近30年安徽省地表干湿时空变化及对农业影响

采用FAO Penman-Monteith模型, 并利用安徽省辐射观测资料对其净辐射项进行修正, 计算近30年安徽省的参考作物蒸散量。用此计算值和相应时段的降水量计算干燥度 (I_a), 并进行了基于干燥度指标不同时间尺度的区域地表干湿状况变化分析。分析表明:1971—2000年安徽省年干燥度平均值I_a=1的等值线为湿润区和半湿润区的分界线, 该分界线与1000 mm的年雨量线有很好的一致性, 同时也具有清晰的农业意义。20世纪70—90年代I_a=1的等值线南北波动, 其波动区域正是安徽省江淮分水岭易旱区。在此基础上分析了半湿润区、波动区域和湿润区降水量、参考作物蒸散量和干燥度年代际、年际和半年际的变化趋势及变异率以及逐月干旱频率及其对农业的影响。     

乌兰布和沙漠可能蒸散的研究

在测定该区2000～2005年气象因子的基础上,分析研究了乌兰布和沙漠沙地可能蒸散的月变化特点,比较分析了应用Penman方程、Thornthwaite公式和Holdridge 3种方法计算的可能蒸散。结果指出Penman方程计算的可能蒸散和水面蒸发量具有显著的直线性相关,可应用Penman方程计算所得的可能蒸散评价该区的水分蒸发特点。研究指出可能蒸散月变化与月平均温度的变化基本一致,全年最大的月份是7～8月,全年累计可能蒸散量为3 041 mm。     

几种蒸散计算方法在怀来地区的适用性研究

作物蒸散量即为植株蒸腾与棵间蒸发之和,准确地测定作物实际蒸散量,对研究农作物节水种植技术、加强水资源管理和制定合理的灌溉计划具有十分重要的意义。文章应用2013年生长季(5-10月)自动称重式蒸渗仪实测河北怀来地区夏玉米的蒸散量,从月、日两个时间尺度评价Penman-Monteith(FAO P-M)、Hargreaves、Priestley-Taylor三种基于参考作物蒸散量计算实际蒸散的方法在怀来地区的适用性,结果表明:(1)三种方法计算的夏玉米月、日实际蒸散相对于蒸渗仪实测结果均存在一定偏差,FAO P-M方法与Hargreaves方法表现较好,准确度相差不大,Priestley-Taylor方法准确性最差;(2)影响实际蒸散计算结果的主要气象因子为太阳净辐射和温度,Hargreaves方法计算结果在怀来地区可信度较高;(3)Hargreaves方法所需参数较少,在计算量方面占有很大的优势,在怀来地区适用性最好。     

大型称重式蒸渗仪测定的冬小麦农田的蒸散规律研究

利用大型称重式蒸渗仪实测数据,对冬小麦蒸散耗水规律进行研究。结果表明：1）冬小麦的目蒸散量变化曲线呈单峰型,中午大,早晚小。蒸散量在分蘖期出现小峰值,此后逐渐降低,返青后又不断增大,在孕穗期土壤水分亏缺严重,作物蒸散量增加速率有所下降。2）Penman—Monteith法估算的实际蒸散量比蒸渗仪实测值略高,怛两者的相关...     

广东省干旱逐日动态监测指标简介

根据土壤水份平衡原理,采用逐日气象资料建立逐日土壤水份模拟模型。模型为2层模型,假定上层土壤最大有效含水量为30mm,下层土壤最大有效含水量为250mm,逐日土壤水份计算包括补水和失水过程。1）补水过程：降水量优先补充上层土壤,达到其最大有效含水量后,多余降水补充下层土壤,下层土壤达到其最大有效含水量后,多余水份产生径流;2）失水过程：实际蒸散是可能蒸散和土壤干湿程度的函数,可能蒸散采用世界粮农组织（FAO）推荐的Penman—Monteith修正公式计算。在上层土壤中蒸散以可能速率发生,直到耗尽所有卜层土壤水份,不足部分从下层土壤中散失,下层土壤实际供水量取决于前一日末的下层土壤有效含水量。     

