Potentiel des donnees AMSR-E et RADARSAT-2 pour le suivi des cycles de gel/dégel du sol dans des zones agricoles au Canada

Soil freezing and thawing processes are of particular importance for agricultural areas. For example, frozen soils can increase the runoff during snowmelt in the spring. Freezing and thawing also have a direct influence on the sowing and harvesting dates, as well as on the crop yield. A better understanding of those phenomena is therefore important, and several researchers focused on this topic in the past. Due to its sensitivity to changes in the state of water, microwave remote sensing is an appropriate tool for that purpose. The main objective of this study is to monitor soil freezing and thawing processes using AMSR-E and RADARSAT-2 polarimetric data acquired over an agricultural area located near Saskatoon (Saskatchewan). With AMSR-E data, the goals are to compare different combinations of frequencies for the spectral gradient's algorithm regarding their capacity for detecting frozen soils, and to analyze the temporal dynamics of the brightness temperature in order to find a new indicator of soil freezing. As for RADARSAT-2 data, several polarimetric parameters and techniques are tested in order to identify soil freezing. For the first part concerning AMSR-E data, a global precision for the discrimination of frozen and thawed soils higher than 90% was obtained with the spectral gradient's algorithm, for the combinations including high (18.7 and 36.5 GHz) and low (6.9 and 10.7 GHz) frequencies as well as for the one using only high frequencies. It is shown that, for the combination based on the 18.7 and 36.5 GHz frequencies, results are improved when a negative threshold is used for the spectral gradient. When high and low AMSR-E frequencies are combined, a null threshold is on the contrary appropriate, which constitutes an operational advantage. A new algorithm for detecting frozen soils, based on a thresholding approach applied to the spectral gradient of polarization difference and the brightness temperature at 36.5 GHz, was also proposed. The performances of the new algorithm to discriminate frozen and thawed soils are very similar to those obtained using the spectral gradient of brightness temperature (global precision around 90% and probability of detecting frozen soils between 70% and 85%). The performances are also slightly higher for the combinations including the lower AMSR-E frequencies. However, annual statistics for the spectral gradient of polarization difference are required to calculate the thresholds. The results obtained with AMSR-E data highlight the relevance of including SMOS L-band brightness temperatures for the calculation of brightness temperature and polarization difference spectral gradients. The qualitative analysis of the results obtained using RADARSAT-2 data shows that surface scattering dominates volume scattering for frozen soils, which can be explained by the rough fields in the study area, as compared to the signal's wavelength (C-band). Nevertheless, several polarimetric parameters indicate a slight increase of the volume scattering in frozen soils, which is theoretically expected. This was observed for the linear and circular depolarization ratios, the amplitude of the HHVV, RLLL and RLRR correlation coefficients, as well as for the pedestal height. Also, the entropy and [alpha overline]-angle of the Cloude-Pottier target decomposition increase slightly in frozen soils ; the same is true for the volume scattering component of the Freeman-Durden and Yamaguchi target decompositions, with an equivalent decrease of the surface scattering component. Despite these interesting observations, a quantitative analysis of the results is necessary in order to evaluate the usefulness of polarimetry regarding the detection of frozen soils. This would allow the validation of the behavior, possibly caused by soil freezing, of the mean value and the standard deviation of the HHVV phase difference and the standard deviation of the RLLL and RLRR phase differences

Mesoscale monitoring of the soil freeze/thaw boundary from orbital microwave radiometry

A technique was developed for mapping the spatial extent of frozen soils from the spectral characteristics of the 10.7 to 37 GHz radiobrightness. Through computational models for the spectral radiobrightness of diurnally heated freesing soils, a distinctive radiobrightness signature was identified for frozen soils, and the signature was cast as a discriminant for unsupervised classification. In addition to large area images, local area spatial averages of radiobrightness were calculated for each radiobrightness channel at 7 meteorologic sites within the test region. Local area averages at the meteorologic sites were used to define the preliminary boundaries in the Freeze Indicator discriminate. Freeze Indicator images based upon Nimbus 7, Scanning Multichannel Microwave Radiometer (SMMR) data effectively map temporal variations in the freeze/thaw pattern for the northern Great Plains at the time scale of days. Diurnal thermal gradients have a small but measurable effect upon the SMMR spectral gradient. Scale-space filtering can be used to improve the spatial resolution of a freeze/thaw classified image

