This study has purpose on deducting problems of evacuation plan for vulnerable populations in disaster and suggesting improvement plan through analysis of disaster weakness in domestic rural region aiming at vulnerable populations in disaster like old people containing most of domestic rural population, sometimes being in blind spot of safety when landslide or disaster occur. As a result, we could know that rural regions have high proportion of vulnerable populations in disaster like old people, also being so weak to landslide and slope collapse. So we suggested development of manual describing prevention of disaster and evacuation for vulnerable populations in disaster like old people and disaster evacuation organization for house and minimizing solution for damage of human life through improvement of steep slope evaluation criteria.

This study is to estimate the spatial soil moisture using multiple linear regression model (MLRM) and 15 minutes interval Land Surface Temperature (LST) data of Communication, Ocean and Meteorological Satellite (COMS). For the modeling, the input data of COMS LST, Terra MODIS Normalized Difference Vegetation Index (NDVI), daily rainfall and sunshine hour were considered and prepared. Using the observed soil moisture data at 9 stations of Automated Agriculture Observing System (AAOS) from January 2013 to May 2015, the MLRMs were developed by twelve scenarios of input components combination. The model results showed that the correlation between observed and modelled soil moisture increased when using antecedent rainfalls before the soil moisture simulation day. In addition, the correlation increased more when the model coefficients were evaluated by seasonal base. This was from the reverse correlation between MODIS NDVI and soil moisture in spring and autumn season.

Soil erosion has been issued in many countries since it causes negative impacts on ecosystem at the receiving water bodies. Therefore best management practices to resolve the problem in a watershed have been developed and implemented. As a prior process, there is a need to define soil erosion level and to identify the area of concern regarding soil erosion so that the practices are effective as they are designed. Universal Soil Loss Equation (USLE) were developed to estimate potential soil erosion and many Geographic Information System (GIS) models employ USLE to estimate soil erosion. Sediment Assessment Tool for Effective Erosion Control (SATEEC) is one of the models, the model provided several opportunities to consider various watershed peculiarities such as breaking of slope length, monthly variation of rainfall, crop growth at agricultural fields, etc. SATEEC is useful to estimate soil erosion, however the model can be implemented with ArcView software that is no longer used or hard to use currently. Therefore SATEEC based on ArcView was rebuild for the ArcGIS software with all modules provided at the previous version. The rebuilt SATEEC, ArcSATEEC, was programmed in ArcPy and works as ArcGIS Toolset and allows considering monthly variations of rainfall and crop growth at any watershed in South-Korea. ArcSATEEC was applied in Daecheong-dam watershed in this study, monthly soil erosion was estimated with monthly rainfall and crop growth variation. Annual soil erosion was computed by summing monthly soil erosion and was compared to the conventional approach to estimate annual soil erosion. The annual soil erosion estimated by the conventional approach and by summing monthly approach did not display much differences, however, ArcSATEEC was capable to provide monthly variation of soil erosion.

Recent studies about irrigation water use have focused on agricultural reservoir operation in irrigation period. At the same time, it is significant to store water resource in reservoir during non-irrigation period in order to secure sufficient water in early growing season. In this study, Representative Concentration Pathways (RCP) 4.5, 8.5 scenarios with the Global Climate Model (GCM) of The Second Generation Earth System Model (CanESM2) were downscaled with bias correlation method. Cumulative precipitation during non-irrigation season, October to March, was analyzed. Interaction between cumulative precipitation and carry-over storage was analyzed with linear regression model for ten study reservoirs. Using the regression model, reservoir drought response ability was evaluated with expression of excess and deficiency. The results showed that future droughts will be more severe than past droughts. Especially in case of non-exceedance probability of 10%, drought in southern region seemed to be serious. Nine study reservoirs showed deficiency range from 10% to 55%, which turned out to be vulnerable for future drought. Only Jang-Chan reservoir was secure for early growing season in spite of drought with deficiency of 8% and -2%. The results of this study represents current agricultural reservoirs have vulnerability for the upcoming drought.

