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用修改的普里斯特利-泰勒模型和Landsat图像来估计乌达姆辛格纳格区的作物蒸发

Anurag Satpathi¹, Abhishek Danodia², Salwan Ali Abed³

¹Department of Agrometeorology, College of Agriculture, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, 263145, India.

Scientific reports

|September 13, 2024

概括

使用修改的普里斯特利-泰勒 (MPT) 模型与陆地卫星数据估计了乌达姆辛格纳格的准确每日蒸发透气量 (ET). MPT模型显示出强烈的验证,证实了其用于精确ET估计的有效性.

科学领域:

水文学水文学
遥感遥感遥感遥感
农业科学农业科学

背景情况:

精确的每日蒸发透气 (ET) 估计对于水资源管理和农业规划至关重要.
在ET估计中的挑战包括数据准确性,云层覆盖,气溶和陆地覆盖的变化.
修改后的普里斯特利-泰勒 (MPT) 模型为可靠的ET估计提供了一个潜在的解决方案.

研究的目的:

应用修改后的普里斯特利-泰勒 (MPT) 模型进行每日蒸发转化 (ET) 估计.
利用Landsat 8和9数据集在乌达姆辛格纳格地区进行ET估计.
使用 lysimeter 数据验证 MPT 模型的性能.

主要方法:

修改后的普里斯特利-泰勒 (MPT) 模型的应用.
从2022-23年开始利用Landsat 8和9卫星图像.
使用lysimeter观察到的蒸发分数进行验证.

主要成果:

从12月到4月,平均ET率在1.33至3.20毫米/天-1之间.
在MPT模型中,与lysimeter数据 (R2 = 0.71) 显示出强烈的相关性.
验证指标包括0.04mm day-1的平均偏差误差和0.62mm day-1.1的RMSE.

结论:

修改后的普里斯特利-泰勒 (MPT) 模型是有效的在研究区域准确的每日ET估计.
该研究提供了关于能量流和ET速率的空间和时间变化的见解.
结果支持MPT模型在类似农业地区进行水资源评估的能力.

关键词:

农业气象学农业气象学蒸发转化是指蒸发转化修改的普里斯特利-泰勒陆地卫星

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