The EGU General Assembly最新文献

The Fukushima nuclear accident released large quantities of radionuclides into the environment in March 2011 and generated a 3000-km² plume of soils heavily contaminated with Cs-137. Soil erosion in the region mainly takes place during typhoons generally occurring between July and October (Laceby et al., 2016). During these events, rivers draining the main plume may transport large quantities of sediment and radiocesium. Typhoon Hagibis that occurred in October 2019 was the most intense rainfall event affecting the Fukushima region (rainfall range: 77–558 mm) since the nuclear accident in 2011. It led to extensive landsliding and river overflow.

The impact of this event on sediment sources and Cs-137 contamination was quantified through the implementation of sediment fingerprinting using geochemistry and spectrocolorimetry as potential input properties. The signature of potential source material (including cropland prepared for recultivation after decontamination, forests and subsurface material originating from landslides and channel bank collapse; n=57) was compared with that of sediment deposits collected in the Mano and Niida River catchments late in October 2019. Results show that cropland supplied the main source of sediment (average: 54%) along with forests (41%). In contrast, the contribution of subsurface material (5%) was much lower, likely because landslides and channel bank erosion mainly took place after the flood peak (Evrard et al., 2020). However, this material that deposited at the foot of hillslopes after the typhoon may be mobilized and delivered to the river network by subsequent rainfall events.

Overall, this flood did not modify the decreasing trend observed in terms of Cs-137 contamination in sediment transiting these rivers between 2011 and 2019. Concentrations in Cs-137 observed in sediment collected in 2019 were on average 84–93% lower than those measured after the accident in 2011. These results demonstrate the effectiveness of decontamination conducted on agricultural and residential soils in the region (Evrard et al., 2019), although the role of forests – that have not been remediated – as a perennial source of sediment and radiocesium in the region remains to be investigated over the longer term.

References

Evrard, O., Durand, R., Nakao, A., Patrick Laceby, J., Lefèvre, I., Wakiyama, Y., Hayashi, S., Asanuma-Brice, C. and Cerdan, O., 2020. Impact of the 2019 typhoons on sediment source contributions and radiocesium concentrations in rivers draining the Fukushima radioactive plume, Japan. Comptes Rendus Géoscience, 352(3): 199-211.

Evrard, O., Laceby, J.P. and Nakao, A., 2019. Effectiveness of landscape decontamination following the Fukushima nuclear accident: a review. SOIL, 5(2): 333-350.

Laceby, J.P., Chartin, C., Evrard, O., Onda, Y., Garcia-Sanchez, L. and Cerdan, O., 2016. Rainfall erosivity in catchments contaminated with fa

Fractures can provide principal fluid flow pathways in the Earth’s crust, making them a critical feature influencing subsurface geoenergy applications, such as the storage of anthropogenic waste, emissions or energy. In such scenarios, fluid-conductive fault and fracture networks are synonymous with two-phase flow, due to the injection of an additional fluid (e.g. CO₂) into an already saturated (e.g. brine) system. Predicting and modelling the resulting (partly-)immiscible fluid-fluid interactions, and the nature of fluid flow, on the field-scale, requires an understanding of the constitutive relationships (e.g. relative permeability and capillary pressure) governing fluid flow on the single-fracture scale. In addition to capillary and viscous forces, fracture relative permeability is influenced by aperture heterogeneity, arising from surface roughness. The degree to which surface roughness controls relative permeability behaviour in fractures remains unclear. As all fractures display roughness to various degrees, furthering our understanding of two-phase flow in fractures benefits from a systematic investigation into the impact of roughness on flow properties. To this end, we performed co-injection experiments on two 3D-printed (polymeric resin) fractures with different controlled and quantified surface roughness distributions (Joint Roughness Coefficients of 5 & 7). Brine and decane were simultaneously injected at a series of incrementally decreasing brine fractional flow rates (1, 0.75, 0.5, 0.25, and 0), at low total volumetric flow rates (0.015 mL/min). Steady-state fluid occupancy patterns, preferential flow pathways and overall fluid saturations in each fracture were imaged and compared using an environmental laboratory-based μ-CT scanner with a 5.8 μm voxel size (EMCT; Ghent University Centre for X-ray Computed Tomography). Experimental results highlight the importance of roughness on the relative permeability behaviour of fractures, which is, for example, a principal control on leakage rates from geological stores.

To solve many geological and geophysical problems, it is very important to study variations of the Earth's magnetic field. The observed variations are usually obtained from data from observatories or temporary variation stations. However, while performing various regional magnetic prospecting works, the network of observatories is not complete enough to account for the variation field correctly.

In this regard, it is becoming necessary to interpolate the data on variations from the points of irregular network. At the same time, obtaining the optimal algorithm is an ambiguous task, its solution requires taking a whole list of factors into account that determine regularity of distribution of physical parameters over the area.

This project represents an interpolation algorithm using method of complex weighting coefficients. The technique was tested on data from the Intermagnet observatories for central Europe, and the obtained accuracy was ± 2 nT. Comparative analysis with known interpolation methods by interpolation methods was carried out.

