| 9 | 0 | 13 |
| 下载次数 | 被引频次 | 阅读次数 |
[目的]黄河“几字弯”地区水沙关系不协调,准确模拟不同降雨条件下坡面产流产沙过程,对认识坡面水沙响应机制和支撑水土保持调控具有重要意义。[方法]基于合同沟试验场2023—2024年54组人工模拟降雨试验,设置3种坡度(5°、10°、15°)、3种植被覆盖度〔低(14%~17%)、中(50%~58%)、高(72%~77%)〕和3个雨强(21、50、93 mm/h)组合情景;结合前期土壤含水率与稳定入渗过程,采用贝叶斯方法优化SCS-CN模型参数,并耦合RUSLE模型,模拟坡面水沙过程。[结果]试验揭示植被覆盖度是坡面产流产沙的主导因子,在21mm/h和50 mm/h雨强下贡献率均超过85%,在93mm/h雨强下高于74%;坡度作用随雨强增大而增强,在93mm/h雨强下贡献率升至19.95%。优化后的SCS-CN模型显著提高了径流模拟精度,NSE由0.68提高至0.85,RMSE由3.8mm降至2.1mm;与RUSLE耦合后,能够较好模拟不同条件下的坡面产流产沙过程。[结论]低、中雨强条件下植被覆盖度对坡面减流减沙起主导作用,高雨强条件下坡度对侵蚀动力的促进作用增强。综合考虑前期土壤水分、稳定入渗过程及CN参数优化,提高了SCS-CN模型在研究区坡面尺度上的适用性。
Abstract:[Objective] The water-sediment relationship in the Ω-shaped bend region of the Yellow River is unbalanced. Accurate simulation of slope runoff and sediment yield under different rainfall conditions is important for understanding slope-scale runoff-sediment responses and supporting soil and water conservation. [Methods] Based on 54 artificial rainfall simulation experiments conducted at the Hetonggou test site during 2023–2024, combined scenarios were designed with three slope gradients (5°, 10°, and 15°), three vegetation coverage levels [low (14%~17%), medium (50%~58%), and high (72%~77%)], and three rainfall intensities (21, 50, and 93 mm/h). By incorporating antecedent soil moisture content and the stable infiltration process, the key parameters of the SCS-CN model were optimized using a Bayesian approach, and the optimized model was coupled with RUSLE to simulate slope runoff and sediment processes. [Results] The experiments revealed that vegetation coverage was the dominant factor controlling slope runoff and sediment yield, with contribution rates above 85% at rainfall intensities of 21 and 50 mm/h and above 74% at a rainfall intensity of 93 mm/h. The effect of slope increased with rainfall intensity, reaching 19.95% at a rainfall intensity of 93 mm/h. The optimized SCS-CN model substantially improved runoff simulation accuracy, with NSE increasing from 0.68 to 0.85 and RMSE decreasing from 3.8 mm to 2.1 mm. After coupling with RUSLE, the model performed well in simulating runoff and sediment yield under different conditions. [Conclusion] Vegetation coverage plays a dominant role in reducing runoff and sediment under low and moderate rainfall conditions, whereas slope exerts a stronger effect on erosion dynamics under high-intensity rainfall conditions. Considering antecedent soil moisture content, stable infiltration process, and CN parameter optimization can improve the applicability of the SCS-CN model at the slope scale in the study area.
[1] 孙倩, 于坤霞, 李占斌, 等. 黄河中游多沙粗沙区水沙变化趋势及其主控因素的贡献率[J]. 地理学报, 2018, 73(5): 945-956.
[2]郝天翀, 胡仪喣, 毛雪松, 等. 基于最优路径阈值的新疆复合温湿极端事件识别与公路工程风险分析[J/OL]. 水利水电技术(中英文), 1-17[2026-03-12].
[3] YAN X, NUNES J P, SUN J N, et al. Restored vegetation dominates the decrease in surface and subsurface runoff on the Loess Plateau[J]. Journal of Hydrology, 2024, 640: 131730.
[4] 王晓颖, 宋培兵, 徐红霞, 等. 调水工程水源区与受水区径流丰枯遭遇研究[J]. 水利水电技术(中英文), 2025, 56(2): 125-136.
[5] 廖如婷, 徐宗学, 叶陈雷, 等. 典型LID设施多尺度径流调控效应研究[J]. 水利水电技术(中英文), 2025, 56(3): 61-75.
[6] 薛建春, 尹梓嘉, 丁志斌. 黄河几字弯地区土地利用演变与生态系统健康耦合分析[J]. 水土保持研究, 2026, 33(4): 350-362.
[7] 赵勇, 王浩, 邓铭江, 等. 黄河几字弯水网: 南水北调西线配套东延工程构想[J]. 水利学报, 2023, 54(9): 1015-1024.
[8] 李轲妤, 仇志强, 蒋昕桐, 等. 黄土高原河流悬沙粒径时空变异及驱动因素研究[J]. 地球环境学报, 2026, 17(1): 128-141.
[9] HE Z M, JIA G D, LIU Z Q, et al. Field studies on the influence of rainfall intensity, vegetation cover and slope length on soil moisture infiltration on typical watersheds of the Loess Plateau, China[J]. Hydrological Processes, 2020, 34(25): 4904-4919.
