[논문]GCM 예측자료를 이용한 기후변화가 짐바브웨 옥수수 생산에 미치는 영향 및 불확실성 분석

은코모제피 템바; 정상옥

doi:10.5389/ksae.2012.54.4.083

GCM 예측자료를 이용한 기후변화가 짐바브웨 옥수수 생산에 미치는 영향 및 불확실성 분석
General Circulation Model Derived Climate Change Impact and Uncertainty Analysis of Maize Yield in Zimbabwe 원문보기

한국농공학회논문집 = Journal of the Korean Society of Agricultural Engineers, v.54 no.4, 2012년, pp.83 - 92

은코모제피 템바 (Department of Agricultural Engineering, Kyungpook National University) , 정상옥 (Department of Agricultural Engineering, Kyungpook National University)

초록
AI-Helper

짐바브웨는 식량부족을 격어 오고 있으며, 이는 기후변화에 따른 수자원의 부족, 인구증가, 개발 및 환경보전 등으로 인하여 앞으로는 더욱 심화될 것으로 보인다. 3가지 배출시나리오 (A2, A1B, B1)에 대한 13개의 GCM 기후자료로부터 상세화한 기후예측값과 AquaCrop 작물모형을 이용하여 기후변화가 짐바브웨의 주곡인 옥수수의 수확량에 미치는 영향과 모형예측값의 불확실성을 분석하였다. 작물생육환경이 잘 유지된다고 가정하고 옥수수 잠재생산량을 모의한 결과 기준년도 (1970s)에 비해 2020s, 2050s and 2090s 년대에 평균 (범위) 8 % (6-9 %), 14 % (10-15 %) 및 16 % (11-17 %) 증가할 것으로 예측되었다. 같은 기간에 대한 물의 생산성은 평균 (범위) 7 % (4-13 %), 13 % (6-30 %) 및 15% (6-23 %) 증가할 것으로 예측되었다. 기온의 꾸준한 상승과 대기중 이산화탄소 농도 증가로 인한 시비효과로 인하여 미래에는 옥수수 단위 생산량과 물의 생산성이 증가할 것으로 예측되었으며 증가 범위를 보면 모형간의 변동성이 상당히 큰 것을 알 수 있었다. 본 연구결과는 기후변화가 짐바브웨의 옥수수 생산량에 미치는 영향과 변동성을 제시하므로서 장기적인 식량계획의 기초자료로 이용될 수 있을 것이다.

주제어

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

The study presents a method to predict the impacts of climate change on the yield of maize and assess the associated uncertainty in three high maize production provinces of Zimbabwe. Evaporation was simulated to gradually increase over the future periods at a higher rate than the transpiration and had higher uncertainty.

제안 방법

org) for the periods of 2011-2030 (2020s), 2046-2065 (2050s) and 2080-2099 (2090s) for the 13 GCMs used in this study (Table 2). 30 year mean monthly values were adopted to eliminate natural inter-annual to inter-decadal variability. GCMs are systems of partial differential equations based on the basic laws of physics, fluid motion, and chemistry.
An alternative approach (used herein) would be to use a crop model to simulate the yield responses to a broader range of climate states or scenarios, capturing a wider uncertainty space for integrated assessment models. Climate projections for the B1, A1B, and A2 scenarios of the IPCC Special Report on Emissions Scenarios (SRES) were used in this study. The mean annual atmospheric CO₂ concentration is estimated to reach 856, 717 and 549 ppm by 2100 for the A2, A1B and B1 scenarios respectively.
The purpose of this study is to generate climate scenarios from multiple GCMs, simulate multiple maize yield forecasts and assess them for uncertainty. AquaCrop crop model was chosen in this study because the model can use few parameters while maintaining accuracy making it attractive for locations where some information may be unavailable.
While it is ideal to use observed records for the baseline, suitable data were not readily available and this study relied on an International Water Management Institute (IWMI) modeled dataset with a spatial resolution of 10 minutes-Arc (New et al., 2002). The IWMI database is currently the most extensive global climate database in terms of resolution, coverage and number of parameters that is available in the public domain (Droogers and Allen, 2002).

대상 데이터

com). Future climate data for Kutsaga station were from the IPCC 4^th assessment report and were downloaded from the IPCC Data Distribution Center (http://www.ipcc-data.org) for the periods of 2011-2030 (2020s), 2046-2065 (2050s) and 2080-2099 (2090s) for the 13 GCMs used in this study (Table 2). 30 year mean monthly values were adopted to eliminate natural inter-annual to inter-decadal variability.
Kutsaga Research Station in Harare city (17° 56' S, 31° 05' E;1,479 m above mean sea level) was selected for this study to reflect typical farm management practices under commercial production conditions for NR II.
Agriculture in Zimbabwe is spread across five natural agro-ecological zones that range from areas of high rainfall and productivity in the north to areas of extremely low productivity where rainfall is sparse and variable in the south. This study was conducted on 3 provinces mostly situated in natural agro-ecological region II (NR II), located in the north-eastern part of the Zimbabwe (Fig. 1). Kutsaga Research Station in Harare city (17° 56' S, 31° 05' E;1,479 m above mean sea level) was selected for this study to reflect typical farm management practices under commercial production conditions for NR II.

이론/모형

The change factor (CF) procedure was used as in Chung and Nkomozepi (2012). Key advantages of the CF approach are the ease and speed of application and the direct scaling of the scenario in line with changes suggested by the GCM or RCM.

