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作 者:宋江平[1,2] 李忠武 刘春[1,2] 王丹阳 陈佳[3] 彭浩 肖海兵 郭俊军 SONG Jiangping1,2 , LI Zhongwu1,2,3 , LIU Chun1,2 , WANG Danyang1,2 , CHEN Jia3, PENG Hao1,2 , XIAO Haibing3, GUO Junjun4(1. College of Environmental Science and Engineering, Hunan University, Changsha 410082 ; 2. Key Laboratory of Environmental Biology and Pollution Control ( Hunan University), Ministry of Education, Changsha 410082; 3. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, CAS and MWR, Yangling, Shaanxi 712100; 4. Soil and Water Conservation Monitoring Station of Hunan Province, Changsha 410007)
机构地区:[1]湖南大学环境科学与工程学院,长沙410082 [2]湖南大学环境生物与控制教育部重点实验室,长沙410082 [3]中国科学院水利部水土保持研究所黄土高原土壤侵蚀与旱地农业国家重点实验室,陕西杨凌712100 [4]湖南省水土保持监测总站,长沙410007
出 处:《水土保持学报》2018年第1期32-38,共7页Journal of Soil and Water Conservation
基 金:国家重点研发计划项目(2017YFC0505401);湖南省水利科技项目(湘水科计[2016]194-38)
摘 要:探明径流小区尺度下不同水土流失治理模式的径流泥沙效应,对于大尺度水土流失治理具有重要意义。通过野外标准径流小区自然降雨试验探究了湘北红壤低山丘陵地带3种典型水土流失治理模式(S1模式:坡改梯+经果林,S2模式:等高沟垄+农作物,S3模式:平整撂荒坡面+草本)径流泥沙效应。结果表明:3种治理模式在次降雨诱导下平均径流量为S3(1.84m^3)>S1(1.03m^3)>S2(0.78m^3),平均泥沙流失量为S3(1.191t/hm^2)>S1(0.411t/hm^2)>S2(0.311t/hm^2);3种治理模式在A、B、C雨型诱导下(K-均值聚类)累积径流量均为S3(33.19,15.25,14.13 m^3)>S1(19.40,9.06,6.48 m^3)>S2(16.60,5.89,4.15m^3),累积泥沙流失量也表现出了相同规律,即S3(14.474,10.863,15.153t/hm^2>S1(7.521,2.695,3.766t/hm^2)>S2(6.149,1.685,2.741t/hm^2);不同治理模式泥沙流失对径流响应特征均呈极显著正相关(P<0.01,r>0),相关系数(r)分别为0.853,0.920,0.677,其中,S1、S2和S3模式泥沙流失量与径流量线性回归斜率(k)分别为0.356,0.420,0.493,表明S3模式泥沙流失对径流的响应最明显,S2模式次之,S1模式泥沙流失对径流响应程度较小。因此,3种典型模式在控制水土流失方面具有明显不同的效果。Clarifying the runoff and sediment in runoff plot under different soil and water loss control patterns plays an important role for large-scale soil and water loss. In this study, the runoff and sediment of red soil under three typical soil and water loss control patterns (S1 pattern: Slope change ladder +Fruit trees, S2 pattern: Contour trench and ridge + Crops, S3 pattern: Flat waste land slope +Herbs) were investigated through the field standard runoff areas under natural rainfall experiment in low hilly areas. The results showed that the average runoff volume under three control patterns was S3 (1.84 m3) 〉 S1 (1.03 m3) 〉S2 pattern (0.78 m3), and the average sediment yield was S3 (1. 191 t/hm2)〉S1 (0. 411 t/hm2) 〉S2 pattern (0. 311 t/hm2). The cumulative runoff under the three control patterns was S3 (33.19, 15.25, 14.13 m3) 〉 S1 (19.40, 9. 06, 6. 48 m3) 〉 S2 pattern (16. 60, 5. 89, 4. 15 m3) in the A, B, and C rainfall types (K-means clustering). The cumulative sediment also showed the similar trend that was S3 (14. 474, 10. 863, 15. 153 t/hm2 ) 〉S1 (7. 521, 2. 695, 3. 766 t/hm2) 〉 S2 pattern (6. 149, 1. 685, 2. 741 t/hm2). Different control patterns maintained a significant positive correlation between sediment yield had significant positive correlations with runoff volume under the tree control patterns (P〈0. 01, r 〉 0). The correlation coefficient (r) was 0. 853,0. 920, and 0. 677, respectively. Furthermore, the linear volume was 0. 356, 0. 420 and 0. 493, respectively under degree of sediment to runoff in different control patterns patterns have significantly different effects for controlling regression slope (k) of sediment yield and runoff S1, S2, and S3 patterns, indicating the response was S3 〉 S2 〉 S1 pattern. Thus, three typical soil and water loss.
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