Estimation of flood risk index considering the regional flood characteristics: a case of South Korea

Global warming is increasing the variability of climate change and intensifying hydrologic cycle components including precipitation, infiltration, evapotranspiration, and runoff. These changes increase the chance of more severe and frequent natural conditions, and limit ecosystem function and human activities. Adaptation to climate change requires assessment of the potential disaster risk. The objectives of this study were to estimate the flood risk index (FRI) considering regional flood characteristics at the national level and to prioritize the factors affecting flood risk through principal component analysis. FRI was estimated based on the Delphi survey results from 50 water resources experts in South Korea. The potential risk analysis was conducted for 229 local governments in South Korea. The results showed that natural and social factors were more influential flood risk factors to South Korea than administrative and economic and facility factors. Specifically, natural, social, administrative and economic, and facility factors were, respectively, highest at Jindo-Gun in Jennam-Do, Gumi-Si in Kyongsanbuk-Do, Dong-Gu in Incheon-Si, and Suwon-Si, Kyonggi-Do. Overall, the highest FRI is shown in Anyang-Si, Kyongggi-Do. The spatial distribution of the FRI was high in the southeastern coastal region and basins of the two biggest rivers in South Korea, and normalized flood frequency followed spatial patterns similar to FRIs. This study provided information on the relative flood risk index among administrative units for investment prioritization in flood risk management. In this regard, the suggested FRI is expected to significantly contribute to methodical and economic improvements in budget allocations for flood risk management.     

Metabolomic approach for age discrimination of Panax ginseng using UPLC-Q-Tof MS

An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-Tof MS)-based metabolomic technique was applied for metabolite profiling of 60 Panax ginseng samples aged from 1 to 6 years. Multivariate statistical methods such as principal component analysis and hierarchical clustering analysis were used to compare the derived patterns among the samples. The data set was subsequently applied to various metabolite selection methods for sophisticated classification with the optimal number of metabolites. The results showed variations in accuracy among the classification methods for the samples of different ages, especially for those aged 4, 5, and 6 years. This proposed analytical method coupled with multivariate analysis is fast, accurate, and reliable for discriminating the cultivation ages of P. ginseng samples and is a potential tool to standardize quality control in the P. ginseng industry.     

Network context and selection in the evolution to enzyme specificity

Enzymes are thought to have evolved highly specific catalytic activities from promiscuous ancestral proteins. By analyzing a genome-scale model of Escherichia coli metabolism, we found that 37% of its enzymes act on a variety of substrates and catalyze 65% of the known metabolic reactions. However, it is not apparent why these generalist enzymes remain. Here, we show that there are marked differences between generalist enzymes and specialist enzymes, known to catalyze a single chemical reaction on one particular substrate in vivo. Specialist enzymes (i) are frequently essential, (ii) maintain higher metabolic flux, and (iii) require more regulation of enzyme activity to control metabolic flux in dynamic environments than do generalist enzymes. Furthermore, these properties are conserved in Archaea and Eukarya. Thus, the metabolic network context and environmental conditions influence enzyme evolution toward high specificity.     

Assessing the effect of watershed slopes on recharge/baseflow and soil erosion

Aquatic ecosystems are threatened by increasing variability in the hydrologic responses. In particular, the health of river ecosystems in steeply sloping watersheds is aggravated due to soil erosion and stream depletion during dry periods. This study suggested and assessed a method to improve the adaptation ability of a river system in a steep watershed. For this, this study calibrated soil and water assessment tool (SWAT) for runoff and sediment, and quantified the changes in hydrologic responses such as groundwater recharge rate soil erosion and baseflow according to two scenarios for adjustment of the watershed slope (steep to mild). Here, one scenario was set by three measured slopes, and the other was set by fixing the entire watershed slopes with 5 %. Moreover, SWAT and web-based hydrograph analysis tool (WHAT) models were applied to estimate groundwater recharge, soil erosion, and baseflow in the Haean-myeon watershed in South Korea. The results show that the reduction of watershed slope increased groundwater recharge and baseflow, and decreased sediment. Specifically, groundwater recharge rate was increased from 257.10 to 364.60 mm, baseflow was increased from 0.86 to 1.19 m³/s, and sediment was decreased from 194.6 to 58.1 kg/km². Based on these results, the suggested method will positively contribute to aquatic ecosystems and farming environments in a steeply sloping watershed due to improvements in the quantity and quality of river water.