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In this study, we characterized the variation of sampling errors using the Waymire-Gupta-rodriguez-Iturbe multi-dimensional rainfall model (WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considering in this study are those far using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of mentally rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather norma1 to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain area than in the down stream plain area.

This study introduces an integrated decision support system (DSS) for the water supply system in Fukuoka City, Japan. The objective is to conceive a comprehensive tool that may aid decision-makers to derive the best water supply alternatives from a multi-reservoir system in order to minimize the long-term drought damages and threat of water shortage. The present DSS consists of graphical user interface (GUI), a database manager, and mathematical models for runoff analysis, water demand forecasting, and reservoir operation. The methodology applied explicitly integrates the drought risk assessment based on the concept of reliability, resiliency, and vulnerability, as constraints to derive the management operation. The application of the DSS to the existing water supply system in Fukuoka City was found to be an efficient tool to facilitate the examination of a sequence of water supply scenarios toward an improved performance of the actual water supply system during periods of drought.

A grid-based KIneMatic wave soil-water EROsion and deposition Model (KIMEROM) that predicts temporal variation and spatial distribution of sediment transport in a watershed was developed. This model uses ASCII-formatted map data supported from the regular gridded map of GRASS (U.S. Army CERL, 1993)-GIS (Geographic Information Systems), and generates the distributed results by ASCIIl-formatted map data. For hydrologic process, the kinematic wave equation and Darcy equation were used to simulate surface and subsurface flow, respectively (Kim, 1798; Kim et al., 1993). For soil erosion process, the physically-based soil erosion concept by Rose and Hairsine (1988) was used to simulate soil-water erosion and deposition. The model adopts sing1e overland flowpath algorithm and simulates surface and subsurface water depth, and sediment concentration at each grid element (or a given time increment. The model was tested to a 162.3 km$^2$ watershed located in the tideland reclaimed area of South Korea. After the hydrologic calibration for two storm events in 1999, the results of sediment transport were presented for the same storm events. The results of temporal variation and spatial distribution of overland flow and sediment areas are shown using GRASS.

As one of advanced uses of radar, a physically based rainfall prediction method which uses a conceptual rainfall model assimilated by information from volume scanning radar is shown. As another example of advanced utilization of weather radar, results from analyzing a hierarchical time-scale structure in dependency of rainfall distribution en topography are shown.

The daily inflow is apparently one of nonlinear and complicated phenomena. The nonlinear and complexity make it difficult to model the prediction of daily flow, but attractive to try the neural networks approach which contains inherently nonlinear schemes. The study focuses on developing the forecasting models of daily inflows to a large dam site using neural networks. In order to reduce the error caused by high or low outliers, the back propagation algorithm which is one of neural network structures is modified by combining a regression algorithm. The study indicates that continuous forecasting of a reservoir inflow in real time is possible through the use of modified neural network models. The positive effect of the modification using tole regression scheme in BP algorithm is showed in the low and high ends of inflows.

Methods to measure and estimate transpiration of a forest composed of evergreen broad-leaved trees (Pasania edulis Makino) are studied. Heat pulse velocity has been measured along with soil moisture and micrometeorological factors at the Fukuoka Experimental Forest, the Research Institute of Kyushu University Forests in Fukuoka, Japan (33$^{\circ}$38'N, 130$^{\circ}$31'E, alt. 75m). Tree cutting measurement was conducted to convert the heat pulse velocity into sap flow and transpiration. A big leaf model to calculate transpiration and Interception loss is examined and the estimated values are compared with the measured values obtained from the heat pulse measurement. The results show that 1) Pasania edulis Makino posessing radial pore structure had relatively high water content and high heat pulse velocity even within the central part of the stem near the pith, 2) the heat pulse velocity was well correspond to the water uptake in the tree cutting measurement, 3) the estimation of sap flow based on the heat pulse velocity is accurate, and 4) the big leaf model using the parameters obtained from measurement of a portable photosynthesis system in one day in summer gives reasonable estimation of transpiration independent of seasons and weather.

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Anticipated water scarcity in the first half of this century is one of the most concerned international issues. However, even though the issue has an international impact and world wide monitoring is critical, there are limited number of global estimates at present. In this study, annual water availability was derived from annual runoff estimated by land surface models using Total Runoff Integrating Pathways (TRIP) with 0.5 degree by 0.5 degree longitude/latitude resolution globally. Global distribution of water withdrawal for each sector in the same horizontal spatial resolution was estimated based on country-base statistics of municipal water use, industrial water use, and agricultural intake, using global geographical information system with global distributions of population and irrigated crop land area. The total population under water stress estimated for 1995 corresponded very well with former estimates, however, the number is highly depend on how to assume the ratio how much water from outside of the region can be used for water resources within the region. It suggests the importance of regional studies evaluating the possibility of water intake as well as the validity of the investment for water resources withdrawal facilities.

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