Forecasting daily reference evapotranspiration using the Blaney–Criddle model and temperature forecasts

Accurate daily reference evapotranspiration (ET_o) forecast is essential for real-time irrigation scheduling. An attempt was made to forecast ET_o using the Blaney–Criddle (BC) model and temperature forecasts in this study. Daily meteorological data for the period 2000–2014 at five stations in East China were collected to calibrate and validate the BC model against the FAO56 Penman–Monteith (FAO56-PM) model. Temperature forecasts up to 7 days’ lead time for 2012–2014 were input to the calibrated BC model to forecast ET_o. It is found that the performance of the BC model for ET_o forecast is further improved at all stations after monthly calibration. Average accuracy of forecasted ET_o (error within 1.5 mm d^?1) ranged from 82.7% to 89.3%, average values of mean absolute error (MAE) varied between 0.73 and 0.82 mm d^?1, average values of root mean square error (RMSE) ranged from 0.95 to 1.08 mm d^?1, and average values of the correlation coefficient (R) and concordance index (d) were more than 0.75 and 0.89, respectively. Furthermore, the error in ET_o forecast caused by error in temperature forecast is acceptable. The encouraging results indicate that the proposed method can be an alternative and effective solution for forecasting daily ET_o in East China.     

Proper methods and its calibration for estimating reference evapotranspiration using limited climatic data in Southwestern China

Proper methods for estimating reference evapotranspiration (ET₀) using limited climatic data are critical, if complete weather data are unavailable. Based on the weather data of 19 stations in Guizhou Province, China, several simple methods for ET₀ estimation, including the Hargreaves, Priestley–Taylor, Irmak–Allen, McCloud, Turk, and Valiantzas methods, were involved in comparison with the standard FAO-56 Penman–Monteith (PM) method. The Turk equation performs well for estimating ET₀ in humid locations. Both the Turk method and the Valiantzas method initially performed acceptably with mean root-mean-square difference (RMSD) of 0.1472 and 0.1282 mm d^?1, respectively, with only requiring parameters of temperature (T), relative humidity (RH), and sunshine duration (n). The corresponding calibration formulas to Turk and Valiantzas method were suggested as the most appropriate method for ET₀ estimation with the RMSD of 0.0098 and 0.0250 mm d^?1, respectively. The local calibrated Hargreaves–Samani method performed well and can be applied as the substitute of FAO-56 PM method under the condition that only the daily mean, maximum, and minimum temperatures were available, and local calibrated McCloud method was acceptable if only the mean temperature was available.     

Short-term forecasting of daily crop evapotranspiration using the ‘Kc-ETo’ approach and public weather forecasts

Short-term forecasting of daily crop evapotranspiration (ET_c) is essential for real-time irrigation management. This study proposed a methodology to forecast short-term daily ET_c using the ‘K_c-ET_o’ approach and public weather forecasts. Daily reference evapotranspiration (ET_o) forecasts were obtained using a locally calibrated version of the Hargreaves-Samani (HS) model and temperature forecasts, while the crop coefficient (K_c) was estimated from observed daily ET_o and ET_c. The methodology was evaluated by comparing the daily ET_c forecasts with measured ET_c values from a field irrigation experiment during 2012–2014 in Yongkang Irrigation Experimental Station, China. The overall average of the statistical indices was in the range of 0.96–1.27 mm d^?1 for the mean absolute error (MAE), 1.53–2.55 mm d^?1 for the mean square error (MSE), 1.77–2.30 mm d^?1 for the normalized mean square error (NMSE), 27.5–29.4% for the mean relative error (MRE), 0.71–0.44 for the correlation coefficient (R) and 0.46–0.05 for the mean square error skill score (MSESS). Sources of error werewere K_c estion, temperature forecasts and HS model that does not consider wind speed and humidity, and.the largesourceof error is K_c determination, which suggested that care should be taken when forecasting ET_c with estimated K_c values in the study area.     

Calibration and validation of four common ET0 estimation equations by lysimeter data in a semi-arid environment

In this study, four different methods for reference crop evapotranspiration (ET₀) were calibrated and validated for estimation of daily to mean monthly ET₀ by weighing lysimeter data during 2005–2006 and 2004–2005, respectively, in a semi-arid region. The value of the constant in the Hargreaves–Samani method changed from 0.0023 to 0.0026 for daily to mean monthly ET₀, and can be used in stations with only air temperature data. The constant of the aerodynamic resistance equation in the FAO-56 Penman–Monteith method (208.0) changed to 85.0. The value of coefficient a in the FAO-24-Radiation method was between ?0.5 and ?0.67. Further, the empirical equations were modified to estimate the value of b in the FAO-24-Radiation method and C in the FAO-24 corrected Penman method. The results showed that the modified FAO-56, corrected Penman–Monteith and FAO-24-Radiation methods are the most appropriate for estimating daily to mean monthly ET₀. Furthermore, the modified FAO-24 corrected Penman method was ranked in fourth place and its accuracy was lower than that of the other methods. However, it is appropriate for estimating mean monthly ET₀. Smoothing the daily data decreased the fluctuation in measured daily weather data and ET₀ measured by lysimeter, and consequently resulted in a higher accuracy in the estimation of daily ET₀.     

