Estimation of reference evapotranspiration and crop coefficient in wheat under semi-arid environment in India

Abstract

The comparison of six standard reference evapotranspiration (ETo) estimate models was carried out with measured lysimeter evapotranspiration (ETc) in wheat crop in a semi-arid environment at Rahuri, India. The globally accepted reference evapotranspiration model of FAO 56 Penman Monteith underestimated the references ETo by 19.2% (420.5 mm) over lysimeter ET (520.7 mm). Out of the remaining five models, the Hargreaves model ranked first and was overestimated by 6.5% followed by the Blaney Criddle model (underestimated by ?5.6%). The references ETo by pan evaporation model underestimated the reference ETo to the extent of ?28.8%. The influence of statistical indicators like RMSE, MBE which was computed by considering Lysimeter ETc as standard, was quite low in the Hargreaves model compared to the rest of the models and hence, the Hargreaves method is quite acceptable for ETo estimates as this method requires much less climatic parameters (temperature and extraterrestrial radiation) than Penman Monteith (FAO56) and Modified Penman of FAO 24 as these models require aerodynamic and radiation terms, besides additional physical terms in former models of ETo estimates. The seasonal crop coefficients were 1.24, 1.13, 0.94, 0.85, 1.06 and 1.40 in Penman Monteith, Modified Penman, Hargreaves, Radiation balance, Blaney Criddle and Pan Evaporation models, respectively.     

实测草坪蒸散量评价P-M模型在北京地区适用性

为了研究北京地区的参考作物蒸散(reference evapotranspiration,ET0)特征以及Penman-Monteith(P-M)模型的适用性,2012-2014年生长季,应用蒸渗仪实测了冷季型高羊茅(Festuca arundinacea)、暖季型野牛草(Buchloe dactyloides)和乡土草种青绿苔草(Carex leucochlora)3种草坪的蒸散,应用自动气象站监测了试验地的太阳辐射、温度、空气相对湿度、风速等气象参数,通过P-M模型计算获得了ET0。将同期的P-M模型计算值与实测值进行了不同天气以及不同尺度下的比较分析,应用线性回归斜率与决定系数(R2)以及均方根误差(root mean square error,RMSE)与一致性指数(d)等统计参数进行了一致性评价。结果表明,P-M模型计算ET0与实测值在日、周、月尺度上均呈现一致的变化趋势。北京地区ET0高峰出现于5月,蒸散速率分别为4.18±0.27(P-M模型)、4.43±0.98(高羊茅)、3.96±0.23(青绿苔草)、3.53±0.25 mm/d(野牛草),10月最低。P-M模型计算的ET0与太阳辐射、平均气温、最高气温均呈极显著的线性关系,其中ET0与太阳辐射回归的R2最高,达到0.885。天气影响P-M模型的准确性,P-M模型计算ET0与草坪实测值的比值随着太阳辐射的降低(从晴天到雨天)而升高。P-M模型高估了阴雨天下的ET0。P-M模型计算ET0与实测值的RMSE和d值均随评价尺度减小而增大。实测ET0在3种草坪间差异显著,高羊茅青绿苔草野牛草。P-M模型计算ET0与高羊茅实测值的一致性最高,具有接近1.0的回归方程斜率(0.99~1.03)、最小的均方根误差(0.62~1.05 mm/d)和最高的一致性指数(0.89~0.90)。P-M模型在北京地区有较好的适用性,但在阴雨天气及春季低温情况下会高估ET0。     

杨凌地区冬小麦和夏玉米蒸发蒸腾和作物系数的确定

为了得到适合陕西杨凌地冬小麦和夏玉米的需水规律和作物系数，该文采用FAO推荐的双作物系数法对田间试验数据进行了分析计算，计算了冬小麦和夏玉米蒸发蒸腾量，确定了适合当地气候冬小麦和夏玉米的基础作物系数。     

