In assessing the impact of climate change, the use of a multimodel ensemble (MME) is required to quantify uncertainties between scenarios and produce downscaled outlines for the simulation of climate under the influence of different factors including topography. This study of climate change scenarios from 13 global climate models (GCMs) assesses the impacts of future climate change. Unlike South Korea, North Korea lacks studies using climate change scenarios of the Coupled Model Intercomparison Project Phase 5 (CMIP5) and only recently did the country start the projection of extreme precipitation episodes. As such, one of the main purposes of this study is to predict changes in the average climatic conditions of North Korea in the future. The result of comparing downscaled climate change scenarios with observation data for a reference period indicates the high applicability of the MME. Furthermore, this study classifies climatic zones by applying the Köppen–Geiger climatic zones classification to the MME, which is validated for future precipitation and temperature. The result suggests that the continental climate that covers the inland area for the reference climate is expected to shift into the temperate climate. Moreover, the coefficient of variation (CV) in the temperature ensemble is particularly low for the southern coast of the Korean Peninsula, and, accordingly, a high possibility of the shifting climatic zone of the coast is predicted.

Precipitation is essential for understanding hydrological processes and identifying the characteristics that must be considered to protect human lives and property from natural disasters. Hydrological analyses assume that precipitation shows stationarity. However, because of the recent changes in climate, the stationarity of climate data has been widely debated, and a need has arisen to analyze its nonstationary nature. In this study, we reviewed a method to analyze the stationarity of annual precipitation data from 37 meteorological stations that have recorded data for more than 45 years. Six stations that showed abnormal precipitation during the previous year were selected to evaluate the normality of future precipitation. The results showed that a significant trend was present in four out of 37 stations with unstable precipitation in 22 stations and persistent precipitation in 4 stations. The stationarity analysis of future annual precipitation using climate change scenarios suggested that no trend would be present in 11 stations and that unstable precipitation would be present in six stations. Persistent precipitation was identified in four stations. A comparison between the historical and predicted precipitation data conducted with the climate change scenarios showed that an increasing number of stations presented nonstationarity. Therefore, both stationarity and nonstationarity should be considered when performing hydrological analyses using annual precipitation data in Korea. Accordingly, prior to conducting any such analyses, the effect of climate change on annual precipitation should also be considered.

The purpose of this study is to predict the behaviour of debris flow under climate change. The behaviour of debris flow on the slope and its mechanism is evaluated through numerical simulations using the climate change scenario Representative Concentration Pathways (RCP) 4.5 and RCP 8.5, and the developed numerical model is applied to the analysis of real areas. The results from the application of the numerical model based on climate change in this study to the Gangwon region in Korea indicated that the flow discharge and flow depth of debris flow increase drastically as the return period is longer, and the Future 2 case, a future target period, showed the largest peak value of the flow discharge of debris flow with a large value of wave amplitude on the distribution curve for the debris flow discharge. In the case of flow depth, even though the wave amplitude of flow depth slightly increased as the year increased, its distribution shared a similar tendency. The value of flow depth was high. It is expected that the results of this study will provide information necessary to predict damage due to debris flow in the climate-changing future, and to prevent damage to human life in coastal areas.

Climate change significantly affects water supply availability due to changes in the magnitude and seasonality of runoff and severe drought events. In the case of Korea, despite high water supply ratio, more populations have continued to suffer from restricted regional water supplies. Though Korea enacted the Long-Term Comprehensive Water Resources Plan, a field survey revealed that the regional government organizations limitedly utilized their drought-related data. These limitations present a need for a system that provides a more intuitive drought review, enabling a more prompt response. Thus, this study presents a rating curve for the available number of water intake days per flow, and reviews and calibrates the Soil and Water Assessment Tool (SWAT) model mediators, and found that the coefficient of determination, Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) from 2007 to 2011 were at 0.92, 0.84, and 7.2%, respectively, which were “very good” levels. The flow recession curve was proposed after calculating the daily long-term flow and extracted the flow recession trends during days without precipitation. In addition, the SWAT model’s flow data enables the quantitative evaluations of the number of available water intake days without precipitation because of the high hit rate when comparing the available number of water intake days with the limited water supply period near the study watershed. Thus, this study can improve drought response and water resource management plans.

This paper proposes a disaster risk assessment system for the natural disaster with Jenks Natural Breaks Classification. The exposure indicators and vulnerability indicators are organized to disaster risk factors for the each receptors. The receptors evaluated the risk assessment are 9 and composed of people, industry, public facilities, educational and research facilities, medical and welfare facilities, amenity facilities, agriculture, livestock industry, and roads. All indicators are composed of 107,555 grid-based data having the codes of the region in the country. With Jenks natural breaks classification, the disaster risk assessment criteria for each receptors were presented per the disaster risk grade (Level 1 ~ Level 4). All of the criteria were evaluated with the grid-base data per the receptors and the evaluated results were presented by the maps of Korea. Through this study, the disaster risk assessment criteria can be used as the reference and forecasting for the natural disaster in Korea.