太子河流域参考作物腾发量演变特征及气候影响因素分析

采用太子河流域内8个气象站1960～2005年间气象资料，应用Penman-Montieth公式计算了46年间逐月参考作物腾发量(ET₀)，对参考作物腾发量及气象要素的年际变化特征、月际变化特征及趋势进行了分析，应用统计检验方法分析了影响流域参考作物腾发量变化的主要气象因素。结果表明：近46年间太子河流域ET₀值呈现缓慢下降趋势，年内ET₀值分布以5、6月份最高，1月份最低。影响ET₀的主要气候要素按影响程度强弱依次为日照、风速、温度、相对湿度。     

纵向岭谷区参考作物腾发量变化的特点和趋势

以Penman Montieth方程分析了西南纵向岭谷区大理、元江、保山、昆明、景洪站46～48年的逐日ET₀及其余25个站1961～2000年逐月ET₀系列。研究结果表明：日最高温度是年内ET₀变化主导因素，年际变化主要受日照时数影响，个别站为最高气温或风速，短期ET₀变化与雾无直接关系。利用Mann-Kendall法对各站年际、年内分季节ET₀趋势检验，56.7%站点的年ET₀呈显著增加趋势，分布于澜沧江耿马-思茅-勐海一带以及横断山区维西、福贡等地。分季节逐日ET₀变化趋势为，昆明夏秋季显著下降，景洪冬春季显著增加，元江、保山、大理有增有减。降水量增加、气温升高，蒸发和日照时数减少，导致80%的站ET₀呈下降趋势，湿润指数普遍增加。     

基于GEP和地理位置信息的湘鄂地区月参考作物腾发量模拟计算

参考作物腾发量(ET0)是计算植被蒸散发的关键因子,准确估算ET0对水资源管理、灌溉制度设计等具有重要意义。本研究利用湘鄂地区46个气象站点1955—2005年的逐月气象数据,包括月最高气温、最低气温、平均风速、日照时数以及相对湿度,用FAO-56 Penman-Monteith法计算各站的逐月ET0值。然后结合基因表达式编程(GEP)算法挖掘公式的能力,以各站点的地理位置信息(纬度、经度、海拔)及月序数为输入,以多年逐月平均ET0值为输出,建立基于地理位置信息的月ET0模型,并与传统ET0模型的计算结果进行比较。结果表明,所建立的模型具有足够的精度,校正、检验阶段的决定系数(R2)和均方根误差(RMSE)分别为0.934、0.951和10.050 mm、8.628 mm;与Hargreaves和Priestley-Taylor法相比,基于地理位置信息建立的GEP模型的结果均方根误差最小,变化范围为8.628~9.967 mm。本研究所建立的月ET0模型具有明确的表达式,简单易用,在湘鄂地区仅利用地理位置信息计算逐月ET0是可行的,可以利用该模型进行月尺度的灌溉制度设计和植被蒸散发的估算。     

Evaluation of some equations for estimating evapotranspiration in the south of Iran

The Penman–Monteith (PM) equation is the most common method of estimating reference crop evapotranspiration (ET _o) for different climates of the world. This equation needs full weather data, however, few stations with complete weather data exist in Fars Province, in the south of Iran. Therefore, other equations based on more readily available weather data, such as temperature and rainfall, can be used instead of the PM equation in Fars Province. Four calibrated equations have been proposed in previous studies for Fars Province using weather data up to 2000. These equations were the Hargreaves equation (H), a new equation based on monthly temperature and rainfall (R), the Thornthwaite equation (T) and the Blaney–Criddle equation (B). Using weather data for 2001 to 2006 from 14 stations in Fars Province and outside the province, this study determined the best equations for estimating ET _o in each month and each station, rather than using the PM equation. The results revealed that equations H, R, T and B showed a good correlation to the PM equation, and can be used to estimate monthly ET _o in the study area. Also, the best equation for each location in Fars Province in each month of the year can be determined by using prepared distribution maps. Furthermore, the results showed that there was no specific relationship between the climate at the station and the best equation for estimating ET _o.     