基于温度的参考作物蒸散量计算方法的适用性评价

参考作物蒸散量是表征气候干湿程度、植被耗水量、生产潜力及水资源供需平衡的重要指标之一。以海口和敦煌两个气候相差较大的站点为例,利用Irmark-Allen、Hargreaves、Jensen-Haise 3种基于温度的ET 0计算方法,计算了 2013 2015 年两个站点的参考作物蒸散量,以FAO98 Penman-Monteith方法计算所得结果为标准,依据相关系数(R)及其显著性(P)、均方根误差(RMSE)和平均偏差(MBE)等量化指标,分别对3种方法计算结果在两个站点月和日序列的适用性进行评价,并对这3种方法进行本地化修正优化和检验。结果表明:本地化前,Irmark-Allen方法在海口的计算与Penman-Monteith的偏差最小且相关性好( R =0.97, P <0.01,RMSE=0.38 mm/d,MBE=-0.01 mm/d),其他两种方法均高估。3种基于温度的ET 0方法在敦煌都有很大的误差,其中Irmark-Allen方法在夏季偏低,在冬季偏高;Hargreaves方法整体偏高;Jensen-Haise方法在冬季不适用,出现无效负值,而在其他时段偏高。本地化后,3种基于温度的ET 0方法在两个地区都得到明显改善,其中Jensen-Haise方法在海口效果最好( R =0.96, P< 0.01,RMSE=0.61 mm/d,MBE=0.003 mm/d),在敦煌效果也是最好的( R =0.96, P <0.01,RMSE=0.69 mm/d, MBE=-0.02 mm/d)。     

参考作物蒸散模型对比分析及评价

利用山东省6个气象台站45 a(1960-2004年)的逐日气象资料并选用7种参考作物蒸散模型,分别计算了上述各地的参考作物蒸散,对模型结果进行时空分布对比分析;进而以FAO推荐的Penman-Monteith模型为对照,利用最小一乘法对其余6种模型进行优化并对优化前后的模型进行时空比较.结果表明:Makkink模型在6个台站的时空分布模拟效果均最好,Mass-transfer模型在7-8月明显偏低,Net Radiation模型各站全年基本都偏高;根据不同月份的相对偏差情况,采用最小一乘法进行分月优化,优化后的模型预测月参考作物蒸散标准误差小于5 mm,平均相对误差小于8.5%,台站的年参考作物蒸散相对误差也基本小于10%,说明这些含参数较少的模型经优化后基本上可用,当资料缺损时不失为Penman-Monteith模型的替代模型.     

基于Penman-Monteith模型的蒸散模拟评估分析

根据南京地区粳稻、籼稻两个品种水稻分别在干旱、水层条件下的逐时、逐日蒸散量观测资料,采用Penman-Monteith模型(以下简称PM模型)对水稻蒸散量进行模拟,并对比模拟蒸散值与观测蒸散值。通过计算,对PM模型的可靠性进行验证。结果表明:(1)水层条件下PM模型的精度比干旱条件下高。(2)模拟值乘以作物系数后,与蒸散实际测量值更加接近。(3)通过敏感性分析可知,使用PM模型进行蒸散量模拟时,方程中各个因子取值的准确性对模拟结果的精确度有较大影响,计算时要合理确定各个因子值。(4)水层条件下稻田的蒸散量明显大于干旱条件下的蒸散量。     

吉林省参考作物蒸散量的时空变化特征及影响因素

基于吉林省50个气象站1960—2014年逐日最高气温、最低气温、日照时数、风速数据,采用Penman-Monteith算法,计算各站逐日参考作物蒸散量,进而计算各站及全省四季和年平均参考作物蒸散量,利用数理统计方法,结合地理信息系统软件,分析参考作物蒸散量的时空变化特征及主要气候影响因子。结果表明:近55 a,吉林省年平均参考作物蒸散量为876 mm,年参考作物蒸散量呈显著下降趋势(p <0. 01);空间分布差异显著,由东南向西北逐级递增,56%的站点呈显著下降趋势(p <0. 05)。参考作物蒸散量夏季最大、春季次之、冬季最小,且均呈下降趋势,但只有春季的下降趋势显著(p <0. 01);春、夏、秋、冬季与年平均参考作物蒸散量在空间分布上基本一致,但气候倾向率为负值以及通过显著性检验的站点数依次减少。全省四季和年参考作物蒸散量均与降水呈显著负相关,与日照时数、风速、最高气温呈显著正相关;其中年、春、夏、秋季与气温日较差以及春、夏、秋季与平均气温也呈显著正相关;冬季与最低气温、平均气温呈显著正相关;而典型站点参考作物蒸散量各季节影响因素及影响大小略有差异,各气象因子的共同作用导致了参考作物蒸散量的变化。     

