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GSA session on Critical Zone and Data Science
admin
2020-07-18
发布年2020
语种英语
国家国际
领域地球科学
正文(英文)
Article Type: 
Start Date: 
Saturday, July 18, 2020 - 10:30

Dear Critical Zone and Data Science Community,

As you prepare abstracts for the upcoming Geological Society of America (GSA) online annual meeting 2020, please consider submitting to Session T225: From Pattern to Process and Back: Data Driven Insights in Critical Zone Sciences. We hope to bring together an interdisciplinary group of scientists, working to understand the process of the critical zone, using a combination of observational data and novel computational tools. The complete session description is copied below.

We hope you can join us online this October. Abstracts are due August 4!

https://community.geosociety.org/gsa2020/home

Best,

Hang Wen and Julia Perdrial

 

Our session:

T225. From Pattern to Process and Back: Data Driven Insights in Critical Zone (CZ) Sciences

The CZ, the zone of life that spans from the top of the tree canopy to the actively cycled groundwater, is studied in highly interdisciplinary and collaborative settings that generate large quantities of data on CZ inputs, composition and exports. Over recent decades, investigations at CZ observatories (CZOs) and long-term-monitoring observatories (LTMOs) have generated increasing variety, volume and velocity of data, facilitated in part by the application of new sensor technologies. These “Big Data” sets on the CZ enable us to identify patterns in CZ dynamics, including coupled and nonlinear hydrologic, geomorphic, and biogeochemical processes, and CZ responses to external forcing, including climate change and anthropogenic stressors. We invite contributions that i) investigate current challenges in environmental and geoscience (e.g. declining water quality, changes to elemental cycling or ecosystem response to disturbances) using a data driven approach, ii) apply novel analysis tools to accommodate data of mixed densities across spatial and temporal scales, and /or iii) combine data driven approaches with process-based, experimental and field observational insights.

 

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来源平台Critical Zone Exploration Network
文献类型新闻
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/283987
专题地球科学
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GB/T 7714
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