BigData Enhancement to the Integrated Environmental Quality Sensing system to capture in situ measurements to dynamically characterize fate and transport of solutes in hydrobiogeochemical systems

There is a lack of cost-effective and easy-to-use tools and services for complex data streams which is characterized by multi-dimensional features including large data volumes, variety, velocity and veracity that are commonly referred to as BigData- BigData creates a scalability challenge for environmental system solutions that use traditional relational databases to perform organization, retrieval, analysis, sharing, and integration with modeling- Model testing and validation require developing linkages to experimental systems and existing databases to establish community benchmarks and develop a holistic understanding of the mechanisms and impacts of processes in subsurface environments- Biological and Environmental Research personnel need tools and services that deal with the extreme complexity and variety of data that is generated from the watershed and terrestrial ecosystem experiments and observations, such that the data can be integrated with modeling to advance the predictive understanding of complex, multi-scale, coupled, and biologically based environmental systems behaviors- In situ measurements of subsurface properties and processes at high spatial and temporal resolutions with near real-time recording for capturing physicochemical parameters are a necessity for BigData solutions-