使用太阳诱导的叶绿素光改善参考作物的蒸发透气估计
Renjun Wang1,2, Shuaiqiang Zhang1,2, Jianghua Zheng3,4
1College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830046, PR China.
Scientific reports
|October 3, 2025
概括
准确的基准作物蒸发转化率 (ET0) 估计对于水资源管理至关重要. 使用太阳诱导的叶绿素光 (SIF) 和基底作物系数 (Kcb) 的新混合模型提高了ET0的准确性,优于传统方法.
科学领域:
- 水文学的水文学
- 遥感 遥感 遥感 遥感
- 农业学是一种农业学.
背景情况:
- 准确的基准作物蒸发透气 (ET0) 估计对于水资源管理和作物用水需求至关重要.
- 传统的ET0模型经常受到不完整的气象数据的影响.
- 太阳诱导的叶绿素光 (SIF) 为ET0估计提供了一个有前途的替代方案.
研究的目的:
- 开发一个改进的基于SIF的ET0估计模型,考虑环境变量.
- 提高ET0估计的精度和时空分辨率.
- 为干旱和半干旱地区提供精确ET0估计的新方法.
主要方法:
- 将基底作物系数 (Kcb) 纳入ET0_SIF模型,以创建混合模型 (RET0_SIF).
- 整合了RET0_SIF模型与卫星观测和再分析数据进行高分辨率ET0估计 (RET0_SIFd).
- 对22个监测站验证了该模型,并将其与Penman-Monteith (ET0PM) 方法进行了比较.
主要成果:
- RET0_SIF模型显著提高了ET0估计的准确性,并捕获了季节性变化.
- 与ET0PM.相比,RET0_SIF在与ET0PM.相比的最小偏差下表现出优于传统模型的性能.
- RET0_SIFd显示出西向东的空间模式下降,以及ET0.0的时间趋势正面.
结论:
- 基于SIF的混合模型 (RET0_SIF) 为ET0估计提供了更准确的方法.
- 这种方法通过结合环境因素,有效地解决了现有模型的局限性.
- 高分辨率的ET0估计为干旱和半干旱环境中的水资源管理提供了宝贵的见解.
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