中文摘要：

潜在蒸散发是水文循环和能量循环的一项重要组成,准确估算蒸散发对农业水资源有效利用具有重要的理论和现实意义。为获得精度稳定可靠的蒸散发估计值同时只需较少的气象资料,以沂沭河上游流域（临沂控制站）为研究区,提出改进的双线性曲面回归模型（bilinear surface regression model,BSRM）计算站点的潜在蒸散量。以实测蒸发数据折算的陆面潜在蒸散量为标准,同时以彭曼公式（P-M）为参考与之对比,检验和评价3种BSRM模型的精度,并分析各气象因子对潜在蒸散量的影响。结果表明：3种BSRM模型中,基于日照百分率、气温和相对湿度建立的双线性曲面回归模型模拟精度最高,以基于日照百分率计算的太阳辐射、气温、相对湿度建立的双线性曲面回归模型次之,以基于Hargreaves-Allen方程计算的太阳辐射、气温和相对湿度建立的双线性曲面回归模型模拟精度最差。基于日照百分率、气温和相对湿度建立的BSRM模型的模拟精度略优于P-M公式,但所需的气象因子较少,计算方法简单;且受气象因子的变化影响较少,模拟精度稳定可靠,是一种有效的替代方法。

英文摘要：

The accurate estimation of potential evapotranspiration（ET0） is an important content of hydrological cycle and flux cycle, which has an important theoretical and practical significance for effective use of agricultural water resources in the context of climate change. In order to acquire stable and reliable estimation method of evapotranspiration that need only a small number of climatic factors, an improved ET0 estimation method of bilinear surface regression model（BSRM） was used to calculate the daily evapotranspiration based on the observed meteorological data from 6 weather stations in the upper Yishu River watershed（34.37°-36.38°N, 117.40°-119.18°E）. Three types of BSRM models were considered according to the difference in computing solar radiation in this study. In the first method, the relative insolation duration and the ET0 estimation was based on the calculated solar radiation, relative humidity and air temperature（BSRM（n/N））. In the second method, relative humidity, air temperature and solar radiation computed by relative insolation duration and extra-terrestrial radiation were used for ET0 estimation（BSRM（Rs））. In the third method, three variables of solar radiation computed by Hargreaves-Allen equation, relative humidity and air temperature were used for ET0 estimation（BSRMt）. Meanwhile, Penman-Monteith（P-M） equation was used to estimate the ET0 as a reference and comparison method. The precision of the 3 kinds of BSRM approaches was tested and evaluated based the standard of land surface potential ET0 calculated by the means of conversion coefficient and observed evapotranspiration. On the base of above studies, the influential factors of ET0 were further analyzed. The results showed that the model precision for ET0 estimation was highest in BSRM（n/N）, followed by BSRM（Rs） and BSRMt. The BSRM（n/N） method has the minimum mean absolute of error and root mean square of error（0.48 and 0.64 mm）. The P-M equation and BSRM（n/N） method could yield