• Economic and Environmental Geology
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• v.57 no.2
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• pp.107-117
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• 2024

The objective of this study is to estimate riverbed fluctuations and the volume of aggregate extraction attributable to climate change. Rainfall-runoff modeling, utilizing the SWAT model based on climate change scenarios, as well as long-term riverbed fluctuation modeling, employing the HEC-RAS model, were conducted for the Nonsan River basin. The analysis of rainfall-runoff and sediment transport under the SSP5-8.5 scenario for the early part of the future indicates that differences in annual precipitation may exceed 600 mm, resulting in a corresponding variation in the basin's sediment discharge by more than 30,000 tons per year. Additionally, long-term riverbed fluctuation modeling of the lower reaches of the Nonsan Stream has identified a potential aggregate extraction area. It is estimated that aggregate extraction could be feasible within a 2.455 km stretch upstream, approximately 4.6 to 6.9 km from the confluence with the Geum River. These findings suggest that the risk of climate crises, such as extreme rainfall or droughts, could increase due to abnormal weather conditions, and the increase in variability could affect long-term aggregate extraction. Therefore, it is considered important to take into account the impact of climate change in future long-term aggregate extraction planning and policy formulation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.235-243
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• 2021

River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.