Fig. 1 The group without notable performance degradation
Fig. 2 The group with notable performance degradation
Table 1 Selection of study sites according to geographical classification system in Korea
Table 2 Variables and Role Relationships between Response Variability and Vulnerability of Climate Change regarding to Pumping Stations
Table 4 Selection of parameters for meteorological data analysis
Table 5 Result of statistical analysis by POLS, RE, and LASSO regression method
Table 6 Test results of performance evaluation model through statistical analysis
Table 7 Performance evaluation score prediction using performance evaluation model
Table 3 Input/output variables related to the performance evaluation model
참고문헌
- Choi, J. M., 2017. Creation of Korean standard weather data of 70 stations for securing reliability of a building energy evaluation and its Globalization, 6-89. Ministry of Land, Infrastructure and Transport.
- Choi, C. H., J. S. Kim, J. H. Kim, H. Y. Kim, W. J. Lee, and H. S. Kim, 2017. Development of heavy rain damage prediction function using statistical methodology. Journal of the Korean Society of Hazard Mitigation 17(3): 331-338 (in Korean). doi:10.9798/KOSHAM.2017.17.3.331.
- Choi, W., H. J. Kim, S. S. Yoon, J. O. Kim, N. S. Jung, H. J. Lee, Y. C. Han, and J. J. Lee, 2008. Survey for the management of reservoirs under control of local authorities of reservoir of city.gun in Korea. Journal of the Korean Society of Agricultural Engineers 50(3): 31-41 (in Korean). https://doi.org/10.5389/KSAE.2008.50.3.031
- Efron, B., T. Hastie, I. Johnstone, and R. Tibshirani, 2004. Least angle regression. Journal of the Annals of Statistics 32(2): 407-499. https://doi.org/10.1214/009053604000000067
- Han, C. R., 2017. Lectures on Panel Data Analysis. Seoul: Bakyoungsa.
- Hastie, T., J. Friedman, R. Tibshirani, 2001. The Elements of Statistical Learning [electronic resource] : Data Mining, Inference, and Prediction. New York, NY : Springer New York : Imprint: Springer.
- IPCC, 2014. Climate change 2014: Synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. Geneva, Switzerland: IPCC.
- Kim, H. D., 2018. Development of stability evaluation and management technique for agricultural production infrastructure due to climate change impacts, 7-172. Sejong: Ministry of Agriculture, Food and Rural Affairs.
- Kim, J. O., H. J. Kim, J. J. Lee, and M. K. Ko, 2002. Supporting system far safe appraisal and management of agricultural structures using relational database and geographic information. Journal of the Korean Society of Agricultural Engineers 44(3): 101-110 (in Korean).
- Kim, K. S., 1976. Climate of Korea. Seoul: ilmunsa.
- Kim, S. J., S. J. Bae, J. Y. Choi, S. P. Kim, S. K. Eun, S. H. Yoo, T. I. Jang, N. Y. Goh, S. W. Hwang, S. J. Kim, T. S. Park, K. H. Jeong, and S. H. Song, 2018. Analysis on the impact of climate change on the survey of rural water district and agricultural production infrastructure. Journal of the Korean Society of Agricultural Engineers 60(5): 1-15 (in Korean). doi:10.5389/KSAE.2018.60.5.001.
- Kim, S. J., S. M. Kim, and S. M. Kim, 2013. A study on the vulnerability assessment for agricultural infrastructure using principal component analysis. Journal of the Korean Society of Agricultural Engineers 55(1): 31-38 (in Korean). doi:10.5389/KSAE.2013.55.1.031.
- Kim, Y. S., K. M. Shin, M. P. Jung, I. T. Choi, and K. K. Kang, 2016. Classification of agroclimatic zones considering the topography characteristics in South Korea. Journal of Climate Change Research 7(4): 507-512 (in Korean). doi: 10.15531/ksccr.2016.7.4.507.
- Korea Meteorological Administration, Domestic climate data. http://www.weather.go.kr. Accessed 5 Nov. 2018.
- Korea Meteorological Administration, RCP Climate Change Scenario. http://www.climate.go.kr. Accessed 5 Nov. 2018.
- Korea Rural Community Corporation, 2018. Statistical yearbook of land and water development for agriculture 2017, 462-463. Naju, South Jeolla, Korea.
- Lee, C. B., N. S. Jung, S. K. Park, and S. O. Jeon, 2015. A study on the typology of agricultural reservoir for effective safety inspection systems. Journal of the Korean Society of Agricultural Engineers 57(5): 89-99 (in Korean). doi:10.5389/KSAE.2015.57.5.089.
- Lee, J. G., M. W. Kim, and T. H. Shin, 2011. Assessment of Appropriate Period and Cost(P&C) of Repair and Improvement for Irrigational Structures. Journal of Korean National Committee on Irrigation and Drainage 18(2): 142-160 (in Korean).
- Lee, J. J., 2011. Integrated safety management system for agricultural infrastructure in response to climate change. Rural Resources 53(3): 2-8 (in Korean).
- Lee, S. H., I. H. Heo, K. M. Lee, and W. T. Kwon, 2005. Classification of local climatic regions in Korea. Asia-Pacific Journal of Atmospheric Sciences 41(6): 983-995 (in Korean).
- Min, I. S., and P. S. Choi, 2009. STATA panel data analysis. Seoul, The Korean Association of STATA.
- Ministry of Agriculture, Food and Rural Affairs, 2017. Ordinance on management of agricultural production infrastructure (7 Dec. 2017), Sejong, Korea.
- Myeong, S. J., and D. G. Lee, 2009, Assessing vulnerability to climate change of the physical infrastructure in Korea through a survey of professionals. Journal of Environmental Impact Assessment 18(6): 347-357 (in Korean).
- Myung, S. J., 2009. Assessing vulnerability to climate of the physical infrastructure in Korea and developing adaptation strategies I, 8-109. Seoul: Korea Environment Institute.
- Myung, S. J., 2010. Assessing vulnerability to climate of the physical infrastructure in Korea and developing adaptation strategies II, 45-92. Seoul: Korea Environment Institute.
- Nau, R., 2019. What's the bottom line? How to compare models. https://people.duke.edu/-rnau/compare.htm. Accessed 7 May. 2019.
- Park, K. T., 2017. Development of evaluation techniques for performance-based management and operation of SOC facilities in Korea, 469-519. Anyang, Gyeonggi: Korea Agency for Infrastructure Technology Advancement.
- RAWRIS (Rural Agricultural Water Resource Information System), http://rawris.ekr.or.kr. Accessed 29 Oct. 2018.
- RIMS (Rural Infrastructure Management System), http://rims.ekr.or.kr. Accessed 29 Oct. 2018.
- Singh, A., 2019. Evaluation metrics for regression models-MAE vs MSE vs RMSE vs RMSLE. https://akhilendra.com/evaluation-metrics-regression-mae-mse-rmse-rmsle/. Accessed 8 May. 2019.
- Yoon, K. S., 2017. Establishment database of safety diagnosis history and safety diagnosis for agricultural infrastructure, 178-338. Ansan, Gyeonggi: Korea Rural Community Corporation.