In general method to estimate the water supplies in the large-scale basin, indirect estimation method such as unit loading factor method has been used. However, the estimated water supplies are much different to the real water supplies used in the any basin because these general methods estimate them considering water supply demands only. Especially, water supplies for irrigation are big different to the real water supplies in which the water supplies for irrigation are depend on the weather conditions such as evaporation, basin conditions such as infiltration, the reservoir operation rule for irrigation water, and distribution methods. Thus, a new estimation method is developed to estimate the real water demands which is essential factors for the effective water resources operation in the basin. This method is for estimating the water supplies and return rates based on the survey of the irrigation reservoirs and the analysis of effects to the stream flows, return flows, and water supplies for irrigation which water supplies and return rates are used in the basin water management model. The water supply usages in each subbasin are validated by comparisons between the simulated discharges from the basin water management model and the discharges measured in the control points.

Estimation of crop consumptive use is a key term of agricultural water resource systems design and operation. The 10-year return period drought has special aspects as a reference period in design process of irrigation systems in terms of agricultural water demand analysis so that crop evapotranspiration (ETc) about the return period also has to be analyzed to assist understanding of crop water requirement of paddy rice. In this study, The ETc of 10-year return period drought was computed using frequency analysis by 54 meteorological stations. To find an optimal probability distribution, 8 types of probability distribution function were tested by three the goodness of fit tests including ${\chi}^2$(Chi-Square), K-S (Kolmogorov-Smirnov) and PPCC (Probability Plot Correlation Coefficient). Optimal probability distribution function was selected the 2-parameter Log-Normal (LN2) distribution function among 8 distribution functions. Using the two selected distribution functions, the ETc of 10-year return period drought was estimated for 54 meteorological stations and compared with prior study results suggested by other researchers.

This study is aimed at the development of a runoff forecasting model by using the Fuzzy inference system and Neural Network model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting. The Neuro-Fuzzy (NF) model were used in this study. The NF model, recently received a great deal of attention, improve the existing Neural Networks by the aid of the Fuzzy theory applied to each node. The study area is the downstreams of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model respectively. The schematic diagram method and the statistical analysis are conducted to evaluate the feasibility of rainfall-runoff modeling. The model accuracy was rapidly decreased as the forecasting time became longer. The NF model can give accurate runoff forecasts up to 4 hours ahead in standard above the Determination coefficient $(R^2)$ 0.7. In the comparison of the runoff forecasting using the NF and TANK models, characteristics of peak runoff in the TANK model was higher than ones in the NF models, but peak values of hydrograph in the NF models were similar.

This study is to grasp and analyse the temporal and spatial distribution of record-breaking heavy snowfall rarely occurred in the middle and southwest region of South Korea during March of 2004 and December of 2005 respectively. Snow cover area was extracted using the channels 1, 3 and 4 of NOAA AVHRR images and the snow depth distribution was spatially interpolated using snowfall data of meteorological stations. Using administration boundary and Digital Elevation Model from 1:5,000 NGIS digital map, the snowfall impact was assessed spatially and compared with the reports at that time. The damaged area by heavy snowfall over 15 cm snow depth could be identified successfully within the spatial extent of snowfall area extracted by NOAA AVHRR image.

The purpose of this study was to determine the optimum mix proportion of latex modified mortar for agricultural underwater concrete structures repair. The experimental variables included a latex and antiwashout admixture amount, binder-sand ratio, water-binder ratio. This study were evaluated a repair performance and environment effect of latex modified repair mortar for agricultural underwater concrete structures. The pH test was conducted to evaluated the environmental effect and the flow test was peformed to evaluated the workability. Also, compressive, flexural and bond tests were conducted. Test results show that the optimum mix proportion of latex modified repair mortar for agricultural underwater concrete structures, was achieved by 1:1.5 binder-sand ratio, 5% latex ratio (weight of binder), 1.3% antiwashout admixture ratio (weight of binder), 0.33 water-binder ratio and 10% silica lune replacement ratio (weight of cement). The environmental effect and repair performance of optimum mix proportion satisfied all target performance.

