[논문]시설재배를 고려한 미래 농지이용 변화와 기후변화가 관개 필요수량에 미치는 영향 평가

손무빈; 한대영; 김진욱; 신형진; 이용관; 김성준

doi:10.11108/kagis.2020.23.4.120

시설재배를 고려한 미래 농지이용 변화와 기후변화가 관개 필요수량에 미치는 영향 평가
Assessment of Future Agricultural Land Use and Climate Change Impacts on Irrigation Water Requirement Considering Greenhouse Cultivation 원문보기

한국지리정보학회지 = Journal of the Korean Association of Geographic Information Studies, v.23 no.4, 2020년, pp.120 - 139

손무빈 (건국대학교 일반대학원 사회환경플랜트공학과) , 한대영 (건국대학교 일반대학원 사회환경플랜트공학과) , 김진욱 (건국대학교 일반대학원 사회환경플랜트공학과) , 신형진 (한국농어촌공사 농어촌연구원) , 이용관 (건국대학교 일반대학원 사회환경플랜트공학과) , 김성준 (건국대학교 공과대학 사회환경공학부)

초록
AI-Helper

본 연구에서는 CLUE-s(Conversion of Land Use and its Effects at Small regional extent)와 RCP(Representative Concentration Pathway) 4.5 및 8.5 HadGEM3-RA(Hadley Centre Global Environmental Model version 3 Regional Atmosphere)시나리오를 사용하여 미래 농지이용 변화와 기후변화가 관개 필요수량에 미치는 영향을 평가하였다. 논산시(55,517.9ha)의 농지이용 항목으로 논, 밭, 시설재배지를 고려하고 DIROM (Daily Irrigation Reservoir Operation Model)을 이용해 탑정저수지 수혜구역(5,713.3ha)에 대한 관개 필요수량(Irrigation Water Requirement, IWR)을 추정하였다. CLUE-s를 이용한 미래 농지이용 변화를 모의하기 위해 환경부의 2007년, 2013년, 2019년의 토지피복도 6개 항목(수역, 시가지, 논, 밭, 산림, 시설재배지)을 적용하였다. 그 결과, 2100년은 2013년에 비해 논과 밭이 5.0%, 7.6% 감소했으며, 시설재배지는 24.7% 증가하는 것으로 전망되었다. 미래의 농지이용과 기후변화를 모두 고려한 경우의 RCP 4.5 및 RCP 8.5 모두 2090s(2090~2099) IWR은 미래 기후변화만 고려한 경우에 비해 논과 밭에서는 각각 2.1%, 1.0% 감소하고 시설재배지에서는 11.4% 증가하는 것으로 전망되었다.

Abstract ▼ AI-Helper

This study is to assess the future agricultural land use and climate change impacts on irrigation water requirement using CLUE-s(Conversion of Land Use and its Effects at Small regional extent) and RCP(Representative Concentration Pathway) 4.5 and 8.5 HadGEM3-RA(Hadley Centre Global Environmental Model version 3 Regional Atmosphere) scenario. For Nonsan city(55,517.9ha), the rice paddy, upland crop, and greenhouse cultivation were considered for agricultural land uses and DIROM(Daily Irrigation Reservoir Operation Model) was applied to benefited areas of Tapjeong reservoir (5,713.3ha) for Irrigation Water Requirement(IWR) estimation. For future land use change simulation, the CLUE-s used land uses of 2007, 2013, and 2019 from Ministry of Environment(MOE) and 6 classes(water, urban, rice paddy, upland crop, forest, and greenhouse cultivation). In 2100, the rice paddy and upland crop areas decreased 5.0% and 7.6%, and greenhouse cultivation area increased 24.7% compared to 2013. For the future climate change scenario considering agricultural land use change, the RCP 4.5 and RCP 8.5 2090s(2090~2099) IWR decreased 2.1% and 1.0% for rice paddy and upland crops, and increased 11.4% for greenhouse cultivation compared to pure application of future climate change scenario.

