首页> 外文期刊>Journal of Science and Technology of Agriculture and Natural Resources >Correlation of Selianinov Hydrothermal Coefficient with Reference Evapotranspiration and Crop Water Requirement for Some Selected Crops and Different Weather Sites of Iran
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Correlation of Selianinov Hydrothermal Coefficient with Reference Evapotranspiration and Crop Water Requirement for Some Selected Crops and Different Weather Sites of Iran

机译:伊朗部分作物和不同气象点的Selianinov热液系数与参考蒸散量和作物需水量的相关性

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The most important factor in determining crop water requirement is estimation of evapotranspiration (ET). Majority of the methodsestimate ET apply series of relatively complex formula,which is then used to determine crop evapotranspiration (ETc). The parameters used in aforesaid methods are: Solar radiation, wind speed, humidity, etc. Unfortunately, in Iran and many countries, long-term records of these parameters are not readily available. The purpose of this study is to calculate the Selianinov Hydrothermic Index that merely requires daily temperature and precipitation data in order to determine correlation coefficients (r) versus ET and Crop Water Requirement (CWR) of some agricultural crops of Iran. First, the Selianinov index is calculated from daily precipitation and temperature during the growth season. Further, the results are correlated against both ETc and CWR. The model results indicate inverse (negative) strong exponential and polynomial relations between the dependent and independent variables. Coefficient of determination (R2) for polynomial equations (on average 0.84) in all crops was better than exponential equations (on average 0.72). Correlation between Selianinov index and CWR indicates that coefficient of determination in both equations was close together (0.83 for polynomial equations and 0.82 for exponential equations).
机译:决定作物需水量的最重要因素是蒸散量(ET)的估算。估计ET的方法多数采用一系列相对复杂的公式,然后用于确定作物的蒸散量(ETc)。上述方法中使用的参数是:太阳辐射,风速,湿度等。不幸的是,在伊朗和许多国家,这些参数的长期记录尚不可用。这项研究的目的是计算仅需要每日温度和降水量数据的塞利亚尼诺夫水热指数,以确定伊朗某些农业作物的相关系数(r)与ET和作物需水量(CWR)。首先,根据生长季节的每日降水量和温度计算出Selianinov指数。此外,结果与ETc和CWR相关。模型结果表明因变量和自变量之间的反(负)强指数和多项式关系。在所有作物中,多项式方程的确定系数(R2)(平均为0.84)要好于指数方程(平均为0.72)。 Selianinov指数与CWR之间的相关性表明,两个方程式的确定系数都很接近(多项式方程式为0.83,指数方程式为0.82)。

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