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.     

参考作物腾发量计算方法在新疆地区的适用性研究

新疆维吾尔族自治区地域辽阔，气候特征空间差异性显著。准确估算各地区的参考作物腾发量(ET₀)是新疆节水灌溉设计的基础。该文选用6种计算公式利用新疆4个典型气候区的气象资料计算了ET₀。并以Penman-Monteith方法作为标准，对其它方法进行评价。结果表明在新疆各气候区1948Penman法估算的ET₀值较FAO-24 Penman与FAO-24 Radiation方法更接近于P-M法的计算结果；在缺少资料的地区，Hargreaves方法或湿润区用Priestley-Taylor方法均可以得到与P-M法估值相当的结果；同时分析了P-M法计算的ET₀值和水面蒸发量之间的关系，为利用水面蒸发资料估算新疆地区ET₀值提供参考。     

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.     

基于随机样本的神经网络模型估算参考作物腾发量

参考作物腾发量(ET₀)是计算作物需水量、制定灌溉制度和进行水资源管理的主要参数之一。计算参考作物腾发量(ET₀)的方法众多，为规范ET₀的求法，联合国粮农组织(FAO)推荐采用修改的Penman-Monteith方法。该文指出不需要收集长序列气象资料，而以随机样本建立学习速率和动量因子自适应的BP神经网络模型估算参考作物腾发量(ET₀)的方法，并且与FAO推荐的Penman-Monteith法计算值对比分析，结果表明：利用随机样本建立的的BP神经网络模型可以很好的反映气象因子(最高温度、最低温度、最大湿度、最小湿度、净辐射和风速)与参考作物腾发量(ET₀)的非线性函数映射关系，并且取得了良好的估算效果，给出了国家自然科学基金重点项目研究区内蓝旗试验站2004年的时间尺度为日、十日参考作物腾发量(ET₀)的计算及对比分析过程。     

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.     

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。     

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。     

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.     

温室内香蕉树蒸腾量预报的试验研究

在温室内研究了香蕉树蒸腾量和小气候的关系，用5种方法计算了温室内的参考作物腾发量，用20 cm蒸发皿测定温室内的水面蒸发力，并和测定的香蕉树蒸腾量进行对比。试验结果显示香蕉树蒸腾量和蒸发皿水面蒸发量的回归系数(R²)最高，为0.94，而和5种公式计算的参考作物腾发量的回归系数为0.47～0.60，以蒸发皿水面蒸发量计算温室内的作物蒸腾量要优于以参考作物腾发量计算作物蒸腾量的方法。温室内香蕉树的蒸腾量和20 cm蒸发皿蒸发量线性相关，可以此计算温室内作物的蒸腾量。     

利用小蒸发皿观测资料确定参考作物蒸散量方法研究

参考作物蒸散量是土壤－植被－大气系统水分能量平衡模型的重要参数，如何准确获得将直接影响模型应用和最终模拟预测精度。该文利用分布于黄土高原地区65个气象站1971～2000年的气象资料，以FAO推荐的Penman-Monteith方法确定的参考作物蒸散量为标准，提出了根据平均相对湿度与风速为变量确定由20 cm小蒸发皿观测的水面蒸发量计算参考作物蒸散量的系数Kp。结果表明：由蒸发皿观测值计算的3 d或更长尺度的ET₀与Penman-Monteith方法计算的ET₀结果一致性很高，在对Kp方程系数进行适当的地域性调整后，由蒸发皿观测值和Kp确定的ET₀与Penman-Monteith方法确定的ET₀结果一致，从而认为在黄土高原地区参考作物蒸散量计算可以应用20 cm蒸发皿系数法。     

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.     

Evaluation of pan coefficient equations for estimating reference crop evapotranspiration in the arid region

Reference evapotranspiration (ET₀) can be estimated on basis of pan evaporation data (E_pan), whose measurements have the advantage of low cost, simplicity of the measuring equipment, simple data interpretation and application as well as suitability for locations with limited availability of meteorological data. E_pan values were converted to ET₀ using the pan evaporation coefficient (K_pan). In this study, seven common K_pan equations were evaluated for prediction of ET₀ in the growing season (April to October) in arid region of Iran. The Cuenca approach was best suited compared to the standard FAO Penman–Monteith method (FAO-56 PM).     

