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Recent work has shown that unconfined smectite clays swell upon exposure to supercritical (SC) CO 2 due to uptake in the clay interlayer region. Such swelling behaviour is expected to cause internal stress development under geometrically confined conditions pertaining to geological storage of CO 2 , but this has not been widely investigated. Here, we report uniaxial compaction/swelling tests performed, using a 1-D compaction cell, on pre-pressed discs of Wyoming (Na-SWy-1) and Arizona (Ca-SAz-1) montmorillonite, as well as on smectite-bearing shale. We explore the axial (Terzaghi) effective stress generated in these materials upon exposure to 10 MPa CO 2 pressure under conditions where total swelling (including poroelastic effects) is restricted to axial strains below 3%. The experiments were performed at 44 °C. In each experiment, the sample was first equilibrated with lab air (RH ≈ 40%–60% at T = 20–25 °C) at the experimental temperature and pre-compacted at ∼60 MPa axial stress to generate a dense reproducible microstructure. A lower axial normal stress of 25.9–40.9 MPa was then applied and the loading piston held in fixed position. This yielded an effective (Terzaghi) overburden stress of 9.6–24.7 MPa upon introduction of CO 2 at 10 MPa, thus simulating burial depths of ∼0.8–2.0 km. Following CO 2 introduction, axial swelling stresses developed rapidly, independently of the direct effect of increased pore pressure, attaining values of 7.1–12.4 MPa at equilibrium, compared with ∼2 MPa obtained using inert Ar. Experiments on Na-SWy-1 montmorillonite showed that the swelling stress generated upon exposure to CO 2 decreases with increasing initial and final effective normal stress, suggesting that overburden stress suppresses swelling (stress) development in smectite, presumably by limiting the amount of CO 2 uptake by the material investigated. The swelling stresses observed imply that CO 2 penetration into caprocks and faults in geological storage systems will lead to an increase in effective normal stress components, which in turn will tend to promote closure of fractures and enhance sealing integrity. However, further work is needed to improve understanding of the processes underlying the swelling of smectite caused by CO 2 and to evaluate any risks posed to caprock and fault integrity by swelling-induced shear stresses. [ABSTRACT FROM AUTHOR]

Smectites are common constituents of claystones, mudstones and shales and are often present in the caprocks and faults that seal potential CO2 storage reservoirs at depths up to 2 or even 3km. Whilst the marked swelling behaviour of smectites caused by hydration through interlayer sorption of water molecules has been extensively studied, less is known regarding possible interactions of the mineral structure with supercritical CO2. To explore the possibility of such effects, and to assess any implications for CO2 storage, we performed unconfined volumetric strain (dilatometry) measurements on compacted pellets of montmorillonite, a common smectite frequently present in smectite-bearing shales and fault gouges. This was done by exposing SWy-1 and Na-SWy-2 type smectite samples (Wyoming) to CO2 in a high pressure optical cell. We used this cell to assess the strain response to exposure to CO2 at the P–T conditions expected in relatively shallow carbon dioxide storage reservoirs, i.e. at a temperature of 45°C and CO2 pressures up to 15MPa. Samples were heat-treated prior to exposure to CO2 to obtain initial hydration states (d 001-spacing), determined independently using X-ray diffraction methods. Our results show that SWy-1 and Na-SWy-2 montmorillonites swell almost instantaneously (in a few seconds) to an equilibrium state when exposed to (supercritical) CO2 at the conditions investigated, with both materials exhibiting closely similar behaviour. Swelling strain increases systematically with CO2 pressure in the range 1–7MPa, but only slightly at higher pressures. The SWy-1 data show maximum swelling strain for an initial d 001 spacing of 11.1Ǻ, reaching 2.46±0.45% at a CO2 pressure of 15MPa. For initial d-spacings down to the fully dehydrated state of 9.8Ǻ, swelling decreases systematically with decreasing d-spacing at all pressures investigated. Only minor swelling (0.55±0.47% at 10MPa CO2 pressure) is found for an initial d 001 spacing of 9.8Ǻ. For smectite-bearing caprocks and faults sealing carbon sequestration reservoirs, our results imply that CO2 penetration can be expected to cause swelling of a few percent in the affected zone, closing small fractures or joints and thus reducing bulk permeability. [ABSTRACT FROM AUTHOR]

