Rapid industrial development along Thailand’s eastern seaboard has increased pollution and environmental degradation in this densely populated region of the country. A growing problem is illegal disposal of industrial waste in abandoned borrow pits in many locations, especially in the capital Bangkok and its neighboring provinces. Previous work has identified the most likely illegal dumping sites in Chachoengsao Province. The focus of this work was to establish an impact assessment of potential dumping sites using a geographic information system (GIS) in order to create a patrolling and monitoring program for areas at highest risk. The impact assessment is based upon exposure and sensitivity factors of the illegal dumping sites. The exposure factor attempts to quantify the likelihood of illegal dumping; it includes distances from borrow pits to the nearest villages and highways, as well as the areas of the borrow pits. The sensitivity factor assesses the probability of environmental contamination; it includes site topography, ground permeability, aquifer characteristics, and distances to the nearest rivers. GIS was used to compute distances and to overlay other site characteristics. Variables within exposure and sensitivity factors were weighted based upon previous studies and recent expert analysis to compute exposure and sensitivity indices. Maps were then created in GIS for particular exposure and sensitivity factors, and overall impact assessment maps were constructed to indicate zones with low, medium, and high risk. These assessment maps could be adopted by local and regional governmental agencies, as well as local citizens, as part of preventive measures to conserve the local community and environment. Identification of high-risk areas can contribute to the initiation of a monitoring and patrolling program to prevent illegal dumping and preserve environmental and natural resources.

Abstract Central Skåne (Scania) in southern Sweden hosts evidence of extensive Jurassic volcanism in the form of mafic volcanic plugs and associated volcaniclastic deposits that entomb well-preserved macro-plant and spore–pollen assemblages. Palynological assemblages recovered from the Höör Sandstone are of Hettangian–Pliensbachian age and those from the overlying lahar deposits are dated as Pliensbachian–early Toarcian (?). Palynomorph assemblages from these units reveal significantly different ecosystems, particularly with respect to the gymnospermous components that represented the main canopy plants. Both palynofloras are dominated by osmundacean, marattiacean and cyatheacean fern spore taxa but, whereas the Höör Sandstone hosts abundant Chasmatosporites spp. pollen produced by plants related to cycadophytes, the volcanogenic deposits are dominated by cypress family pollen ( Perinopollenites ) with an understorey component rich in putative Erdtmanithecales (or possibly Gnetales), and collectively representing vegetation of disturbed habitats. Permineralized conifer wood attributed to Protophyllocladoxylon sp., belonging to plants that probably produced the abundant Perinopollenites grains, is abundant in the volcanigenic strata, and shows sporadic intraseasonal and multi-year episodes of growth disruption. Together with the relatively narrow but marked annual growth rings, and the annual and mean sensitivity values that span the complacent–sensitive domains, these features suggest growth within Mediterranean-type biomes subject to episodic disturbance.

Abstract The MAGFLOW model for lava-flow simulations is based on the cellular automaton (CA) approach, and uses a physical model for the thermal and rheological evolution of the flowing lava. We discuss the potential of MAGFLOW to improve our understanding of the dynamics of lava-flow emplacement and our ability to assess lava-flow hazards. Sensitivity analysis of the input parameters controlling the evolution function of the automaton demonstrates that water content and solidus temperatures are the parameters to which MAGFLOW is most sensitive. Additional tests also indicate that temporal changes in effusion rate strongly influence the accuracy of the predictive modelling of lava-flow paths. The parallel implementation of MAGFLOW on graphic processing units (GPUs) can achieve speed-ups of two orders of magnitude relative to the corresponding serial implementation, providing a lava-flow simulation spanning several days of eruption in just a few minutes. We describe and demonstrate the operation of MAGFLOW using two case studies from Mt Etna: one is a reconstruction of the detailed chronology of the lava-flow emplacement during the 2006 flank eruption; and the other is the production of the lava-flow hazard map of the persistent eruptive activity at the summit craters.

Abstract Autogenic fluvial dynamics, including river avulsion, influence the distribution of channel sand bodies in alluvial deposits. Over long timescales, autogenically organized avulsions can generate stratigraphic patterns such as clusters of sand bodies when avulsions preferentially return to previous channel locations, or evenly spaced sand bodies when avulsions preferentially fill topographic lows. Consequently, quantifying stratigraphic patterns may provide an avenue for reconstructing paleoavulsion dynamics from ancient deposits. Several quantitative approaches have been used to quantify the degree to which channel-belt deposits are distributed randomly, evenly, or with clustered patterns; however, to date, there are only a few examples where these metrics have been applied in outcrop studies. Here we present a quantitative analysis of stratigraphic architecture in the lower Williams Fork Formation (Cretaceous, Colorado) to quantify the paleoavulsion pattern in this interval. A spatial-point-process statistic (the K function) and the compensation statistic are applied to stratigraphic data mapped from a terrestrial lidar digital outcrop model. Both analyses show random channel-body distributions and random basin filling at short (less than 200 m) spatiotemporal scales, which suggests that lower Williams Fork channels avulsed randomly. To evaluate the sensitivity of the K function to different degrees of stratigraphic organization, we use a two-dimensional (2D) geometric model to build synthetic stratigraphy with different degrees of sand-body clustering. Model results show that the lower Williams Fork data set should be of sufficient size and resolution to detect strong clustering signals, if they were present. This type of sensitivity analysis is helpful for comparing results of spatial-point-process analyses among outcrop examples with confidence. The random paleoavulsion pattern inferred from lower Williams Fork stratigraphy in this locality contrasts with previously published analyses that show qualitative clustering at larger scales; however, these results are not incompatible if avulsions remained clustered regionally over long timescales.

Abstract We describe the results from an application of a distributed, transient infiltration–slope-stability model for an 18 km 2 area of southwestern Seattle, Washington, USA. The model (TRIGRS) combines an infinite slope-stability calculation and an analytic, one-dimensional solution for pore-pressure diffusion in a soil layer of finite depth in response to time-varying rainfall. The transient solution for pore-pressure response can be superposed on any steady-state groundwater-flow field that is consistent with model assumptions. Applied over digital topography, the model computes a factor of safety for each grid cell at any time during a rainstorm. Input variables may vary from cell to cell, and the rainfall rate can vary in both space and time. For Seattle, topographic slope derived from an airborne laser swath mapping (ALSM)–based 3 m digital elevation model (DEM), maps of soil and water-table depths derived from geotechnical borings, and hourly rainfall intensities were used as model inputs. Material strength and hydraulic properties used in the model were determined from field and laboratory measurements, and a tension-saturated initial condition was assumed. Results are given in terms of a destabilizing intensity and duration of rainfall, and they were evaluated by comparing the locations of 212 historical landslides with the area mapped as potentially unstable. Because the equations of groundwater flow are explicitly solved with respect to time, the results from TRIGRS simulations can be portrayed quantitatively to assess the potential landslide hazard based on rainfall conditions.