石羊河流域气候变化对参考作物蒸发蒸腾量的影响

根据甘肃省气象局石羊河流域的6个气象站近50年的观测资料，应用1998年FAO最新推荐的Penman-Monteith公式计算了50年各月参考作物蒸发蒸腾量ET₀，分析了ET₀的月际变化和年际变化特征，除武威与肃南站ET₀呈逐年显著减少趋势外，其他各站的ET₀值均表现为逐年增加趋势，各个站ET₀ 20世纪90年代较80年代均有明显增加，说明气候变化对ET₀的影响较大；并分析了平均气温、平均最高气温、年日照时数、平均风速、平均相对湿度、年降水量、年蒸发量、海拔高度与ET₀的相关性，各站ET₀与平均相对湿度相关性最好；石羊河流域ET₀空间变化也较大，从山区到绿洲平原ET₀多年平均值呈递增趋势。     

Estimation of daily reference evapotranspiration by neuro computing techniques using limited data in a semi-arid environment

In this paper, the daily reference evapotranspiration (ET₀) for Bulawayo Goetz was estimated from climatic data using neuro computing techniques. The region lacks reliable weather data and experiences inconsistencies in the measuring process due to inadequate and obsolete measuring equipment. This paper aims to propose neuro computing techniques as an alternative methodology to estimating evapotranspiration. Firstly, ET₀ was calculated using FAO-56 Penman-Monteith (PM) equation from available climatic data. Data was divided into training, testing and validation for neuro computing purposes. The study also investigated the effect of different normalisation techniques on neuro computing ET₀ estimation accuracy. In another application, neuro-computing ET₀ estimates were compared against those obtained using empirical methods and their calibrated versions. The Z-score normalisation technique for all data sets gave best results with a Multi-layer perceptron (5–5-1) model having RMSE, MAE and R² values in the range 0.12–0.25 mm day^?1, 0.08–0.15 mm day^?1 and 0.94–0.99 respectively. There were no significant differences in ET₀ estimation accuracy by neuro computing techniques due to normalisation technique. The Neuro computing techniques were superior to empirical methods in ET₀ estimation for Bulawayo Goetz. The Neuro computing techniques are recommended for use in cases of limited climatic data at Bulawayo Goetz.     

应用自适应神经模糊推理系统(ANFIS)的ET0预测

参照作物腾发量是计算作物需水量和进行灌溉预报的基础要素。该文利用自适应神经模糊推理系统(ANFIS)所具有的直接通过模糊推理实现输入层与输出层之间非线性映射能力，和神经网络的信息存储和学习能力，将其应用于参照作物腾发量预测中。根据相关分析，输入变量选择日照时数和日最高气温；用5年共1827个数据组对系统进行训练，建立了参照作物腾发量预测系统。利用该系统对近年213个数据组进行了实际预测，与Penman-Monteith方法计算结果进行比较，结果相关性良好。     

喀斯特与非喀斯特地区参考作物蒸散量时空变化分析——以广西壮族自治区为例

参考作物蒸散量(ET_0)是确定植被生态系统需水量的关键因子,其时空分布特征及主要影响因素分析对于制定植被恢复策略与区域水资源配置方案具有重要意义。本文基于FAO-56 Penman-Monteith公式和广西地区25个气象站点1960—2010年的逐日资料,计算了各站点的ET_0,在此基础上采用GIS的克里金插值、Spearman秩次相关法和通径分析方法分析了广西喀斯特与非喀斯特地区ET_0的时空变化特征及其影响因子。结果表明,51年来广西各站点多年平均ET_0为1 138 mm×a~(-1);空间分布呈由南向北、由低纬度向高纬度递减的特征,高值区主要分布在非喀斯特地区,低值区主要分布在喀斯特地区。喀斯特与非喀斯特地区年ET_0累积距平曲线均呈"N"型分布;20世纪70年代最高,90年代最低,21世纪以来年ET_0有所回升,但仍低于51年平均值。此外,喀斯特地区ET_0年际变化小于非喀斯特地区。日照时数、风速和平均温度是影响非喀斯特地区年ET_0变化的主要气象因子,而相对湿度则通过与其他气象因子的相互作用间接对喀斯特地区年ET_0的变化产生较大影响。在季节尺度上,日照时数和平均气温在各季节都是ET_0最主要的影响因子,与ET_0呈正相关关系;风速在喀斯特地区冬、春两季对ET_0的间接作用系数为负,在非喀斯特地区并未发现这一现象。了解不同地区ET_0的变化趋势是植被生态需水定额计算的必要措施。     

