Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

水循环 生物地球化学循环 地球系统科学 环境科学 蒸散量 全球变化 背景(考古学) 持续性 水资源 环境资源管理 地球科学 气候变化 地理 地质学 考古 海洋学 化学 环境化学 生物 生态学
作者
Eric F. Wood,Joshua K. Roundy,Tara J. Troy,Rens van Beek,Marc F. P. Bierkens,Eleanor Blyth,Ad de Roo,Petra Döll,M. B. Ek,J. S. Famiglietti,David Gochis,Nick van de Giesen,Paul R. Houser,Peter R. Jaffé,Stefan Kollet,Bernhard Lehner,Dennis P. Lettenmaier,C. D. Peters‐Lidard,Murugesu Sivapalan,Justin Sheffield,Andrew J. Wade,P. G. Whitehead
出处
期刊:Water Resources Research [Wiley]
卷期号:47 (5) 被引量:769
标识
DOI:10.1029/2010wr010090
摘要

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10 9 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

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
1秒前
1秒前
caocao发布了新的文献求助10
1秒前
hi发布了新的文献求助10
1秒前
wujun完成签到,获得积分10
2秒前
佟语雪完成签到,获得积分10
2秒前
畅快的店员完成签到,获得积分20
2秒前
bluer发布了新的文献求助10
3秒前
科研通AI6.1应助hahahah采纳,获得10
3秒前
4秒前
小柏学长完成签到,获得积分10
4秒前
5秒前
斯文败类应助苦思力采纳,获得10
5秒前
rock发布了新的文献求助10
5秒前
1234发布了新的文献求助10
6秒前
科研通AI6.2应助Eureka采纳,获得10
6秒前
昏睡的小笼包儿完成签到,获得积分20
7秒前
特昂唐完成签到 ,获得积分10
7秒前
帅气的小翟完成签到,获得积分10
7秒前
8秒前
李大能发布了新的文献求助10
8秒前
9秒前
oy发布了新的文献求助10
9秒前
10秒前
10秒前
丘比特应助un采纳,获得10
11秒前
11秒前
zychaos发布了新的文献求助10
11秒前
期待未来完成签到,获得积分10
11秒前
14秒前
14秒前
Jingtaixing完成签到,获得积分10
14秒前
执着大山完成签到,获得积分10
14秒前
科研通AI6.1应助希希采纳,获得10
14秒前
潘越发布了新的文献求助10
14秒前
15秒前
linkman发布了新的文献求助10
15秒前
15秒前
陈梓锋完成签到 ,获得积分10
15秒前
Mars完成签到,获得积分10
15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
Kinesiophobia : a new view of chronic pain behavior 2000
Research for Social Workers 1000
Mastering New Drug Applications: A Step-by-Step Guide (Mastering the FDA Approval Process Book 1) 800
The Social Psychology of Citizenship 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5911931
求助须知:如何正确求助?哪些是违规求助? 6829115
关于积分的说明 15783578
捐赠科研通 5036777
什么是DOI,文献DOI怎么找? 2711421
邀请新用户注册赠送积分活动 1661737
关于科研通互助平台的介绍 1603823