Data Fusion of Remote Sensing and Real Time Field Data in Support of Enhanced River Basin Operations
A need exists to integrate real-time field and remotely sensed data to estimate streamflow, evapo-transipiration (ET), soil moisture, etc. This research seeks to examine ways to:
* Compile real-time or near real-time field and remotely sensed data from a variety of locations using a wide array of sensors and platforms for input into models for estimating current localized streamflows, evapo-transpiration, evaporation, and soil moisture
* Produce 1-4 day forecasts that accurately predict water demand and optimize water deliveries
* Take advantage of the Bureau of Reclamation Geographic Information System (BORGIS)-Western Water Information Network enterprise GIS infrastructure to make these data discoverable and accessible
* Make use of these resources to improve water scheduling
* Assess the impact of Colorado River salinity projects on surface salt and wetlands.
The goal is to provide a frequently updated, integrated picture of river basins to decisionmakers (snow cover, soil moisture, crop conditions, etc.) to decisionmakers.
Need and Benefit
Currently available remotely sensed data lack the resolution and timeliness to give water users up-to-date basin conditions and make one to four day forecasts. Doppler radar technology is not available in all Provo Area Office basins. Economical and timely means, such as the use of unmanned aerial vehicles, need to be tested so that high quality remotely sensed water resource data can be delivered to water users. This work with go far toward optimizing water deliveries and conserving supply. What is sought is the integration of real-time field and remote sensing data to create a so-called virtual river. This virtual river will be combined with online tools to enhance basin-wide operations. Farmers might also use this capability for water scheduling.
Contact the Principal Investigator for information about these documents.
This information was last updated on February 27, 2015
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