후속연구

It is hoped that this study will encourage similar analyses for other crops and regions to determine what patterns exist in climate impacts uncertainty, and to develop ways of communicating uncertainty in the Zimbabwean context.

참고문헌 (24)

Cane, M. A., G. Eshel and R. W. Buckland, 1994. Forecasting Zimbabwean maize yield using eastern equatorial Pacific sea surface temperature. Nature 370: 204-205.

상세보기
Chung, S.-O. and T. Nkomozepi, 2012. Uncertainty of paddy irrigation requirement estimated from climate change projections in the Geumho river basin, Korea. Paddy and Water Environment. published online DOI: 10.1007/s10333-011-0305-z.
Chung, S.-O., 2009. Climate change impacts on paddy irrigation requirement in the Nakdong river basin. Journal of the KSAE 51(2): 35-41 (in Korean).
Chung, S.-O., 2010. Simulating evapotranspiration and yield responses of rice to climate change using FAOAquaCrop. Journal of the KSAE 52(3): 57-67 (in Korean).
Droogers, P. and R. G. Allen, 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and Drainage Systems 16: 33-45.

상세보기
FAO (Food and Agriculture Organization), 2006. Fertilizer use by crop in Zimbabwe. ftp://ftp.fao.org/agl/agll/docs/fertusezimbabwe.pdf accessed on 8 Jan, 2012.
Fildes, R. and N. Kourentzes, 2011. Validation and forecasting accuracy in models of climate change. International Journal of Forecasting 27: 968-995.

상세보기
Harrison, L., J. Michaelsen, C. Funk, and G. Husak, 2011. Effects of temperature changes on maize production in Mozambique. Climate Research 46: 211-222.

상세보기
Holzkamper A., P. Calanca, and J. Fuhrer, 2012. Statistical crop models: predicting the effects of temperature and precipitation changes. Climate Research 51:11-21.

상세보기
Hong, E. M., J. Y. Choi, S. H. Lee, S. H. Yoo and M. S. Kang, 2009. Estimation of paddy rice evapotranspiration considering climate change using LARS-WG. Journal of the KSAE 51(3): 25-35 (in Korean).
Manatsa, D., I. W. Nyakudya, G. Mukwada, and H. Matsikwa, 2011. Maize yield forecasting for Zimbabwe farming sectors using satellite rainfall estimates. Natural Hazards 59: 447-463.

상세보기
New, M., D. Lister, M. Hulme and I. Makin, 2002. A high resolution data set of surface climate over global land areas. Climate Research 21: 1-25.

상세보기
Nkomozepi, T. and S.-O. Chung, 2011a. Assessing the effects of climate change on irrigation water requirements for corn in Zimbabwe. Journal of the KSAE 53(1): 47-55.
Nkomozepi, T. and S.-O. Chung, 2011b. Simulation of the effects of climate change on yield of maize in Zimbabwe. Journal of the KSAE 53(3): 65-73.

원문보기 상세보기
Nkomozepi, T. and S.-O. Chung, 2012. Assessing the trends and uncertainty of maize net irrigation water requirement estimated from climate change projections for Zimbabwe. Agricultural Water Management. published online DOI:10.1016/j.agwat.2012.05.004.
Nyakudya, I. W. and L. Stroosnijder, 2011. Water management options based on rainfall analysis for rain fed maize (Zea mays L.) production in Rushinga district, Zimbabwe. Agricultural Water Management 98: 1649-1659.

상세보기
Raes, D., A. Sithole, A. Makarau, and J. Milford, 2004. Evaluation of first planting dates recommended by criteria currently used in Zimbabwe. Agricultural and Forest Meteorology 125: 177-185.

상세보기
Raes, D., P. Steduto, T. C. Hsiao, and E. Fereres, 2010. AquaCrop reference manual, AquaCrop version 3.1, FAO, Land and Water Division, Rome, Italy.
Ruane, A. C., L. D. Cecil, R. M. Horton, R. Gordon, R. McCollum, D. Brown, B. Killough, R. Goldberg, A. P. Creeley, and C. Rosenzweig, 2011. Climate change impact uncertainties for maize in Panama: Farm information, climate projections, and yield sensitivities. Agricultural and Forest Meteorology. published online. DOI:10.1016/j.agrmet.2011.10.015.
Savva, A. and K. Frenken, 2002. Crop Water Requirements and Irrigation Scheduling. Irrigation manual Module 4. FAO Sub-regional office for east and southern Africa, Harare, Zimbabwe. 42-48.
Taylor, A. H., J. I. Allen and P. A. Clark, 2002. Extraction of a weak climatic signal by an ecosystem. Nature 416: 629-632.

상세보기
Yao, F. M., P. C. Qin, J. H. Zhang, E. Lin and V. Boken, 2011.Uncertainties in assessing the effect of climate change on agriculture using model simulation and uncertainty processing methods. Chinese Science Bulletin 56: 729？737.

상세보기
Zinyengere, N., T. Mhizha, E. Mashonjowa, B. Chipindu, S. Geerts and D. Raes, 2011. Using seasonal climate forecasts to improve maize production decision support in Zimbabwe. Agricultural and Forest Meteorology 151: 1792-1799.

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 highresolution climate scenarios. Journal of the KSAE 54(2): 15-26 (in Korean).

저자의 다른 논문 :

LOADING...

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증