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红壤裸露坡地次降雨土壤侵蚀规律
引用本文:秦伟,左长清,晏清洪,王昭艳,杜鹏飞,燕楠.红壤裸露坡地次降雨土壤侵蚀规律[J].农业工程学报,2015,31(2):124-132.
作者姓名:秦伟  左长清  晏清洪  王昭艳  杜鹏飞  燕楠
作者单位:1. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室,北京 100048; 中国水利水电科学研究院水利部水土保持生态工程技术研究中心,北京 100048
2. 中国农业大学水利与土木工程学院,北京,100083
3. 中国水利水电科学研究院国际泥沙研究培训中心,北京,100044
基金项目:水利部公益性行业科研专项经费项目(200901047);国家自然科学基金(31200535);江西省水利厅科技项目(KT201404);中国水利水电科学研究院科研专项(泥基本科研1415)
摘    要:揭示红壤裸露坡地次降雨土壤侵蚀规律可为红壤坡地水土流失防治和水土保持效益评价提供科学依据。该文基于典型红壤区裸露坡地试验小区134场次降雨气象、水文观测资料,选取雨量、历时和雨强为特征指标,综合采用快速聚类和判别聚类,划分确定出3种雨型:A雨型(高频次、短历时、小雨量、大雨强),B雨型(中频次、中历时、中雨量、中雨强)和C雨型(低频次、长历时、大雨量、小雨强)。其中,A雨型是造成红壤裸露坡地土壤侵蚀的主要降雨类型。通过Pearson相关分析和Mann-Kendall检验表明,红壤裸露坡地土壤侵蚀主要受雨强和雨量共同影响,雨强的指标中以最大30 min雨强与其关系最为密切,是导致土壤侵蚀变化的直接因素,雨量则通过改变雨强产生一定的间接影响。土壤侵蚀强度随最大30 min雨强增大过程中,在15 mm/h处存在明显转折,最大30 min雨强小于该值前,侵蚀强度呈缓慢增大,大于该值后,侵蚀强度快速增大。土壤侵蚀与雨量整体呈同步增大,但不同雨型的单位雨量侵蚀能力表现为A雨型B雨型C雨型。在排除前期降雨影响的前提下,利用数理统计方法建立了南方红壤裸露坡地次降雨土壤侵蚀强度与雨量和最大30 min雨强的幂函数统计关系,用于3类雨型下的侵蚀预报时整体精度较好,且更适于短历时暴雨。以上研究将为深入揭示红壤坡地土壤侵蚀规律和构建预报模型提供有益参考。

关 键 词:土壤  侵蚀  降雨  红壤区  坡地  次降雨  降雨类型
收稿时间:9/2/2014 12:00:00 AM
修稿时间:1/5/2015 12:00:00 AM

Regularity of individual rainfall soil erosion in bare slope land of red soil
Qin Wei,Zuo Changqing,Yan Qinghong,Wang Zhaoyan,Du Pengfei and Yan Nan.Regularity of individual rainfall soil erosion in bare slope land of red soil[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(2):124-132.
Authors:Qin Wei  Zuo Changqing  Yan Qinghong  Wang Zhaoyan  Du Pengfei and Yan Nan
Institution:1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China; 2. Research Center on Soil and Water Conservation of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100048, China;,1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China; 2. Research Center on Soil and Water Conservation of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100048, China;,3. College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China;,1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China; 2. Research Center on Soil and Water Conservation of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100048, China;,4. International Resesearch and Traning Center on Erosion and Sedimentation, China Institute of Water Resources and Hydropower Research, Beijing 100044, China; and 1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China; 2. Research Center on Soil and Water Conservation of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100048, China;
Abstract:Abstract: It is valuable for soil and water loss control and its benefits evaluation to understand the relationship between rainfall and soil erosion process. In order to make clear what rainfall type accelerates soil erosion on slopes of red soil in south part of China, and to ascertain the response of soil erosion intensity to rainfall characteristic under various rainfall types, data of meteorology and hydrology of 134 individual rainfalls in experimental plots on bare slopes of red soil in north part of Jiangxi Province were collected and analyzed. The amount, duration and intensity of rainfall were selected as the characteristic indices for erosive rainfall. Two methods including quick clustering and discriminant clustering were introduced to classify the rainfall types resulting in soil erosion. Pearson correlation analysis was then used to find the main indices that contributed the most to the slope soil erosion. Further, Mann-Kendall test and the other statistics method were used to determine the relationship between soil erosion intensity and the rainfall characteristic indices under different rainfall types. The results showed that the erosive rainfall in north part of Jiangxi Province could be classified into three types: type A (high frequency, short duration, minor amount of rainfall, and strong rainfall intensity), type B (medium frequency, medium duration, medium amount of rainfall, and medium rainfall intensity) and type C (low frequency, long duration, great amount of rainfall, and low rainfall intensity). Soil erosion on bare slopes of red soil in south part of China was mainly caused by type A. During the process of individual rainfall, soil erosion on bare slopes of red soil was mainly affected by the joint influences of rainfall intensity and amount, the former resulted in erosion change directly through the closest index - maximum 30 min rainfall intensity, the latter had indirectly effects by changing the former. With the increase of maximum 30 min rainfall intensity, soil erosion occurred remarkably different properties at rainfall intensity of 15 mm/h. The soil erosion increased relatively slowly before that critical point but increased rapidly after the point. Generally, soil erosion intensity increased with the amount of rainfall, whereas the erosion ability of different rainfall types varied, which followed the pattern: type A > type B > type C. Excluding the influence of rainfall happened in earlier time, the erosion intensity on bare slopes of red soil had a significant power function relationship with both the maximum 30 min rainfall intensity and the rainfall amount, however, the exponents and coefficients were different when different rainfall types occurred. It has been proven that this model is not only best for intensive rainfall with short duration, but also runs very well while applying to erosion prediction for all three rainfall types - the values of multiple correlation coefficient and the Nash-Suttclife efficiency coefficient were both above 0.9, and the average relative error was less than 25%. In conclusion, this study is very helpful both in exploring further red soil erosion laws and in process-based prediction model establishment.
Keywords:soils  erosion  precipitation  red soil region  slope land  individual rainfall  rainstorm types
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