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Ecohydrologic process networks: 1. Identification
Benjamin L. Ruddell
,
Praveen Kumar
Prairie Research Institute
Civil and Environmental Engineering
Climate, Meteorology and Atmospheric Sciences
National Center for Supercomputing Applications (NCSA)
Institute for Sustainability, Energy, and Environment
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Engineering
Process Flow
100%
Nodes
100%
Functional Group
100%
Directional
100%
Relative Strength
100%
Sufficient Condition
100%
Directionality
100%
Process System
100%
Nonlinear Behavior
100%
System State
100%
Data Series
100%
Feedback Information
100%
Regional Scale
100%
Growing Season
100%
Entropy Transfer
100%
Keyphrases
Process Networks
100%
Information Flow
66%
Ecohydrology
66%
Drought
33%
Information Feedback
33%
Functional Groups
16%
Statistical Methods
16%
Statistical Significance
16%
Relative Strength
16%
Nonlinear Behavior
16%
Measuring System
16%
Information Theory
16%
Two-state
16%
Dissipative Systems
16%
System State
16%
Coupled Processes
16%
Extreme Drought
16%
Information Networks
16%
Growing Season
16%
Time Series Data
16%
Corn-soybean
16%
Network Technique
16%
System Scaling
16%
Flow Process
16%
Statistical Time
16%
Self-organization Behavior
16%
Transfer Entropy
16%
Feedback Coupling
16%
FLUXNET
16%
Directional Link
16%
System Process
16%
Network Capture
16%
Mathematics
Timescale
100%
Statistical Method
50%
Concludes
50%
Sufficient Condition
50%
Statistical Significance
50%
Time Series Data
50%
System State
50%
Dissipative System
50%
Earth and Planetary Sciences
Timescale
100%
Time Series
50%
Synchronism
50%
Growing Season
50%
Physics
Methods: Statistical
100%
Synchronism
100%