Modeling the sediment yield from landslides in the Shihmen Reservoir watershed,Taiwan

Landslides generate enormous volumes of sediment in mountainous watersheds; however, quantifying the downstream transport of landslide‐derived sediment remains a challenge. Landslide erosion and sediment delivery to the Shihmen Reservoir watershed in Taiwan was estimated using empirical landslide frequency–area and volume–area relationships, empirical landslide runout models, and the Hydrological Simulation Program‐ FORTRAN (HSPF). Landslide erosion rates ranged from 0.4 mm yr^‐1 to 2.2 mm yr^‐1 during the period 1986–2003, but increased to 7.9 mm yr^‐1 following Typhoon Aere in 2004. The percentage of landslide sediment delivered to streams decreased from 78% during the period 1986–1997 to 55% in 2004. Although the delivery ratio was lower, the volume of landslide sediment delivered to streams was 2.81 × 10⁶ Mg yr^‐1 in 1986–1997 and 8.60 × 10⁶ Mg yr^‐1 in 2004. Model simulations indicate that only a small proportion of the landslide material was delivered downstream. An average of 13% of the landslide material delivered to rivers was moved downstream during the period 1986–1997. In 2004, the period including Typhoon Aere, the annual fluvial sediment yield accounted for approximately 23% of the landslide material delivered to streams. In general, the transfer of sediment in the fluvial system in the Shihmen Reservoir watershed is dominantly transport limited. The imbalance between sediment supply and transport capacity has resulted in a considerable quantity of landslide material remaining in the upper‐stream regions of the watershed. Copyright © 2012 John Wiley & Sons, Ltd.     

Increased As load to the Uchen stream due to mine drainage and soils in the abandoned Kangwon mining district of Korea

To determine the appropriate allocation of resources for the future restoration of the abandoned mining district of Kangwon in Korea, identification of the main pollutants and the main sources discharging these pollutants is crucial. Therefore, a 2-year study was undertaken to quantify the amount of pollutants in the Uchen stream (a potential sink for contamination), which runs through the district, and to determine the potential sources of these pollutants, including mine drainage and soil. Arsenic (As) was the main pollutant in mine drainage and soils showing concentrations above the Korean regulated standard levels of 50 μg L⁻¹ and 50 mg kg⁻¹ for water and soil, respectively. In addition, the pollution index (PI) showed that mine drainages were polluted by As to a moderate (2 ≤ PI < 3) or strong (4 ≤ PI < 5) degree. Consequently, As load in mine drainage and soil contributed to increased amounts of As in the stream. The As loads in mine drainages (11 and 587 g month⁻¹ for mine adit 1 and 2, respectively) accounted for only 9% of the total As load to the stream (6,378 g month⁻¹); and the influence of mine drainages on As contents in the stream was more reliant on the total volume of mine drainage generated rather than the As concentration in the mine drainage. Approximately 91% of the As in the stream was derived from the soils within the study area.     

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.     

Ensemble-based landslide susceptibility maps in Jinbu area, Korea

Ensemble techniques were developed, applied and validated for the analysis of landslide susceptibility in Jinbu area, Korea using the geographic information system (GIS). Landslide-occurrence areas were detected in the study by interpreting aerial photographs and field survey data. Landslide locations were randomly selected in a 70/30 ratio for training and validation of the models, respectively. Topography, geology, soil and forest databases were also constructed. Maps relevant to landslide occurrence were assembled in a spatial database. Using the constructed spatial database, 17 landslide-related factors were extracted. The relationships between the detected landslide locations and the factors were identified and quantified by frequency ratio, weight of evidence, logistic regression and artificial neural network models and their ensemble models. The relationships were used as factor ratings in the overlay analysis to create landslide susceptibility indexes and maps. Then, the four landslide susceptibility maps were used as new input factors and integrated using the frequency ratio, weight of evidence, logistic regression and artificial neural network models as ensemble methods to make better susceptibility maps. All of the susceptibility maps were validated by comparison with known landslide locations that were not used directly in the analysis. As the result, the ensemble-based landslide susceptibility map that used the new landslide-related input factor maps showed better accuracy (87.11% in frequency ratio, 83.14% in weight of evidence, 87.79% in logistic regression and 84.54% in artificial neural network) than the individual landslide susceptibility maps (84.94% in frequency ratio, 82.82% in weight of evidence, 87.72% in logistic regression and 81.44% in artificial neural network). All accuracy assessments showed overall satisfactory agreement of more than 80%. The ensemble model was found to be more effective in terms of prediction accuracy than the individual model.     

