I-Corps: A low cost GPS snow sensor

University Of Colorado At Boulder, Boulder CO

Investigators

Abstract

Snow is an important component of both regional and global climate systems, as well as a critical storage component in the hydrologic cycle. Of particular interest is the snow water equivalent (SWE) which considers both depth and density. However, the methods and sensors currently available to measure SWE, or even just snow depth, are either restricted to a single point or expensive (e.g., aircraft based methods.) An emerging option for remotely determining snow depth is the utilization of existing networks of GPS base stations, as is currently being investigated by CU professors Kristine M. Larson (PI), Eric E. Small (co-PI), Mark W. Williams and Dennis M. Akos under NSF grants. Multipath, the reflection of signals off the ground and other nearby surfaces, is here used to estimate the snow depth over a comparably large area. However, this method has two drawbacks. A survey-grade basestation including receivers and antennas is expensive, around $20k, and since geodesy-type antennas are designed to mitigate low elevation signals the resulting quality of the estimates suffers compared to what could be offered by a custom solution. To overcome this, this project proposes the development and marketing of a snow sensor based on a mass-market GPS receiver coupled with a custom antenna, that potentially can be produced at low cost in reasonable quantities. The sensor also has the potential to be used to estimate soil moisture content and vegetation growth. At present, available snow depth information is temporally and/or spatially limited, the knowledge about the current state of the snow water equivalent potentially available for runoff is similarly limited. Thus, a widely-deployed network of affordable and accurate wide area snow sensors will increase the knowledge and understanding of the hydrologic cycle and potentially improve both climate and weather models. Furthermore, it may also prove valuable for water management facilities where snow levels are an important source of information when predicting droughts. Also, farmers and the tourism industry are also likely to benefit from the information this sensor can provide. It is possible that soil moisture and vegetation growth can also be measured with the snow sensor, however additional research effort will be required to assess the full capabilities. The prototypes and production units will "call home" with the raw data rather than provide measurements directly. The users can then access processed estimates online. This has several benefits; it offers a convenient method of accessing data, it allows for refinement of the algorithms as more data and insight becomes available and it is also possible, at the users' discretion, to make the data available to the scientific community.