Landslide susceptibility analysis using GIS and artificial neural network

The purpose of this study is to develop landslide susceptibility analysis techniques using an arti?cial neural network and to apply the newly developed techniques to the study area of Yongin in Korea. Landslide locations were identi?ed in the study area from interpretation of aerial photographs, ?eld survey data, and a spatial database of the topography, soil type and timber cover. The landslide‐related factors (slope, curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter) were extracted from the spatial database. Using those factors, landslide susceptibility was analysed by arti?cial neural network methods. The landslide susceptibility index was calculated by the back‐propagation method, which is a type of arti?cial neural network method, and the susceptibility map was made with a geographic information system (GIS) program. The results of the landslide susceptibility analysis were veri?ed using landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide location. A GIS was used to ef?ciently analyse the vast amount of data, and an arti?cial neural network to be an effective tool to maintain precision and accuracy. The results can be used to reduce hazards associated with landslides and to plan land use and construction. Copyright © 2003 John Wiley & Sons, Ltd.     

A Review on Marine N2 Fixation: Mechanism,Evolution of Methodologies,Rates, and Future Concerns

Ocean Science Journal - Investigations on marine N2 fixation have gained momentum since 1960s with eventual establishments of relevant methodologies to identify species involved and quantify the...     

Biomonitoring of coastal pollution status using protozoan communities with a modified PFU method

Structural and functional parameters of protozoan communities were assessed as indicators of water quality in Korean coastal waters in the summer of 2000. A modified polyurethane foam unit (PFU) method, named the bottled PFU (BPFU) system, was used in order to carry out the bioassessment. Both parameters suggested that biomonitoring using the BPFU system was more effective than the conventional PFU method in offshore areas. The species number collected by the BPFU system generally decreased as pollution intensity increased at three main stations and was greater than that collected using the PFU method (paired t-test, t = 4.83, p < 0.0001). The Margalef diversity index coincided well with the water conditions. The diversity index values calculated from the BPFU system were also significantly higher than those from the PFU method (paired t-test, t = 5.37, p < 0.0001). Furthermore, the functional parameters, i.e. S(eq),G and T90%, correlated with the pollution status and could thus clearly discriminate the different classes of water quality.     

Estimation of the Roll Hydrodynamic Moment Model of a Ship by Using the System Identification Method and the Free Running Model Test

When a fast container ship or a naval vessel turns, accompanying roll motions occur. This roll effect must be considered in the horizontal equations of the motion of the ship to predict the maneuverability of the ship properly. In this paper, a new method for determining a model structure of the hydrodynamic roll moment acting on a ship and for estimating the hydrodynamic coefficients is proposed. The method utilizes a system identification technique with the data from sea trial tests or from free running model (FRM) tests. To obtain motion data that is applied to the proposed algorithm, an FRM of a large container ship was developed. Using this model ship, standard maneuvering tests were carried out on a small body of water out of doors. A hydrodynamic roll moment model was constructed utilizing the data from turning circle tests and a 20-20 zig-zag test. This was then confirmed through a 10-10 zig-zag test. It was concluded that a model structure of the hydrodynamic roll moment model could be established without difficulty through a system identification method and FRM tests.     

Seasonal variation in the community and size structure of nano- and microzooplankton in Gyeonggi Bay,Yellow Sea