Combined analyses of chemometrics and kriging for identifying groundwater contamination sources and origins at the Masan coastal area in Korea

Hydrogeochemical analyses including the basic statistics of chemical components, Piper??s trilinear diagram, and Mazor??s compositional bivariate diagram revealed that the main source and origin of groundwater contamination was seawater intrusion in the study area. However, the other sources and origins of groundwater contamination could be found by the combined analyses of chemometrics and kriging. Cluster analysis was helpful for the classification on the basis of the contamination characteristics of groundwater quality; however, it was not sufficient for the apportionment of groundwater contamination sources. Factor analysis (FA) determined three factors with 81.07% in total variance: Factor 1 for seawater contamination, Factor 2 for nitrate contamination, and Factor 3 for iron contamination. Factor analysis determined the sources of groundwater contamination; however, it could not discover the origins of contaminants except Factor 1. In backward stepwise mode, discriminant analysis decreased the number of parameters from 18 to 6 in discriminating the contaminant type with 96.2% correctness. TDS, Ca, NO₃, Mn, Fe, and Br were the most significant parameters for the discrimination of contaminants. Kriging analysis was very useful for the understanding of correlation and similarity between contaminants and factors of FA, and for the investigation of contaminant origins. It also showed that the similarity between factor scores and contaminant concentrations was proportional to the magnitudes of factor loadings for contaminants. This study represented that the combined analyses of chemometrics and kriging were very indispensable to the identification of groundwater contamination sources and origins, as well as for the spatial classification and assessment of groundwater quality.     

A semi-continuous measurement of gaseous ammonia and particulate ammonium concentrations in PM<Subscript>2.5</Subscript> in the ambient atmosphere

Ammonia has a short residence time in the atmosphere and rapidly neutralizes acid gases that occur near its source, requiring a rapid measurement system for ammonia and particulate ammonium concentrations to better understand their sources, temporal variation of ammonia emissions, and the formation of secondary ammonium aerosols. A semi-continuous measurement system, consisting of a diffusion scrubber, a particle growth chamber, an air-liquid separator, and a fluorescent detector, was developed to determine both gaseous ammonia (NH₃) and particulate ammonium (NH ₄ ⁺ ) in PM_2.5 in the ambient atmosphere of Gwangju, South Korea, during the months of March, April, July, and September of 2007. During the sampling periods, the average concentrations of ammonia and ammonium were found to be 2.33?±?1.29 μg/m³ and 1.89?±?0.99 μg/m³, respectively. Although the average gaseous ammonia concentration was highest in March, the particulate ammonium concentration was higher during the warmer season, reaching 2.08?±?1.07 μg/m³ and 2.32?±?0.94 μg/m³ in April and July, respectively, while only 1.68?±?0.61 μg/m³ in March and 1.24?±?0.99 μg/m³ in September. It is proposed that the higher availability of acid species during the warmer months produced a significant amount of particulate ammonium sulfate. Diurnal fluctuation of ammonia and ammonium during the warmer months showed that their peak time occurred at approximately 10:00 am. Both ammonia and ammonium concentrations were better correlated during the warmer months than during the cooler months. Further, the data suggest that the ammonia and ammonium were measured under well dispersed conditions, and multiple sources contributed to the ammonia at the sampling site.     

Polybrominated diphenyl ethers and polychlorinated biphenyls in sediments of southwest Taiwan: regional characteristics and potential sources

Very little information is available on the contamination of coastal sediments of Taiwan by PBDEs and PCBs. In this study, we determined the concentrations of 19 PBDE and 209 PCB congeners in 57 surface sediment samples to identify the possible sources of PBDEs and PCBs. The total PBDE and PCB concentrations ranged from below detection limit to 7.73 ng/g and 0.88-7.13 ng/g, respectively; these values are within the ranges observed for most coastal sediments worldwide. The PBDE congeners were dominated by BDE-209 (50.7-99.7%), with minor contributions from penta- and octa-BDEs. The signatures of PCB congeners suggested that PCB residues in Kaohsiung coast may be the legacy of past use or the result of ongoing inputs from the maintenance, repair and salvage of old ships. Principal component analysis of the congener-specific composition of PBDEs and PCBs revealed distinct regional patterns that are related to the use of commercial products.     

