Title :
Automated Determination of Snow Water Equivalent by Acoustic Reflectometry
Author :
Kinar, Nicholas J. ; Pomeroy, John W.
Author_Institution :
Centre for Hydrol., Univ. of Saskatchewan, Saskatoon, SK, Canada
Abstract :
Snow water equivalent (SWE) is commonly determined using gravimetric and depth measurement techniques. Previous research has demonstrated the ability to determine SWE from the propagation and reflection of acoustic waves. Despite the advantages of the acoustic technique, it has not been adapted so that SWE can be determined in an automated fashion. This paper presents a new technique for determining SWE by the application of acoustics. A maximum-length sequence was used as the input to the layered snowpack system. Signal processing of the reflected wave and a recursive algorithm was used to model the sound pressure wave as it passed through the snowpack. Embedded systems were designed to implement the signal processing and calculations so that SWE could be quickly determined at a field location. The systems were deployed at sites near Whitehorse, YT, and at sites in the Rocky Mountains of Alberta, Canada. Comparisons were made between SWE estimated by the acoustic technique and SWE determined by gravimetric sampling. These comparisons demonstrated that the acoustic SWE measurement performed with the embedded systems and the new signal processing technique can provide SWE estimates that are of comparable accuracy to SWE calculated from gravimetric samples.
Keywords :
acoustic waves; geophysical signal processing; hydrological techniques; snow; Alberta; Canada; Rocky Mountains; Whitehorse; Yukon; acoustic reflectometry; acoustic waves propagation; acoustic waves reflection; embedded systems; gravimetric-depth measurement techniques; layered snowpack system; maximum-length sequence; recursive algorithm; signal processing; snow water equivalent determination; sound pressure wave; Acoustic devices; acoustic propagation; acoustic signal processing; acoustics; snow;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2009.2019730