• Journal of Environmental Science International
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• v.30 no.11
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• pp.937-944
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• 2021

In this study, water resource topics, infrastructure, water supply, users, and economic indicators based on statistical annual standards for evaluating water welfare were selected by examining domestic and foreign water resource-related indicators. The level of water welfare was evaluated relative to 23 cities and counties in Daegu and Gyeongsangbuk-do using data from the Statistical yearbook, and places with high value of indicators urbanization and large populations were excellent in the infrastructure field, but overall analysis showed that small and medium-sized cities had higher levels. It is judged that it is necessary to develop continuous research and indicators that can evaluate and quantify the level of physical welfare that the people can feel by utilizing the results of this study. In future studies, it is necessary to systematically evaluate the level of water welfare by local governments in Korea through more diverse evaluation items and detailed indicators for each item so that it can be used as basic data for realizing water welfare.

• Korean Journal of Medicinal Crop Science
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• v.2 no.1
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• pp.7-13
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• 1994

This study was conducted to investigate the relationships between yearly variations of climatic factors and yearly variations of productivity in Alisma plantago L. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were collected from the Statistical Year Book of Seungju province, Reserach Report of Seungju Extension Station of Rural Development Administration, and farmers for 10 years from 1983 to 1992. The meteorological data gathered at the Seungju Weather Station for the same period were used to find out the relationships between climatic factors and productivity. Yearly variation of the amount of precipitation in October and the minimum temperature in November were large with coefficients of variation(C.V.) of 106.44, 144.08%, respectively, but the variation of the average temperature, maximum temperature, minimum temperature from July to September were relatively small. Fresh weight and dry weight of roots vary greatly with C. V. of 30.62, 31.85%, respectivly. Plant height and stem length show more or less small C. V. of 5.51, 6. 26%, respectively and leaf width, leaf length, number of stems and root diameter show still less variation. Correlation coefficients between maximum temperature in November and plant height, stem diamter, number of stems, root diamter and dry weight of roots are positively significant at the 5% level. There are high signficant positive correlations observed, between yield and yield components. The maximum temperature would be used as a predictive variable for the estimation of dry weight of roots and number of stems. Simple linear regression equations by the least square method are estimated for number of stems $(Y_1)$ and the maximum temperature in November(X) as $Y_1=4.7114+0.5333\;X\;(R^2=0.4410)$, and for dry weight of roots$(Y_2)$ and the maximum temperature in November(X) as $Y_2=55.0405+14.3233\;X\;(R^2=0.4511)$