Climate change causes changes in rainfall patterns, temperature and drought frequency. Climate change impact influences on water management and crop production. It is critical issue in agricultural industry. Rice is a staple cereal crop in South Korea and Korea uses a ponding system for its paddy fields which requires a significant amount of water. In addition, water supply has inter-relationship with crop production which indicates water productivity. Therefore, it is important to assess overall impacts of climate change on water resource and crop production. A water footprint concept is an indicator which shows relationship between water use and crop yield. In addition, it generally composed of three components depending on water resources: green, blue, grey water. This study analyzed the change trend of water footprint of paddy rice under the climate change. The downscaled climate data from HadGEM3-RA based on RCP 8.5 scenario was applied as future periods (2020s, 2050s, 2080s), and historical climate data was set to base line (1990s). Depending on agro-climatic zones, Suwon and Jeonju were selected for study area. A yield of paddy rice was simulated by using FAO-AquaCrop 5.0, which is a water-driven crop model. Model was calibrated by adjusting parameters and was validated by Mann-Whitney U test statistically. The means of water footprint were projected increase by 55 % (2020s), 51 % (2050s) and 48 % (2080s), respectively, from the baseline value of $767m^2/ton$ in Suwon. In case of Jeonju, total water footprint was projected to increase by 46 % (2020s), 45 % (2050s), 12 % (2080s), respectively, from the baseline value of $765m^2/ton$. The results are expected to be useful for paddy water management and operation of water supply system and apply in establishing long-term policies for agricultural water resources.

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of $R^2$ and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ${\pm}1^{\circ}C{\sim}{\pm}3^{\circ}C$ and average annual rainfall to ${\pm}5%{\sim}{\pm}30%$, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.

Along with climate change, it is reported that the scale and the frequency of extreme climate events (e.g. heavy rain, typhoon, etc.) show unstable tendency of increase. In case of Korea, also, the frequency of heavy rainfall shows increasing tendency, thus causing natural disaster damage in downtown and agricultural areas by rainfall that exceeds the design criteria of hydraulic structures. In order to minimize natural disaster damage, it is necessary to analyze how extreme precipitation event changes under climate change. Therefore a new design criteria based on non-stationarity frequency analysis is needed to consider a tendency of future extreme precipitation event and to prepare countermeasures to climate change. And a quantitative and objective characteristic analysis could be a key to preparing countermeasures to climate change impact. In this study, non-stationarity frequency analysis was performed and inundation risk indices developed by 4 inundation characteristics (e.g. inundation area, inundation depth, inundation duration, and inundation radius) were assessed. The study results showed that future probable rainfall could exceed the existing design criteria of hydraulic structures (rivers of state: 100yr-200yr, river banks: 50yr-100yr) reaching over 500yr frequency probable rainfall of the past. Inundation characteristics showed higher value in the future compared to the past, especially in sections with tributary stream inflow. Also, the inundation risk indices were estimated as 0.14 for the past period of 1973-2015, and 0.25, 0.29, 1.27 for the future period of 2016-2040, 2041-2070, 2071-2100, respectively. The study findings are expected to be used as a basis to analyze future inundation damage and to establish management solutions for rivers with inundation risks.

In this study, the validity and applicability of the multipurpose fishway which has been constructed for the upstream migration of fish at Chuksan river in Uljin is assessed and analyzed by a commercial software. The upper slab types of fishway in this investigation are reinforced concrete slab (S1 type) and reinforced concrete slab with steel plate (S2 type). The three different sizes of subway passage ($0.8m{\times}0.1m$, $0.8m{\times}0.2m$, $0.8 m{\times}0.3m$) and velocities (0.6 m/s, 1.2 m/s, 1.8 m/s) of Chuksan fishway was investigated and compared for the Chuksan in government design code. The analysis showed that the maximum stress and bending moment of S1 type decreased 1~21 % and 12~27 % compared to the Chuksan in government design code, respectively. Also, the maximum stress of and bending moment of S2 type decreased 11~32 % and 27~39 %. From the numerical analysis, it was found that the S2 type was greatly effective and the subway passage size of $0.8m{\times}0.2m$ was most safe. This result can be utilized to be the basic data for design of the Multipurpose fishway.

Biomass gasification produces syngas or producer gas as low calorific fuel gas that can be used as a fuel for combustion or prime movers as well as chemical synthesis. Internal combustion engines are readily available with lower costs and easily used for producing distributed power using biomass syngas. In this study, a dual fuel diesel engine was used to evaluate its performance when biomass syngas is used for fuel. The engine was originally developed for biogas application with a diesel engine with a 2,607 cc displacement. Both diesel fuel and syngas consumptions were observed at the different load conditions. The results indicate that the dual fuel engine showed a reasonably good performance and up to 63 % of diesel fuel saving.