• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.3
• /
• pp.567-577
• /
• 2015

Climate and land use changes have impact on availability water resource by hydrologic cycle change. The purpose of this study is to evaluate the hydrologic behavior by the future potential climate and land use changes in Anseongcheon watershed ($371.1km^2$) using SWAT model. For climate change scenario, the HadGEM-RA (the Hadley Centre Global Environment Model version 3-Regional Atmosphere model) RCP (Representative Concentration Pathway) 4.5 and 8.5 emission scenarios from Korea Meteorological Administration (KMA) were used. The mean temperature increased up to $4.2^{\circ}C$ and the precipitation showed maximum 21.2% increase for 2080s RCP 8.5 scenario comparing with the baseline (1990-2010). For the land use change scenario, the Conservation of Land Use its Effects at Small regional extent (CLUE-s) model was applied for 3 scenarios (logarithmic, linear, exponential) according to urban growth. The 2100 urban area of the watershed was predicted by 9.4%, 20.7%, and 35% respectively for each scenario. As the climate change impact, the evapotranspiration (ET) and streamflow (ST) showed maximum change of 20.6% in 2080s RCP 8.5 and 25.7% in 2080s RCP 4.5 respectively. As the land use change impact, the ET and ST showed maximum change of 3.7% in 2080s logarithmic and 2.9% in 2080s linear urban growth respectively. By the both climate and land use change impacts, the ET and ST changed 19.2% in 2040s RCP 8.5 and exponential scenarios and 36.1% in 2080s RCP 4.5 and linear scenarios respectively. The results of the research are expected to understand the changing water resources of watershed quantitatively by hydrological environment condition change in the future.

• Journal of Korea Water Resources Association
• /
• v.51 no.10
• /
• pp.905-916
• /
• 2018

The purpose of this study is to evaluate the climate change impact on watershed hydrology and flow duration in Geum River basin ($9,645.5km^2$) especially by extreme scenarios. The rainfall related extreme index, STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes) was adopted to select the future extreme scenario from the 10 GCMs with RCP 8.5 scenarios by four projection periods (Historical: 1975~2005, 2020s: 2011~2040, 2050s: 2041~2070, 2080s: 2071~2100). As a result, the 5 scenarios of wet (CESM1-BGC and HadGEM2-ES), normal (MPI-ESM-MR), and dry (INM-CM4 and FGOALS-s2) were selected and applied to SWAT (Soil and Water Assessment Tool) hydrological model. The wet scenarios showed big differences comparing with the normal scenario in 2080s period. The 2080s evapotranspiration (ET) of wet scenarios varied from -3.2 to +3.1 mm, the 2080s total runoff (TR) varied from +5.5 to +128.4 mm. The dry scenarios showed big differences comparing with the normal scenario in 2020s period. The 2020s ET for dry scenarios varied from -16.8 to -13.3 mm and the TR varied from -264.0 to -132.3 mm respectively. For the flow duration change, the CFR (coefficient of flow regime, Q10/Q355) was altered from +4.2 to +10.5 for 2080s wet scenarios and from +1.7 to +2.6 for 2020s dry scenarios. As a result of the flow duration analysis according to the change of the hydrological factors of the Geum River basin applying the extreme climate change scenario, INM-CM4 showed suitable scenario to show extreme dry condition and FGOALS-s2 showed suitable scenario for the analysis of the drought condition with large flow duration variability. HadGEM2-ES was evaluated as a scenario that can be used for maximum flow analysis because the flow duration variability was small and CESM1-BGC was evaluated as a scenario that can be applied to the case of extreme flood analysis with large flow duration variability.

• Journal of Korea Water Resources Association
• /
• v.51 no.10
• /
• pp.863-874
• /
• 2018

The purpose of this study is to evaluate the future climate change impact on stream aquatic ecology health of Han River watershed ($34,148km^2$) using SWAT (Soil and Water Assessment Tool) and random forest. The 8 years (2008~2015) spring (April to June) Aquatic ecology Health Indices (AHI) such as Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI) and Fish Assessment Index (FAI) scored (0~100) and graded (A~E) by NIER (National Institute of Environmental Research) were used. The 8 years NIER indices with the water quality (T-N, $NH_4$, $NO_3$, T-P, $PO_4$) showed that the deviation of AHI score is large when the concentration of water quality is low, and AHI score had negative correlation when the concentration is high. By using random forest, one of the Machine Learning techniques for classification analysis, the classification results for the 3 indices grade showed that all of precision, recall, and f1-score were above 0.81. The future SWAT hydrology and water quality results under HadGEM3-RA RCP 4.5 and 8.5 scenarios of Korea Meteorological Administration (KMA) showed that the future nitrogen-related water quality in watershed average increased up to 43.2% by the baseflow increase effect and the phosphorus-related water quality decreased up to 18.9% by the surface runoff decrease effect. The future FAI and BMI showed a little better Index grade while the future TDI showed a little worse index grade. We can infer that the future TDI is more sensitive to nitrogen-related water quality and the future FAI and BMI are responded to phosphorus-related water quality.

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