评估预测地下滴灌湿润模式的半经验模型性能

Saeid Zamani , Kaveh Ostad-Ali-Askari , Rouhollah Fatahi Nafchi , Giuseppe Provenzano
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引用次数: 0

摘要

背景由于土壤水分布的复杂性,准确预测湿润模式并不容易,这导致文献中提出的一些模型效率低下。这些模型没有考虑灌溉系统的水力特性,仅根据水量或渗透率、土壤水动力特性以及渗流环境的其他条件来建立。由于地下滴灌(SDI)渠道下湿润前沿估计的重要性,我们提出了一个半经验模型,利用易于获取的 SDI 系统数据来预测配水和再分配阶段的湿润模式。为了开发该模型并评估其性能,在一个装满粘壤土的土箱中 0.20 米深处放置了三根 16 毫米的滴管,喷头间距分别为 0.2 米、0.4 米和 0.5 米,出水量为 2-5 升/小时。在 50、100 和 150 kPa 的工作压力下,连续注水 3 小时,并在 1、2、3 和 24 小时后测量每个侧向的润湿模式几何形状。结果和结论结果表明,所提出的模型能最准确地估计润湿深度和宽度。润湿深度的 RMSE 和 MAE 统计指标分别为 0.001-0.002 m 和 0.004-0.009 m,而润湿宽度的相关指标分别为 0.001-0.003 m 和 0.005-0.016 m。与其他著名模型相比,这些数值的误差最小。因此,利用 SDI 系统可获得的水力参数,该模型可以对湿润模式进行可接受的预测。意义在本研究中,横向水力分析的结果被独特地用于确定湿润前沿的尺寸。此外,结果表明,该模型成功地预测了作为线源的横向下方的湿润模式。而其他模型通常用于估算点源周围的湿润前沿。
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Assessing a semi-empirical model performance to predict the wetting patterns in subsurface drip irrigation

Context

Because of the complexity of soil water distribution, accurate prediction of wetting pattern is not easily accessible and this has led to a inefficiency in some proposed models in the literature. These models do not consider the hydraulic characteristics of the irrigation system and are developed solely on the basis of the water volume or infiltration rate, soil hydrodynamic properties, and other conditions of the percolation environment.

Objective

Due to the importance of the estimation of wetting front beneath Subsurface Drip Irrigation (SDI) laterals, a semi-empirical model using easily accessible data of the SDI system is proposed to predict the wetting patterns in both distribution and redistribution phases. The aforementioned model has been developed based on a novel approach that couples the governing equations of the lateral hydraulics with empirical equations derived by dimensional analysis.

Methods

To develop the model and evaluate its performance, three 16-mm drip line pipes with 0.2, 0.4, and 0.5 m emitter spacing, and 2–5 l/h discharge were placed at 0.20 m depth in a soil box filled with clay loam soil. Water was applied for 3 hours at 50, 100, and 150 kPa operating pressures, and the wetting patterns’ geometries were measured in each lateral after 1, 2, 3, and 24 h. The performance of the model was then assessed and compared with that of three other models.

Results and conclusion

The result demonstrated that the proposed model provides the most accurate estimations of the wetting depths and widths. RMSE and MAE statistical indexes of the wetting depth were 0.001–0.002 m and 0.004–0.009 m, respectively, whereas those associated with the wetting width were 0.001–0.003 m and 0.005–0.016 m, respectively. These values resulted in the lowest error when compared with the corresponding obtained from other well-known models. Consequently, the model allows acceptable predictions of the wetting patterns using accessible hydraulic parameters of the SDI system.

Significance

Uniquely, the results of the lateral hydraulic analysis were applied to determine the wetting front dimensions in this study. Also, the results demonstrated that the model was successful in wetting pattern prediction beneath the lateral as a line source. While other models usually are used to estimate the wetting front around a point source.

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