주제어

표/그림 (12)

그림 FIGURE 1. Flowchart in this study
그림 FIGURE 2. Annual change of (a) Rice paddy and Upland crop areas in Nonsan and (b) Greenhouse area in South Korea and Nonsan from 1976 to 2019
그림 FIGURE 3. Study area (a) Land use and (b) Watershed environment of Topjeong reservoir
그림 FIGURE 4. Driving factors of CLUE-S modeling
표 TABLE 1. Meteorological data correction methods in Greenhouse cultivation (KRC, 2003)
표 TABLE 2. Comparison of observed versus predicted land use area in 2018
표 TABLE 3. The future land uses from 2020 to 2100 (Unit : ha)
그림 FIGURE 5. The changed area of land use of (a) Rice paddy, (b) Upland crop, (c) Greenhouse cultivation from 2013 to 2100
그림 FIGURE 6. Annual average temperature and precipitation
표 TABLE 4. Precipitation and temperature change of RCP 4.5, RCP 8.5 HadGEM3-RA
표 TABLE 5. The future irrigation water requirement of Agricultural area
그림 FIGURE 7. The future irrigation water requirement of (a) Rice paddy (b) Upland crop, and (c) Greenhouse cultivation in RCP 4.5 HadGEM3-RA and (d) Rice paddy (e) Upland crop, and (f) Greenhouse cultivation in RCP 8.5 HadGEM3-RA

참고문헌 (32)

Cho, G.H., K.H. Han and K.S. Choi. 2019. Analysis of Water Supply Reliability of Agricultural Reservoirs Based on Application of Modified Penman and Penman-Monteith Methods. Journal of the Korean Society of Agricultural Engineers 61(6): 93-101.
Choi, J.Y., S.H. Yu, Y.G. Oh, S.H. Lee, and D.G. Yun. 2012. Evaluation of future agricultural water demand in consideration on agricultural environment factor impact of the climate change. Water for future 45(2):73-83.
Chung, E.S., K. Park, and K.S. Lee. 2011. The relative impacts of climate change and urbanization on the hydrological response of a Korean urban watershed. Hydrological Processes 25(4):544-560.

상세보기
Jang, W.S., N.S. Jung, and K.W. Park. 2008. Development of a Paddy Field Estimation Model Considering Shift-share Effects. Journal of The Korean Society of Agricultural Engineers 50(3):83-89.

원문보기 상세보기
Kim, H.K, E.J. Lee, S.W. Park, and M.S. Kang, 2009 Assessment of the Impacts of the Impervious Surface Change in the Farm Region on Watershed Hydrology. Journal of the Korean Society of Agricultural Engineers 51(6):17-23.

원문보기 상세보기
Kim, H.Y., and S.W. Park. 1988. Simulating Daily Inflow and Release Rates for Irrigation Reservoirs(1) : Modeling Inflow Rates by A Linear Reservoir Model. Journal of the Korean Society of Agricultural Engineers 30(1):50-62.
Kim, S.J., and Y.J. Lee. 2007. The effect of spatial scale and resolution in the prediction of future land use using CA-Markov technique. Journal of the Korean Association of Geographic Information Studies 10(2):57-69.
Kim, S.J., S.J. Bae, H.S. Jeong, H.K. Kim, and S.W. Park. 2018. Effects of the Brackish Water Desalination System on Soil Environment and Growth in Squash Greenhouse Cultivation Area. Journal of the Korean Society of Agricultural Engineers 60(3):113-121.

원문보기 상세보기
KOSIS(Korean Statistical Information Service). 2018. Agricultural Area Survey.
KOSIS(Korean Statistical Information Service). 2018. Cadastral Statistics.
KRC(Korean Rural Cooperation). 2003. A study on Estimated Method for Water Requirement of Upland Irrigation in Jeju (II). p.79-80.
KRC(Korean Rural Cooperation). 2018. Introduction of water supply system for greenhouse cultivaton of rice paddy. p.6-9.
KRC(Korean Rural Cooperation). 2020. Reservoir storage ratio, https://www.alimi.or.kr/(AccessedOctober 20, 2020).
KREI(Korea Rural Economic Institute). 2018. Agricultural prospect model KREI-KASMO 2018 operation and devlopment research p.1-3.
Lee, J.H. 1998. Food Supply and Demand Problems and Response Strategies. Journal of Community Nutrition 3(3):466-521.
Lee, K.Y., and K.S. Choi. 2009. Development of clean water supplying system for greenhouse cultivation and convenience water (I). Journal of the Korean Society of Agricultural Engineers 51(5):95-100.