Abstract: The study presented in this paper is to investigate the possibility of using spaceborne remote sensing data for groundwater head prediction. Remotely-sensed soil moisture time series of SWI (Soil Water Index) derived from ERS (European Remote Sensing) scatterometers are used to predict groundwater head dynamics in the Rhine–Meuse basin, where over four thousand observed groundwater head time series are available. Our study consists of three evolving research steps. First, the correlation between observed time series of groundwater head and SWI is investigated. Second, SWI time series are used as input to a transfer-function noise (TFN) model for temporal prediction (forecasts) of groundwater heads. Third, TFN models with spatially interpolated parameters are used with SWI time series for spatio-temporal prediction of groundwater heads. Here, HAND (Height Above Nearest Drainage) as derived from a digital elevation model is used as auxiliary information. Results show that the correlation between SWI and groundwater head time series is apparent, particularly in areas with shallow groundwater, and that correlation increases when a time-lag is taken into account. Temporal predictions with TFN models reproduce observed groundwater head time series well at locations with shallow groundwater, but results are poor for locations with deep groundwater. The spatio-temporal prediction method is not able to estimate the absolute value of groundwater heads. However, head variation in terms of timing and amplitude is predicted reasonably well, in particular in areas with shallow groundwater. This suggests that, once a groundwater model is suitably calibrated, remotely sensed soil moisture data could be used to improve groundwater prediction in an operational data-assimilation framework. [Copyright &y& Elsevier]

Abstract: Bubonic plague, caused by the bacteria Yersinia pestis, persists as a public health problem in many parts of the world, including central Kazakhstan. Bubonic plague occurs most often in humans through a flea bite, when a questing flea fails to find a rodent host. For many of the plague foci in Kazakhstan the great gerbil is the major host of plague, a social rodent well-adapted to desert environments. Intensive monitoring and prevention of plague in gerbils started in 1947, reducing the number of human cases and mortalities drastically. However, the monitoring is labour-intensive and hence expensive and is now under threat due to financial constraints. Previous research showed that the occupancy rate of the burrow systems of the great gerbil is a strong indicator for the probability of a plague outbreak. The burrow systems are around 30m in diameter with a bare surface. This paper aims to demonstrate the automatic classification of burrow systems in satellite images using object-oriented analysis. We performed field campaigns in September 2007 and May and September 2008 and acquired corresponding QuickBird images of the first two periods. User''s and producer''s accuracy values of the classification reached 60 and 86%, respectively, providing proof of concept that automatic mapping of burrow systems using high-resolution satellite images is possible. Such maps, by better defining great gerbil foci, locating new or expanding foci and measuring the density of great gerbil burrow systems could play a major role in a renewed monitoring system by better directing surveillance and control efforts. Furthermore, if similar analyses can separate occupied burrow systems from empty ones, then very-high-resolution images stand to play a crucial role in plague surveillance throughout central Asia. [Copyright &y& Elsevier]

High spatial resolution images allow us to assess the spatial structure and variability of natural vegetation characteristics. In order to optimize quantitative image analysis, we looked for the optimal spatial resolution to map natural vegetation in a Mediterranean environment. The optimal spatial resolution was then related to the spatial characteristics of the scene and the mapped parameters. Based on the relation between airborne hyperspectral imagery and field dataset consisting of 227 measured plots of Leaf Area Index (LAI) and aboveground biomass, we found an optimal pixel size of 55 and 95 m for the mapping of LAI and aboveground biomass, respectively. The optimal spatial resolution we found is determined by the spatial structure of the mapped parameters on the one hand, and by the effects of shading patterns and gaps in the canopy on the other. The spatial properties of scene elements influencing the optimal spatial resolution can be detected effectively using average local variance functions and variograms, provided that these are studied at a wide spatial range. The use of an optimally sized mapping unit instead of the original 5 m pixels resulted in an improvement of mapping accuracy of 7 to 17%. It is therefore recommended that the image support used is considered carefully in all quantitative mapping projects based on remotely sensed imagery. [Copyright &y& Elsevier]

