In this study, the hydraulic gradient was calculated using the groundwater level and rainfall observed in the Hyogyo-ri area for a year, and the change in the hydraulic gradient according to the rainfall was analyzed. It was found that the groundwater level increased as the rainfall increased in all groundwater wells in the research site, and the groundwater level rise decreased as the altitude of the groundwater well increased. The hydraulic gradient in the research site ranged from 0.016 to 0.048, decreasing during rainfall and increasing after the end of the rainfall. As the rainfall increased, the groundwater level rise in the low-altitude area was more than the high-altitude area, and the hydraulic gradient decreased due to the difference in groundwater level rise according to the altitude. Through this study, it was found that the influence of rainfall is dominant for the fluctuation of the hydraulic gradient in the unconfined aquifer.

Moving average precipitation provides periodic precipitation patterns by solving precipitation irregularities. However, due to uncertain moving average periods, excessive data smoothing occurs, which limit the possibility to analyze groundwater levels in the short term. Nonetheless, groundwater level fluctuation can compensate these limitations as it can calculate appropriately for unit time and verify the effect of precipitation penetrated into groundwater in a short time period. In this study, the characteristics of groundwater level were evaluated using groundwater level fluctuation to compensate for limitations of groundwater level analysis using moving average precipitation. In addition, the groundwater quality was investigated using the electrical conductivity fluctuation. The study site was Hyogyo-ri, Yesan-si, Chungcheongnam-do. Four observation wells and an automated weather system were used. The correlation between groundwater level fluctuation and precipitation (Case 1) and the correlation between groundwater level and moving average precipitation (Case 3) were compared. In the analysis for 1 hour data, the correlation coefficient of Case 1 was higher than that of Case 3, and in the analysis for 1 day data, the correlation coefficient of Case 3 was higher than that of Case 1.

In this study, the necessity for a village unit Automatic Weather System (AWS) was suggested to obtain correct agricultural weather information by comparing the data of AWS of the weather station with the data of AWS installed in agricultural villages 7 km away. The comparison sites are Hyogyo-ri and Hongseong weather station. The seasonal and monthly averaged and cumulative values of data were calculated and compared. The annual time series and correlation was analyzed to determine the tendency of variation in AWS data. The average values of temperature, relative humidity and wind speed were not much different in comparison with each season. The difference in precipitation was ranged from 13.2 to 91.1 mm. The difference in monthly precipitation ranged from 1.2 to 75.4 mm. The correlation coefficient between temperature, humidity and wind speed was ranged from 0.81 to 0.99 and it of temperature was the highest. The correlation coefficient of precipitation was 0.63 and the lowest among the observed elements. Through this study, precipitation at the weather station and village unit area showed the low correlation and the difference for a quantitative comparison, while the elements excluding precipitation showed the high correlation and the similar annual variation pattern.