrix pores-exhibits distinct EC signatures due to differences in transport pathways and residence times. CFDs histograms were fitted using a mixture of multivariate normal distributions and decomposed into conduit flow (low EC, rapid transport), fracture flow (intermediate EC), and matrix flow (high EC, slow percolation). The proportional contributions of each component were then quantified. In addition, a boosted regression tree (BRT) model was used to assess the relative importance of 56 potential controlling factors and to identify the dominant rainfall characteristics regulating conduit and fracture flow contributions. Piecewise regression analysis (PRA) was further employed to construct nonlinear relationships between key rainfall variables and the contributions of conduit and fracture flow, allowing the identification of critical thresholds for flow activation and maximum runoff capacity.The results show that although conduit flow and fracture flow contribute only 4.1% and 6.6% to annual runoff, respectively, their importance increases dramatically during individual storm events. During extreme rainfall, the daily peak contribution of conduit flow reached up to 39.2%, while fracture flow peaked at 61.8%. The BRT model identified daily rainfall amount as the primary controlling factor, with relative importance exceeding 76% for both flow components. In contrast, antecedent soil moisture and other variables played a minor role, each contributing less than 10%. These findings confirm the strongly event-driven nature of rapid runoff generation in this karst system, characterized by short response times and weak hydrological memory. Single rainfall events act as the dominant trigger, with limited dependence on antecedent wetness. The PRA results revealed a clear sigmoidal (“S-shaped”) response of conduit and fracture flow contributions to increasing daily rainfall. Two distinct rainfall thresholds were identified for each flow component. The initial activation thresholds were 11 mm for fracture flow and 12 mm for conduit flow. The saturation thresholds were 32.5 mm and 49 mm, respectively. Below the activation threshold, the contributions of conduit and fracture flow to streamflow were negligible. Beyond the saturation threshold, their contributions stabilized and no longer increased with rainfall. This plateau indicates that the transport capacities of the subsurface networks had reached their maximum, constrained by physical structure and hydraulic conductivity. The higher saturation threshold of conduit flow suggests a greater storage and transmission capacity compared to fracture networks. Once saturation is reached, additional runoff must be generated through alternative mechanisms, such as matrix flow or surface runoff, reflecting a combined infiltration-excess and saturation-excess runoff generation process in karst systems.By integrating high-resolution EC monitoring with statistical modeling, this study quantitatively elucidates the threshold behavior of rapid flow in karst aquifers. It overcomes the limitations of traditional tracer experiments and recession curve analyses, which often fail to capture transient hydrological responses in highly heterogeneous environments. The identification of dual rainfall thresholds provides a robust scientific basis for improving the parameterization of rapid flow components in both conceptual and numerical hydrological models. Incorporating such threshold mechanisms and structural constraints is essential for enhancing flood forecasting and peak discharge prediction in karst regions.In summary, studies of karst hydrological processes must move beyond linear and continuous representations of rainfall−runoff relationships. This study quantitatively demonstrates the nonlinear dynamics and dual-threshold responses of conduit and fracture flow to rainfall, thereby advancing the mechanistic understanding of preferential flow in the karst critical zone. Future research should focus on testing the applicability of these thresholds across different lithologies, spatial scales, and climatic conditions. Such efforts will provide crucial support for sustainable water resources planning and flood risk management in karst regions.
- karst small watershed /
- conduit-fracture flow /
- threshold effect /
- dynamic variation of electrical conductivity

HTML

图 1 研究区及周边水文地质条件（蓝色虚线圈内为试验区）

Figure 1. Hydrogeological conditions of the study area (outlined by the blue dashed line)

下载: 全尺寸图片幻灯片

图 2 电导率频率分布（CFDs）分析方法的概念原理图 a：日尺度径流电导率动态变化特征；b：电导率频率直方图及成分划分

Figure 2. Conceptual schematic diagram of the Conductivity Frequency Distribution (CFDs) analysis method a: daily-scale dynamic variation characteristics of runoff conductivity ; b: conductivity frequency histogram and component classificaition

下载: 全尺寸图片幻灯片

图 3 监测期内溪流水电导率动态变化特征

Figure 3. Dynamic variation characteristics of stream flow conductivity during the monitoring period

下载: 全尺寸图片幻灯片

图 4 管道流和裂隙流对小流域径流的贡献比例

Figure 4. Contribution ratio of conduit flow and fracture flow to stream flow in small watershed

下载: 全尺寸图片幻灯片

图 6 管道流和裂隙流降雨阈值效应

Figure 6. Rainfall threshold behaviors of conduit flow and fracture flow

下载: 全尺寸图片幻灯片

图 5 管道流和裂隙流影响因素重要性

Figure 5. Relative importance of influencing factors on conduit flow and fracture flow

下载: 全尺寸图片幻灯片

表 1 建模所选变量

Table 1. Variables selected for modelling

变量	单位	描述
前n天降雨量	mm	第1天至第27天的前期总降雨量
偏度	−	27天内日降雨量的空间分布
连续干燥日	天	年最大连续降雨＜1 mm的天数
连续湿润日	天	年最大连续降雨≥1 mm的天数
强降雨天数和强降雨量	天/mm	降雨≥50 mm的天数和总降雨量
暴雨天数和暴雨量	天/mm	降雨≥25 mm的天数和总降雨量
坡面地表径流的降雨阈值	天/mm	发生坡面地表径流的降雨（>44.7 mm）天数和降雨量
坡面地下径流的降雨阈值	天/mm	发生坡面地下径流的降雨（>39.5 mm）天数和降雨量
流域尺度的降雨阈值	天/mm	发生流域地表径流的降雨（>13 mm）天数和降雨量
1-5天内的最大降雨量	mm	最大连续1 - 5天降雨量
降雨变异系数	−	n天降雨的变异系数
平均降雨量	mm	27天内湿润日（降雨>1 mm）的平均降雨量
降雨频率	−	27天内降雨日（降雨>1 mm）与27天的比值
潜在蒸散发	mm	−
平均气温	℃	日平均气温
最高气温	℃	日最高气温
增强型植被指数	−	表征植被生长状况，越大表明越茂盛

下载: 导出CSV

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