An Enabling Software Framework For Monitoring and Modeling Hydro Geophysical Processes in The Critical Zone Across Different Spatial And Temporal Scales

Thursday, 27 July 2017: 10:30 AM
Paul Brest West (Munger Conference Center)
Roelof Versteeg1, Baptiste Dafflon2, Emmanuel Leger2, Mike van der Werf3, Marco de Kleine3, Marios Karaoulis3, Haiyan Zhou1, Anastasia Rodzianko1, Doug Val Johnson1 and Haruko M Wainwright2, (1)Subsurface Insights, Hanover, NH, United States, (2)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (3)Deltares, Delft, Netherlands
Effective understanding of the critical zone requires use of diverse multi scale, multi domain data (geophysical, geochemical, hydrological, remote sensing) collected by different groups in multiscale, multi domain models (developed by different domain scientists). Enabling software capabilities have been developed by the science community such as Landlab (modeling), ODM2 (Data storage) and Hydroshare (data and model sharing). Coupled models have been developed between reactive transport models and electrical geophysical codes (e.g. PFLOTRAN/E4D). Ontological tools have been developed for mediation between different models and data sources and different web based front end interfaces have been developed which provide access to all of these capabilities.

One challenge with these tools is that they are not yet fully integrated and – because of their different target audiences – are non trivial to couple for non experts. Consequently, scientists spend large amounts of time implementing one-off solutions for data manipulation. We have developed a modular vertically integrated cloud based software framework which was designed from the ground up for effective site and process monitoring. This software framework (PAF – Predictive Assimilation Framework) is multitenant software and provides automation of data ingestion, processing and visualization of hydrological, geochemical and key geophysical (ERT/DTS) data.

The core organizational element of PAF is a project/user one in which capabilities available to users are controlled by a combination of available data and access permissions. All PAF capabilities (both data and processing, which is mostly done through python workflows) are exposed through APIs, making it easy to quickly add new components. One PAF capability which should be of interest for hydrogeophysical applications is the automation of electrical geophysical ingestion and processing and the ability for co analysis and visualization of the raw and processed data with other data of interest (e.g. soil temperature, soil moisture, precipitation).