Prediction of daily reference evapotranspiration by a multiple regression method based on weather forecast data

Prediction of daily reference evapotranspiration (ET ₀) is the basis of real-time irrigation scheduling. A multiple regression method for ET ₀ prediction based on its seasonal variation pattern and public weather forecast data was presented for application in East China. The forecasted maximum temperature (T _max), minimum temperature (T _min) and weather condition index (WCI) were adopted to calculate the correction coefficient by multilinear regression under five time-division regimes (10 days, monthly, seasonal, semi-annual and annual). The multiple regression method was tested for its feasibility for ET ₀ prediction using forecasted weather data as the input, and the monthly regime was selected as the most suitable. Average absolute error (AAE) and root mean square error (RMSE) were 0.395 and 0.522 mm d^?1, respectively. ET ₀ prediction errors increased linearly with the increase in temperature prediction error. A temperature error within 3 K is likely to result in acceptable ET ₀ predictions, with AAE and average absolute relative error (AARE) <0.142 mm d^?1 and 5.8%, respectively. However, one rank error in WCI results in a much larger error in ET ₀ prediction due to the high sensitivity of the correction coefficient to WCI and the large relative error in WCI caused by one rank deviation. Improving the accuracy of weather forecasts, especially for WCI prediction, is helpful in obtaining better estimations of ET ₀ based on public weather data.     

蒸渗仪测定滴灌枣树不同时间尺度下腾发强度特征

为精确测定、准确模拟阿克苏地区滴灌枣树腾发过程,基于大型称重式蒸渗仪测定枣树全生育期逐时及逐日腾发强度（ET）,利用水量平衡方程、PM公式及经典统计原理,分析不同时间尺度下叶面积指数（LAI）、气象因素[温度（I）、风速（V）、净辐射（R_n）]、表层土壤含水率（W）与枣树腾发强度的相关关系并建立预测模型。结果表明：枣树日内腾发强度呈单峰型变化趋势,夜间变化幅度较小且腾发贡献率低。枣树全生育期逐日腾发强度变化呈先增大后减小的趋势,花期的腾发强度最大,为4.42 mm·d^-1;全生育期腾发总量为640.83 mm,其中花期和果实生长发育期耗水量占比较大,分别为38.61%和32.72%。在小时和日时间尺度上,影响腾发强度的主要因素不完全相同,且影响程度有所差异。综合考虑各影响因素,以萌芽期、花期、果实发育期为基础,分别建立以小时、日尺度下估算腾发强度的经验模型ET₁（h）=0.153+0.004T+0.012V+0.176R_n+0.002W+0.067LAI、ET₂（d）=-3.325+0.081T+0.163R_n+0.069W+2.089LAI,拟合度R²均在0.7以上,以果实发育期与成熟期数据对模型进行检验,纳什效率系数分别达0.63、0.80。经偏相关检验,冠层净辐射（R_n）对两种尺度的腾发强度均影响最显著,因此以枣树全生育期数据量为基础,仅建立冠层净辐射（R_n）与腾发强度的回归模型ET₁（h）=-0.063 3R_n²+0.361 2R_n—0.003 7、ET₂（d）=-0.018 3R_n²+0.684 7R_n–1.642 1,R²分别为0.704 7与0.743 6,可满足缺少数据支撑情况下的腾发过程估算。这些模型明确了阿克苏地区滴灌枣树腾发机制及影响程度,可为水分管理精准化提供计算基础。     

Evaluation and calibration of simple methods for daily reference evapotranspiration estimation in humid East China

