Estimation of a reliable evapotranspiration model and crop coefficient in red gram ( Cajanus cajan L .) for semi-arid environments in India

The study aims to compute the reference evapotranspiration (ETo) by six standard methods such as Penman Monteith, Modified Penman, Hargreaves, Radiation Balance, Blaney Criddle and Pan Evaporation by using the meteorological data of the All India Coordinated Research Project on Water Management at Rahuri, India (long. 74° 18′, lat. 19° 45′). These methods were compared with lysimeter crop evapotranspiration (ETc) by statistical tools. The results revealed that the total lysimeter ETc of red gram in 132 days' growing period (sowing to harvest) was 494?mm and the ETo in the above-mentioned models were 485.2, 486.9, 544.6, 547.6, 563.9 and 485.2?mm, respectively. Out of six models, ETo of Modified Penman and Pan Evaporation methods were very much close to lysimeter ETc, but the coefficient of variation was very high, i.e., 43.05% and 23.91%, respectively. But in the Hargreaves and Blaney Criddle methods, the coefficient of variation was low, i.e., 15.97% and 12.6%, respectively. Besides low coefficient of variation, these two methods require limited meteorological parameters such as minimum and maximum temperature, radiation. For generating these parameters even at regional level, minimum expenditure is involved. The crop coefficient (Kc) estimated by Hargreaves (Kc 0.90) and the Blaney Criddle (0.87) model for the entire growing season was very much close to the Food and Agricultural Organization (FAO) 56 model, and this can be used for estimating the irrigation requirement of red gram.     

Crop evapotranspiration of chilli in the tropics

Abstract

The rate of crop evapotranspiration though can be predicted theoretically but the actual field study would give a more accurate data. Result from a simple lysimeter study showed that the daily rate of actual crops evapotranspiration, ETa of chilli (Capsicum annum) under the tropical condition was in the range between 4.94–7.72 mm. Their actual crop evapotranspiration/ reference crop evapotranspiration ratio, ETa/ETo ratio was between 0.94 to 1.76 depending on the growth stages of the crops. The estimated monthly value of ETo using Blaney‐Criddle was about 5 mm/day.     

甘肃地区参考作物蒸散量时空变化研究

区域水土平衡模型的建立通常需要确定计算参考作物蒸散量的模型,这一模型的精确与否,直接影响整体预测模型的最终预报精度.运用FAO-24 Blaney-Criddle法、FAO-24 Radiation法、FAO PPP-17 Penman法及FAO Penman-Monteith(98) 4种方法,对甘肃省1981～2000年33个站点的月参考作物蒸散量进行了计算.对比分析结果表明,AO Penman-Monteith(98)模型的精度与灵敏度均显示了较强的优越性.运用该模型对甘肃省参考作物蒸散量的时空分布特征进行研究表明:甘肃省参考作物蒸散量年内逐月演变曲线呈单峰状;年际蒸散量变化与夏季年际波动变化存在较高一致性;全年参考作物蒸散量分布具有从东南向西北递增的趋势.     

Measurements and estimates of potential evapotranspiration over Egypt

Mehanna (1976) estimated potential evapotranspiration (PE) for a number of stations in Egypt, using Penman's method with adjustment of the constants of the radiation term and the aerodynamic term, such that they would agree with measurements of radiation in Egypt and with estimations by Omar (1971a,b) of PE in a large field at Giza, to the southwest of Cairo. Measurements of PE were made at Bahtim, about 20 km to the north of Cairo, by evapotranspirometers.In the FAO Irrigation and Drainage Paper No. 24 on “Crop Water Requirements” (Doorenbos and Pruitt,1977) four methods were given for the calculation of PE; Blaney—Criddle, radiation, Penman (adjusted) and pan evaporation. It was considered that the Penman method was the most accurate of those given.The main features of comparison of the Mehanna and FAO's estimates of PE with measurements at Bahtim were that Mehanna, and three of the FAO's estimates (Blaney—Criddle, radiation and pan evaporation) are within ±10%0 of the measurements while the Penman estimate was 15% higher. An estimate of PE at Aswan was based on measurements of pan evaporation and estimates of evaporation from a large water surface at both Bahtim and Aswan, together with measurement of PE at Bahtim. The estimates by the methods of Mehanna, Blaney—Criddle, radiation and Penman lie in the limits 0—6% of the estimate based on measurements while the pan evaporation estimate is markedly lower. Comparison of the estimates at eight stations over Egypt shows that the Penman estimate is higher than the other estimates in Northern Egypt. The pan evaporation estimate is lower than the other estimates except at Bahtim where it is generally higher than Mehanna's and Blaney—Criddle's estimates. The low values of the pan evaporation estimates at Assuit and Aswan are remarkable.     

