Combining Ground‐Penetrating Radar With Terrestrial LiDAR Scanning to Estimate the Spatial Distribution of Liquid Water Content in Seasonal Snowpacks

Estimates of snow water equivalent (SWE) with ground-penetrating radar can be used to calibrate and validate measurements of SWE over large areas conducted from satellites and aircrafts. However, such radar estimates typically suffer from low accuracy in wet snowpacks due to a built-in assumption of dry snow. To remedy the problem, we suggest determining liquid water content from path-dependent attenuation. We present the results of a field evaluation of this method which demonstrate that, in a wet snowpack between 0.9 and 3 m deep and with about 5 vol% of liquid water, liquid water content is underestimated by about 50% (on average). Nevertheless, the method decreases the mean error in SWE estimates to 16% compared to 34% when the presence of liquid water in snow is ignored and 31% when SWE is determined directly from two-way travel time and calibrated for manually measured snow density.

Download Full-text

Correction to “Complex dielectric permittivity measurements from ground-penetrating radar data to estimate snow liquid water content in the pendular regime”

Water Resources Research ◽

10.1029/2009wr008959 ◽

2010 ◽

Vol 46 (2) ◽

Cited By ~ 2

Author(s):

John H. Bradford ◽

Joel T. Harper ◽

Joel Brown

Keyword(s):

Dielectric Permittivity ◽

Water Content ◽

Liquid Water ◽

Ground Penetrating Radar ◽

Liquid Water Content ◽

Radar Data ◽

Complex Dielectric Permittivity ◽

Ground Penetrating ◽

Permittivity Measurements

Download Full-text

Application of Ground-Penetrating Radar and a Combined Penetrometer–Moisture Probe for Evaluating Spatial Distribution of Soil Moisture and Soil Hardness in Coastal and Inland Windbreaks

Geosciences ◽

10.3390/geosciences10060238 ◽

2020 ◽

Vol 10 (6) ◽

pp. 238

Author(s):

Kenta Iwasaki ◽

Makoto Tamura ◽

Hirokazu Sato ◽

Kazuhiko Masaka ◽

Daisuke Oka ◽

...

Keyword(s):

Spatial Distribution ◽

Soil Moisture ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Ground Penetrating Radar ◽

Soil Compaction ◽

Soil Moisture Condition ◽

Soil Hardness ◽

Ground Penetrating

The development of a method to easily investigate the spatial distribution of soil moisture and soil hardness in tree windbreaks is necessary because these windbreaks often decline due to inappropriate soil moisture condition and soil compaction. This research examined the applicability of ground-penetrating radar (GPR) and a combined penetrometer–moisture probe (CPMP) for evaluating the spatial distribution of soil moisture and soil hardness in four windbreaks with different soil characteristics. A GPR-reflecting interface was observed at a less permeable layer in a coastal windbreak and at a depth affected by soil compaction in an inland windbreak with andosol. The spatial distribution of the groundwater table could also be evaluated by examining the attenuation of GPR reflection in a coastal windbreak. In contrast, GPR was not applicable in an inland windbreak with peat because of high soil water content near the soil surface. The CPMP could detect vertical distributions of soil hardness and soil water content regardless of soil type. The CPMP was useful for interpreting GPR profiles, and GPR was useful for interpolating the information about the horizontal distribution of soil moisture and soil hardness between survey points made with the CPMP. Thus, the combination of GPR and a CPMP is ideal for examining the two-dimensional spatial distribution of soil moisture and soil hardness at windbreaks with soils for which both methods are applicable.

Download Full-text

Imaging the structure of cave ice by ground-penetrating radar

The Cryosphere ◽

10.5194/tc-5-329-2011 ◽

2011 ◽

Vol 5 (2) ◽

pp. 329-340 ◽

Cited By ~ 12

Author(s):

H. Hausmann ◽

M. Behm

Keyword(s):

Electromagnetic Wave ◽

Internal Structure ◽

Liquid Water ◽

Ground Penetrating Radar ◽

Wave Speed ◽

Liquid Water Content ◽

Thin Layers ◽

Ice Formation ◽

Alpine Regions ◽

Ground Penetrating

Abstract. Several caves in high elevated alpine regions host up to several meters thick ice. The age of the ice may exceed some hundreds or thousands of years. However, structure, formation and development of the ice are not fully understood and are subject to relatively recent investigation. The application of ground-penetrating radar (GPR) enables to determine thickness, volume, basal and internal structure of the ice and provides as such important constraints for related studies. We present results from four caves located in the Northern Calcareous Alps of Austria. We show that the ice is far from being uniform. The base has variable reflection signatures, which is related to the type and size of underlying debris. The internal structure of the cave ice is characterized by banded reflections. These reflection signatures are interpreted as thin layers of sediments and might help to understand the ice formation by representing isochrones. Overall, the relatively low electromagnetic wave speed suggests that the ice is temperate, and that a liquid water content of about 2% is distributed homogenously in the ice.

Download Full-text

A synthetic study to assess the applicability of full-waveform inversion to infer snow stratigraphy from upward-looking ground-penetrating radar data

Geophysics ◽

10.1190/geo2015-0152.1 ◽

2016 ◽

Vol 81 (1) ◽

pp. WA213-WA223 ◽

Cited By ~ 4

Author(s):

Lino Schmid ◽

Jürg Schweizer ◽

John Bradford ◽

Hansruedi Maurer

Keyword(s):

Water Content ◽

Liquid Water ◽

A Priori ◽

Waveform Inversion ◽

Liquid Water Content ◽

A Priori Information ◽

Full Waveform ◽

Snow Stratigraphy ◽

Priori Information ◽

Ground Penetrating

Snow stratigraphy and liquid water content are key contributing factors to avalanche formation. Upward-looking ground-penetrating radar (upGPR) systems allow nondestructive monitoring of the snowpack, but deriving density and liquid water content profiles is not yet possible based on the direct analysis of the reflection response. We have investigated the feasibility of deducing these quantities using full-waveform inversion (FWI) techniques applied to upGPR data. For that purpose, we have developed a frequency-domain FWI algorithm in which we additionally took advantage of time-domain features such as the arrival times of reflected waves. Our results indicated that FWI applied to upGPR data is generally feasible. More specifically, we could show that in the case of a dry snowpack, it is possible to derive snow densities and layer thicknesses if sufficient a priori information is available. In case of a wet snowpack, in which it also needs to be inverted for the liquid water content, the algorithm might fail, even if sufficient a priori information is available, particularly in the presence of realistic noise. Finally, we have investigated the capability of FWI to resolve thin layers that play a key role in snow stability evaluation. Our simulations indicate that layers with thicknesses well below the GPR wavelengths can be identified, but in the presence of significant liquid water, the thin-layer properties may be prone to inaccuracies. These results are encouraging and motivate applications to field data, but significant issues remain to be resolved, such as the determination of the generally unknown upGPR source function and identifying the optimal number of layers in the inversion models. Furthermore, a relatively high level of prior knowledge is required to let the algorithm converge. However, we feel these are not insurmountable and the new technology has significant potential to improve field data analysis.

Download Full-text