小流域水文循环过程中蒸散发量模拟方法评价

蒸散发(ET)在农业灌溉和水资源管理中起着重要作用。ET可通过FAO-Penman-Monteith方法(ET_(FPM))进行准确估算,ET_(FPM)方法是ET估算的标准参考方法,此方法需要提供更为详实的气象数据。对于ET的估算,需要寻找使用较少的输入数据,而不会影响预测准确性的替代方法。研究运用5个基于辐射的模型,包括Makkink(ET_(MAK))、Priestley和Taylor(ET_(PT))、Abtew(ET_(ABT))、Jensen-Haise(ET_(JH))、McGuinness和Bordne(ET_(MB)),3个基于温度的模型,包括Hargreaves and Samani(ET_(HS))、Hamon(ET_(HAM))和Linacre(ET_(LIN)),以及1个基于空气动力学的模型Penman(ET_(PEN)),通过使用韩仓河流域周边6个气象水文站的长期数据,将选取的模型与ET_(FPM)模型在月尺度和生长季节尺度上进行比较评价。结果表明,ET_(JH)、ET_(HAM)分别是67%,33%研究区域每月ET的最佳预测方法。在研究区域中,基于辐射的方法优于基于温度的方法。植被生长季节ET累积值表明,Jensen-Haise和Hamon方法在暖季和秋冬季生长期表现最佳,而春季生长期最佳预测方法仅包括Jensen-Haise方法。最佳替代方法和ET_(FPM)方法之间的差异表明,最佳替代方法在某些地区的估算可信度不高,因此在使用之前应考虑ET模型可预测性能的时空变化。     

新疆参考作物蒸散发趋势转折与大尺度气候变率的关系

参考作物蒸散发(reference crop evapotranspiration,ET₀)能够全面反映一个地区的蒸散发能力,在农业高效节水灌溉等领域得到了广泛应用。近年来大多数研究通常将ET₀与局地气象因子的变化进行敏感性分析,忽略了大尺度气候变率对ET₀的遥相关影响。该研究基于新疆地区84个气象站点的逐日气象资料和气候变率指数,采用多元线性回归和Cramer’s突变检验等方法,探究了厄尔尼诺南方涛动(El Nino-Southern Oscillation,ENSO)、印度洋偶极子(Indian Ocean Dipole,IOD)、太平洋年代际振荡(Pacific Decadal Oscillation,PDO)和北大西洋多年代际振荡(Atlantic Multidecadal Oscillation,AMO)等大尺度气候变率与新疆地区ET₀趋势转折的关系。结果表明：1960—2020年ET₀总体呈下降趋势,平均递减率为0.75 mm/a;1998年为ET₀     

Calibration of Hargreaves–Samani equation for estimating reference evapotranspiration in semiarid and arid regions

The Penman–Monteith (FAO-56 PM) equation is suggested as the standard method for estimating evapotranspiration (ET₀) by the International Irrigation and Drainage Committee and Food and Agriculture Organization (FAO). On the other hand, the Hargreaves–Samani (HS) equation is an alternative method compared with the FAO-56 PM equation. In the present study, the original coefficient C of the HS equation is calibrated based on the FAO-56 PM equation for estimating the reference ET₀ from 15 meteorological stations in central Iran (about 170,000 km²) under semiarid and arid conditions. After calibration, the new values for C are ranged from 0.0018 to 0.0037. The mean bias error (MBE), the root mean square error (RMSE), and the ratio of average estimations of ET₀ (R) values for all stations are ranged from 0.12 to 5.38, ?5.35 to 1.15 mm d^?1 and 0.64 to 1.28 for the HS equation and from 0.12 to 2.48, ?2.2 to 0.60 mm d^?1, and 1.00 to 1.05 for the calibrated Hargreaves–Samani equation (CHS), respectively. Results indicate that the average RMSE and MBE values are decreased by 40% and 66%, respectively. Relationships for calibrating the C coefficient on the basis of annual average of daily temperature range (ΔT) and wind speed (V) are proposed, calibrated, and validated. Hence, the CHS equation can be used for ET₀ estimates with acceptable accuracy instead of the FAO-56 PM method.     

