Remotely Managing Operation, Data Collection and processing in Modern Automated ET Networks

Abstract:

The significant increase in overall data generation and available computing power in the recent years has greatly improved spatial and temporal data coverage of evapotranspiration (ET) measurements on multiple scales, ranging from a single station to continental scale ET networks. With the increased number of ET stations and increased amount of data flowing from each station, modern tools are needed to effectively and efficiently handle the entire infrastructure (hardware, software and data management). These tools can automate key stages of ET network operation, remotely providing real-time ET rates and alerts for the health of the instruments. This can help maximize time dedicated to answering research questions, rather than to station management. This year, the Chinese Ecosystem Research Network (CERN) within the Chinese Academy of Sciences implemented a large-scale 27-station national ET network across China to measure and understand the water cycle from a variety of ecosystems. It includes automated eddy covariance systems, on-site flux computations, wireless communication, and a network server for system, data, and user management. This presentation will discuss the latest information on the CERN network, methods and hardware for ET measurements, tools for automated data collection, data processing and quality control, and data transport and management of the multiple stations. This system description is beneficial for individuals and institutions interested in setting up or modifying present ET networks consisting of single or multiple stations spread over geographic locations ranging from single field site or watershed to national or continental scale.