干旱状况下小区域灌溉冬小麦农田生态系统水热传输

该文采用涡度相关技术测定小区域灌溉冬小麦农田实际蒸散量和农田能量平衡各分量,分析表征农田地表获取能量再分配经典参数Priestly-Taylor系数（α=LE/LEeq）的变化特征。结果表明,在华北地区冬小麦返青至成熟期内,日变化过程中白天时间段内, Priestley-Taylor系数呈“U”型变化趋势,7︰00～18︰00 时刻内,α平均值为（1.324±0.334）,正午前后保持在1.05～1.17之间。 在冬小麦生育期季节变化过程中,Priestley-Taylor系数（α）平均值为（1.473±0.454）,远高于在湿润下垫面时（α＝1.26）的数值,在抽穗开花期内土壤水分充足时α最大值为2.317,拔节时期土壤水分胁迫时α值为0.410。干旱少雨状况下,进行小面积充分灌溉时,由于存在农田热平流现象将导致过多的蒸发蒸腾水分耗散,降低农田灌溉水的利用效率。     

CERES-Wheat模型中两种蒸发蒸腾量估算方法比较研究

基于CSM-CERES-Wheat模型中Priestley-Taylor(PT)和FAO56 Penman-Monteith(PM)2种蒸发蒸腾量估算方法分别模拟了冬小麦2011—2012年和2012—2013年2个生长季的累积蒸发蒸腾量、日蒸发蒸腾量、土壤含水率、地上干物质以及籽粒产量,并对2种方法的模拟结果进行了评价和比较。对2种方法模拟的蒸发蒸腾量值与试验区域内大型称量式蒸渗仪的实测结果进行了比较,结果表明,基于PT和PM方法的CERES-Wheat模型均可以准确地模拟干旱-半干旱地区冬小麦的蒸发蒸腾量,累积蒸发蒸腾量和日蒸发蒸腾量的误差分别小于5.4%和3.4%。同时,模型还可以模拟土壤水分动态情况,在0~20 cm土层,CERES-Wheat模型的模拟值与实测值的标准化均方根误差(RRMSEn)为39.38%,模拟结果较差,但20 cm土层以下,2种方法的模拟值与实测值的RRMSEn均小于23.1%,且对40~60 cm土层的模拟结果最好。CERES-Wheat模型基于PT和PM方法对冬小麦在2011—2012年和2012—2013年生长季地上生物量的模拟值与实测值的RRMSEn分别为13.57%和22.76%,产量的RRMSEn分别为11.80%和15.42%,模拟结果均较好。另外,CSM-CERES-Wheat模型基于PT方法模拟的蒸发蒸腾量小于基于PM方法的模拟值,而PT方法对土壤含水率的模拟结果高于PM方法的模拟结果,且PT方法对地上生物量以及产量的模拟结果高于PM方法,用2种方法模拟的成熟期地上生物量及产量的RRMSEn值均在25%以内。总之,CSM-CERES-Wheat模型采用2种方法对蒸发蒸腾量、土壤含水率及干物质和产量的模拟结果均较好,表明该模型在我国干旱-半干旱地区的应用性较好,可为该地区不同水分条件下冬小麦的生长情况提供理论支持。     

华北平原杨树人工林蒸散发估算研究

以华北平原人工杨树林为对象,应用Penman-Monteith、Priestley-Taylor和Hamon模型估算蒸散发量,并以Penman-Monteith模型估算结果为基准,对Priestley-Taylor和Hamon模型进行了修正。结果表明,修正前,Priestley-Taylor和Hamon模型与Penman-Monteith模型的相关系数分别为0.388和0.531,Hamon模型估算的月总蒸散发量结果偏高10.9mm,Priestley-Taylor估算的结果偏低27.3mm;修正后,Priestley-Taylor和Hamon修正公式,相关系数分别提高到0.731和0.761。     

豫西北几种ET_0计算方法的比较及Hargeaves公式的修正

根据豫西北地区30年的气象资料,选用辐射法中的Makkink公式和Priestley-Taylor公式以及温度法的Hargreaves公式和McCloud公式计算了ET0,并以Penman-Monteith公式为标准,分别对各公式年值和旬均值的绝对误差、相对误差和累计误差进行分析,结果显示Hargreaves公式的精度最高。为了进一步提高Hargreaves公式的应用精度,建立了线形回归方程,并对其进行了修正。     

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAO PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process; net radiation (Rn), air temperature (T), vapor pressure deficit (Δe), and wind speed (U); and has presented very good results when compared to data from lysimeters populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAO PM method using estimated input variables, as recommended by FAO Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Δe, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAO PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAO PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day⁻¹. For these cases, U data were replaced by the normal values for the region and Δe was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Δe data were missing, mainly when calibrated locally (RMSE = 0.40 mm day⁻¹). When Rn was missing, the FAO PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day⁻¹. When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day⁻¹, were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day⁻¹).     