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。     

未来主要气候情景下黄淮海地区参考作物蒸散量时空分布

探索未来主要气候情景下参考作物蒸散量(reference evapotranspiration,ET0)的时空分布可为农业水资源科学配置,科学应对气候变化对农业生产的影响提供基础数据支撑。该文利用黄淮海及周围88个站点1961-2010年逐日气象数据,Penman-Monteith公式估算的ET0为因变量,采用非线性回归分析方法对Hargreaves公式进行参数属地化订正,基于1961-2005年温度日序列,利用统计降尺度模型(statistical downscaling model,SDSM)以及大气环流模型(general circulation models,GCMs)中加拿大地球系统模式(the second generation of Canadian Earth System Model,Can ESM2)得到代表性浓度(representative concentration pathways,RCPs)4.5和8.5两种排放情景下2010-2100年温度日序列,通过率定的Hargreaves公式预测黄淮海地区ET0,并采用普通克里格(ordinary Kriging)方法进行空间化处理。结果表明:率定后的Hargreaves公式与Penman-Monteith公式的相关指数波动范围为0.65~0.85,平均值为0.80,SDSM模拟的最低温度、最高温度率定期和验证期的确定性系数都在0.95以上;未来两种气候情景下,黄淮海地区ET0整体上均呈增加趋势;RCP4.5情景下ET0从河北与山东、河南交界处形成的"勺"状向周围逐渐减小,在河北唐山与乐亭、江苏东台、河南驻马店附近达到最小值;RCP8.5情景下黄淮海地区2020 s(2011-2040年)、2050 s(2041-2070年)ET0的空间分布和RCP4.5非常相似,但2080 s(2071-2100年)ET0的空间分布差异较大,最高值主要分布在山东惠民县附近、河南新乡附近、安徽蚌阜和江苏盱眙附近。如不采取科学的应对措施,未来ET0的增加,可能会进一步加剧该区水资源短缺程度,该研究可为黄淮海地区水资源的优化管理和灌溉制度制定提供科学参考。     

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.     

农田土壤环境监测渗漏池系统的构建技术及应用

粗放的农田管理措施导致耕地质量连年下降,过量的投入品从农田流失至河流湖泊,特别是农田养分、重金属和农残等的淋溶加剧了农业面源污染的风险。渗漏池作为农业环境监测的重要装置,可分析土壤渗滤液的各成分及其淋洗特征,建立运移模型,评估不同农业措施对农田生态系统的影响,进而为完善农田管理措施提供技术支持。该文针对农业环境研究中的主要渗漏池类型,归纳总结了各类渗漏池的构建与布设方法,对渗漏池中的土壤装填、土壤表层隔离和渗漏液取样的方法等进行了系统描述,分析了不同渗漏池类型的优缺点,讨论了影响渗漏池监测结果的主要因素,并结合渗漏池在农田环境监测中的发展现状,提出了建议与展望。总体而言,各类渗漏池各有优缺点,渗漏池的构建应以具体研究需求为导向,结合地质地形条件、作物种植环境及自身建设水平等情况,在试验可接受的偏差范围和建设预算内,有针对性地构建适宜自身条件平台的渗漏池,从而实现低成本和高精确度的研究体系。     

半干旱地区不同水文年Hargreaves和P-M公式的对比分析

该文运用P-M和Hargreaves公式,对河南新乡市4个典型水文年参考作物蒸散量进行了计算,并以P-M公式的计算结果为标准,对Hargreaves公式计算结果进行分析.研究结果表明:Hargreaves公式计算的年值偏差随降水量的增加而增大,但在各典型年的第1～12旬和31～36旬,两公式旬值计算结果没有显著差别;偏差出现在第13～30旬,各典型年Hargreaves公式的计算值均大于P-M公式的计算值.另外,该文建立了各典型年两公式在第13～30旬的回归关系,修正后的Hargreaves公式能很好的在新乡市应用,并且为其他类似的半干旱地区准确运用Hargrcaves公式计算ET0提供参考.     

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.     

