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Multiple Linear Correlation Analysis of Daily Reference Evapotranspiration

机译:日参考蒸散量的多元线性相关分析

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An accurate estimation of reference evapotranspiration (ET_0) is of paramount importance for many studies such as hydrologic water balance, irrigation system design and management, crop yield simulation, and water resources planning and management. Simple regression techniques, may sometimes, provide adequate estimation of ET_0. Implementation of regression methods considering all the predictor variables may, however, lead to overfit and consequent reduction in the predictive capability. The regression models for ET_0 have been developed in the present study for Tirupati, Nellore, Rajahmundry, Anakapalli and Rajendranagar regions of Andhra Pradesh, India by following step-wise procedure, eliminating superfluous predictor variables based on statistical criteria. The sunshine hours, wind velocity, temperature and relative humidity influenced ET_0 in the study area. The linear regression models developed in terms of predictor variables may conveniently be applied in the regions selected for the present study and, in the regions with similar climatic conditions for satisfactory ET_0 estimation.
机译:对于许多研究,例如水文水平衡,灌溉系统设计和管理,作物产量模拟以及水资源计划和管理,准确估计参考蒸散量(ET_0)至关重要。有时,简单的回归技术可能会提供足够的ET_0估计。但是,考虑所有预测变量的回归方法的实施可能会导致过度拟合并因此导致预测能力下降。 ET_0的回归模型已在本研究中针对印度安得拉邦的蒂鲁伯蒂,内洛尔,拉贾蒙德里,阿纳卡帕利和拉金德拉纳加尔地区进行了逐步开发,并根据统计标准消除了多余的预测变量。日照时间,风速,温度和相对湿度影响了研究区域的ET_0。根据预测变量开发的线性回归模型可以方便地应用于为本研究选择的区域,以及具有相似气候条件的区域,以进行令人满意的ET_0估计。

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