Abstract
River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system’s overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB.
Highlights
We have demonstrated that our system developed for Heihe Watershed Allied Telemetry Experimental Research (HiWATER) and its online observational data support platform can provide observational managers and researchers with online data services, including the visualization of two-dimensional, three-dimensional, or multidimensional geoscience data; on-demand data downloading; the automatic generation of observational inspection reports and FTP support; and computing services, such as data-aided analysis, geographic information system (GIS) spatial support, and professional model analysis
The authors of this study developed the integrated observational data control system (IODCS) in the Heihe River Basin (HRB) so that researchers may directly obtain the observational elements collected from a specific area within the required time interval from the system according to their research needs while keeping data acquisition process simple and efficient
The IODCS developed in this paper is a highly standardized, strongly interactive, secure, and reliable instance of CI application
Summary
Most of these systems were constructed for data delivery, storage, and visualization. Unified standards and integrated systems of descriptions, organization, transmissions, interfaces, management, and applications of massive quantities of observational data are missing. This issue has become one of the most significant challenges for managing and sharing big Earth data [15,16,17]. Regarding observational data from the IoT, which are usually termed streaming data and feature high speeds, large volumes, and uncertainties, traditional data reception, management, and visualization are confronted with challenges.
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