• Journal of Wetlands Research
• /
• v.18 no.2
• /
• pp.154-165
• /
• 2016

Recently, the frequency of extreme rainfall event has increased due to climate change and impermeable area also has increased due to rapid urbanization. Therefore, we ought to prepare countermeasures for flood reduction to reduce the damage. To consider climate change, the frequency based rainfall was calculated according to the aimed period(reference : 1971~2010, Target period I : 2011~2040, Target period II : 2041~2070, Target period III : 2071~2100) and the flood discharge was also calculated by climate change using HEC-HMS model. Also, the flood elevation was calculated by each alternative through HEC-RAS model, setting 5 sizes of drainage pumps and reservoirs respectively. The flood map was constructed using topographical data and flood elevation, and the economic analysis was conducted for reduction of flood damage using Multi dimension - Flood Damage Analysis, MD-FDA. As a result of the analysis on the flood control effect, a head of drainage pump was reduced by 0.06m up to 0.44m while it was reduced by 0.01m up to 1.86m in the case of a detention pond. The flooded area shrunk by up to 32.64% from 0.3% and inundation depth also dropped. As a result of a comparison of the Benefit/Cost index estimated by the economic analysis, detention pond E in period I and pump D in period II and III were deemed appropriate as an alternative for climate change. The results are expected to be used as good practices when implementing the flood control works considering climate change.

• Journal of Korea Water Resources Association
• /
• v.55 no.11
• /
• pp.931-939
• /
• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.26 no.2
• /
• pp.127-139
• /
• 2024

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.

• Korean Journal of Ecology and Environment
• /
• v.34 no.1 s.93
• /
• pp.1-8
• /
• 2001

During April 1993 to November 1994, cations, anions, and conductivity were analyzed to examine how summer monsoon influences the ionic content of Taechung Reservoir, Korea. Interannual variability of ionic content reflected hydrological characteristics between the two years(high-flood year in 1993 vs. draught year in 1994). Cations, anions and conductivity were lowest during peak inflow in 1993 and highest during a drought in 1994. Floods in 1993 markedly decreased total salinity as a result of reduced Ca$^{2+}$ and HCO$_{3}\;^{-}$ and produced extreme spatial heterogeneity (i.e., longitudinal, vertical, and horizontal variation) in ionic concentrations. The dominant process modifying the longitudinal (the headwaters-to-downlake) and vertical (top-to-bottom) patterns in salinity was an interflow current during the 1993 monsoon. The interflow water plunged near a 27${\sim}$37 km-location (from the dam) of the mid-lake and passed through the 10${\sim}$30m stratum of the reservoir, resulting in an isolation of epilimnetic high conductivity water (>100 ${\mu}$S/cm) from advected river water with low conductivity (65${\sim}$75 ${\mu}$S/cm), During postmonsoon 1993, the factors regulating salinity differed spatially; salinity of downlake markedly declined as a result of dilution through the mixing of lake water with river water, whereas in the headwaters it increased due to enhanced CaCO$_{3}$ (originated from limestone/metamorphic rock) of groundwaters entering the reservoir. This result suggests an importance of the basin geology on ion compositions with hydrological characteristics. In 1994, salinity was markedly greater (p<0.001) relative to 1993 and ionic dilution did not occur during the monsoon due to reduced inflow. Overall data suggest that the primary factor influencing seasonal ionic concentrations and compositions in this system is the dilution process depending on the intensity of monsoon rainfall.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.4
• /
• pp.264-272
• /
• 2013

Climate changes have caused not only changes in the frequency and intensity of extreme climate events, but also temperature and precipitation. The damages on agricultural production system will be increased by heavy rainfall and snow. In this study we assessed vulnerability of crop cultivation facility and animal husbandry facility by heavy rain in 232 agricultural districts. The climate data of 2000 years were used for vulnerability analysis on present status and the data derived from A1B scenario were used for the assessment in the years of 2020, 2050 and 2100, respectively. Vulnerability of local districts was evaluated by three indices such as climate exposure, sensitivity and adaptive capacity, and each index was determined from selected alternative variables. Collected data were normalized and then multiplied by weight value that was elicited in delphi investigation. Jeonla-do and Gangwon-do showed higher climate exposures than the other provinces. The higher sensitivity to abnormal weather was observed from the regions that have large-scale cultivation facility complex compared to the other regions and vulnerability to abnormal weather also was higher at these provinces. In the projected estimation based on the SRES A1B, the vulnerability of controlled agricultural facility in Korea totally increased, especially was dramatic between 2000's and 2020 year.