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1.西藏农牧大学, 西藏 林芝 860100
2.四川省升钟水土保持监测站, 四川 南部 637388
Received:05 May 2025,
Revised:2025-08-11,
Published:10 December 2025
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黄卫, 况志宇, 尹惠妍, 等.嘉陵江典型小流域降雨特征对不同土地利用类型产流产沙的影响[J].水土保持通报,2025,45(6):87-97.
Huang Wei, Kuang Zhiyu, Yin Huiyan, et al. Effects of rainfall characteristics on runoff and sediment yield under different land use types in typical small watershed of Jialing River [J]. Bulletin of Soil and Water Conservation,2025,45(6):87-97.
黄卫, 况志宇, 尹惠妍, 等.嘉陵江典型小流域降雨特征对不同土地利用类型产流产沙的影响[J].水土保持通报,2025,45(6):87-97. DOI: 10.13961/j.cnki.stbctb.2025.06.020. CSTR: 32312.14.stbctb.2025.06.020.
Huang Wei, Kuang Zhiyu, Yin Huiyan, et al. Effects of rainfall characteristics on runoff and sediment yield under different land use types in typical small watershed of Jialing River [J]. Bulletin of Soil and Water Conservation,2025,45(6):87-97. DOI: 10.13961/j.cnki.stbctb.2025.06.020. CSTR: 32312.14.stbctb.2025.06.020.
目的
2
研究嘉陵江典型小流域不同降雨特征与不同土地利用类型对坡面产流产沙的影响特征,为该区域水土流失的防治和土壤侵蚀控制提供技术支撑和理论依据。
方法
2
以嘉陵江流域南部县李子口小流域为研究区,基于2019—2023年连续5 a的降雨、径流深、土壤流失量等观测数据,运用
K
-均值聚类法对降雨特征进行分类,分析侵蚀性降雨特征及类型;通过皮尔逊相关性分析降雨特征与产流产沙的线性关联强度,采用多元线性回归分析构建径流深、土壤流失量与降雨特征的预测模型;并利用地理探测器探测各单因子及交互因子对产流产沙的解释力,揭示降雨特征对不同土地利用类型产流产沙的影响规律。
结果
2
①小流域侵蚀性降雨可分为3类:Ⅰ类降雨(小雨量、短历时、低强度)、Ⅱ类降雨(中雨量、长历时、中强度)、Ⅲ类降雨(大雨量、中历时、高强度),与Ⅰ,Ⅱ类降雨相比,Ⅲ类降雨发生的频次较低,但其降雨侵蚀力较强,在同一土地利用类型下,Ⅲ类降雨造成的坡面径流深和土壤流失量均明显较大。 ②不同土地利用类型径流小区产流产沙特征差异明显,径流深和土壤流失量均表现为:裸地
>
坡耕地
>
乔木林地。 ③各降雨特征指标与不同土地利用类型的坡面径流深和土壤流失量均呈正相关关系,其中降雨量、降雨侵蚀力对坡面径流深和土壤流失量影响更为显著。 ④小流域坡面产流产沙单因子解释力最大的是降雨量,其次是最大30 min雨强(
I
30
),经因子交互探测后大多表现为双因子增强和非线性增强。
结论
2
在川东北低山丘陵区,降雨量、
I
30
和降雨侵蚀力是影响坡面产流产沙的最主要因素,坡耕地是造成该区域水土流失的主要原因,而乔木林地通过多重水文调控机制,相较于裸地减流效益可达88%,减沙效益可达99%,故农地退耕还林还草是减少水土流失的有效措施之一。
Objective
2
The effects of rainfall characteristics and land use types on slope runoff and sediment yield in a typical small watershed of the Jialing River were investigated, in order to provide technical support and a theoretical basis for soil and water conservation and erosion control in this region.
Methods
2
The Lizikou small watershed in Nanbu County within the Jialing River Basin was selected as the study area. Based on five consecutive years of observational data from 2019 to 2023, including rainfall, runoff depth, and soil loss,
K
-means clustering method was used to classify rainfall characteristics, enabling analysis of erosive rainfall characteristics and types. Pearson correlation analysis was applied to evaluate the strength of linear correlation between rainfall characteristics and runoff and sediment yield. Multiple linear regression analysis was used to construct predictive models for runoff depth and soil loss based on rainfall characteristics. Additionally, the geodetector method was employed to explore the explanatory power of single factors and their interactions on runoff and sediment yield, so as to reveal the effect ive patterns of rainfall characteristics on runoff and sediment yield under different land use types.
Results
2
① Erosive rainfall in the small watershed was classified into three types: Type I (small rainfall amount, short duration, low intensity), Type Ⅱ (moderate rainfall amount, long duration, moderate intensity), and Type Ⅲ (large rainfall amount, medium duration, high intensity). Compared with Types I and Ⅱ, Type Ⅲ rainfall occurred less frequently but exhibited higher erosi
vity. For the same land use type, Type Ⅲ rainfall resulted in significantly greater slope runoff depth and soil loss. ② Significant differences in runoff and sediment yield were observed among plots with different land use types. Runoff depth and soil loss decreased in the order: bare land
>
slope cropland
>
arbor forest land. ③ All rainfall characteristic indicators were positively correlated with slope runoff depth and soil loss under different land use types. Among them, rainfall amount and rainfall erosivity had more pronounced effects. ④ Within the small watershed, rainfall amount had the greatest single-factor explanatory power for slope runoff and sediment yield, followed by
I
30
(maximum 30-minute rainfall intensity). After interaction-factor detection, most interactions were characterized by double-factor enhancement or nonlinear enhancement.
Conclusion
2
In the low mountainous and hilly regions of northeastern Sichuan, rainfall amount,
I
30
, and rainfall erosivity are the most critical factors influencing slope runoff and sediment yield. Slope cropland is the primary cause of soil erosion in this region, while arbor forest land can reduce runoff by up to 88% and sediment yield by up to 99% compared to bare land through multiple hydrological regulation mechanisms. Therefore, returning cropland to forests and grasslands is an effective measure to reduce soil erosion.
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