Riverside, the Tennessee Valley Authority (TVA), and Center for Advanced Decision Support for Water and Environmental Systems (CADSWES) recently teamed up for a three-day RiverWare training session at Riverside’s corporate headquarters in Fort Collins, CO. The session was led by Water Resources Engineer David Neumann of the CADSWES team from the University of Colorado in Boulder. This training provided a base knowledge in RiverWare, including building object-oriented models, developing simulation rules, and analyzing simulation results, which are essential for modelling the hydrologic response of a river system. Riverside will apply this knowledge in a variety of ways, such as developing short-term operational plans and seasonal forecast operations for systems that include reservoirs, diversions, and reaches. TVA is an active user of RiverWare, and this training furthered our important working relationship with TVA.
Riverside and our partners at GDIT were the major developers of a new public website and database for data records of Deep-Sea Corals and Sponges, launched by the National Oceanic and Atmospheric Administration (NOAA): https://deepseacoraldata.noaa.gov/.
The public site is built on the National Database for Deep-Sea Corals and Sponges maintained by NOAA’s Deep Sea Coral Research and Technology Program and is hosted at our National Centers for Environmental Information (NCEI) labs in Stennis, Mississippi. Learn more details here: http://ow.ly/Tslg0
By Jason Polly, GIS Group Leader
Riverside recently completed a project supporting the State of Nebraska by collecting statewide agriculture field data, which will be used for updating 2015 statewide land cover classifications. Land cover datasets are used in various disciplines including: conducting hydrologic studies, change modeling, and irrigation consumptive use assessments. These developed land cover products allow the state to make better decisions related to water use by understanding how and where resources are being used.
To start, Riverside employees integrated seasonal satellite imagery into a real-time GPS-tracking, GIS-based field collection system. By utilizing 2015 multi-temporal satellite signatures, we were able to review ground truth data directly from both seasonal perspectives and field-based observations. We gathered information related to crop types, irrigation, and till status using the collection tools and stored the information in a project database.
Field data collection workflow using laptop data collection tool
Our fearless collection team traversed the state and only stopped for the occasional free center-pivot car wash and frequent turkey crossings while honing our detective-like field skills in identification and subsequent mapping. We sampled more than 11,000 fields covering numerous collection criteria requirements and subsequent types.
Next steps will use the collected data in classifying individual planted crop types for all fields within the state boundary. For reference, more than 19 million estimated acres were recorded planted within the state in 2014 (USDA, 2014 Crop Production Summary) and less than half (47%) is corn.
Field-collected photos of sample locations for dryland sorghum (top), irrigated soybeans (bottom-left), and dryland corn (bottom-right)