Uncertainty of Simulated Paddy Rice Yield using LARS-WG Derived Climate Data in the Geumho River Basin, Korea
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho riverbasin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for theGeumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1Band B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and AgriculturalOrganization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index ofagreement (IoA), prediction efficiency (R2), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were usedto evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed R2 of 0.78, 0.90 and 0.96 respectivelyafter adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projectionsfor Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of4.5 °C in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddyrice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s,respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and 0.173 t· ha-1 for the 2020s, 2050s and 2090s, respectively.
Abstract
This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho riverbasin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for theGeumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1Band B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and AgriculturalOrganization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index ofagreement (IoA), prediction efficiency (R2), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were usedto evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed R2 of 0.78, 0.90 and 0.96 respectivelyafter adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projectionsfor Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of4.5 °C in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddyrice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s,respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and 0.173 t· ha-1 for the 2020s, 2050s and 2090s, respectively.
참고문헌 (24)
- Abedinpoura, M., "Performance evaluation of AquaCrop model for maize crop in a semi-arid environment", Agricultural Water Management, 110, pp.55~66 (2012)
- 정상옥, "FAO-AquaCrop을 이용한 기후변화가 벼 증발산량 및 수확량에 미치는 영향 모의", 한국농공학회논문집, 52(3), pp.57~64 (2010), 한국농공학회
- Chung, S.-O., "Uncertainty of paddy irrigation requirement estimated from climate change projections in the Geumho river basin, Korea", Paddy and Water Environment, 10(3), pp.175~185 (2012)
- Craufurd, P. Q., "Crop science experiments designed to inform crop modeling", Agricultural and Forest Meteorology, 170, pp.8~18 (2013)
- Dono, G., "Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems", Agricultural Systems, 117, pp.1~12 (2013)
- IPCC (Intergovernmental Panel on Climate Change), "Climate change 2007: the physical science basis, In Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change" (2007), Cambridge University Press
- Kassam, A., "FAO Methodologies on Crop Water Use and Crop Water Productivity", Expert meeting on crop water productivity, ~ (2001)
- Kim, H. -Y., "Impacts of climate change on paddy rice yield in a temperate climate", Global Change Biology, 19(2), pp.548~562 (2013)
- Kumar, S., "Comparative response of maize and rice genotypes to heat stress : status of oxidative stress and antioxidants", Acta Physiologiae Plantarum, 34(1), pp.75~86 (2012)
- Moriasi, D. N., "Model evaluation guidelines for systematic quantification of accuracy in watershed simulations", Transactions of the ASABE, 50(3), pp.885~900 (2006)
- Nkomozepi, Temba, "Simulation of the Effects of Climate Change on Yield of Maize in Zimbabwe", 한국농공학회논문집, 53(3), pp.65~73 (2011), 한국농공학회
- Nkomozepi, T., "Assessing the trends and uncertainty of maize net irrigation water requirement estimated from climate change projections for Zimbabwe", Agricultural Water Management, 111, pp.60~67 (2012)
- Raes, D., "AquaCrop 3.1plus Reference manual", FAO, ~ (2011)
- Seck, P. A., "Crops that feed the world 7 : Rice", Food Security, 4, pp.7~24 (2012)
- Semenov, M. A., "Use of a stochastic weather generator in the development of climate change scenarios", Climatic Change, 35, pp.397~414 (1997)
- Shah, F., "Impact of high-temperature stress on rice plant and its traits related to tolerance", Journal of Agricultural Science, 149, pp.545~556 (2011)
- Supit, I., "Assessing climate change effects on European crop yields using the Crop Growth Monitoring System and a weather generator", Agricultural and Forest Meteorology, 164, pp.96~111 (2012)
- Tallec, T., "Crops' water use efficiencies in temperate climate : Comparison of stand, ecosystem and agronomical approaches", Agricultural and Forest Meteorology, 168, pp.69~81 (2013)
- Todorovic, M., "Assessment of AquaCrop, CropSyst, and WOFOST Models in the Simulation of Sunflower Growth under Different Water Regimes", Agronomy Journal, 101, pp.509~521 (2009)
- "Climate change impacts and adaptation assessment on rice production in Khon Kaen province of Thailand. The 2nd International Conference on Applied Science (ICAS)" (2011)[URL]
- Wang, Y. P., "Large-area rice yield forecasting using satellite imageries", International Journal of Applied Earth Observation and Geo-information, 12, pp.27~35 (2010)
- Ye, L., "Climate change impact on China food security in 2050", Agronomy for Sustainable Development, 33(2), pp.363~374 (2013)
- Yun, J. I., "Predicting regional rice production in South Korea using spatial data and crop-growth modeling", Agricultural Systems, 77, pp.23~38 (2003)
- Zhang, T., "Responses of rice yields to recent climate change in China : An empirical assessment based on long-term observations at different spatial scales(1981-2005)", Agricultural and Forest Meteorology, 150, pp.1128~1137 (2010)