利用时域反射仪测定的土壤水分估算农田蒸散量

简要介绍了时域反射仪（TDR）测定土壤含水量的原理和方法,根据TDR实测的土壤水分和农田水量平衡原理,估算了冬小麦生育期内不同供水条件下的农田蒸散量,探讨了TDR探针不同埋设方式对测定土体贮水量以及对估算的农田蒸散量的影响,根据充分供水区测定的最大可能蒸散量、非充分供水区的实际蒸散量,以及用气象资料计算的参考作物蒸散量,分别计算了冬小麦生育期内的作物系物Kc和土壤水分胁迫系数Ks。     

Estimation of daily reference evapotranspiration with limited climatic data using machine learning approaches across different climate zones in New Mexico

Theoretical and Applied Climatology - Reference evapotranspiration (ET0) is a major factor for water resource management. Although the FAO Penman–Monteith model is the highly recommended for...     

Performance evaluation of modified versions of Hargreaves equation across a wide range of Iranian climates

Reference evapotranspiration (ET_o) is significant for water resources planning and environmental studies. Many equations have been developed for ET_o estimation in various geographic and climatic conditions, of which, the Penman–Monteith FAO 56 (PMF-56) equation was accepted as reference method. A major complication in estimating ET_o by the PMF-56 model is the requirement for meteorological data that may not be readily available from typical weather stations in many areas of the globe. This restriction necessitates use of simpler models which require less input data. In this study, the original and five modified versions of the Hargreaves equation that require only temperature and rainfall were evaluated in humid, semi-humid, semi-arid and arid climates in Iran. The results showed that the original and modified versions of the Hargreaves equation had the poorest performance in semi-humid climate and the best performance in windy humid environment. Further, the ET_o estimations with the Hargreaves equations having rainfall parameter were poor as compared to those from the PMF-56 method under majority of the climatic situations studied.     

Single and dual crop coefficients and crop evapotranspiration for wheat and maize in a semi-arid region

In this study, weighing lysimeters were used to investigate the daily crop coefficient and evapotranspiration of wheat and maize in the Fars province, Iran. The locally calibrated Food and Agriculture Organization (FAO) Penman–Monteith equation was used to calculate the reference crop evapotranspiration (ET_o). Micro-lysimetry was used to measure soil evaporation (E). Transpiration (T) was estimated by the difference between crop evapotranspiration (ET_c) and E. The single crop coefficient (K _c) was calculated by the ratio of ET_c to ET_o. Furthermore, the dual crop coefficient is composed of the soil evaporation coefficient (K _e) and the basal crop coefficients (K _cb) calculated from the ratio of E and T to ET_o, respectively. The maximum measured evapotranspiration rate for wheat was 9.9 mm?day^?1 and for maize was 10 mm?day^?1. The total evaporation from the soil surface was about 30 % of the total wheat ET_c and 29.8 % of total maize ET_c. The single crop coefficient (K _c) values for the initial, mid-, and end-season growth stages of maize were 0.48, 1.40, and 0.31 and those of wheat were 0.77, 1.35, and 0.26, respectively. The measured K _c values for the initial and mid-season stages were different from the FAO recommended values. Therefore, the FAO standard equation for K _c-_mid was calibrated locally for wheat and maize. The K _cb values for the initial, mid-, and end-season growth stages were 0.23, 1.14, and 0.13 for wheat and 0.10, 1.07, and 0.06 for maize, respectively. Furthermore, the FAO procedure for single crop coefficient showed better predictions on a daily basis, although the dual crop coefficient method was more accurate on seasonal scale.     

