为了揭示气候变化影响下华北平原粮食作物需水量的空间差异规律,应用统计降尺度模型对RCP4.5气候情景气象要素进行降尺度,用彭曼公式计算作物需水量,用统计评价法对华北山前平原、中部平原和滨海平原典型农业区的缺水程度进行评价。结果表明:1)粮食作物需水量与年均最高气温之间存在较强相关关系,现状气候条件下年均最高气温每升高1 ℃,华北山前平原保定农业区粮食作物需水量增大38.8 mm,中部平原德州农业区增大44.8 mm,滨海平原沧州农业区增大50.6 mm;RCP4.5气候情景下年均最高气温每升高1 ℃,保定农业区增大29.1 mm, 德州农业区增大44.2 mm,沧州农业区增大39.6 mm。2)从现状条件下到RCP4.5气候情景,3个典型地区的灌溉需水量均有不同程度的升高,其中沧州地区升高幅度最大,为5.4%;保定地区升高幅度最低,为4.8%。3)从现状条件到RCP4.5气候情景,山前平原和中部平原缺水程度有所升高,滨海平原缺水程度呈降低特征。
英文摘要:
In order to reveal the spatial variation of grain crop water requirement (W_R) in the North China Plain under climate change, we downscaled the meteorological elements of RCP4.5 scenarios through the methods of SDSM, calculated the crop water requirement by Penman equation, and evaluated the water deficiency rates of piedmont plain, central alluvial plain and littoral plain through statistical methods. The results indicated that: 1) There was a strong relationship between crop W_R and annual average maximum temperature. Under present climate conditions, a rise of 1 ℃ would increase the annual crop W_R by 38.8 mm in Baoding, 44.8 mm in Dezhou, and 50.6 mm in Cangzhou. In RCP4.5 scenarios, the annual crop W_R would increase by 29.1 mm in Baoding, 44.2 mm in Dezhou, and 39.6 mm in Cangzhou as the annual average maximum temperature elevates by 1 ℃. 2) From the current climate conditions to the RCP4.5 scenarios, there is an increase of crop irrigation water requirement (I_ R) to different degrees, with the largest increase of 5.4% in Cangzhou and the lowest 4.8% in Baoding. Under the present climate conditions, the I_ R is 717.14 mm in Baoding, 729.52 mm in Dezhou, and 686.32 mm in Cangzhou. In RCP4.5 scenarios, the I_ R is 751.50 mm in Baoding, 729.52 mm in Dezhou, and 723.64 mm Cangzhou. 3) From the present climate status to the RCP4.5 scenarios, the water deficiency rates (W_a) of the piedmont plain and central alluvial plain will increase, while that of the littoral plain has the tendency of declining. 4) Under the present climate conditions, the annual average W_a(2011-2070) is 53% in Baoding, 47% in Dezhou, and 48% in Cangzhou. In RCP4.5 scenarios, the annual average W_a is 55% in Baoding, 49% in Dezhou, and 47% in Cangzhou. 5) Through building the evaluation index system of natural water deficiency rates, we can find that the highest level of W_a is greater than 50%, the medium level 30%-50%, and the lowest level less than 30%. 6) The probability density function (PDF) of W_a fits Weibull distribution well. Under the present climates, the highest level of maximum probability of W_a is 0.634 9 in Baoding, followed by Dezhou, 0.490 2, and the lowest in Cangzhou, 0.476 0. 7) In RCP4.5 scenarios, the maximum probability of W_a is at a high level in Baoding (0.698 2), and the next is at a medium level. In Dezhou, the maximum probability of W_a is also at a high level, reaching 0.515 2, and the next is at a medium level. In Cangzhou, the W_a of maximum probability is at a medium level (0.506 2), and the next is at a high level.