원문보기 상세보기
Lee, Y.G., U.H. Cho, and S.J. Kim. 2016. Prediction of Land-Use Change based on Urban Growth Scenario in South Korea using CLUE-s Model. Journal of the Korean association of Geographic Information Studies 19(3):75-88.

원문보기 상세보기
MAFRA(Ministry of Agriculture, Food and Rural Affairs). 2014. Rural water use rationalization plan 2015-2024. p.284-382.
MAFRA(Ministry of Agriculture, Food and Rural Affairs). 2019. Major Statistics of Agriculture, Food and Rural Affairs.
Nam, W.H？, E.M. Hong, T.C. Kim and J.Y. Choi. 2014. Projection of Future Water Supply Sustainability in Agricultural Reservoirs under RCP Climate Change Scenarios. Journal of the Korean Society of Agricultural Engineers 54(4):59-68.
NIER(National Institute of Environmental Research). 2014. A research on control targets and strategies for impervious surface management. p.1-2.
NIMR(National Institute of Meteorological Research). 2011. Climate change scenario report 2011 to respond to the IPCC 5th assessment report. p.4-6.
Nonsan City. 2019. 59th Nonsan Statistical Yearbook.
Oh, Y.G., J.Y. Choi, S.H. Yoo, and S.H. Lee. 2011. Prediction of land-cover change based on climate change scenarios and regional characteristics using cluster analysis. Journal of the Korean Society of Agricultural Engineers 53(6):31-41.

원문보기 상세보기
Park, J.H., S.H. No, and G.S. Lee. 2013. Outlook analysis of future discharge according to land cover change using CA-Markov technique based on GIS. Journal of the Korean Association of Geographic Information Studies 16(3):25-39.

원문보기 상세보기
Ryu, J.C., K.H. Ahn, M.D. Han, H.S. Hwang, J.W. Choi, Y.S. Kim, and K.J. Lim. 2014. Evaluation and application of CLUE-S model for spatio-temporal analysis of future land use change in total water pollution load management system. Journal of Korean Society on Water Environment 30(4):418-428.

원문보기 상세보기
Shin, A.K., K.W. Jung, and I.K. Jung. 2018. A study on unit agricultural water reqruiement calculation for facility cultivation crops in preparation of facility cultivation expansion in rice fields. Korean National Committee on Irrigation and Drainage 2018(62):103-115.
Veldkamp, A. and L.O. Fresco. 1996. CLUE-CR: an integrated multi-scale model to simulate land use change scenarios in Costa Rica. Ecological modeling 91(1-3):231-248.

상세보기
Verburg, P.H., G.H.J. De Koning, K. Kok, A. Veldkamp, and J. Bouma. 1999. A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecological modeling 116(1):45-61.

상세보기
Verburg, P.H., W. Soepboer, A. Veldkamp, R. Limpiada, V. Espaldon, and S.S.A. Mastura. 2002. Modeling the spatial dynamic of regional land use:the CLUE-S model. Environmental Management 30(3):391-405.

상세보기
Yoo, S.H., J.Y. Choi, S.H. Lee, Y.G. Oh, and N.Y. Park. 2012. The Impacts of Climate Change on Paddy Water Demand and Unit Duty of Water using High-Resolution Climate Scenarios. Journal of the Korean Society of Agricultural Engineers 54(2):15-26.

원문보기 상세보기
Zhang, P., Y. Liu, Y. Pan, and Z. Yu. 2013. Land use pattern optimization based on CLUE-S and SWAT models for agricultural non-point source pollution control. Mathematical and Computer Modelling 2013(58):588-595.

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