To investigate the seasonal variation and community structure of nano- and microzooplankton in Gyeonggi Bay of the Yellow Sea, the abundance and carbon biomass of nano- and microzooplankton were evaluated at 10-day intervals from January 1997 to December 1999. Four major groups of nano- and microzooplankton communities were classified: heterotrophic ciliates, heterotrophic dinoflagellates (HDF), heterotrophic nanoflagellates (HNF), and copepod nauplii. The total carbon biomass of nano- and microzooplankton ranged from 10.2 to 168.8 μg C L⁻¹ and was highest during or after phytoplankton blooms. Nano- and microzooplankton communities were composed of heterotrophic ciliates (7.4–81.4%; average 41.7% of total biomass), HDF (0.1–70.3%; average 26.1% of total biomass), copepod nauplii (1.6–70.6%; average 20.7% of total biomass), and HNF (0.8–59.5%; average 11.5% of total biomass). The relative contribution of individual components in the nano- and microzooplankton communities appeared to differ by seasons. Ciliates accounted for the most major component of nano- and microzooplankton communities, except during summer and phytoplankton blooming seasons, whereas HDF were more dominant during the phytoplankton blooming seasons. The abundance and biomass of nano- and microzooplankton generally followed the seasonal dynamics of phytoplankton. The size and community distribution of nano- and microzooplankton was positively correlated with size-fractionated phytoplankton. The carbon requirement of microzooplankton ranged from 60 to 83% of daily primary production, and was relatively high when phytoplankton biomass was high. Therefore, our result suggests that the seasonal variation in the community and size composition of nano- and microzooplankton appears to be primarily governed by phytoplankton size and concentration as a food source, and their abundance may greatly affect trophic dynamics by controlling the seasonal abundance of phytoplankton.     

Modelling hydrological response to a fully‐monitored urban bioretention cell

Municipalities and agencies use green infrastructure to combat pollution and hydrological impacts (e.g., flooding) related to excess stormwater. Bioretention cells are one type of infiltration green infrastructure intervention that infiltrate and redistribute otherwise uncontrolled stormwater volume. However, the effects of these installations on the rest of the local water cycle is understudied; in particular, impacts on stormwater return flows and groundwater levels are not fully understood. In this study, full water cycle monitoring data were used to construct and calibrate a two‐dimensional Richards equation model (HYDRUS‐2D/3D) detailing hydrological implications of an unlined bioretention cell (Cleveland, Ohio) that accepts direct runoff from surrounding impervious surfaces. Using both preinstallation and postinstallation data, the model was used to (a) establish a mass balance to determine reduction in stormwater return flow, (b) evaluate green infrastructure effects on subsurface water dynamics, and (c) determine model sensitivity to measured soil properties. Comparisons of modelled versus observed data indicated that the model captured many hydrological aspects of the bioretention cell, including subsurface storage and transient groundwater mounding. Model outputs suggested that the bioretention cell reduced stormwater return flows into the local sewer collection system, though the extent of this benefit was attenuated during high inflow events that may have exhausted detention capacity. The model also demonstrated how, prior to bioretention cell installation, surface and subsurface hydrology were largely decoupled, whereas after installation, exfiltration from the bioretention cell activated a new groundwater dynamic. Still, the extent of groundwater mounding from the cell was limited in spatial extent and did not threaten other subsurface infrastructure. Finally, the sensitivity analysis demonstrated that the overall hydrological response was regulated by the hydraulics of the bioretention cell fill material, which controlled water entry into the system, and by the water retention parameters of the native soil, which controlled connectivity between the surface and groundwater.     

A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China

A statistical dynamic model for forecasting Chinese landfall of tropical cyclones (CLTCs) was developed based on the empirical relationship between the observed CLTC variability and the hindcast atmospheric circulations from the Pusan National University coupled general circulation model (PNU-CGCM).In the last 31 years,CLTCs have shown strong year-to-year variability,with a maximum frequency in 1994 and a minimum frequency in 1987.Such features were well forecasted by the model.A cross-validation test showed that the correlation between the observed index and the forecasted CLTC index was high,with a coefficient of 0.71.The relative error percentage (16.3%) and root-mean-square error (1.07) were low.Therefore the coupled model performs well in terms of forecasting CLTCs;the model has potential for dynamic forecasting of landfall of tropical cyclones.     

