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Modeling and simulation of GPR wave propagation through wet snowpacks: testing the sensitivity of a method for snow water equivalent estimation
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geovetenskap och miljöteknik.
Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
Malå GeoScience AB.
2012 (Engelska)Ingår i: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 74-75, s. 11-20Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Snow water equivalent (SWE) of a snowpack is an important input to the distributed snow hydrological models used for runoff predictions in areas with annual snowpacks. Since the conventional method of manually measuring SWE is very time-consuming, more automated methods are being adopted, such as using ground penetrating radar operated from a snowmobile with SWE estimated from radar wave two-way travel time. However, this method suffers from significant errors when liquid water is present in the snow.In our previous work, a new method for estimating SWE of wet snowpacks from radar wave travel times and amplitudes was proposed, with both these parameters obtained from a common mid-point survey. Here we present a custom ray-based model of radar wave propagation through wet snowpacks and results of MATLAB simulations conducted to investigate the method's sensitivity to measurement errors and snowpack properties. In particular, for a single-layer snowpack up to 2.1 m deep and with liquid water content up to 4.5% (by volume), the simulations indicate that SWE can be estimated with an error of ± 5% or less if (a) the noise (measurement errors) in the resulting amplitude has a standard deviation less than 15% and(b) the noise in two-way travel time has a standard deviation less than 0.075 ns (22.5% and 0.15 ns for a snowpack less than 1.3 m deep).

Ort, förlag, år, upplaga, sidor
2012. Vol. 74-75, s. 11-20
Nationell ämneskategori
Geokemi Inbäddad systemteknik
Forskningsämne
Tillämpad geologi; Inbyggda system
Identifikatorer
URN: urn:nbn:se:ltu:diva-10124DOI: 10.1016/j.coldregions.2012.01.006ISI: 000302507300002Scopus ID: 2-s2.0-84857912531Lokalt ID: 8de777d9-2930-4f95-bced-6d71c18c0d0bOAI: oai:DiVA.org:ltu-10124DiVA, id: diva2:983064
Anmärkning
Validerad; 2012; 20120126 (ysko)Tillgänglig från: 2016-09-29 Skapad: 2016-09-29 Senast uppdaterad: 2018-07-10Bibliografiskt granskad

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Sundström, NilsKruglyak, Andrey

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