基于称重式蒸渗仪实测日值评价16种参考作物蒸散量(ET_0)模型

参考作物蒸散量(ET_0)的准确估算是作物需水量及区域农业水分供需计算的关键,尽管已提出大量方法,但缺乏基于实测值的严格检验。本文利用北京小汤山2012年称重式蒸渗仪实测日值,检验16个ET_0模型,包括5个综合法、6个辐射法、5个温度法模型。依据均方根误差RMSE值,各模型估算效果的排序为FAO79 Penman=1963 Peman1996 Kimberly PenmanFAO24 PenmanFAO56 Penman-Monteith(PM)TurcFAO24 Blaney-Criddle(BC)DeBruin-KeijmanJensen-HaisePriestley-Taylor(PT)FAO24RadiationHargreavesMakkinkHamonMcloudBlaney-Criddle(BC)。总体而言,综合法表现最好,其RMSE在1.33~1.47mm·d~(-1),以FAO79 Penman和1963 Penman为最好;辐射法次之,其RMSE在1.48~1.77mm·d~(-1),以Turc最好;温度法检验效果最差,其RMSE在1.50~2.68mm·d~(-1),以FAO24 BC为最好。FAO79Penman和1963 Penman比最好的辐射法和温度法模型的精度分别高10%和13%。综合法、辐射法模型普适性好于温度法的原因在于其均含有影响ET_0的关键因子——辐射或饱和水汽压差VPD。所有模型均具有低蒸发条件下高估、高蒸发条件下低估的阈值特点,综合法及辐射法平均低估0.14mm·d~(-1)和0.33mm·d~(-1),而温度法平均高估0.52mm·d~(-1)。前两类方法 ET_0阈值相对较低,更适于低蒸发力条件,而温度法较适于高蒸发力条件。所有综合法、辐射法模型及温度法的Hargreaves和FAO24 BC法估算值与实测值变化趋势一致,说明模型结构合理,可通过参数校正提高精度;但对于与实测值趋势不吻合的温度法,模型结构尚需优化。VPD和最大湿度RHx是影响综合法、辐射法估算偏差的两大主要因子,其中VPD对低估类模型偏差影响最大,且偏差随着VPD增加而增大;而RHx对高估类综合法模型(1963 Penman、FAO79 Penman)偏差影响最大,且偏差随RHx增加而减小。校正后的PT(1.38)、Makkink(0.83)、Turc(0.014)及Hamon(1.248)系数大于原系数,而Hargreaves(0.0019)和BC(0.192)校正系数低于原系数。此外,PT与Hamon的系数利用最小相对湿度、Turc和Makkink系数利用VPD、Hargreaves和BC系数利用辐射或日照时数能得到最佳估算。FAO56 PM表现不佳(RMSE=1.47mm·d~(-1))的原因与站点气候干燥程度、较低的空气动力项权重有关。后人对原始Penman式的诸多修正并没有显著改善精度,因此建议在类似气候条件地区继续使用老版本Penman式。同时,对FAO56 PM的进一步检验将有助于回答"FAO56 PM是否真正比其它综合法具有优势,在何种气候下表现好,在高蒸发条件下低估是否为普遍现象"等科学问题。

Evaluation of 16 Models for Reference Crop Evapotranspiration (ET0) Based on Daily Values of Weighing Lysimeter Measurements

Accurate estimation of reference crop evapotranspiration (ET0) is essential due to its critical role in determining crop water use and regional assessment of water supply and demand. Though numerous models have been developed, their rigorous test with measured data is lacking. In this paper daily estimates of 16 ET0 models, including five combination-, six radiation- and five temperature-based ones, were evaluated with measurements from April through October in 2012 at a semiarid site of Xiaotangshan, Beijing, China. Daily ET0 was measured by two weighing lysimeters (length×width×depth =1.3m×1.3m×2.3m) located in a fescue grass (Festuca arundinacea Schreb) plot surrounded by a 167ha crop. On basis of root mean square error (RMSE) we found the performance ranking: FAO79 Penman =1963 Peman>1996 Kimberly Penman>FAO24 Penman>FAO56 Penman-Monteith (PM)>Turc>FAO24 Blaney-Criddle(BC)>DeBruin-Keijman>Jensen-Haise>Priestley-Taylor(PT)>FAO24 Radiation>Hargreaves>Makkink>Hamon>Mcloud>Blaney-Criddle(BC). Overall, the combination models performed best with RMSE of 1.33-1.47mm?d-1, followed by the radiation models with RMSE of 1.48-1.77mm?d-1 and the temperature models with RMSE of 1.50-2.68mm?d-1. The best FAO79 Penman and 1963 Penman were respectively 10% and 13% more accurate than the best radiation(Turc)and temperature(FAO24 Blaney-Criddle) models. Better performance of the combination and radiation models was due to that they explicitly contain dominant factors(radiation or vapor pressure deficit(VPD))influencing ET0. All models tended to overestimate at low evaporative rate while underestimate at high rate the measured values, exhibiting threshold feature, but on average the combination and radiation methods respectively underestimated by 0.14mm?d-1 and 0.33mm?d-1, whereas the temperature method overestimated by 0.52mm?d-1. The former two had relatively lower threshold ET0 than the latter, and they were thus more applicable to low evaporative condition, and vice versa for the latter. All combination and radiation models, and the Hargreaves and FAO24 BC in temperature method captured measurement trend and showed robust structure. To improve them future efforts should be on local calibration, but for temperature models not capturing measurement trend future focus should be on structure optimization. VPD and maximum humidity RHx were two main factors affecting deviation of combination and radiation methods. The former affected models with underestimation in a positive manner, and the latter affected those with overestimation (1963 Penman、FAO79 Penman) in a negative manner. The calibrated coefficients of the PT (1.38), Makkink (0.83), Turc (0.014) and Hamon (1.248) were higher while those of the Hargreaves (0.0019) and BC (0.192) were lower than the original ones. Coefficients of PT and Hamon can also be best estimated with minimum humidity, and those of Turc and Makkink with VPD, and Hargreaves and BC with radiation or sunshine hours. The degree of climate dryness of the study site and the lower relative weight to the aerodynamic component were responsible for poor behavior (RMSE=1.47mm?d-1) of the FAO56 PM. Later modifications to wind function of original Penman appeared fruitless, and therefore we suggest continued use of the older Penman equations in climate similar to our site in China. Meanwhile, more tests of the FAO56 PM against measurements would be valuable to answer questions like "Is the FAO56 PM really superior to the older Penman equations solely in terms of accuracy", "in what climate it performs better" and "Is it common that it underestimates in high evaporative condition".