Storm‐coverage effect on dynamic flood‐frequency analysis: empirical data analysis

In this study, a dynamic flood‐frequency analysis model considering the storm coverage effect is proposed and applied to six sub‐basins in the Pyungchang River basin, Korea. The model proposed is composed of the rectangular pulse Poisson process model for rainfall, the Soil Conservation Service curve number method for infiltration and the geomorphoclimatic instantaneous unit hydrograph for runoff estimation. Also, the model developed by Marco and Valdes is adopted for quantifying the storm‐coverage characteristics. By comparing the results from the same model with and without the storm‐coverage effect consideration, we could quantify the storm‐coverage effect on the flood‐frequency analysis. As a result of that, we found the storm‐coverage effect was so significant that overestimation of the design flood was unavoidable without its consideration. This also becomes more serious for larger basins where the probability of complete storm coverage is quite low. However, for smaller basins, the limited number of rain gauges is found to hamper the proper quantification of the storm‐coverage characteristics. Provided with a relationship curve between the basin size and the storm coverage (as in this study), this problem could be overcome with an acceptable accuracy level. Copyright © 2003 John Wiley & Sons, Ltd.     

Climate Regime Shift and Phytoplankton Phenology in a Macrotidal Estuary: Long-Term Surveys in Gyeonggi Bay,Korea

Phytoplankton are finely tuned to the seasonality of their environment, and shifts in the timing of phytoplankton phenology provide some of the most compelling evidence that species and ecosystems are being influenced by global climate change. Evaluation of a 50-year dataset of climatic parameters, a 12-year dataset of nutrients, and a 15-year dataset of phytoplankton biomass and composition in Gyeonggi Bay of the Yellow Sea revealed that the climate has shifted from a cold to a warm phase in the last few decades and that recent warm climatic and eutrophication trends are affecting phytoplankton biomass, phenology, and structure. In Gyeonggi Bay, climatic and ecological regime shifts were detected during the 1990s and 2000s, respectively. The asymmetric relationship between climate and ecological regime shift probably depends on macrotidal system configurations that are more resistant to environmental perturbation. The spring diatom blooms observed in the 1990s have moved forward to winter blooms in the 2000s because early winter warming has been induced by higher light and precipitation, which has removed prior light limitation and control of diatom blooms. Summer blooms are triggered by enhanced nutrients, which leads to frequent and recurring dominance of dinoflagellates and diatoms, supporting the hypothesis that summer phenology might be brought about by local processes such as eutrophication, as well as by climate change. Overall, differences in phenological trends can be brought about by differences in the underlying drivers of seasonality. Based on the results of this study, perspectives are drawn regarding the utility of phenology as an organizing principle for analysis of pelagic ecosystems.     

Simulating short‐circuiting flow in a constructed wetland: the implications of bathymetry and vegetation effects

Short‐circuiting flow, commonly experienced in many constructed wetlands, reduces hydraulic retention times in unit wetland cells and decreases the treatment efficiency. A two‐dimensional (2‐D), physically based, distributed modelling approach was used to systematically address the effects of bathymetry and vegetation on short‐circuiting flow, which previously have been neglected or lumped in one‐dimensional wetland flow models. In this study, a 2‐D transient hydrodynamics with advection‐dispersion model was developed using MIKE 21 and calibrated with bromide tracer data collected at the Orlando Easterly Wetland Cell 7. The estimated topographic difference between short‐circuiting flow zone and adjacent area ranged from 0·3 to 0·8 m. A range of the Manning roughness coefficient at the short‐circuiting flow zone was estimated (0·022–0·045 s m^?1/3). Sensitivity analysis of topographical and vegetative heterogeneity deduced during model calibration shows that relic ditches or other ditch‐shaped landforms and the associated sparse vegetation along the main flow direction intensify the short‐circuiting pattern, considerably affecting 2‐D solute transport simulation. In terms of hydraulic efficiency, this study indicates that the bathymetry effect on short‐circuiting flow is more important than the vegetation effect. Copyright © 2009 John Wiley & Sons, Ltd.