模拟降雨下坡面微地形量化及其与产流产沙的关系

为揭示坡面微地形对土壤侵蚀过程的响应,该文通过人工模拟降雨试验,结合三维激光扫描仪技术,研究了不同雨强连续降雨条件下黄土坡面微地形变化特征及其与产流产沙的响应关系。结果表明所选取的5个常规地形因子(微坡度、地形起伏度、地表切割度、洼地蓄积量、地表粗糙度)对坡面侵蚀的响应表现出相似的趋势,即随着侵蚀的加剧,地形因子数值逐渐增大;场降雨后,地表粗糙度的增幅最小,分别是3%、8%、17%,对侵蚀的响应最弱,洼地蓄积量的增幅最大,分别增大11.82、18.86、83.33倍,对侵蚀的响应最强;同一雨强下随着连续降雨的进行,产流率稳定,1 mm/min雨强下输沙率基本稳定,1.5与2 mm/min下输沙率不断减小;2 mm/min雨强下输沙率和累积输沙量,远大于其他2个雨强处理;地形因子之间有很强的相关性,但能从不同侧面反映地形的信息,而且都与产流率和累积产沙量之间有较好的线性关系。研究可为进一步揭示黄土区坡面土壤侵蚀机理提供参考。

Surface micro topography quantification and its relationship with runoff and sediment under simulated rainfall

Abstract: The micro topography condition reflects surface change and erosion degree, and thus is one of the important factors affecting soil erosion. It is necessary to figure out how the micro topography affects the soil erosion. The objective of this study was to quantify micro topography at loess slope and to demonstrate the relationship between micro topography and soil erosion. In order to achieve the objective, an indoor artificial rainfall experiment was conducted at Key Laboratory of Northwest Water Resources and Environment Ecology of Ministry of Education, Xi'an University of Technology in 2013. Three rain intensity treatments of 1, 1.5, and 2 mm/min. For each treatment, continuous rainfall was carried out for 4 times. During the experiment, runoff volume and sediment yield were measured. 3D point cloud data of the slope before and after rain were collected by Trimber FX 3 D laser scanner. After pretreatment such as denoising, the data were used to calculate index of micro topography. To avoid bias of a single indicator, 5 index were used to quantify micro topography of slope including slope(S), roughness(R), relief amplitude (RA), surface incision (SI), and depression storage (DS). The results showed that the topographic index varied with continuous rainfall. During the continuous rainfall, the slope increased from 5.740° to 8.026°, 8.677°, 9.053°, and 9.153° with rain intensity of 1 mm/min, from 5.506° to 8.317°, 9.300°, 10.908°, and 10.909°with rain intensity of 1.5 mm/min, from 5.857° to 14.306°, 16.546°, 17.196°, and 17.924°with rain intensity of 2 mm/min. After the last rainfall, the SA increased by 3%, 8%, and 17% respectively under rain intensity of 1, 1.5, and 2 mm/min. The DS increased by 11.82, 18.86, and 83.33 times respectively under rain intensity of 1, 1.5, and 2 mm/min. The change of SA was smallest and that of DS was largest among the 5 indexes. Therefore, the response to erosion was smallest for SA but largest for DS; During the four times of rainfall, the runoff rates were 43.509, 45.739, 44.212, 46.702 L/(m2·h) successively with rain intensity of 1 mm/min, 55.226, 60.306, 61.146, 61.399 L/(m2·h) successively with rain intensity of 1.5 mm/min, and 89.134, 106.384, 111.142, 115.869 L/(m2·h) successively with rain intensity of 2 mm/min. The sediment discharge after each of the four rainfall were 0.648, 0.512, 0.615, and 0.688 kg/(m2·h) successively with rain intensity of 1 mm/min, 1.948,1.297,0.946, and 0.576 kg/(m2·h) successively with rain intensity of 1.5 mm/min, 9.491, 7.291, 4.252, and 2.213 kg/(m2·h) successively with rain intensity of 2 mm/min. Runoff rate and sediment discharge with rain intensity 1 mm/min were stable during the continuous rainfall process, and sediment discharge with rain intensity of 1.5 and 2 mm/min decreased until the rainfall continued a certain period of time. After the fourth rain, the accumulative runoff volume were 135.123, 178.558, 307.892 L/m2 respectively with rain intensity of 1, 1.5, and 2 mm/min, and the accumulative sediment discharge were 8.490, 16.502, 73.320 kg/m2 respectively. So the total runoff coefficients are 0.751, 0.659, 0.847 respectively. The sediment discharge and the accumulative sediment discharge with rain intensity of 2 mm/min were far larger than those with other two rainfall intensity. There were high correlations among topographic indicators and parameters of runoff and sediment. Principal components analysis (PCA) revealed one component and the weight of S, R, RA, SI, and DS for the component were 0.997, 0.993, 0.999, 0.999, and 0.987 respectively. It indicated that one component could include all information that the 5 micro topography factors expressed. Even so, these index could describe the topographic information from different aspects. The results can provide valuble information for further studies on the loess area and for clarifying mechanism of slope soil erosion.