应用地表温度与植被指数梯形空间关系估算陆面蒸散量

提出了以Priestley-Taylor方程为基础,综合利用地面气象观测数据与卫星遥感观测数据的陆面蒸散量估算方法。其基本思路是:基于地表能量平衡原理,利用遥感观测与地面气象观测数据,计算给定气温条件下全植被覆盖与祼土地面在极湿、极干状况下的地表温度,构建每个像元的地表温度(Ts)与植被指数(VI)的理论梯形空间,进而根据该象元Ts-VI坐标点在该梯形中的位置,计算其Priestley-Taylor系数,并利用Priestley-Taylor方程估算像元的蒸散比。利用美国一个半干旱地区的地面观测数据进行了精度验证,结果表明该方法具有较理想的精度,蒸散量估算的平均绝对误差约为35.5%。     

简化参照作物蒸散量（ETo）计算公式在青海省高寒区的适用性分析

【目的】以Penman-Monteith FAO-56公式为参照,分析Hargreaves、Priestley-Taylor和Makkink 3种简化的参照作物蒸散量(ETo)公式在青海高寒区的适用性。【方法】以青海省5个气候区(湿润、半湿润、半干旱、干旱和极端干旱)11个气象站1984-2011年的旬气象资料计算ETo,建立分析3种简化公式旬ETo与PenmanMonteith FAO-56公式的线性回归方程,并对比其年值的均方根误差率,分析3种简化公式的适用性。【结果】Hargreaves公式在大多数站点都低估了ETo,但在湿润和半湿润区的计算结果较好;Priestley-Taylor公式在多数站点都高估了ETo;Makkink公式在所有站点都低估了ETo,但其旬ETo值的误差最小,其与PMF-56公式的线性回归结果也最好。除极端干旱区外,Priestley-Taylor和Makkink公式计算的ETo与PMF-56公式的年均方根误差率均小于15%。【结论】Hargreaves公式只适用于青海省的湿润和半湿润区,Priestley-Taylor和Makkink公式可以直接用于青海省极端干旱区以外地区ETo的计算。     

旱作春玉米农田Priestley-Taylor模式参数的变化

Priestley-Taylor(PT)参考作物蒸散(ET₀)估算模式系数(α)的本地化研究,对于确定水资源高效利用的半旱地农业生产措施及精准灌溉具有非常重要的意义。本文以FAO(1998)推荐的Penman-Monteith (PM)参考作物蒸散估算方法为标准,采用涡度相关技术并根据气象数据信息,监测半干旱气候条件下旱作春玉米农田尺度水、热交换传输过程,以分析Priestley-Taylor模式参数α的变化特征并确定其本地化估算参数值。结果表明,年时间尺度变化过程中高海拔半干旱气候条件下根据PT模式推荐系数α=1.26确定的参考作物蒸散量(ET_{0-PT 1.26})估算值,在11月至来年4月份非作物生长季期间平均偏低21.2%,在5月至9月份旱作春玉米生育期内平均高于PM模式的参考作物蒸散量(ET_0-PM)估算值5.5%,研究站点旱作春玉米生长季本地化适宜的PT模式系数α值为1.15±0.06。在季节变化过程中,旱作春玉米农田近正午时刻实际PT模式系数平均值呈单峰型变化趋势,春玉米抽雄抽穗开花期达到高峰,平均值为0.67±0.08,苗期最低,仅为0.26±0.13,全生育期平均值为0.50±0.21。若要在半干旱气候地区根据PT模式准确估算参考作物蒸散量,需进行PT模式参数的本地化研究。     

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。     

Comparison of two remote sensing models for estimating evapotranspiration: algorithm evaluation and application in seasonally arid ecosystems in South Africa

Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration (ET) models in recent years, important information gaps still exist on the accuracy of the models particularly in arid and semi-arid environments. In this study, we evaluated the Penman-Monteith based MOD16 and the modified Priestley-Taylor (PT-JPL) models at the daily time step against three measured ET datasets. We used data from two summer and one winter rainfall sites in South Africa. One site was dominated by native broad leaf and the other by fine leafed deciduous savanna tree species and C₄ grasses. The third site was in the winter rainfall Cape region and had shrubby fynbos vegetation. Actual ET was measured using open-path eddy covariance systems at the summer rainfall sites while a surface energy balance system utilizing the large aperture boundary layer scintillometer was used in the Cape. Model performance varied between sites and between years with the worst estimates (R²<0.50 and RMSE>0.80 mm/d) observed during years with prolonged mid-summer dry spells in the summer rainfall areas. Sensitivity tests on MOD16 showed that the leaf area index, surface conductance and radiation budget parameters had the largest effect on simulated ET. MOD16 ET predictions were improved by: (1) reformulating the emissivity expressions in the net radiation equation; (2) incorporating representative surface conductance values; and (3) including a soil moisture stress function in the transpiration sub-model. Implementing these changes increased the accuracy of MOD16 daily ET predictions at all sites. However, similar adjustments to the PT-JPL model yielded minimal improvements. We conclude that the MOD16 ET model has the potential to accurately predict water use in arid environments provided soil water stress and accurate biome-specific parameters are incorporated.