Pool and riffle characteristics in relation to channel gradient

频道(广播) 浅滩 水流动力 地质学 水文学(农业) 沉积物 压力梯度 地貌学 溪流 海洋学 岩土工程 计算机网络 计算机科学 电气工程 工程类
作者
Ellen Wohl,Kirk R. Vincent,Dorothy J. Merritts
出处
期刊:Geomorphology [Elsevier BV]
卷期号:6 (2): 99-110 被引量:116
标识
DOI:10.1016/0169-555x(93)90041-y
摘要

The depths of pools relative to the dephts of runs and riffles were correlated with reach-scale channel gradient along three rivers in coastal northern California. The sample included 122 pools formed in channels with gradients from 0.172 to 0.002. Relative pool depth on these rivers, and relative distance between pools, increase as channel gradient decreases. Mean pool:riffle depth is 2.8:1 at the highest channel gradient, and 6.2:1 at the lowest gradient, while mean pool:riffle length is 1:0.8 at high channel gradient, and 1:1.8 at low channel gradient. We hypothesize that these trends reflect changes in energy expenditure with decreasing gradient, as a result of the flow's ability to erode its channel boundaries. Channel reaches with high gradients are characterized by resistant channel boundaries, coarse material, and relatively low discharge and total stream power. Channel reaches with low gradients have less resistant channel boundaries, finger-grained bed material, and higher values of discharge and total stream power. These changes in channel and flow characteristics with decreasing gradient result in flows in high-gradient reaches expending a greater proportion of their energy in overcoming boundary and internal resistance, with less energy available for channel-bed scour and the formation of pools in their relatively resistant channels. In contrast, with less energy available for channel-bed scour the channel bed, creating deeper pools because the channel boundaries are less resistant, and the proportion of flow energy available for sediment entrainment and transport should be greater.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
酷波er应助谨慎的翩跹采纳,获得10
刚刚
陶醉若云发布了新的文献求助10
2秒前
xinmi发布了新的文献求助10
3秒前
4秒前
Hello应助风中亦玉采纳,获得10
5秒前
酷酷的芙蓉完成签到,获得积分10
9秒前
10秒前
祖努尔完成签到 ,获得积分10
10秒前
陶醉若云完成签到,获得积分10
10秒前
Lylin发布了新的文献求助10
10秒前
11秒前
13秒前
13秒前
阿锋完成签到 ,获得积分10
13秒前
15秒前
科研通AI6.2应助whisky采纳,获得10
16秒前
17秒前
小迪真傻发布了新的文献求助10
19秒前
WWW发布了新的文献求助10
21秒前
上官若男应助Emo666采纳,获得10
22秒前
Jeff完成签到,获得积分10
23秒前
谨慎的翩跹完成签到,获得积分10
24秒前
好运莲莲lala完成签到,获得积分10
26秒前
MQueen完成签到,获得积分10
28秒前
28秒前
共享精神应助jtyt采纳,获得10
29秒前
96121发布了新的文献求助10
30秒前
30秒前
自然的剑封完成签到,获得积分10
32秒前
YUEYUEYUE发布了新的文献求助10
33秒前
西西弗斯完成签到,获得积分0
33秒前
西in发布了新的文献求助30
34秒前
36秒前
昨夜書完成签到 ,获得积分10
36秒前
小昌完成签到 ,获得积分10
36秒前
陈坤完成签到,获得积分10
37秒前
在水一方应助小迪真傻采纳,获得10
38秒前
Silence完成签到,获得积分10
38秒前
39秒前
41秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Superabsorbent Polymers: Synthesis, Properties and Applications 500
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6351554
求助须知:如何正确求助?哪些是违规求助? 8166034
关于积分的说明 17185163
捐赠科研通 5407637
什么是DOI,文献DOI怎么找? 2862955
邀请新用户注册赠送积分活动 1840520
关于科研通互助平台的介绍 1689577