1955-2015年陕西省潜在蒸散量时空变化特征及成因

为深入认识气候变化下陕西潜在蒸散量（ET₀）年际和年内的变化特征及主要影响因素，根据陕西省20个气象站点逐日气象数据，利用Penman-Monteith公式计算了1955—2015年全省潜在蒸散量，运用累积距平、Mann-Kendall突变检测、最优分割、反距离加权插值等分析方法，分析了年均及四季潜在蒸散量时空变化特征；并采用偏相关、多元回归模型对影响潜在蒸散量的主导气象要素进行了定量研究。结果表明:（1）1955—2015年，陕西省年ET₀呈微弱上升趋势，变化率为1.03 mm/10 a，分时段ET₀呈“倒S”型变化。（2）从季节看，春、夏、秋、冬季平均ET₀变化率分别为3.72，0.12，0.36，-2.95 mm/10 a。（3）研究区内年及季节平均ET₀的空间分布存在明显地带性规律特征。（4）平均气温是全年及春、秋、冬季ET₀变化的主导因素，日照是夏季ET₀变化的主导因素。这些结果表明陕西省潜在蒸散量的时空变化具有阶段性、地带性，其影响因素具有季节性。研究可为气候变化下陕西省水资源科学配置以及影响评估提供依据。

Spatial and Temporal Variations of Potential Evapotranspiration in Shaanxi Province and the Quantification of the Causes from 1955 to 2015

In order to have a thorough recognition of the variation characteristics and influencing factors of potential evapotranspiration (ET₀) in Shaanxi Province under the climate change. Based on 20 meteorological sites of daily weather data from 1955 to 2015 in Shaanxi Province, the Penman-Monteith (P-M) is utilized to calculate the potential evapotranspiration (ET₀). The spatial and temporal variations of annual and seasons ET₀ are analyzed by using cumulative distance, Mann-Kendall mutation detection, the optimal partition method, inverse distance weighted interpolation (IDW) and other mathematical methods. The dominant meteorological elements influencing ET₀ are quantitatively studied by using partial correlation and multiple regression models. The results showed that the annual ET₀ of Shaanxi Province from 1955 to 2015 presented slight rising trend with the rate of 1.03 mm/decade. ET₀ changed as the inverted S-shape over the periods. The average ET₀ rates in spring, summer, autumn and winter were 3.72 mm/decade, 0.12 mm/decade, 0.36 mm/decade and -2.95 mm/decade. The spatial distribution of annual and seasonal ET₀ in the study area was significant variation pattern of latitudinal direction zonality. The main impacting factor was average temperature in spring, autumn and winter, but was sunshine duration in summer. The above results indicated that the ET₀ in Shaanxi Province had the characteristics of stage and zonality, influencing factors had the seasonal characteristics. The results would provide valuable information for water resources optimal allocation and assessment in Shaanxi Province.