Assessment of shallow landslide susceptibility using the transient infiltration flow model and GIS-based probabilistic approach

This study proposes a probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by combining a transient infiltration flow model and Monte Carlo simulations. The spatiotemporal change in pore water pressure over time caused by rainfall infiltration is one of the most important factors causing landslides. Therefore, the transient infiltration hydrogeological model was adopted to estimate the pore water pressure within the hill slope and to analyze landslide susceptibility. In addition, because of the inherent uncertainty and variability caused by complex geological conditions and the limited number of available soil samples over a large area, this study utilized probabilistic analysis based on Monte Carlo simulations to account for the variability in the input parameters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. To evaluate its effectiveness, the proposed analysis method was applied to a study area that had experienced a large number of landslides in July 2006. For the susceptibility analysis, a spatial database of input parameters and a landslide inventory map were constructed in a GIS environment. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. In addition, the probabilistic method exhibited better performance than the deterministic alternative. Thus, analysis methods that account for uncertainties in input parameters are more appropriate for analysis of an extensive area, for which uncertainties may significantly affect the predictions because of the large area and limited data.     

Biomass growth characteristics of 13-year-old <Emphasis Type="Italic">Pinus densiflora</Emphasis> S. et Z. in a post-fire plantation on different contour conditions in Samcheuk,Korea

We used preliminary data to estimate the growth volume of artificially reforested Pinus densiflora in a post-fire area on three different contour conditions. We compared the growth of P. densiflora on a south-facing slope (S_sth), north-facing slope (S_nth) and ridge area (Ridge), using 7 trees selected from each stand aspect. The tree height, diameter and growth volume were measured and the dry weight of each plant part were compared and analyzed. The results revealed that the total dry weight was highest on S_sth (5992.3 g), followed by S_nth (4833.2 g) and lowest on Ridge (3160.1 g). The height growth was highest on S_nth (285.8 cm), followed by S_sth (274.5 cm) and lowest on Ridge (211.5 cm). The diameter growth was greatest on S_sth (7.37 cm), followed by S_nth (7.10 cm) and lowest on Ridge (5.72 cm). The volume growth was highest on S_sth (4257.7 cm³), followed by S_nth (3750.7 cm³) and lowest on Ridge (2093.7 cm³). Therefore, we should consider and include the concept of slope orientation together with differences in habitat environments in afforestation projects when creating artificial forests with P. densiflora. These study results can serve as important preliminary data for future establishment of artificial forest of P. densiflora in a post-fire plantation.     

Performance of Weibull function as a diameter distribution model for <Emphasis Type="Italic">Pinus thunbergii</Emphasis> stands in the eastern coast of South Korea

This study was carried out to determine the performance of percentile-based Weibull diameter distribution model for Pinus thunbergii stands thriving along the eastern coast of South Korea. The parameter recovery technique was used to estimate the three parameters of the Weibull model. The analysis demonstrated satisfactory results based on the following test statistics for the principal percentile models: fit index (FI) range from 0.501 (minimum diameter) to 0.932 (50th diameter percentiles) and root mean square error (RMSE) range from 0.112 (quadratic mean diameter) to 3.572 (minimum diameter). The developed model was further evaluated by determining the mean bias (ē) in trees per ha (TPH) for each diameter class, and the results showed highest over-prediction in the 20 cm, and under-prediction in the 16 cm and 24 cm diameter classes. The goodness of fit tested by Kolmogorov-Smirnov (KS) test showed no significant differences (p>0.05) between the observed and predicted diameter distributions for almost all plots. Using site index and aboveground biomass (AGB) models developed for P. thunbergii in South Korea, a model to predict the AGB per ha for each diameter class and subsequently the total AGB of the stand was created. An application guide was also created, which will serve as a decision-support tool for forest managers in quantifying the future total AGB in P. thunbergii stands located in the eastern coast of South Korea and, subsequently, the quantification of potential carbon stocks aside from being a vital input in designing efficient management and protection strategies for these stands.     

Molecular characterization of four genes highly expressed during megalopa stage in Chinese mitten crab,Eriocheir sinensis

Ocean Science Journal - The molecular markers to distinguish different larval stages have various applications in ecological studies. Using the differential display RT-PCR technique, we isolated...     

Coherent Flow Structures and Pollutant Dispersion in a Street Canyon

Boundary-Layer Meteorology - Coherent flow structures and pollutant dispersion in a spanwise-long street canyon are investigated using a parallelized large-eddy-simulation model. Low- and...     

Voronoi Meshing to Accurately Capture Geological Structure in Subsurface Simulations

Mathematical Geosciences - Mesh generation lies at the interface of geological modeling and reservoir simulation. Highly skewed or very small grid cells may be necessary to accurately capture the...     

Tracing solute infiltration using a combined method of dye tracer test and electrical resistivity tomography in an undisturbed forest soil profile

An accurate prediction of solute infiltration in a soil profile is important in the area of environmental science, groundwater and civil engineering. We examined the infiltration pattern and monitored the infiltration process using a combined method of dye tracer test and electrical resistivity tomography (ERT) in an undisturbed field soil (1 m × 1 m). A homogeneous matrix flow was observed in the surface soil (A horizon), but a preferential flow along macropores and residual rock structure was the dominant infiltration pattern in the subsurface soil. Saturated interflow along the slopping boundaries of A and C1 horizons and of an upper sandy layer and a lower thin clay layer in the C horizon was also observed. The result of ERT showed that matrix flow started first in A horizon and then the infiltration was followed by the preferential flows along the sloping interfaces and macropores. The ERT did not show as much detail as the dye‐stained image for the preferential flow. However, the area with the higher staining density where preferential flow was dominant showed a relatively lower electrical resistivity. The result of this study indicates that ERT can be applied for the monitoring of solute transportation in the vadose zone. Copyright © 2010 John Wiley & Sons, Ltd.     

Informing adaptation responses to climate change through theories of transformation

Transformative actions are increasingly being required to address changes in climate. As an aid to understanding and supporting informed decision-making regarding transformative change, we draw on theories from both the resilience and vulnerability literature to produce the Adaptation Action Cycles concept and applied framework. The resulting Adaptation Action Cycles provides a novel conceptualisation of incremental and transformative adaptation as a continuous process depicted by two concentric and distinct, yet linked, action learning cycles. Each cycle represents four stages in the decision-making process, which are considered to be undertaken over relatively short timeframes. The concept is translated into an applied framework by adopting a contextual, actor-focused suite of questions at each of the four stages. This approach compliments existing theories of transition and transformation by operationalising assessments at the individual and enterprise level. Empirical validation of the concept was conducted by collaborating with members of the Australian wine industry to assess their decisions and actions taken in response to climate change. The contiguous stages represented in the Adaptation Action Cycles aptly reflected the diverse range of decision-making and action pathways taken in recent years by those interviewed. Results suggest that incremental adaptation decision-making processes have distinct characteristics, compared with those used in transformative adaptation. We provide empirical data to support past propositions suggesting dependent relationships operate between incremental and transformative scales of adaptation.