Frost heave in compressible soils

We develop a mathematical model of frost heave in compressible soils based on a morphological instability of the ice–soil interface. The theory accounts for heave and soil consolidation,while avoiding the frozen fringe assumption. Using a Lie-B¨acklund transformation an analytical solution to the governing equations is found. Two solidification regimes occur: a compaction regime in which the soil consolidates to accommodate the ice lenses, and a heave regime during which the soil is fully consolidated and heaves. The rate of heave is found to be independent of the rate of freezing, consistent with field and laboratory observations

Improving the sensitivity of future GW observatories in the 1-10 Hz band: Newtonian and seismic noise

The next generation gravitational wave interferometric detectors will likely be underground detectors to extend the GW detection frequency band to frequencies below the Newtonian noise limit. Newtonian noise originates from the continuous motion of the Earth’s crust driven by human activity, tidal stresses and seismic motion, and from mass density fluctuations in the atmosphere. It is calculated that on Earth’s surface, on a typical day, it will exceed the expected GW signals at frequencies below 10 Hz. The noise will decrease underground by an unknown amount. It is important to investigate and to quantify this expected reduction and its effect on the sensitivity of future detectors, to plan for further improvement strategies. We report about some of these aspects. Analytical models can be used in the simplest scenarios to get a better qualitative and semi-quantitative understanding. As more complete modeling can be done numerically, we will discuss also some results obtained with a finite-element-based modeling tool. The method is verified by comparing its results with the results of analytic calculations for surface detectors. A key point about noise models is their initial parameters and conditions, which require detailed information about seismic motion in a real scenario. We will describe an effort to characterize the seismic activity at the Homestake mine which is currently in progress. This activity is specifically aimed to provide informations and to explore the site as a possible candidate for an underground observatory. Although the only compelling reason to put the interferometer underground is to reduce the Newtonian noise, we expect that the more stable underground environment will have a more general positive impact on the sensitivity.We will end this report with some considerations about seismic and suspension noise

Accumulation of 5-hydroxynorvaline in maize (Zea mays) leaves is induced by insect feeding and abiotic stress.

Plants produce a wide variety of defensive metabolites to protect themselves against herbivores and pathogens. Non-protein amino acids, which are present in many plant species, can have a defensive function through their mis-incorporation during protein synthesis and/or inhibition of biosynthetic pathways in primary metabolism. 5-Hydroxynorvaline was identified in a targeted search for previously unknown non-protein amino acids in the leaves of maize (Zea mays) inbred line B73. Accumulation of this compound increases during herbivory by aphids (Rhopalosiphum maidis, corn leaf aphid) and caterpillars (Spodoptera exigua, beet armyworm), as well as in response to treatment with the plant signalling molecules methyl jasmonate, salicylic acid and abscisic acid. In contrast, ethylene signalling reduced 5-hydroxynorvaline abundance. Drought stress induced 5-hydroxynorvaline accumulation to a higher level than insect feeding or treatment with defence signalling molecules. In field-grown plants, the 5-hydroxynorvaline concentration was highest in above-ground vegetative tissue, but it was also detectable in roots and dry seeds. When 5-hydroxynorvaline was added to aphid artificial diet at concentrations similar to those found in maize leaves and stems, R. maidis reproduction was reduced, indicating that this maize metabolite may have a defensive function. Among 27 tested maize inbred lines there was a greater than 10-fold range in the accumulation of foliar 5-hydroxynorvaline. Genetic mapping populations derived from a subset of these inbred lines were used to map quantitative trait loci for 5-hydroxynorvaline accumulation to maize chromosomes 5 and 7

Microwave emissions from snow

The radiation emitted from dry and wet snowpack in the microwave region (1 to 100 GHz) is discussed and related to ground observations. Results from theoretical model calculations match the brightness temperatures obtained by truck mounted, airborne and spaceborne microwave sensor systems. Snow wetness and internal layer structure complicate the snow parameter retrieval algorithm. Further understanding of electromagnetic interaction with snowpack may eventually provide a technique to probe the internal snow propertie

Soil freezing in northern aapa mires:freeze/thaw -detection using portable L-band radiometer