水稻蒸散特征及日尺度作物系数估算*5

基于南京2012年水稻生长季蒸渗仪水稻实际蒸散数据及相应生物、气象环境资料,对水稻生长季的参考作物蒸散量、实际蒸散量及作物系数进行分析,并建立作物系数估计模型。结果表明：水稻生长季内逐日参考作物蒸散量呈单峰曲线变化,峰值出现在分蘖-拔节期;逐日实际蒸散量变化则表现为双峰型,耗水双高峰发生于分蘖-抽穗期。日参考作物蒸散量和实际蒸散量均有明显的季节性变化特征。水稻生长季内实际作物系数趋势变化特征与FAO修正作物系数较一致,但二者在数值上具有较大差异,建立的水稻作物系数与其影响因子（叶面积指数、气温、净辐射）的关系模型检验表明,其拟合度为0.887,将模型应用于计算水稻农田蒸散量,其拟合度为0.943,说明模型能较精确地估算稻田日蒸散量。该模型基于日尺度影响因子,在一定程度上简化了水稻作物系数的计算过程,明确了不同类型因子对水稻作物系数的影响程度,可应用于水稻作物系数的连续动态估算。     

水稻蒸散特征及日尺度作物系数估算

基于南京2012年水稻生长季蒸渗仪水稻实际蒸散数据及相应生物、气象环境资料,对水稻生长季的参考作物蒸散量、实际蒸散量及作物系数进行分析,并建立作物系数估计模型。结果表明：水稻生长季内逐日参考作物蒸散量呈单峰曲线变化,峰值出现在分蘖-拔节期;逐日实际蒸散量变化则表现为双峰型,耗水双高峰发生于分蘖-抽穗期。日参考作物蒸散量和实际蒸散量均有明显的季节性变化特征。水稻生长季内实际作物系数趋势变化特征与FAO修正作物系数较一致,但二者在数值上具有较大差异,建立的水稻作物系数与其影响因子（叶面积指数、气温、净辐射）的关系模型检验表明,其拟合度为0.887,将模型应用于计算水稻农田蒸散量,其拟合度为0.943,说明模型能较精确地估算稻田日蒸散量。该模型基于日尺度影响因子,在一定程度上简化了水稻作物系数的计算过程,明确了不同类型因子对水稻作物系数的影响程度,可应用于水稻作物系数的连续动态估算。     

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.     

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.     

鲁北地区地膜覆盖对棉花需水量、作物系数及水分利用效率的影响

作物系数和需水量是制定作物灌溉制度和计算区域水资源平衡的重要参数,不同气候和不同栽培条件下作物系数和需水量会发生变化。本文通过大田试验,以水量平衡法计算作物需水量、以Penman-Monteith公式计算参照作物蒸散量和作物系数。结果表明,鲁北地区棉花地膜覆盖栽培比露地栽培生育期内作物需水量减少101.5mm,作物系数降低17.6%,水分利用效率增加29.3%。     

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。     

湛江地区适宜参考作物蒸发蒸腾量计算模型分析

用湛江市日平均、旬平均、月平均气象资料,以6种方法计算参考作物蒸发蒸腾量,并以FAO56 Penman-Monteith公式计算结果为标准,评价其他方法在湛江的适用性.结果表明:Hargreaves-Samani方法的年平均参考作物蒸发蒸腾量与FAO56 Penman-Monteith没有显著差异;月平均参考作物蒸发蒸腾量,除个别月份外,其他5种方法与FAO56 Penman-Monteith方法都有显著差异;不同方法计算结果与FAO56 Penman-Monteith法的均方偏差不同的时间尺度表现不同,日值计算,1948 Penman方法最小,Irmark-Allen次之;旬值计算,1948 Penman方法最小,Hargreaves-Samani、Irmark-Allen次之;月值计算Hargreaves-Samani最小,1948 Penman次之.1948 Penman、FAO24 Penman与FAO56 Penman-Monteith法的相关系数较大,Priestley-Taylor、Irmark-Allen次之,Hargreaves-Samani法的较小.     

