SWEdar – an Automated Low-Power Snow Water Equivalent Sensor

The goal of our Phase I USDA-NIFA research contract was to develop a prototype Snow Water Equivalent (SWE) sensor and companion techniques that provide high-resolution snow property estimates to improve forecasting of water resources for agriculture and public consumption mountain weather avalanches floods and hydropower. Our measurement techniques involved the use of Ultra Wide Band (UWB) radar technology. While radar has been used by snow scientists for research for decades due to the complexity of interpreting the radar signal the cost of the instrumentation and the power required UWB technology is not currently used operationally. The largest barrier is the lack of autonomous algorithms for interpreting the radar signal; radar images are normally interpreted by scientists requiring manual intervention. The goal of this Phase II research contract will be to complete the development of a SWEdar sensor which processes the radar data on-board in real-time without any manual intervention and transmits SWE estimates and other weather observables hourly to water and snow stakeholders. To achieve this Phase II goal our proposed work includes the following: • Improving algorithms to solve the wet snow problem that we observed in late season of our Phase I results. This pertains to the transition between wet and dry snow. We believe that accurate detection of the snow surface and internal layers along with prior knowledge of snow conditions from the dry snow measurements will allow us to transmit accurate SWE estimates in all conditions. The new prototype algorithm uses data from multiple radar systems operating at different frequencies and a new lidar sensor to accurately detect the snow surface after low density snowfall.We have determined optimal frequencies but work remains to optimize and test the algorithm that combines data from all sensors for operational use in a real-time configuration. • Transitioning the hardware design from the prototype phase to a commercially available UWB based radar SWE sensor. This effort will involve combining X1 and X4 radar technology and a low-cost lidar and controlling all sensors from a single low power microprocessor. A satellite modem will be integrated for direct to sensor software upgrades and data retrieval. Temperature pressure and humidity sensors will be added to round out the quality of data collected and expand our market base. • Implementing our unique Remote Sensing as a Service (RSaaS) business model as part of the commercialization and marketing plan for the SWE sensor. We anticipate that by the end of the Phase II effort we will have resolved the wet snow problem we encountered in Phase I by mixing radar frequencies and incorporating lidar depth measurements in the late season. We also anticipate completing the development of the next generation SWE sensor hardware. A unique remote sensing platform is created when you combine this next generation sensing technology with our RsaaS business model.By the end of this Phase II effort a new concept on remotely sensed SWE will be commercially available marketed and sold in several regions worldwide.