Error assessment of climate variables for FAO-56 reference evapotranspiration

Meteorological stations, which measure all the required meteorological parameters to estimate reference evapotranspiration (ET_o) using the Food and Agriculture Organization Penman?CMonteith (FAO56-PM) method, are limited in Korea. In this study, alternative methods were applied to estimate these parameters, and the applicability of these methods for ET_o estimation was evaluated by comparison with a complete meteorological dataset collected in 2008 in Korea. Despite differences between the estimation and observation of radiation and wind speed, the comparison of ET_o showed small differences [i.e., mean bias error (MBE) varying ?0.22 to 0.25?mm?day^?1 and root-mean-square-error (RMSE) varying 0.06?C0.50?mm?day^?1]. The estimated vapor pressure differed considerably from the observed, resulting in a larger discrepancy in ET_o (i.e., MBE of ?0.50?mm?day^?1 and RMSE of 0.60?C0.73?mm?day^?1). Estimated ET_o showed different sensitivity to variations of the meteorological parameters??in order of vapor pressure?>?wind speed?>?radiation. It is clear that the FAO56-PM method is applicable for reasonable ET_o estimation at a daily time scale especially in data-limited regions in Korea.     

Estimating sunshine duration from other climatic data by artificial neural network for ET0 estimation in an arid environment

Sunshine duration data are desirable for calculating daily solar radiation (R _s) and subsequent reference evapotranspiration (ET₀) using the Penman–Monteith (PM) method. In the absence of measured R _s data, the Ångström equation has been recommended by the Food and Agriculture Organization (FAO) of the United Nations. This equation requires actual sunshine duration that is not commonly observed at many weather stations. This paper examines the potential for the use of artificial neural networks (ANNs) to estimate sunshine duration based on air temperature and humidity data under arid environment. This is important because these data are commonly available parameters. The impact of the estimated sunshine duration on estimation of R _s and ET₀ was also conducted. The four weather stations selected for this study are located in Sistan and Baluchestan Province (southeast of Iran). The study demonstrated that modelling of sunshine duration through the use of ANN technique made acceptable estimates. Models were compared using the determination coefficient (R ²), the root mean square error (RMSE) and the mean bias error (MBE). Average R ², RMSE and MBE for the comparison between measured and estimated sunshine duration were calculated resulting 0.81, 6.3 % and 0.1 %, respectively. Our analyses also demonstrate that the difference between the measured and estimated sunshine duration has less effect on the estimated R _s and ET₀ by using Ångström and FAO-PM equations, respectively.     

珠江流域实际蒸散发与潜在蒸散发的关系研究

采用水量平衡模型和Penman公式分别计算了珠江流域七个子流域1961—2000年实际蒸散发(I_(ETa))和潜在蒸散发(I_(ETp)),并对供水条件变化下I_(ETa)与I_(ETp)的关系进行了定量化分析,对各子流域I_(ETa)和I_(ETp)关系的理论从属性进行判定,主要结论如下:1)珠江流域年实际蒸散发量远低于潜在蒸散发量,多数子流域I_(ETa)值不到I_(ETp)值的1/2。7个流域面积加权平均I_(ETa)为681.4 mm/a,I_(ETp)为1 560.8 mm/a。从蒸散发的变异性来看,则实际蒸散发I_(ETa)的变异性明显要高于潜在蒸散发I_(ETp)。2)东江、西江、北江、柳江和盘江等5个流域实际蒸散发I_(ETa)都与降水量呈现正相关关系,韩江、郁江两个流域I_(ETa)随降水变化的变化趋势不明显。各子流域的潜在蒸散发I_(ETp)与降水量呈现显著负相关关系。7个子流域平均情况下,随着降水量的增加,I_(ETa)呈现明显的增加趋势,而I_(ETp)呈现明显的下降趋势。3)通过对降水量P与实际蒸散发I_(ETa)及潜在蒸散发I_(ETp)的联合回归方程P-IET回归系数的T检验,判定韩江、柳江和盘江等三个子流域以及七流域面积加权平均I_(ETa)与P和I_(ETp)与P的关系满足理论意义上的严格互补相关;东江、西江、北江等三个流域I_(ETa)与P和I_(ETp)与P的关系满足"非对称"互补相关。4)基于极端干旱和极端湿润的边界条件,推导出非对称条件下的实际蒸散发互补相关理论模型。