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.     

两种Penman-Monteith公式计算草坪草参考腾发量的适用性

为了揭示ASCE和FAO56两种Penman-Monteith公式在计算小时参考作物腾发量（ET0）时的差异,开展了充分供水草坪草腾发量观测试验。基于自动气象站的小时气象数据和蒸渗仪试验结果,在对比两公式计算结果差异基础上,以实测的日草坪腾发量为标准评价了2种计算公式小时ET0的日累积结果及以日的计算结果。结果表明：2种Penman-Monteith公式计算的小时ET0结果存在一定差异,ET0较高的时段差异也比较大。白天FAO56 Penman-Monteith公式的计算结果低于ASCE Penman-Monteith公式的计算结果,夜晚则正好相反,原因在于Cd取值的差异。与实测日ET0结果相比2种公式小时时段的ET0结果的累积值误差均比较大,ASCE的改进并没有使Penman-Monteith在计算结果上取得实质性的改进,相比之下以日为时段的Penman- Monteith公式（ASCE同FAO56）取得了与实测结果最为一致的效果。进一步根据实测的小时ET0数据以及更长序列的日ET0实测结果,评价FAO56 Penman-Monteith和ASCE Penman-Monteith结果的地区适用性将是今后研究内容之一。     

河北省近35年农作物需水量变化趋势分析

根据联合国粮农组织(FAO)推荐的参考作物蒸散计算方法和相关作物系数,利用河北省84个地面气象站的资料,计算了河北省主要作物冬小麦和玉米近35年(1965～1999年)的需水量和缺水量,并分析了其变化趋势.结果表明:河北省主要作物冬小麦和玉米的需水量在近35年呈减少趋势,每10年下降量冬小麦全省平均26 mm,其中中南部地区28 mm,东部地区15mm;夏玉米全省平均9.7 mm,其中南部地区9.4 mm,中部地区10.2mm;春玉米全省平均9.9mm,其中东部地区8.8 mm,北部地区10.5 mm.全省和各区域作物需水量变化均通过0.05信度的显著性检验.不同作物缺水量不同,其中冬小麦最多,全省平均345 mm,夏玉米20 mm,春玉米29 mm;虽然不同作物均表现出缺水增加的趋势,但不显著.     

Study of different climatic conditions to assess the role of solar radiation in reference crop evapotranspiration equations

This study aims to assess radiation-based models versus the FAO Penman–Monteith (FPM) model to determine the best model using linear regression under different weather conditions. The reference evapotranspiration was estimated using 22 radiation-based methods and was compared with the FPM. The results showed that the Stephens method estimates the reference evapotranspiration better than other methods in the most provinces of Iran (nine provinces). However, the values of R² were more than 0.9930 for 24 provinces of Iran. The radiation-based methods estimated the reference evapotranspiration near the Caspian Sea better than other regions. The most precise methods were the Berengena–Gavilan, Modified Priestley–Taylor, and Priestley–Taylor methods for the provinces ES (center of Iran), GI and GO (north of Iran) and the Stephens–Stewart method for IL (west of Iran). Finally, a list of the best performance of each method has been presented to use other regions and next research steps according to the values of mean, maximum, and minimum temperature, relative humidity, solar radiation, elevation, sunshine, and wind speed. The best weather conditions to use radiation-based equations are 23.6–24.6 MJ m^?2 day^?1, 12–20°C, 18–24°C, 5–13°C, and <180 hour month^?1 for solar radiation, mean, maximum, and minimum temperature, and sunshine, respectively.     

额济纳绿洲草地蒸散系数研究

联合国粮农组织推荐的蒸散计算方法中,蒸散系数是计算实际蒸散必不可少的参数。本文从蒸散系数的定义出发,在2005年额济纳绿洲生长季连续观测的基础上,运用波文比能量平衡法计算额济纳绿洲草地的实际蒸散量,利用FAO 56Penman-Monteith模型计算草地的参考蒸散,将实际蒸散与参考蒸散相除即得到额济纳绿洲草地的蒸散系数。通过研究发现:生长季草地的蒸散量(ETc)为446.96mm,从生长季初期开始,草地的蒸散量开始增加,在6月后半月达到最大值6.724mm/d,此后蒸散量开始快速下降,在生长季末期达到最低值1.215mm/d;蒸散系数(Kc)呈现出与蒸散量(ETc)相同的变化趋势,自生长季初期开始蒸散系数快速上升,在6月后半月达到生长季最大值0.623,之后随着草地生长减缓,蒸散系数快速下降,直至生长季末期草地停止生长。对额济纳绿洲草地蒸散系数的计算可以为该地区准确估算草地生态需水量提供依据。     

