A New Method for Computing the Sediment Delivery Ratio for the Hyper-Concentrated Flow Areas of the Loess Plateau, China

IF 6 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Journal of Environmental Informatics Pub Date : 2021-06-16 DOI:10.3808/jei.202100456
T. H. Li, W. Xie
{"title":"A New Method for Computing the Sediment Delivery Ratio for the Hyper-Concentrated Flow Areas of the Loess Plateau, China","authors":"T. H. Li, W. Xie","doi":"10.3808/jei.202100456","DOIUrl":null,"url":null,"abstract":"The sediment delivery ratio (SDR) is an important index for understanding sediment erosion, transportation and deposition features in a river basin. Based on the commonly accepted definition of SDR and the characteristics of the sediment delivery process in hyper-concentrated flow areas of the Loess Plateau, China, a new model for computing the SDR is proposed. The model is a functional relation of fractional form, in which the denominator is the surface runoff of the basin, and the numerator is the water volume needed for saturated sediment discharge in the controlling hydrological station at the exit of the basin when the saturated sediment load is equal to the measured sediment load. Using the proposed SDR equation, the long-term series of SDRs in the Yanhe River basin, a typical hyper-concentrated flow basin in the Loess Plateau, were calculated from 1952 to 2010. The results show that the long-term annual average SDR in the Yanhe River basin was 0.92, which is consistent with the results of previous studies; this finding confirms the validity and effectiveness of the method. The proposed method only requires gauge data of sediment concentration, sediment delivery rate, sediment delivery volume, and runoff ratio from hydrological stations, which makes it easy to use, and it can be used to easily estimate soil erosion in the basin.","PeriodicalId":54840,"journal":{"name":"Journal of Environmental Informatics","volume":"1 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Informatics","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3808/jei.202100456","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 3

Abstract

The sediment delivery ratio (SDR) is an important index for understanding sediment erosion, transportation and deposition features in a river basin. Based on the commonly accepted definition of SDR and the characteristics of the sediment delivery process in hyper-concentrated flow areas of the Loess Plateau, China, a new model for computing the SDR is proposed. The model is a functional relation of fractional form, in which the denominator is the surface runoff of the basin, and the numerator is the water volume needed for saturated sediment discharge in the controlling hydrological station at the exit of the basin when the saturated sediment load is equal to the measured sediment load. Using the proposed SDR equation, the long-term series of SDRs in the Yanhe River basin, a typical hyper-concentrated flow basin in the Loess Plateau, were calculated from 1952 to 2010. The results show that the long-term annual average SDR in the Yanhe River basin was 0.92, which is consistent with the results of previous studies; this finding confirms the validity and effectiveness of the method. The proposed method only requires gauge data of sediment concentration, sediment delivery rate, sediment delivery volume, and runoff ratio from hydrological stations, which makes it easy to use, and it can be used to easily estimate soil erosion in the basin.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
黄土高原高集流区输沙比计算新方法
输沙比(SDR)是了解流域泥沙侵蚀、输沙和沉积特征的重要指标。根据目前普遍接受的SDR定义,结合黄土高原高集中流区输沙过程的特点,提出了一种新的SDR计算模型。模型为分数形式的函数关系,其中分母为流域地表径流量,分子为流域出口控制水文站饱和输沙量与实测输沙量相等时的输沙量。利用所提出的SDR方程,计算了1952 - 2010年黄土高原典型高浓度流域延河流域的SDR长期序列。结果表明:延河流域长期年平均SDR为0.92,与前人研究结果一致;这一发现证实了该方法的正确性和有效性。该方法只需要水文站的输沙浓度、输沙速率、输沙量、径流比等计量数据,使用方便,可方便地估算流域土壤侵蚀。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Environmental Informatics
Journal of Environmental Informatics ENVIRONMENTAL SCIENCES-
CiteScore
12.40
自引率
2.90%
发文量
7
审稿时长
24 months
期刊介绍: Journal of Environmental Informatics (JEI) is an international, peer-reviewed, and interdisciplinary publication designed to foster research innovation and discovery on basic science and information technology for addressing various environmental problems. The journal aims to motivate and enhance the integration of science and technology to help develop sustainable solutions that are consensus-oriented, risk-informed, scientifically-based and cost-effective. JEI serves researchers, educators and practitioners who are interested in theoretical and/or applied aspects of environmental science, regardless of disciplinary boundaries. The topics addressed by the journal include: - Planning of energy, environmental and ecological management systems - Simulation, optimization and Environmental decision support - Environmental geomatics - GIS, RS and other spatial information technologies - Informatics for environmental chemistry and biochemistry - Environmental applications of functional materials - Environmental phenomena at atomic, molecular and macromolecular scales - Modeling of chemical, biological and environmental processes - Modeling of biotechnological systems for enhanced pollution mitigation - Computer graphics and visualization for environmental decision support - Artificial intelligence and expert systems for environmental applications - Environmental statistics and risk analysis - Climate modeling, downscaling, impact assessment, and adaptation planning - Other areas of environmental systems science and information technology.
期刊最新文献
Modelling Soil δ13C across the Tibetan Plateau Using Deep-Learning Impact of Carbon Emissions and Advance Payment on Optimal Decisions for Perishable Products via Parametric Approach of Interval Prediction of the Breeding and Wintering Ranges of Pomacea canaliculata in China Using Ensemble Models Decentralized Algae Removal Technologies for Lake Diefenbaker Irrigation Canals: A Review Real-Time LNG Buses Emissions Prediction Based on a Temporal Fusion Trans-Formers Model
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1