The objectives of this study are an establishment of developing strategies of environment-friendly agriculture(EFA) around the Daecheong and Chungju Dam. To establish strategic target, a series of farm household survey were conducted for farmers residing around the Daecheong and Chungju Dam. The sample size of the survey is 233 respectively. As a result, the farmers recognized that EFA is fit for around Daecheong and Chungju Dam as well as the prospects is very bright. In conclusion, the main streams to develop EFA are come up with vision and purpose around dam area, systematic connection of environment-friendly agricultural capability around dam area, construction of organic resource circulation system, and connecting propulsion with green tourism including quantitative and qualitative upgrade of environment-friendly agricultural products.

The seasonal variation and frequency of rainfalls of Korea peninsula in Changma period show strong local weather phenomenon because of it's topographical and geographical factors in Northeast side of Asia. Based on weather entropy(statistical parameter)-the amount of average weather information-and information ratio, we can define each area's weather representativeness, which can show us more constant form included topographical and geographical factors and seasonal variation. The data used for this study are the daily precipitation and cloudiness during the recent ten years(1990-1999) at the 73 stations in Korea. To synthesize weather Entropy, information ratio of decaying tendency and half-decay distance, Seoul's weather representativeness has the smallest in Summer Changma period. And Puyo has the largest value in September.

This study was carried out to evaluate the artificial neural network algorithm for water quality forecasting in Chungju lake, north Chungcheong province. Multi-layer perceptron(MLP) was used to train artificial neural networks. MLP was composed of one input layer, two hidden layers and one output layer. Transfer functions of the hidden layer were sigmoid and linear function. The number of node in the hidden layer was decided by trial and error method. It showed that appropriate node number in the hidden layer is 10 for pH training, 15 for DO and BOD, respectively. Reliability index was used to verify for the forecasting power. Considering some outlying data, artificial neural network fitted well between actual water quality data and computed data by artificial neural networks.

일반적으로 저수지 최적운영의 목적은 한정된 수자원을 여러 목적으로 최적 분배하여 얻는 이익의 최대화와, 홍수 발생으로 인한 과잉 수량을 안전하게 배제시킴으로써 홍수 취약지역의 피해를 최소화시키는 것으로 구분할 수 있다. 저수지 운영에 대한 연구사를 고찰해 볼 때, 지난 수십 년간 첫 번째 영역에 연구가 집중되었음을 알 수 있다. 본 연구의 목적은, 충주 저수지의 홍수조절을 위한 저수지 최적운영의 방법론 개발에 중점을 두고, 하류 홍수피해 최소화와 댐 안