• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.168-181
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• 2024

Constructed wetlands (CWs) deliver a range of ecosystem services, including the removal of contaminants, sequestration and storage of carbon, and enhancement of biodiversity. These services are facilitated through hydrological and ecological processes such as infiltration, adsorption, water retention, and evapotranspiration by plants and microorganisms. This study investigated the correlations between microbial populations, soil physicochemical properties, and treatment efficiency in a horizontal subsurface flow constructed wetland (HSSF CW) treating runoff from roads and parking lots. The methods employed included storm event monitoring, water quality analysis, soil sampling, soil quality parameter analysis, and microbial analysis. The facility achieved its highest pollutant removal efficiencies during the warm season (>15℃), with rates ranging from 33% to 74% for TSS, COD, TN, TP, and specific heavy metals including Fe, Zn, and Cd. Meanwhile, the highest removal efficiency was 35% for TOC during the cold season (≤15℃). These high removal rates can be attributed to sedimentation, adsorption, precipitation, plant uptake, and microbial transformations within the CW. Soil analysis revealed that the soil from HSSF CW had a soil organic carbon content 3.3 times higher than that of soil collected from a nearby landscape. Stoichiometric ratios of carbon (C), nitrogen (N), and phosphorus (P) in the inflow and outflow were recorded as C:N:P of 120:1.5:1 and 135.2:0.4:1, respectively, indicating an extremely low proportion of N and P compared to C, which may challenge microbial remediation efficiency. Additionally, microbial analyses indicated that the warm season was more conducive to microorganism growth, with higher abundance, richness, diversity, homogeneity, and evenness of the microbial community, as manifested in the biodiversity indices, compared to the cold season. Pollutants in stormwater runoff entering the HSSF CW fostered microbial growth, particularly for dominant phyla such as Proteobacteria, Actinobacteria, Acidobacteria, and Bacteroidetes, which have shown moderate to strong correlations with specific soil properties and changes in influent-effluent concentrations of water quality parameters.