Representation of tropical storms in the northwestern pacific by the Modern-Era Retrospective analysis for research and applications

This study examines the tropical storms simulated in the Modern-Era Retrospective analysis for Research and Applications (MERRA) global atmospheric reanalysis for the recent 12 years (1998–2009), focusing on the tropical storm activity over the Northwestern Pacific. For validation, the International Best Track Archive for Climate Stewardship (IBTrACS) dataset is used as an observational counterpart. Climatological-mean features of the tropical storm genesis, tracks and their maximum intensity are the primary interests in this study. Regarding the genesis location of tropical storms, MERRA is reasonable in resolving major development regions over the South China Sea and the Northwestern Pacific close to the Philippines. The seasonal variation of the number of storms is also reproduced in a realistic way in MERRA, with peak values occurring from July to September. In addition, MERRA tends to reproduce the observed interannual variation of the number of tropical storms during the 12-years, though with a limited accuracy. The simulated paths toward higher latitudes are also reasonable in MERRA, where the reanalysis corresponds well with the observations in resolving frequent paths of westward moving storms and recurving storms toward the northeast. Regarding the intensity, MERRA captures the linear relationship between the minimum center pressure and the maximum wind speed near the surface at the maximum development. Some discrepancies from the observed features are found in the reanalysis, such as less frequent development of storms over the South China Sea and less frequent paths over this region. The reanalysis also does not attain the observed maximum intensity for the resolved tropical storms, particularly underestimating the center pressure. These deficiencies are likely related to limitations in the horizontal resolution and the parameterized physics of the data assimilation system.     

Characteristics of canopy turbulence over a deciduous forest on complex terrain

Canopy turbulence plays an important role in mass and energy exchanges at the canopy-atmosphere interface. Despite extensive studies on canopy turbulence over a flat terrain, less attention has been given to canopy turbulence in a complex terrain. The purpose of this study is to scrutinize characteristics of canopy turbulence in roughness sublayer over a hilly forest terrain. We investigated basic turbulence statistics, conditionally sampled statistics, and turbulence spectrum in terms of different atmospheric stabilities, wind direction and vertical structures of momentum fluxes. Similarly to canopy turbulence over a homogeneous terrain, turbulence statistics showed coherent structure. Both quadrant and spectrum analysis corroborated the role of intermittent and energetic eddies with length scale of the order of canopy height, regardless of wind direction except for shift of peak in vertical wind spectrum to relatively high frequency in the down-valley wind. However, the magnitude of the momentum correlation coefficient in a neutral condition was smaller than typical value over a flat terrain. Further scrutiny manifested that, in the up-valley flow, temperature skewness was larger and the contribution of ejection to both momentum and heat fluxes was larger compared to the downvalley flow, indicating that thermal instability and weaker wind shear in up-valley flow asymmetrically affect turbulent transport within the canopy.     

Performances of two instrumented laboratory models for the study of rainfall infiltration into unsaturated soils

Rainfall infiltration and suction variation in unsaturated soils must be taken into consideration in the analysis of most slope stability problems, particularly in the tropical regions where the annual precipitation is high. The process of rainfall infiltration into unsaturated soils is an extremely complex problem attributed to the non-linearity of the hydraulic property functions of the unsaturated soils. This paper describes in detail two instrumented laboratory models, i.e. one-dimensional soil column, and two-dimensional slope model used to provide experimental evidences for the transient suction variations in the unsaturated soils under certain rainfall conditions. The performances of the laboratory models were tested on four typical types of residual soils, i.e. sand-gravel, silty gravel, sandy silt, and silt (kaolin), and a two-layered soil system, i.e. sandy silt underlain by silty gravel. The results showed that the suction distributions for the single-layered homogeneous soils obtained from the simpler one-dimensional soil column were almost identical to that of two-dimensional slope model. However, the two-dimensional slope model should be employed for the two-layered soil system because of the dominant effect of the lateral flow mechanism. The capillary barrier effect was observed when a less permeable soil layer was underlain by a more permeable soil layer. The minimum suction value in soil is governed by the rainfall intensity, rainfall duration, and the saturated permeability of soil. The infiltration rate of the fine-grained soils that subjected to shrink and crack was independent of the soil permeability, but was significantly governed by the preferential flows developed in the soils.