The current study aims to improve the performance of simple methods for the estimation of daily reference evapotranspiration (ET₀) in humid East China, namely Priestley–Taylor 1972 (P-T 1972), Hargreaves–Samani 1985 (H-S 1985) and Turc 1961 (TU 1961). These methods were evaluated and calibrated based on well-watered grass lysimeter experiments. The FAO-56 Penman–Monteith equation (FAO-56 PM) is the best method, and the radiation-based methods (TU 1961 and P-T 1972) perform much better than the temperature-based method (H-S 1985). In the simple methods, the coefficients are calibrated to: 1.34 for P-T 1972; 0.0186, 23.47 and 17.06 for TU 1961; and 0.0027 and 0.449 for H-S 1985. The locally calibrated TU 1961 and P-T 1972 perform much better than the original, with either the observed ET_0r or the ET_0c obtained by FAO-56 PM as standard. However, local calibration does not significantly improve the performance of the H-S 1985 method. In humid East China, FAO-56 PM is the best method for daily ET₀ calculation. TU 1961, especially if locally calibrated, is the optimal choice as a simple substitute for FAO-56 PM when solar radiation is available. Otherwise, serious local calibration is strongly recommended before applying H-S 1985 for daily ET₀ estimation.     

Comparison of artificial neural networks and prediction models for reference evapotranspiration estimation in a semi-arid region

Estimation of reference evapotranspiration (ET_o) is essential for determination of crop water requirements. In this research, Penman–FAO (P-FAO) and Penman–Monteith (PM) equations were calibrated and validated by lysimeter-measured ET_o with six and four weather parameters. Furthermore, two input structures (six and four weather parameters) to artificial neural networks (ANNs) were investigated. Results showed that the accuracy of the PM equation is greater than that of the P-FAO equation. An empirical equation was developed to estimate daily ET_o using mean daily temperature and relative humidity, and sunshine hours. The accuracy of the equation to estimate daily ET_o using smooth weather data is greater than that of an equation using original data. Furthermore, ANNs were able to estimate ET_o properly. The accuracy of ANNs with six inputs is higher than that obtained using the P-FAO equation and is similar to that determined using the PM equation. A decrease in number of inputs to ANNs generally decreased the accuracy of estimation, however, ANNs were able to estimate ET_o properly when wind speed and solar radiation were unavailable. Furthermore, the accuracy of ANNs, with four input parameters is greater than that obtained using the PM equation and is similar to that obtained with P–FAO and the developed empirical equations.     

西南区域单季稻生长季干湿演变及影响因素分析

结合作物生产开展区域干湿演变及其影响因素研究,对农业可持续发展和粮食安全具有重要的科学意义。本文基于西南水稻种植区316个气象站点1961—2015年的观测资料,利用降水量与参考作物蒸散量(ET_0)的比值计算湿润指数,分析近55年西南区域单季稻生长季干湿演变特征;探讨ET_0对主要气候要素的敏感性及主要气候要素对ET_0的贡献率,对西南区域单季稻生长季干湿演变的影响因素展开研究。结果表明:西南区域单季稻生长季的半湿润区主要分布在四川攀西地区南部、云南中部和东北部,其余地区属湿润区。与1961—1990年相比,1991—2015年研究区域内的半湿润区面积增加、湿润区面积减小。近55年来,单季稻生长季内西南区域有40.8%的站点气候变湿,其余地区气候变干。四川盆地东北部、云南东北部由于降水量的增加和ET_0的减少,气候变湿;四川攀西地区由于降水量增加对湿润指数的正效应大于ET_0增加对湿润指数的负效应,气候变湿;重庆南部、贵州北部和西部由于降水量减少对湿润指数的负效应小于ET_0减少对湿润指数的正效应,气候变湿;云南大部由于降水量的减少和ET_0的增加,气候变干;西南其他区域由于降水量减少对湿润指数的负效应大于ET_0减少对湿润指数的正效应,气候变干。西南区域单季稻生长季ET_0随平均气温和相对湿度的增加而减小,而随日照时数和风速的增加而增加,日照时数和风速的显著下降是ET_0减小的主要原因。研究为气候变化背景下降低西南区域单季稻生长季可能的气候风险提供了科学依据。     

