黄土高原小流域次降雨径流深预报模型
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  • 英文篇名:Rainfall event based runoff prediction model for small watersheds in the Loess Plateau
  • 作者:王浩 ; 张光辉 ; 张永萱 ; 耿韧 ; 栾莉莉
  • 英文作者:Wang Hao;Zhang Ganghui;Zhang Yongxuan;Geng Ren;Luan Lili;School of Geography,Beijing Normal University;State Key Laboratory of Earth Surface Processes And Resource Ecology,Beijing Normal University;
  • 关键词:小流域 ; 次降雨 ; 径流深 ; 预报模型 ; 黄土高原
  • 英文关键词:small watershed;;rainfall event;;runoff depth;;prediction model;;the Loess Plateau
  • 中文刊名:STBC
  • 英文刊名:Science of Soil and Water Conservation
  • 机构:北京师范大学地理学与遥感科学学院;北京师范大学地表过程与资源生态国家重点实验室;
  • 出版日期:2015-10-15
  • 出版单位:中国水土保持科学
  • 年:2015
  • 期:v.13
  • 基金:国家自然科学基金“输沙对坡面侵蚀的影响及其水动力学机理研究”(41271287);国家自然科学基金创新研究群体项目“地表过程模型与模拟”(41321001);国家自然科学基金重点项目“退耕驱动近地表特性变化对侵蚀过程的影响及其动力机制”(41530858)
  • 语种:中文;
  • 页:STBC201505006
  • 页数:6
  • CN:05
  • ISSN:11-4988/S
  • 分类号:35-40
摘要
为了建立结构简单、计算方便的小流域次降雨径流深预报模型,收集黄土高原丘陵沟壑区第Ⅰ、Ⅱ、Ⅲ、Ⅴ副区和高塬沟壑区57个小流域2 424场次降雨径流资料,用1 700场(70%)降雨径流资料分析影响次降雨径流深的流域特征因素和降雨因素,筛选出影响小流域次降雨径流深的主要因子,并基于以上主要因子建立小流域次降雨径流深预报模型,利用剩余的724场(30%)降雨径流数据进行模型验证。结果表明:流域面积、流域狭长度、次降雨量和平均降雨强度是影响黄土高原小流域次降雨径流深的主要因子;基于这4个因子建立黄土高原不同区域小流域次降雨径流深预报模型,模型效率系数>0.542,模型验证的效率系数>0.410。所建模型结构简单、参数易于获取,具有一定的精度和实用性,对于黄土高原不同区域小流域的综合治理规划,特别是水土保持工程措施的设计具有重要意义。
        Situated in northwestern China,the Loess Plateau is covered with loose,fine,uniform,and highly erodible aeolian deposits. The climate varies from semi-arid to sub-humid,with heavy short storms. Because of the erodible soils,steep slopes,heavy storms,low vegetation cover and inappropriate land use,it is one of the most eroded regions in the world. Such serious soil erosion has slowed down socio-economic and environmental development by its direct and indirect influence in this region. Many researchers have realized the seriousness of this issue and started the study of the ways to conserve soil and water,in order to achieve sustainable development of the socio-economic environment by controlling soil erosion and restoring the disturbed ecosystem. They found that rainfall event based runoff in small watersheds was one of the key ways to study soil erosion in the Loess Plateau. However,most of the researchers only focus on subzone Ⅰ. The precipitation and the watershed geometry were divergent at different subzones because of the difference of the climate,soil,shape,and land use. So,it is necessary for the other subzones to develop a rainfall event based runoff prediction model for small watersheds in the Loess Plateau. In this study,we collected precipitation and runoff date from 57 small watersheds andbuilt a database which included 2 424 rainfall events distributed in the subzones Ⅰ,Ⅱ,Ⅲ,Ⅴ and the Plateau subzone,in the Loess Plateau. We simulated the relationship between the runoff depth and the parameters which represent precipitation and watershed geometry,so as to sort out the dominant factors affecting runoff depth in the Loess Plateau. The model was developed based on 1 700( 70%) rainfall events data,and the rest was used for validation. Results showed that the watershed area,the watershed shape,the rainfall amount and the average rainfall intensity were the dominant factors affecting runoff depth in the Loess Plateau. The non-linear regression models were developed based on the four factors for different subzones with the NSE greater than 0. 542. The NSE of validation was greater than 0. 410. The results showed that runoff depth is negatively correlated with the watershed area,but positively correlated with the shape of the watershed,the rainfall amount and the average rainfall intensity. The impacts of the precipitation and the watershed geometry on runoff depth were similar at different subzones,but the strength of the impacts varied at different subzones. The models are accurate for different subzones,have a simple structure,and the parameters were easy to obtain. So,they can be popularized to different regions in the Loess Plateau. Our results are helpful to the comprehensive management of small watershed planning in the Loess Plateau,especially for the design of soil and water conservation measures.
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