‘Quantifying the effects of forest canopy cover on net snow accumulation at a continental, mid‐latitude site’

积雪 环境科学 融雪 天蓬 贯通 树冠 地表径流 水文学(农业) 拦截 水流 自然地理学 大气科学 生态学 流域 地理 地质学 土壤科学 土壤水分 气象学 岩土工程 生物 地图学
作者
W. Veatch,P. D. Brooks,J. R. Gustafson,N. P. Molotch
出处
期刊:Ecohydrology [Wiley]
卷期号:2 (2): 115-128 被引量:119
标识
DOI:10.1002/eco.45
摘要

Abstract Although many studies have investigated the effects of forest cover on streamflow and runoff, and several have examined the effects of canopy density on snowpack accumulation, the impacts of forest canopy density on spatial patterns of snowmelt input to catchments remain relatively underquantified. We performed an intensive snow depth and density survey during maximum accumulation in a mid‐latitude montane environment in northern New Mexico, taking 900 snow depth measurements and excavating six snow pits across a continuum of canopy densities. Snow water equivalent (SWE) data are correlated with forest canopy density ( R 2 = 0·21, p < 0·0001), with maximum snow accumulation in forests with density between 25 and 40%. Forest edges are shown to be highly influential on patterns of snow depth, with unforested areas shaded by forest to their immediate south holding approximately 25% deeper snow than either large open areas or densely forested areas. This indicates that the combination of canopy influences on throughfall and snowpack shading are key processes underlying snow distribution in the high solar load environments typical of mountainous, mid‐latitude areas. We further show that statistical models of snow distribution are improved with the addition of remotely sensed forest canopy information ( R 2 increased in 10 of 11 cases, deviance lowered in 9 of 11 cases), making these findings broadly relevant for improving estimation of water resources, predicting the ecohydrological implications of vegetation and climate change, and informing integrated forest and water resources management. Copyright © 2009 John Wiley & Sons, Ltd.
最长约 10秒,即可获得该文献文件

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
时光完成签到,获得积分10
1秒前
刚刚发布了新的文献求助10
2秒前
2秒前
努力努力再努力CMY完成签到,获得积分10
3秒前
我来也完成签到 ,获得积分10
3秒前
大个应助炙心采纳,获得10
5秒前
xichang发布了新的文献求助10
5秒前
科研通AI5应助科研通管家采纳,获得10
6秒前
8R60d8应助科研通管家采纳,获得10
6秒前
食分子发布了新的文献求助10
6秒前
8R60d8应助科研通管家采纳,获得10
6秒前
于骁完成签到,获得积分10
6秒前
桐桐应助科研通管家采纳,获得10
6秒前
8R60d8应助科研通管家采纳,获得10
6秒前
赘婿应助科研通管家采纳,获得30
7秒前
8R60d8应助科研通管家采纳,获得10
7秒前
Ava应助科研通管家采纳,获得10
7秒前
今后应助科研通管家采纳,获得10
7秒前
科研通AI5应助科研通管家采纳,获得10
7秒前
Hello应助科研通管家采纳,获得10
8秒前
李爱国应助科研通管家采纳,获得10
8秒前
8R60d8应助科研通管家采纳,获得10
8秒前
酷波er应助科研通管家采纳,获得10
8秒前
SciGPT应助科研通管家采纳,获得10
8秒前
Jasper应助科研通管家采纳,获得10
8秒前
无花果应助科研通管家采纳,获得10
8秒前
NexusExplorer应助科研通管家采纳,获得10
8秒前
wkjfh应助科研通管家采纳,获得10
8秒前
英俊的铭应助科研通管家采纳,获得10
8秒前
8秒前
9秒前
爆米花应助hh采纳,获得10
9秒前
打打应助爱听歌土豆采纳,获得10
9秒前
打打应助阿帆采纳,获得10
10秒前
LY_Qin应助花花采纳,获得10
10秒前
11秒前
yhx完成签到,获得积分10
11秒前
情怀应助upward采纳,获得10
12秒前
12秒前
liu发布了新的文献求助10
12秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Animal Physiology 2000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Machine Learning Methods in Geoscience 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3740976
求助须知:如何正确求助?哪些是违规求助? 3283817
关于积分的说明 10036983
捐赠科研通 3000610
什么是DOI,文献DOI怎么找? 1646618
邀请新用户注册赠送积分活动 783804
科研通“疑难数据库(出版商)”最低求助积分说明 750427