Wang Pin;Zhang Zhao;Chen Yi;Wei Xing;Feng Boyan;Tao Fulu;

[Wang, Pin; Zhang, Zhao; Chen, Yi; Wei, Xing; Feng, Boyan] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resources Ecol, Key Lab Environm Change & Nat Disaster, MOE Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China.

[Tao, Fulu] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.

ABSTRACT:  Extreme temperature stress (ETS) is recognized as an important threat to the food supply in China. However, how much yield loss caused by ETS (YLETS) to the irrigated rice production still remains unclear. In this study, we provided a prototype for YLETS assessments by using a process-based crop model (MCWLA-Rice) with the ETS impacts explicitly parameterized, to help understand the spatio-temporal patterns of YLETS and the mechanism underlying the ETS impacts at a 0.5A degrees x 0.5A degrees grid scale in the major irrigated rice planting areas across China during 1981-2010. On the basis of the optimal 30 sets of parameters, the ensemble simulations indicated the following: Regions I (northeastern China) and III2 (the mid-lower reaches of the Yangtze River) were considered to be the most vulnerable areas to ETS, with the medium YLETS of 18.4 and 12.9 %, respectively. Furthermore, large YLETS values (> 10 %) were found in some portions of Region II (the Yunnan-Guizhou Plateau), western Region III1 (the Sichuan Basin), the middle of Region IV_ER (southern China cultivated by early rice), and the west and southeast of Region IV_LR (southern China cultivated by late rice). Over the past several decades, a significant decrease in YLETS was detected in most of Region I and in northern Region IV_LR (with the medians of -0.53 and -0.28 % year(-1), respectively). However, a significant increase was found in most of Region III (including III1 and III2) and in Region IV_ER, particularly in the last decade (2001-2010). Overall, reduced cold stress has improved the conditions for irrigated rice production across large parts of China. Nevertheless, to improve the accuracy of YLETS estimations, more accurate yield loss functions and multimodel ensembles should be developed.

Published in CLIMATIC CHANGE.2016,134(4):635-650

DOI: 10.1007/s10584-015-1545-5