分别利用Hargreaves和PM公式计算西北干旱区ET0的比较

该文根据甘肃张掖气象站1991～2000年的气象资料，利用Hargreaves公式和Penman-Monteith公式计算了参照作物需水量(ET₀)。对比分析结果表明：Hargreaves公式计算的ET_0H年值比Penman-Monteith公式的计算ET_0PM偏低，而在年内6、7、8月份，ET_0H>ET_0PM，9月份两种方法计算结果几乎相等，其他月份ET_0H<ET_0PM。造成这种结果的原因是风速和降雨的影响。根据两种方法的计算结果，提出了适合西北干旱区ET₀的计算公式。     

Penman-Monteith与Penman修正式计算塔里木盆地参考作物潜在腾发量比较

利用1989~1996年阿克苏水平衡试验站的气象资料,对Penman-Monteith公式和Penman修正式计算的参考作物潜在腾发量进行了比较。Penman修正式计算的参考作物潜在腾发量年值略大于Penman-Monteith公式计算的年值,绝对偏差为42~128 mm,相对偏差为3.3~9.8%,且年际间变化不大。各月的参考作物潜在腾发量变化较大,绝对偏差可正可负,1、2、12月小于0,3~10月大于0,相对误差1、12月较大,2、11月较小,其它月份变化不大。导致计算偏差的原因在于两种公式采用了不同的辐射项和空气动力项计算公式和参数。两种公式计算的参考作物潜在腾发量具有显著的线性相关性。     

Trend analysis of reference evapotranspiration in the western half of Iran

Reference evapotranspiration (ET_o) is an important element of the hydrological cycle, and changes in ET_o are of great significance for agricultural water use planning, irrigation system design and management. In this study, annual, seasonal and monthly trends in the Penman-Monteith ET_o at 20 meteorological stations during 1966-2005 in the western half of Iran were examined using the Mann-Kendall test, the Sen's slope estimator and the linear regression. Annual analysis of the ET_o series indicated a positive trend in 70% of the stations according to the Mann-Kendall test and the Sen's slope estimator and in 75% of the stations according to the linear regression. The magnitude of significant positive trends in annual ET_o varied from (+)11.28 to (+)2.30 mm/year. On the seasonal scale, stronger increasing trends were identified in ET_o data in winter and summer compared with those in autumn and spring. Meanwhile, the highest numbers of stations with significant trends were found in the monthly ET_o series in February, while the lowest numbers of stations with significant trends were observed in November. Analysis of the impact of climatic variables on the significant increasing trend in ET_o showed that the increasing trend was mainly caused by a significant increase in air temperature during the study period.     

西北旱区石羊河流域作物耗水点面尺度转化方法的研究

基于DEM与GIS空间分析功能研究了石羊河流域主要农作物春小麦需水量ET_c的时空分异规律。根据8个气象站近50年气象资料，应用1998年FAO推荐的Penman-Monteith公式计算参考作物蒸发蒸腾量ET₀，由收集到的春小麦需水量试验资料获得多年平均作物系数K_c。近50年来流域上游的古浪、天祝春小麦全生育期ET_c呈微弱的增加趋势，中游的凉州区表现出极显著的减少趋势，其他站减少趋势不显著。确立了ET_c与海拔高度、纬度、坡向的多元回归关系，借助Arcview3.3、ArcGIS9.0与Visual Basic6.0软件实现了春小麦ET_c的空间尺度转换，并分析了石羊河流域25%、50%、75%三个不同水文年春小麦ET_c的空间变异情况。石羊河流域春小麦ET_c由山区向绿洲平原递增，多年平均值为270～591 mm。估计值与计算值相差在11.1%以内。     

遗传算法率定参照作物腾发量相关参数的研究

用气象资料计算参照作物腾发量(ET0)的方法需要各种气象(候)和物理参数,净辐射是其中的重要数据之一,而专业测量净辐射的设备在农业气象站里很少安装。为解决计算ET0时缺少太阳净辐射(Rn)测量值这一实际问题,该文采用浑善达克沙地东南缘南沙梁草甸草原区气象站观测的气象资料,用遗传算法模型对联合国粮农组织56号文本(FAO56)推荐值(as和bs)进行率定,计算了对应夏半年(4—9月)和冬半年(1—3月和10—12月)的太阳净辐射和参照作物腾发量,并将率定前后的模拟太阳辐射进行对比分析,用残差估计指数法对该方法模拟的参照作物腾发量模拟精度进行了分析。结果表明:在缺少太阳净辐射测量值的地区,采用FAO56参数(as和bs)推荐值与遗传算法模型率定参数(as和bs)相比,净辐射年内变化趋势一致,采用率定后参数计算的净辐射相对更不稳定,波动更大,但能有效提高参照作物腾发量计算精度。误差较大的模拟值均出现在降雨日前后,降雨虽然并未直接出现在Penman-Monteith公式中,但是降雨必然会对湿度和温度等气象条件造成一定影响,而as和bs是受湿度等因素影响而变化的,其深层次的原因有待进一步分析。