[10] 冯憬, 卫伟, 冯青郁. 黄土丘陵区SCS-CN模型径流曲线数的计算与校正[J]. 生态学报, 2021, 41(10): 4170-4181.
[11] 赵武成, 买小虎, 王琦, 等. 基于SCS-CN模型的黄土高原丘陵区坡地微型集雨垄垄面径流量预测[J]. 生态学杂志, 2022, 41(1): 199-208.
[12] 马勇星, 张栋, 潘成忠, 等. 梯田对黄土区降雨径流过程的影响及SCS-CN模型应用与改进[J]. 农业工程学报, 2022, 38(12): 85-91.
[13] GUO X X, DU M, GAO P, et al. Response of runoff-sediment processes to vegetation restoration patterns under different rainfall regimes on the Loess Plateau[J]. Catena, 2024, 234: 107647.
[14] SHI W H, WANG N. An improved SCS-CN method incorporating slope, soil moisture, and storm duration factors for runoff prediction[J]. Water, 2020, 12(5): 1335.
[15] 王红艳, 张志强, 查同刚, 等. 径流曲线数(SCS-CN)模型估算黄土高原小流域场降雨径流的改进[J]. 北京林业大学学报, 2016, 38(8): 71-79.
[16] 刘鑫雨, 肖玉玲, 邹伟婷, 等. 黄土丘陵沟壑区不同土地利用类型SCS-CN模型研究[J]. 水土保持学报, 2026, 40(2): 166-174.
[17] 曹一鸣, 姬翠翠, 裴向军, 等. 多模型耦合的流域水土流失监测方法研究[J]. 生态学报, 2024, 44(14): 6037-6052.
[18] ZHU H K, CHEN Y B, HUANG Z L. Quantifying the runoff generation mechanisms response to vegetation restoration in the Loess Plateau in China: A novel dual-index identification framework integrated with multinomial logistic regression[J]. Journal of Hydrology, 2026, 664: 134480.
[19] LIAO J, WANG J X, JIAO J Y, et al. RUSLE tends to overestimate soil erosion in revegetated conditions: Evidence from long-term runoff plots monitoring on China’s Loess Plateau[J]. Catena, 2025, 258: 109285.
[20] 黄艳红, 刘广全, 张红武, 等. 黄河流域十大孔兑土壤侵蚀模数变化及其驱动因素分析[J]. 泥沙研究, 2026, 51(1): 38-44.
[21] 池金洺, 刘殿君, 于洋, 等. 黄河流域十大孔兑土地利用变化的土壤侵蚀效应[J]. 泥沙研究, 2023, 48(6): 16-23.
[22] 刘璐, 郭月峰, 姚云峰, 等. 十大孔兑上游土壤侵蚀空间分布及动态变化[J]. 水土保持研究, 2021, 28(4): 34-41.
[23] MCCUEN R H. Approach to confidence interval estimation for curve numbers[J]. Journal of Hydrologic Engineering, 2002, 7(1): 43-48.
[24] Soil Conservation Service. National Engineering Handbook, Section 4: Hydrology[M]. Washington: U.S. Department of Agriculture.
[25] MISHRA S K, JAIN M K, PANDEY R P, et al. Catchment area-based evaluation of the AMC-dependent SCS-CN-based rainfall-runoff models[J]. Hydrological Processes, 2005, 19(14): 2701-2718.
[26] Mishra S K, Singh V P, Singh V P, et al. SCS-CN-based hydrologic simulation package [M].Mathematical Models of small watershed hydrology applications, 2002.
[27] 谷康民, 赵允格, 高丽倩, 等. 黄土高原生物结皮对SCS-CN模型初损率的影响[J]. 应用生态学报, 2021, 32(12): 4186-4194.
[28] BAI R H, WANG X Z, LI J W, et al. The impact of vegetation reconstruction on soil erosion in the Loess plateau[J]. Journal of Environmental Management, 2024, 363: 121382.
[29] 李建明, 丁文峰, 冉文建, 等. 自然降雨特征和作物覆盖对三峡库区紫色土坡耕地产流产沙影响[J]. 农业工程学报, 2025, 41(8): 137-146.
[30] 刘效东, 张卫强, 冯英杰, 等. 森林生态系统水源涵养功能研究进展与展望[J]. 生态学杂志, 2022, 41(4): 784-791.
[31] 朱志卓, 李龙, 张鹏, 等. 水力侵蚀下砒砂岩区植被格局对微地形和侵蚀的影响[J]. 水土保持研究, 2023, 30(3): 10-18.
基本信息:
中图分类号:P481;S157.1
引用信息:
[1]胡泽华,刘晓民,王梓行,等.基于SCS-CN和RUSLE耦合的坡面水沙过程模拟:以合同沟试验场人工降雨为例[J].水利水电技术(中英文)().
基金信息:
“科技兴蒙”行动重点专项项目(2022EEDSKJXM004); 内蒙古自治区教育厅一流学科科研专项项目(YLXKZX-NND-010); 黄河水科学研究联合基金项目(U2443224); 国家自然科学基金面上项目(52579067)
2026-07-22
2026-07-22
2026-07-22