Abstract: Various remote sensing products are used to identify spatial–temporal trends in snow cover in river basins originating in the Himalayas and adjacent Tibetan–Qinghai plateau. It is shown that remote sensing allows detection of spatial–temporal patterns of snow cover across large areas in inaccessible terrain, providing useful information on a critical component of the hydrological cycle. Results show large variation in snow cover between years while an increasing trend from west to east is observed. Of all river basins the Indus basin is, for its water resources, most dependent on snow and ice melt and large parts are snow covered for prolonged periods of the year. A significant negative winter snow cover trend was identified for the upper Indus basin. For this basin a hydrological model is used and forced with remotely sensed derived precipitation and snow cover. The model is calibrated using daily discharges from 2000 to 2005 and stream flow in the upper Indus basin can be predicted with a high degree of accuracy. From the analysis it is concluded that there are indications that regional warming is affecting the hydrology of the upper Indus basin due to accelerated glacial melting during the simulation period. This warming may be associated with global changes in air temperature resulting from anthropogenic forcings. This conclusion is primarily based on the observation that the average annual precipitation over a five year period is less than the observed stream flow and supported by positive temperature trends in all seasons. [Copyright &y& Elsevier]

Abstract: Himalayan glacier tongues are commonly debris covered and they are an important source of melt water. However, they remain relatively unstudied because of the inaccessibility of the terrain and the difficulties in field work caused by the thick debris mantles. Observations of debris-covered glaciers are therefore scarce and airborne remote sensing may bridge the gap between scarce field observations and coarse resolution space-borne remote sensing. In this study we deploy an Unmanned Aerial Vehicle (UAV) before and after the melt and monsoon season (May and October 2013) over the debris-covered tongue of the Lirung Glacier in Nepal. Based on stereo-imaging and the structure for motion algorithm we derive highly detailed ortho-mosaics and digital elevation models (DEMs), which we geometrically correct using differential GPS observations collected in the field. Based on DEM differencing and manual feature tracking we derive the mass loss and the surface velocity of the glacier at a high spatial accuracy. On average, mass loss is limited and the surface velocity is very small. However, the spatial variability of melt rates is very high, and ice cliffs and supra-glacial ponds show mass losses that can be an order of magnitude higher than the average. We suggest that future research should focus on the interaction between supra-glacial ponds, ice cliffs and englacial hydrology to further understand the dynamics of debris-covered glaciers. Finally, we conclude that UAV deployment has large potential in glaciology and it may revolutionize methods currently applied in studying glacier surface features. [Copyright &y& Elsevier]

Abstract: Mapping complex landslides under forested terrain requires an appropriate quality of digital terrain models (DTMs), which preserve small diagnostic features for landslide classification such as primary and secondary scarps, cracks, and displacement structures (flow-type and rigid-type). Optical satellite imagery, aerial photographs and synthetic aperture radar images are less effective to create reliable DTMs under tree coverage. Here, we utilized a very high density airborne laser scanning (ALS) data, with a point density of 140 points m−2 for generating a high quality DTM for mapping landslides in forested terrain in the Barcelonnette region, the Southern French Alps. We quantitatively evaluated the preservation of morphological features and qualitatively assessed the visualization of ALS-derived DTMs. We presented a filter parameterization method suitable for landslide mapping and compared it with two default filters from the hierarchical robust interpolation (HRI) and one default filter from the progressive TIN densification (PTD) method. The results indicate that the vertical accuracy of the DTM derived from the landslide filter is about 0.04m less accurate than that from the PTD filter. However, the landslide filter yields a better quality of the image for the recognition of small diagnostic features as depicted by expert image interpreters. Several DTM visualization techniques were compared for visual interpretation. The openness map visualized in a stereoscopic model reveals more morphologically relevant features for landslide mapping than the other filter products. We also analyzed the minimal point density in ALS data for landslide mapping and found that a point density of more than 6 points m−2 is considered suitable for a detailed analysis of morphological features. This study illustrates the suitability of high density ALS data with an appropriate parameterization for the bare-earth extraction used for landslide identification and characterization in forested terrain. [Copyright &y& Elsevier]