四种参考作物蒸散量综合法的比较

参考作物蒸散量(ET0)的估算是作物需水量计算的关键,诸多估算方法在不同地区具有不同的适应性。本文利用中国农业主产区6个代表站点的气象数据,以FAO 56 Penman-Monteith (PM)为标准,对常用的1963 Penman(Pen63)、FAO 1979 Penman(FAO 79)、FAO 24 Penman(FAO 24)及1996 Kimberly Penman(Kpen)共4种参考作物蒸散量综合方法进行比较评价。结果表明：（1）Pen63、FAO 79及Kpen的日估算值均比PM估算值偏高,FAO 24偏低,其平均偏差分别为0.28、0.52、0和-0.17mm×d-1,相对偏差为16.0%、25.2%、2.4%、-5.3%,相对均方根误差为12.1%、22.4%、14.2%和13.5%。（2）Pen63、FAO 79的月估算值显著高于PM值,在高估最大的5月份平均偏高12.5mm (10.8%)和28.2mm (22.6%)。FAO 24表现为低估,低估最大的月份平均偏低11.4mm (8.1%),但在南方站点多数月份的估算值与PM估算值无显著差异。Kpen月估算值与PM估算值相比,既有高估(5-10月),也有低估,高估最大的月份平均偏高19.7mm(14.5%),且在南方站点的秋冬季有近6个月与PM无显著差异。（3）Pen63和FAO 79的年值均显著大于PM年值,平均偏高103.8mm(11.8%)和191.5mm(21.3%)。FAO 24年平均低估PM值60.9mm (6.3%),Kpen则平均高估50.5mm (5.8%)。（4）时间尺度对评价结果具有一定影响,4种综合法依据日、年值的评价效果排序分别为Pen63＞FAO 24＞Kpen＞FAO 79和Kpen＞FAO 24＞Pen63＞FAO 79。在日尺度下4种方法更适于湿润气候,但年尺度下仅FAO 79和FAO 24较适于湿润气候。可见,4种综合法以Pen63普适性最好,FAO 79最低,因此使用FAO 79前对其进行适应性评价尤为重要。     

非水分胁迫条件下作物腾发的模拟研究

建立了一个充分供水条件下的作物腾发量计算模型ＮＷＳＥ（Ｎｏｎ－Ｗａｔｅｒ Ｓｔｒｅｓｓ Ｅｖａｐｏ－ｔｒａｎｓｐｉｒａｔｉｏｎ）并用田间实验资料进行了验证。模型将作物冠层蒸腾和土壤蒸发作为一个耦联的整体来考虑,可以同时计算棵间蒸发和作物蒸腾。田间实验资料对ＮＷＳＥ模型验证结果表明地表温度模拟值与观测值吻合良好。利用ＮＷＳＥ模型和Ｐｅｎｍａｎ－Ｍｏｎｔｅｉｔｈ公式以及常规气象资料分别计算了作物的最大腾发量。计算结果比较表明,在叶面积指数较小时,ＮＷＳＥ模型计算结果与Ｐｅｎｍａｎ－Ｍｏｎｔｅｉｔｈ计算结果存在差别。在叶面积指数较大时,二者的一致性较好。     

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.     

Penman Monteith模型中水稻冠层阻力的模拟

针对Penman Monteith模型冠层阻力的参数化问题,以南京地区2012-2013年水稻为研究对象,参照Jarvis的气孔阻力模型,建立了水稻的冠层阻力rc与气象、环境因子（太阳净辐射、饱和水汽压差、气温和土壤水分）的关系模型,并以蒸渗仪实测蒸散量资料为对照,对模型的精度进行检验。结果表明,所建水稻冠层阻力模型的拟合度2012年为0.911,2013年为0.810,将模型应用于Penman Monteith公式计算稻田蒸散量,两年的拟合精度分别为0.967和0.953,能较精确地估算稻田耗水量。对模型的敏感性分析表明,饱和水汽压差的拟合参数a2对模型的影响最显著。模型在一定程度上解决了冠层阻力计算复杂,观测量大且易产生观测误差的问题,可作为稻田蒸散的计算方法之一。