scholarly journals Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data

2016 ◽  
Author(s):  
Matthew D. Petkewich ◽  
Ruby C. Daamen ◽  
Edwin A. Roehl ◽  
Paul Conrads
Keyword(s):  
Quality Control ◽  
Water Level ◽  
Depth Estimation ◽  
Network Water ◽  
Level Data ◽  
Water Level Data ◽  
Inferential Sensors

scholarly journals Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

2015 ◽  
Author(s):  
Paul Conrads ◽  
Matthew D. Petkewich ◽  
Andrew M. O'Reilly ◽  
Pamela A. Telis
Keyword(s):  
Water Level ◽  
Depth Estimation ◽  
Level Data ◽  
Water Level Data

Quality Control of Real-Time Water Level Data: The U.S. IOOS® QARTOD Project

2018 ◽  
Vol 52 (2) ◽  
pp. 13-17
Author(s):  
Mark Bushnell
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Sea Level Rise ◽  
Water Level ◽  
Real Time ◽  
Sea Level ◽  
Hampton Roads ◽  
Level Data ◽  
Water Level Data ◽  
The U.S

AbstractWithin the U.S. Integrated Ocean Observing System Program, the Quality Assurance/Quality Control of Real-Time Oceanographic Data (QARTOD) Project develops manuals that describe variable-specific quality control (QC) tests for operational use. The QARTOD's Manual for Real-Time Quality Control of Water Level Data: A Guide to Quality Control and Quality Assurance for Water Level Observations was created with broad support from entities engaged in operational observations of water levels. The process used to generate this manual and all other QARTOD manuals exemplifies the integration of “federal, state, and local government agencies as well as the private and nonprofit sectors” described by the Hampton Roads Sea Level Rise Preparedness and Resilience Intergovernmental Pilot Project.Another project that supports Hampton Roads, Virginia, sea level rise and utilizes multiple partners is the deployment of continuous global positioning system (cGPS) receivers directly on water level sensors. These cGPS installations enable the determination of absolute sea level rise and local land subsidence. Successful transition of cGPS to an operational status requires the application of real-time data QC.

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