This study was performed to evaluate void ratio, compressive and flexural strengths, and pH properties according to the content ratio of rice husk ash, aggregate size, and neutral treatment time of porous concrete with content of rice husk ash produced as an agricultural by-product. The SEM results for cement mortar with a 5% rice husk ash for the weight of cement formed more C-S-H hydrates due to the $SiO_2$ of rice husk ash. In the XRD test, cement mortar with a 5% rice husk ash for the weight of cement registered a higher peak point of approximately $2{\theta}=20{\sim}25^{\circ}$ compared to cement mortar without rice husk ash. According to the results of the XRD and SEM tests, the $SiO_2$ that was a major chemical element of rice husk ash generated a large amount of calcium hydroxide in the early stage of the hydration process of cement leading to the formation of ettringite. The void ratio of porous concrete with rice husk ash decreased with increasing content ratio of rice husk ash. In addition, the void ratio of porous concrete with rice husk ash decreased compared to porous concrete without rice husk ash. The compressive and flexural strength of porous concrete with a 5% and 10% content ratio of rice husk ash slightly increased compared to concrete without rice husk ash. The pH value of porous concrete rapidly decreased immediately after neutral treatment. Then, it gradually increased and decreased again after 14 days. However, the pH value was nearly the same regardless of neutral treatment time in 28 curing days. Also, for neutral treatment, the pH value of porous concrete showed appropriate pH levels (less than 9.5) in all mixtures for planting at 28 curing days.

The LRA(Logistic Regression Analysis) conducts a quantitative analysis by collecting a lot of samples and the AHP(Analytic Hierarchy Program) makes use of expert decision influenced by subjective judgment to a certain degree. This study is to suggest a combination method in mapping landslide hazard by giving equal weight for the result of LRA and AHP. Topographic factors(slope, aspect, elevation), soil dram, soil depth and land use were adopted to classify landslide hazard areas. The three methods(LRA, AHP, the combined approach) was applied to a $520km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9% matching rate for the real landslide sites comparing with the classified areas of high-risk landslide While LRA and AHP Showed 46.1% and 48.7% matching rates respectively. Further studies are recommended to find the optimal combining weight of LRA and AHP with more landslide data.

Defining the correlations between rural amenities, while difficult, is important for the adequate and efficient development of these amenities. In this research, an Interactional Information Measuring Technique(IIMT) using Information Gathering and Utilizing System(IGUS) was developed to objectively analyze the correlations between abstract ideas. In order to analyze correlations between rural amenities, this model used the Korean Dusan World Encyclopedia as IGUS and the relative interactional information was measured. The correlations between rural amenities were analyzed objectively using IIMT with the results satisfying the basic conditions of interactional information suggested in this research.

This paper suggests a hierarchial method to select the target sites for the nonpoint source pollution management considering factors which reflect the interrelationships of significant outflow characteristics of nonpoint source pollution at given sites. The factors consist of land slope, delivery distance to the outlet, effective rainfall, impervious area ratio and soil loss. The weight of each factor was calculated by an analytic hierarchy process(AHP) algorithm and the resulting influencing index was defined from the sum of the product of each factor and its computed weight value. The higher index reflect the proposed target sites for nonpoint source pollution management. The proposed method was applied to the Baran HP#6 watershed, located southwest from Suwon city. The Agricultural Nonpoint Pollution Source(AGNPS) model was also applied to identify sites contributing significantly to the nonpoint source pollution loads from the watershed. The spatial correlation between the two results for sites was analyzed using Moran's I values. The I values were $0.38{\sim}0.45$ for total nitrogen(T-N), and $0.15{\sim}0.22$ for total phosphorus(T-P), respectively. The results showed that two independent estimates for sites within the test water-shed were highly correlated, and that the proposed hierarchial method may be applied to select the target sites for nonpoint source pollution management.