Abstract. Seasonal soil freezing is one of the most significant sources of uncertainty in methane emissions from high latitude wetlands. Although soil freezing can be remotely sensed with current satellite-based instruments, the resolution is not high enough to detect small-scale variations within individual mires. In this study, a lightweight radiometer mounted on an unmanned aerial vehicle (UAV) was tested for detecting the freeze/thaw (F/T) state of the soil in aapa mires in Finnish Lapland. The three main research questions were the suitability of the radiometer for high resolution F/T detection, the existence of possible spatial patterns in the timing of soil freezing, and the effects of environmental factors on these spatial patterns. As this was the first study to use a UAV-mounted radiometer for F/T detection, there was no established method for retrieving the F/T state of the soil from the measured brightness temperature values. In previous studies using satellite-based instruments, the F/T state of the soil is determined by a threshold method where the measured values are scaled pixel-wise between known reference values of thawed and frozen soils and classified based on a fixed threshold. This method was modified for use with UAV measurements. The performance of the radiometer was evaluated by comparing the measurement results with tower-based radiometer and in-situ measurements in the study area. Spatial patterns in the timing of soil freezing were investigated using analysis of variance and measures of spatial autocorrelation. The effects of environmental factors were investigated using generalized linear models (GLM), generalized additive models (GAM), and hierarchical partitioning with environmental variables derived from readily available remote sensing materials. The F/T state of the soil was successfully determined from the UAV measurements, and the results were comparable to those of other measurements in the study area. Variation in the spatial distribution of the timing of soil freezing was detected at the local scale. The soil appeared to freeze as a result of two separate major freezing events and was therefore modeled as a binary response variable. Both GLM and GAM showed that the most significant factors contributing to the spatial patterns were the Enhanced Vegetation Index (EVI), the flark area and the standard deviation of the Topographic Wetness Index (TWI). Hierarchical partitioning highlighted the individual effects of EVI. All detected relationships were strongly correlated with the microtopographic structure of the mire, suggesting that seasonal freezing progresses differently on different surface types

Optical properties and bioavailability of dissolved organic matter along a flow-path continuum from soil pore waters to the Kolyma River mainstem, East Siberia

The Kolyma River in northeast Siberia is among the six largest Arctic rivers and drains a region underlain by vast deposits of Holocene-aged peat and Pleistocene-aged loess known as yedoma, most of which is currently stored in ice-rich permafrost throughout the region. These peat and yedoma deposits are important sources of dissolved organic matter (DOM) to inland waters that in turn play a significant role in the transport and ultimate remineralization of organic carbon to CO2 and CH4 along the terrestrial flow-path continuum. The turnover and fate of terrigenous DOM during offshore transport largely depends upon the composition and amount of carbon released to inland and coastal waters. Here, we measured the ultraviolet-visible optical properties of chromophoric DOM (CDOM) from a geographically extensive collection of waters spanning soil pore waters, streams, rivers, and the Kolyma River mainstem throughout a  ∼  250 km transect of the northern Kolyma River basin. During the period of study, CDOM absorption coefficients were found to be robust proxies for the concentration of DOM, whereas additional CDOM parameters such as spectral slopes (S) were found to be useful indicators of DOM quality along the flow path. In particular, the spectral slope ratio (SR) of CDOM demonstrated statistically significant differences between all four water types and tracked changes in the concentration of bioavailable DOC, suggesting that this parameter may be suitable for clearly discriminating shifts in organic matter characteristics among water types along the full flow-path continuum across this landscape. However, despite our observations of downstream shifts in DOM composition, we found a relatively constant proportion of DOC that was bioavailable ( ∼  3–6 % of total DOC) regardless of relative water residence time along the flow path. This may be a consequence of two potential scenarios allowing for continual processing of organic material within the system, namely (a) aquatic microorganisms are acclimating to a downstream shift in DOM composition and/or (b) photodegradation is continually generating labile DOM for continued microbial processing of DOM along the flow-path continuum. Without such processes, we would otherwise expect to see a declining fraction of bioavailable DOC downstream with increasing residence time of water in the system. With ongoing and future permafrost degradation, peat and yedoma deposits throughout the northeast Siberian region will become more hydrologically active, providing greater amounts of DOM to fluvial networks and ultimately to the Arctic Ocean. The ability to rapidly and comprehensively monitor shifts in the quantity and quality of DOM across the landscape is therefore critical for understanding potential future feedbacks within the Arctic carbon cycle