中国参考作物腾发量时空变化特性分析

分析参考作物腾发量的时空变化特征，有助于了解中国农业及生态需水的分布与演变规律。基于全国范围200多个气象站测站逐日气象观测资料，应用FAO-Penman-Monteith公式，计算得出各站历年逐日参照作物腾发量ET₀。利用GIS的空间分析功能，采用反距离空间插值方法得到全国参考腾发量的分布图，统计分析了不同分区不同时段ET₀的变化情况。结果表明：西北河西走廊地区和南方岭南地区的参考作物腾发量较大，最大值超过1500 mm。而东北黑龙江一带和四川盆地附近，参考作物腾发量较小，在600～700 mm之间。此外，夏季ET₀的分布特征决定了全年ET₀的分布特征。选取4个代表气象站，对其ET₀的历年变化及其与气象因素的关系进行了分析。分析表明，受风速减小和气温增加的共同影响，干旱地区、半干旱地区和半湿润地区的参考作物腾发量呈现减少趋势，湿润地区则相对稳定。     

利用温度资料和广义回归神经网络模拟参考作物蒸散量

参考作物蒸散量(reference evapotranspiration,ET0)精确模拟对水资源高效利用和灌溉制度制定具有重要意义,该文以四川盆地19个气象站点1961-1990年逐日最高、最低温度和大气顶层辐射作为输入参数,FAO-56 Penman-Monteith(PM)模型计算的ET0为标准值,建立基于广义回归神经网络(generalized regression neural network,GRNN)的ET0模拟模型,基于1991-2014年资料进行模型验证,将GRNN模型同Hargreaves(HS1)和改进Hargreaves(HS2)等简化模型的模拟结果进行比较,分析只有温度资料情况下不同模型模拟ET0误差的时空变异性。结果表明:GRNN、HS1和HS2模型均方根误差(root mean square error,RMSE)分别为0.41、1.16和0.70 mm/d,模型效率系数(Ens)分别为0.88、0.13和0.67。3种模型RMSE在时空上均呈现HS1HS2GRNN、Ens均呈现GRNNHS2HS1趋势;与PM模型模拟结果相比,GRNN、HS1和HS2模型模拟结果分别偏大0.8%、45.1%和17.3%。在时空尺度上的误差分析均表明利用温度资料建立的GRNN模型能够较为准确地模拟四川盆地ET0,因此可以作为资料缺失情况下ET0模拟的推荐模型。该研究可为四川盆地作物需水精确预测提供科学依据。     

Ancient Runoff Harvesting Agriculture in the Hyper‐Arid Uvda Valley of Israel: An Agro‐Hydrological Assessment

Archaeological surveys conducted since the 1980s in the hyper‐arid Uvda Valley of southern Israel revealed extensive lands with runoff harvesting systems for growing barley and wheat during ancient times. Despite the impossibility of dating the earth and stone installations of terraces and limans due to their decay over time, a wealth of ancient agricultural tools located across the valley revealed inhabitation between the Late Neolithic, Chalcolithic, and Early Bronze ages. Also, cropping of barley in the valley's runoff harvesting systems took place until the 1950s by local Bedouin populations. The objective of this study was to assess the valley's agronomic potential under current climatic conditions. This was assessed by the analysis of precipitation (P) and reference evapotranspiration (ET_o) data for the rainy seasons during a 17‐year period between 1999–2000 and 2015–2016. Using the ET_o data and the single crop coefficient (K_c) for barley and wheat allowed the calculation of crop evapotranspiration (ET_c) and the seasonal soil water deficit (D). Hydrological assessment of the valley's basin allowed the calculation of potential runoff volumes which could be available for agricultural use on the valley floor. Overall, the results showed a potential for successful cereal cultivation only in one to two years during this 17‐year period. This revealed no viability for local agriculture under current climatic conditions. Insights from this study consist with other studies which indicated considerably drier climatic conditions at present compared to those in ancient times, and even compared to those in the mid‐twentieth century. Copyright © 2017 John Wiley & Sons, Ltd.