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Exploring the characteristic of the extreme climatic events, especially future projection is considerably important in assessing the impacts of climatic change on hydrology and water resources system. We investigate the future patterns of climate extremes (2001-2099) in the Haihe River Basin (HRB) derived from Coupled General Circulation Model (CGCM) multimodel ensemble projections using the Bayesian Model Average (BMA) approach, under a range of emission scenarios. The extremes are depicted by three extreme temperature indices (i.e., frost days (FD), growing season length (GSL), and T >90th percentile (TN90)) and five extreme precipitation indices (i.e., consecutive dry days (CDD), precipitation ≥10 mm (R10), maximum 5-day precipitation total (R5D), precipitation >95th percentile (R95T), and simple daily intensity index (SDII)). The results indicate frost days display negative trend over the HRB in the 21st century, particularly in the southern basin. Moreover, a greater season length and more frequent warm nights are also projected in the basin. The decreasing CDD, together with the increasing R10, R5D, R95T, and SDII in the 21st century indicate that the extreme precipitation events will increase in their intensity and frequency in the basin. Meanwhile, the changes of all eight extremes climate indices under A2 and A1B scenarios are more pronounced than in B1. The results will be of practical significance in mitigation of the detrimental effects of variations of climatic extremes and improve the regional strategy for water resource and eco-environment management, particularly for the HRB characterized by the severe water shortages and fragile ecological environment. [ABSTRACT FROM AUTHOR]

Accounting for over 70% of global water withdrawals, irrigation plays a crucial role in the development of agriculture. Irrigation water requirement ( WIRR ) will be influenced by climate change due to the alteration in soil water balances, evapotranspiration, physiology and phenology under global warming. This is particularly true for rice, a high water-consuming crop. Therefore, exploring the impact of climate change on rice WIRR is of great significance for the sustainable utilization of water resources and food security. This paper aims to investigate spatially and temporally the responses of rice WIRR to climate change in the middle and lower reaches of the Yangtze River (MLRYR), which is one of the most important rice farming districts in China. With the help of the specially developed rice growing period calculation method and water balance model coupled with rice irrigation scheduling, the impacts of climate change on WIRR for early rice, late rice and single cropping rice during the historical (1961–2012) and future (2011–2100) periods were evaluated. Meanwhile, to consider the uncertainty from climate models in future projection, four GCMs under RCP2.6, RCP4.5 and RCP8.5 emission scenarios from the 5th Coupled Model Intercomparison Project (CMIP5) were employed as the input of the water balance model. The results indicate the following: (1) The days of growing period ( DGP ) for all three types of rice display shortened trends in historical and most future periods. However, in the middle region of the MLRYR, the DGP for early rice and late rice would increase by up to10 days in 2080s under RCP8.5 scenario. (2) Over the past 50 years, the WIRR significantly decreased by 1.58 and 2.10 mm yr −1 for late rice and single cropping rice, respectively. While for early rice, the WIRR only slightly decreased by 0.13 mm yr −1 . (3) Projected future WIRR would increase for all three types of rice in the whole region under RCP4.5 and RCP8.5 scenarios (up to 100 mm), but decrease for single cropping and late rice in the southeast region (up to 40 mm). The results can provide beneficial reference and comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization and agricultural management in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]