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首页> 外文期刊>Journal of irrigation and drainage engineering >Analysis of Microclimate Data Measured over Grass and Soybean Canopy and Their Impacts on Penman-Monteith Grass and Alfalfa Reference Evapotranspiration
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Analysis of Microclimate Data Measured over Grass and Soybean Canopy and Their Impacts on Penman-Monteith Grass and Alfalfa Reference Evapotranspiration

机译:草和大豆冠层的小气候数据分析及其对彭曼-蒙特斯草和苜蓿参考蒸腾量的影响

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摘要

The use of Penman-Monteith (PM)-type combination-based energy-balance equations to estimate reference evapotranspiration (ET_(ref)) requires climatic data measured over well-watered and well-maintained reference grass or alfalfa vegetation surfaces. However, establishing and maintaining reference weather stations for a long period of time is a very formidable and expensive process. Thus, expansion of the microclimate data available for use in the PM equation for estimating ET_(ref) is needed. In the absence of reference weather stations. one alternative is using microclimatic data measured over other well-watered vegetation surfaces as inputs to the PM equation. This study determines if weather data collected from a well-watered soybean surface in a semihumid climate can be used for this purpose. Measured and estimated microclimate variables, including net radiation (R_n), average air temperature (T_(ave)), dew-point temperature (T_d), average relative humidity (RH_(ave)), aerodynamic resistance (r_a), and wind speed at 3 m (u_3) of a soybean and a grass canopy in South Central Nebraska, were analyzed and compared. The aerodynamic resistances of the soybean and grass canopies showed the largest percent difference of any of the microclimate variables for both 2007 and 2008. Wind speed was the primary microclimate variable with the largest percent difference between the two fields. The average percent differences in u_3, between the soybean and grass field were 9.0 and 9.8% for 2007 and 2008. Although T_(ave), RH_(ave), and T_d percent differences were not that large, there were distinct seasonalities to the differences. Grass and alfalfa reference evapotranspiration (ET_o and ET_r, respectively) calculations using data from the soybean (ET_(o-s) and ET_(r-s)) and grass (ET_(o-g) and ET_(r-g)) canopies were compared daily and seasonally. Seasonal total ET_o and ET_r estimates using soybean and grass microclimate data were very close, and within 1 and 2% during 2007 (ET_(o-g) = 583 mm and ET_(o-s)= 576 mm; ET_(r-g) = 751 mm and ET_(r-s) = 733 mm), and 4 and 5% during 2008 (ET_(o-g) = 554 mm and ET_(o-s) = 531 mm; ET_(r-g) = 707 mm and ET_(r-s) = 669 mm). In 2007, differences in temperature variables were most correlated to differences in ET_(ref) estimates. In 2008, the greatest correlations of differences in ET_o and ET_r were with differences in T_(ave), RH_(ave), and u_3. The results indicated that the microclimate data measured over an irrigated soybean canopy during normal or wet years (rainfall > 300 mm during the growing season) can be used in place of measurements taken over a grass canopy to estimate ET_o and ET_r in climatic conditions similar to semihumid climatic conditions of South Central Nebraska when reference weather station data are not available to solve the standardized PM equation.
机译:使用Penman-Monteith(PM)型基于组合的能量平衡方程式来估算参考蒸散量(ET_(ref))需要在灌溉良好且保养良好的参考草或苜蓿植被表面上测量的气候数据。但是,长时间建立和维护参考气象站是一个非常艰巨和昂贵的过程。因此,需要扩展可用于PM方程以估计ET_(ref)的微气候数据。在没有参考气象站的情况下。一种替代方法是将在其他灌溉良好的植被表面上测得的微气候数据用作PM方程的输入。这项研究确定了在半湿润气候下从灌溉良好的大豆表层收集的天气数据是否可以用于此目的。测量和估计的微气候变量,包括净辐射(R_n),平均气温(T_(ave)),露点温度(T_d),平均相对湿度(RH_(ave)),空气动力学阻力(r_a)和风速分析并比较了内布拉斯加州中南部3 m(u_3)处的一个大豆和一个草冠层。大豆和草冠层的空气动力学阻力在2007年和2008年的任何微气候变量中显示出最大的百分比差异。风速是主要的微气候变量,两个领域之间的百分比差异最大。 2007年和2008年,大豆田和草地的u_3的平均百分比差异分别为9.0和9.8%。尽管T_(ave),RH_(ave)和T_d百分比差异并不大,但存在明显的季节性差异。使用大豆(ET_(o-s)和ET_(r-s))和草木(ET_(o-g)和ET_(r-g))冠层的数据对草和苜蓿参考蒸散量(分别为ET_o和ET_r)进行计算,每天和季节性比较。使用大豆和草类小气候数据得出的季节总ET_o和ET_r估算值非常接近,在2007年期间分别为1-2%(ET_(og)= 583 mm和ET_(os)= 576 mm; ET_(rg)= 751 mm和ET_ (rs)= 733毫米),以及2008年期间的5%和5%(ET_(og)= 554毫米和ET_(os)= 531毫米; ET_(rg)= 707毫米和ET_(rs)= 669毫米)。在2007年,温度变量的差异与ET_(ref)估计值的差异最相关。在2008年,ET_o和ET_r的差异最大的相关性是与T_(ave),RH_(ave)和u_3的差异相关。结果表明,在正常或湿润年份(在生长季节降雨> 300毫米)在灌溉的大豆冠层上测得的微气候数据可代替在类似于气候条件下的草冠层上测得的值来估算ET_o和ET_r无法获得参考气象站数据来求解标准PM方程时,内布拉斯加州中南部的半湿润气候条件。

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