The Alaskan region (comprising glaciers in Alaska, British Columbia and Yukon) contains the third largest ice volume outside of the Greenland and Antarctic ice sheets, and contributes more to global sea level rise than any other glacierised region defined by the Randolph Glacier Inventory. However, ice loss in this area is not linear, but in part controlled by glacier hypsometry as valley and outlet glaciers are at risk of becoming detached from their accumulation areas during thinning. Plateau icefields, such as Juneau Icefield in Alaska, are very sensitive to changes in Equilibrium Line Altitude (ELA) as this can result in rapidly shrinking accumulation areas. Here, we present detailed geomorphological mapping around Juneau Icefield and use this data to reconstruct the icefield during the “Little Ice Age”. We use topographic maps, archival aerial photographs, high-resolution satellite imagery and digital elevation models to map glacier lake and glacier area and volume change from the Little Ice Age to the present day (1770, 1948, 1979, 1990, 2005, 2015 and 2019 AD). Structural glaciological mapping (1979 and 2019) highlights structural and topographic controls on non-linear glacier recession.  Our data shows pronounced glacier thinning and recession in response to widespread detachment of outlet glaciers from their plateau accumulation areas. Glacier detachments became common after 2005, and occurred with increasing frequency since then. Total summed rates of area change increased eightfold from 1770-1948 (-6.14 km² a^-1) to 2015-2019 (-45.23 km² a^-1). Total rates of recession were consistent from 1770 to 1990 AD, and grew increasingly rapid after 2005, in line with regional warming.

The Arctic winter of 2019-2020 was characterized by an unusually persistent polar vortex and temperatures in the lower stratosphere that were consistently below the threshold for the formation of polar stratospheric clouds (PSCs). These conditions led to ozone loss that is comparable to the Antarctic ozone hole. Ground-based measurements from a suite of instruments at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Canada (80.05°N, 86.42°W) were used to investigate chemical ozone depletion. The vortex was located above Eureka longer than in any previous year in the 20-year dataset and lidar measurements provided evidence of polar stratospheric clouds (PSCs) above Eureka. Additionally, UV-visible zenith-sky Differential Optical Absorption Spectroscopy (DOAS) measurements showed record ozone loss in the 20-year dataset, evidence of denitrification along with the slowest increase of NO₂ during spring, as well as enhanced reactive halogen species (OClO and BrO). Complementary measurements of HCl and ClONO₂ (chlorine reservoir species) from a Fourier transform infrared (FTIR) spectrometer showed unusually low columns that were comparable to 2011, the previous year with significant chemical ozone depletion. Record low values of HNO₃ in the FTIR dataset are in accordance with the evidence of PSCs and a denitrified atmosphere. Estimates of chemical ozone loss were derived using passive ozone from the SLIMCAT offline chemical transport model to account for dynamical contributions to the stratospheric ozone budget.

Low-flow forecasting can help to improve water management at places where a number of uses can be affected by diminishing water supply from rivers. Several French institutes (INRAE, BRGM, EDF, Lorraine University and Météo-France) have been collaborating to set up an operational platform, called PREMHYCE, for low-flow forecasting at the national scale, in cooperation with operational services. PREMHYCE includes five hydrological models and low-flow forecasts can be issued up to 90 days ahead for more than 800 basins. Several input scenarios are considered: ECMWF 14-days ensemble forecasts, ensemble streamflow prediction (ESP) using historical climatic data, and a no precipitation scenario. Outputs from the different hydrological models are combined into a multi-model approach to improve robustness of the forecasts. The tool provides text files and graphical representation of forecasted low-flows, as well as key low-flow indicators, such as the probabilities of being under low-flow thresholds provided by operational services. The presentation will show the main characteristics of this operational forecast platform, its latest developments and the results on the recent low-flow periods.

Monitoring active volcanoes activity passes through the detection of fluctuations in degassing levels which may reflect changes in the magma supply rate and help inform a short-term forecast of on-going eruptions. Infrared hyperspectral imagers, which is an imaging technology still little used for volcanoes monitoring, have been deployed for various field campaigns on active volcanoes recently. For example, the Hyper-Cam LWIR (LongWave InfraRed) ranging between 850-1300 cm^-1 (7.7 - 11.8 µm) with a spectral resolution up to 0.25 cm^-1, provided high spectral resolution images from ground-based measurements of the Mount Etna (Sicily, Italy) plume during IMAGETNA campaign in June 2015. Processing the raw data and retrieving the infrared spectra with the LATMOS (Laboratoire Atmosphères Milieux Observations Spatiales) Atmospheric Retrieval Algorithm (LARA), a robust and a complete radiative transfer model, require a calculation time of ~7 days per image.

One of the main ways of risk mitigation effects of explosive eruptions is to get a fast and accurate quantification of SO₂ fluxes emitted by volcanoes. In this context, using the dataset acquired during IMAGETNA campaign at Mount Etna, a spectra classification methodology has been developed to drastically decrease the calculation time and reach near real-time retrievals of SO₂ slant column densities. The methodology is based on a network built on two layers of information from the extraction of spectral features in the O₃ and SO₂ emission bands. A training dataset of five SO₂ slant column densities images retrieved with the time-consuming pixel-by-pixel retrieval method allowed the creation of a library. The spectra classification makes it possible to process each hyperspectral image in less than 40 seconds. It opens the possibility to infer near real-time estimation of SO₂ emission fluxes from IR hyperspectral imager measurements.