Determination of the potential evapotranspiration and crop coefficient for saffron using a water-balance lysimeter

Agriculture is the major consumer of water and it is possible to decrease water consumption in this sector by proper irrigation scheduling. Irrigation scheduling is based on crop water requirements. Saffron is an important crop in Iran. The main purpose of this study was to determine the potential evapotranspiration and crop coefficient for saffron using single and dual crop coefficients, in Badjgah region, College of Agriculture, Shiraz University, Shiraz, Iran. Three water-balance lysimeters were used for this experiment in a two-year study. Total saffron potential evapotranspiration values were 523 and 640 mm in the first and second growing seasons, respectively. The maximum evapotranspiration rates for saffron were 4.5 and 6.1 mm d^?1 in the first and second growing seasons, respectively. Based on the results of this study, different saffron growing stages for evapotranspiration were 30, 40, 70 and 60 days. Crop coefficient (K _c) values for the initial, mid- and late-season growth stages were 0.41–0.45, 0.93–1.05 and 0.29–0.31 in both years, respectively. Basal crop coefficient (K _cb) values for the initial, mid- and late-season growth stages were 0.15–0.16, 0.41–0.65 and 0.15–0.17 in both years, respectively.     

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。     

基于称重式蒸渗仪的喷灌条件下冬小麦和糯玉米作物系数估算方法

利用位于北京的称重式蒸渗仪,对喷灌条件下的冬小麦和糯玉米需水规律进行了测定,进而计算了两种作物的作物系数。结果表明,冬小麦和糯玉米的作物系数与播种后天数之间的关系均可以用四次多项式来表征。根据FAO-56推荐的作物系数计算方法,计算了两种作物的分段单值作物系数和双作物系数,发现华北平原喷灌条件下冬小麦和糯玉米的作物系数在生育期内的变化可以用FAO-56推荐的模式来描述,但实测值一般大于FAO-56的建议值。为了能利用FAO-56推荐的模式较好地描述喷灌作物系数变化规律,依据实测资料对FAO-56建议的单值作物系数和基础作物系数进行调整后,模拟了两种作物需水量的变化,模拟的作物阶段需水量与实测值吻合良好。     

Development and practical test of a weighable groundwater lysimeter for floodplain sites

Presently, the soil water balance of flood‐influenced soils in fluvial plains is insufficiently described. The new development of a weighable groundwater lysimeter is the basis for recording the water‐balance components precipitation, evapotranspiration, groundwater recharge, capillary rise, and interaction with the water course. Soil‐hydrologic measuring setups at two floodplain sites of the Elbe river serve for direct comparability of lysimeter measurements with data obtained on site. A groundwater control was designed for lysimeters that automatically adjusts the current groundwater level at the floodplain measuring setups and quantifies inflow into or outflow from the lysimeter. It turned out that the lysimeter developed is capable of identifying the individual water‐balance quantities at high accuracy. Contrary to previous assumptions, it was possible to prove groundwater recharge for the floodplain sites.     

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。     

太行山山前平原区蒸散量和作物灌溉需水量的分析

应用Penman-Montieth、Priestley-Taylor和FAO-24 Blaney-Criddle 3种方法计算了太行山山前平原高产区的参考作物蒸散量并对计算结果和利用实际蒸散量计算的作物系数进行了分析,结果表明：Penman-Montieth公式和FAO-24 Blaney-Criddle公式估算的参考作物蒸散量结果相近,而Priestley-Taylor方法结果偏低;在不同公式基础上计算的作物系数也存在着明显的差异,以Penman-Montieth公式为基础计算的作物系数比较合理,FAO-24 Blaney-Criddle计算的作物系数在4月到10月之间比较合理,Priestley-Taylor公式计算的作物系数偏高;在分析了多年作物系数的基础上,对不同水分年型下的作物需水量和灌溉需水量进行了计算,冬小麦和夏玉米季的灌溉需水量分别在270～400 mm和0～330 mm之间。     

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.     

