Abstract
Crop models are robust tools for simulating the impact of climate change on rice development and production, but are usually designed for specific stations and varieties. This study focuses on a more adaptable model called Simulation Model for Rice-Weather Relations (SIMRIW). The model was calibrated and validated in major rice production regions over China, and the parameters that most affect the model’s output were determined in sensitivity analyses. These sensitive parameters were estimated in different ecological zones. The simulated results of single and double rice cropping systems in different ecological zones were then compared. The accuracy of SIMRIW was found to depend on a few crucial parameters. Using optimized parameters, SIMRIW properly simulated the rice phenology and yield in single and double cropping systems in different ecological zones. Some of the parameters were largely dependent on ecological zone and rice type, and may reflect the different climate conditions and rice varieties among ecological zones.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Anderson T R (2010). Progress in marine ecosystem modelling and the “unreasonable effectiveness of mathematics”. J Mar Syst, 81(1–2): 4–11
Angström A (1924). Solar and terrestrial radiation. Report to the international commision for solar research on actinometric investigations of solar and atmospheric radiation. Q J R Meteorol Soc, 50(210): 121–126
Bouman B A M, Van Laar H H (2006). Description and evaluation of the rice growth model ORYZA2000 under nitrogen-limited conditions. Agric Syst, 87(3): 249–273
Brouwer R, DeWit C T (1969). A simulation model of plant growth with special attention to root growth and its consequences. In: Proceedings of the 15th Easter School in Agri Science. University of Nottingham, 224–242
Duan Q, Sorooshian S, Gupta V K (1994). Optimal use of the SCE-UA global optimization method for calibrating watershed models. J Hydrol (Amst), 158(3–4): 265–284
Duncan W G (1971). Simulation of growth and yield in cotton: A computer analysis of the nutritional theory. Proc Beltwide Cotton Prod Res Conf, (78): 45–61
Gao L, Jin Z, Huang Y, Zhang L (1992). Rice clock model-A computer model to simulate rice development. Agric Meteorol, 60(1–2): 1–16
Hayashi Y, Jung Y S (2000). Paddy rice production under possible temperature fluctuation in East Asia. Global Environmental Research, 3: 129–137
Horie T, Centeno G S, Nakagawa H, Matsui T (1997). Effect of elevated carbon dioxide and climate change on rice production in East and Southeast Asia. In: Proceedings of the International Scientific Symposium on Asian Paddy Fields. Saskatchewan: University of Saskatchewan, 913–967
Horie T, Nakagawa H, Ceneno H G S, Kropff M (1995). Rice production in Japan under current and future climates. In: Matthews R B, Kropff M J, Bachelet D, eds. Modeling the Impact of Climate Change on Rice in Asia. Wallingford: CAB International, 143–164
Kropff MJ, Centeno G S, Bachelet D, Lee MH, Mohan Dass S, Horie T, De Feng S, Singh S, Penning De Vries F W T (1993). Predicting the impact of CO2 and temperature on rice production. In: IRRI Seminar Series on Climate Change and Rice. Los Banos: International Rice Research Institute
Lin E, Xiong W, Ju H, Xu Y, Li Y, Bai L, Xie L (2005). Climate change impacts on crop yield and quality with CO2 fertilization in China. Philos Trans R Soc Lond B Biol Sci, 360(1463): 2149–2154
Matthews R B, Kropff M J, Horie T, Bachelet D (1997). Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation. Agric Syst, 54(3): 399–425
Mei F, Wu X, Yao C, Li L, Wang L, Chen Q (1988). Rice cropping regionalization in China. Chinese Journal Rice Science, 2(3): 97–110 (in Chinese)
Peng S, Huang J, Sheehy J E, Laza R C, Visperas R M, Zhong X, Centeno G S, Khush G S, Cassman K G (2004). Rice yields decline with higher night temperature from global warming. Proc Natl Acad Sci USA, 101(27): 9971–9975
Peng S, Ingram K T, Neue H U, Ziska L H (1995). Climate Change and Rice. Berlin, Heidelberg: International Rice Research Institute, Springer-verlag
Prescott J A (1940). Evaporation from a water surface in relation to solar radiation. Transactions of the Royal Society of South Australia, 64: 114–125
Spitters C J T (1986). Separating the diffuse and direct component of global radiation and its implications for modeling canopy photosynthesis Part II. Calculation of canopy photosynthesis. Agric Meteorol, 38(1–3): 231–242
Tao F, Yokozawa M, Hayashi Y, Lin E (2003). Future climate change, the agricultural water cycle, and agricultural production in China. Agric Ecosyst Environ, 97(1–3): 361
Tao F, Yokozawa M, Xu Y, Hayashi Y, Zhang Z (2006). Climate changes and trends in phenology and yields of field crops in China, 1981–2000. Agric Meteorol, 138(1–4): 82–92
Wopereis C S, Defoer T, Idinoba P, Diack S, Dugué M J (2009). Effects of temperature on rice. In: Wopereis M C S, Defoer T, Idinoba P, Diack S, Dugue M J, eds. Curriculum for Participatory Learning and Action Research (PLAR) for Integrated Rice Management (IRM) in Inland Valleys of Sub-Saharan Africa: Technical Manual. Cotonou: Africa Rice Center, 39–42
Xiong W, Tao F, Xu Y, Lin E (2001). Simulation of rice yields under future climate scenarios in China. Agric Meteorol, 22: 9–14
Yin X, Kropff M J (1996). Use of the Beta function to quantify effects of photoperiod on flowering and leaf number in rice. Agric Meteorol, 81(3–4): 217–228
Yoshida S (1981). Fundamentals of Rice Crop Science. Los Banos: International Rice Research Institute, 269
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, S., Tao, F. & Shi, R. Modeling the rice phenology and production in China with SIMRIW: sensitivity analysis and parameter estimation. Front. Earth Sci. 8, 505–511 (2014). https://doi.org/10.1007/s11707-014-0468-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11707-014-0468-1