基于Penman修正式和Penman-Monteith公式的作物系数差异分析

该文针对直接采用20世纪90年代初确定的中国主要作物的作物系数估算作物需水量存在的主要问题,分析了作物系数需要校正的原因:Penman修正式和Penman-Monteith公式在计算ET₀时差异较大,且对生育期较长的越冬作物的影响要高于生育期较短的夏季作物。同时利用河南省18站多年气象资料,分析了引起两公式差异的因素:辐射项处理的不同是引起两公式差异的主要原因。秋冬季,采用两公式计算的月ET₀、ET_rad值差异均高于春夏季,空气动力学项对ET₀值的影响与风速有关,较高的风速可能导致空气动力学项的影响高于辐射项;采用Penman-Monteith公式计算ET_rad值时,受季节、站点情况影响小,稳定性高,18站均表现为:平均气温对ET_rad的影响最小,1、11、12月相对湿度对ET_rad的影响较大,2-10月日照时数对ET_rad的影响较大。并根据2种不同的ET₀估算方法的关系,提出了基于Penman-Monteith公式的作物系数校正方法,对于提高作物需水量的估算精度有重要意义。     

石河子地区参考作物蒸散量变化特征及气候因子的定量分析

基于石河子地区1961—2012年4个气象站数据,采用FAO推荐的Penman-Monteith模型计算了参考作物蒸散量（ET₀）,分析了ET₀时间变化特征及其对气象因子的敏感性,并结合各气象要素的多年相对变化定量分析了气象因子对ET₀的贡献。结果表明:近52年来,石河子地区平均ET₀以1.19 mm/a的趋势增加,2004年为突变年,并存在27 a左右的周期。ET₀变化对各气象要素的敏感性以及气象因子对ET₀变化的贡献有所不同,其中,平均气温的贡献率较小,但其敏感系数最高,对ET₀变化的贡献是最大,使平均气温成为ET₀变化贡献最大的气象因素。突变后最高气温和最低气温的贡献率较大,但其敏感系数较低,平均气温为主导因子明显上升。     

CropSyst作物模型在松嫩平原典型黑土区的校正和验证

通过对CropSyst作物模拟模型进行修订和验证，应用该模型对松嫩平原黑土区主要作物的生产潜力进行了模拟，并对作物生产力模拟的有效方法进行了初步探索。模拟结果表明，对于主要作物的经济产量、全生育期蒸散量、收获时的地上生物量，模拟值与实测值较为接近。模拟值和实测值的均方根误差RMSE为3.59%(小麦地上生物量)～8.02%(小麦产量)，模拟性能指数EF最小为0.76(玉米蒸散量)，最大为0.90(小麦产量)。     

阿克苏河灌区作物理论需水量的时空分布特征

[目的]研究阿克苏河灌区作物的理论需水量的时空变化特征,为该区水资源科学管理、高效利用提供理论依据。[方法]基于灌区内1972—2014年6个气象台站的逐日气象观测数据,采用FAO修正的Penman-Monteith模型,计算参考作物蒸发蒸腾量(ET0),进行空间数据的插值分析,对阿克苏河灌区作物的理论需水量特征分别在空间和时间两个维度上进行探讨。[结果](1)阿克苏河灌区多年平均ET0介于1 118~1 241mm之间,呈现中部以北地区较低,西南部、南部地区较高的规律;(2)春季和夏季的ET0最高,5,6,7月的月均ET0合计为533mm,是作物最需要水分补给的重要时段;(3)自20世纪70年代至今,作物年均蒸发蒸腾量呈现逐渐降低的趋势,2010年以后的变化趋势较为显著;(4)灌区各季节及全年的ET0变化均呈现S形曲线分布,至2014年已接近波谷并有抬升趋势。[结论]在气候变化背景下,阿克苏河灌区作物的理论需水量随时间变化显著,春夏季受蒸腾作用影响是需要补水的关键时期,年际变化呈波动抬升趋势;在空间上亦呈现明显地带分异特点,呈南高北低的特征。