ABSTRACT

Accurate information on cropland evapotranspiration (ET) can facilitate effective agricultural management. However, the application of existing physical models over broad regions may be impeded due to the need for difficult to acquire information about environmental factors that constrain ET. The recently developed near-infrared reflectance of vegetation (NIR_v), which can reasonably characterize ecosystem photosynthesis without the need for additional environmental information, is potentially useful for estimating cropland ET and reducing the difficulty in ET modeling. As such, we proposed two simply formulated semi-empirical models that utilize NIR_v as a major factor constraining cropland ET. The first model, termed Penman–Monteith+ (PM+), computed canopy transpiration using the PM equation along with canopy conductance values estimated from NIR_v-derived gross primary productivity (NIR_v-GPP) and calculated soil evaporation using an empirical approach. Another model, termed underlying water-use efficiency+ (uWUE+), used the uWUE approach along with the NIR_v-GPP to predict ET. We calibrated and validated PM+ and uWUE+ over 32 cropland flux sites and then compared them with six complex models. The better model between PM+ and uWUE+ was applied to estimate regional ET over North China Plain (NCP), where typical C₃ and C₄ crops were planted during 2010–2018, along with remote sensing and meteorological data. Results indicated that the two new models can reasonably estimate cropland ET. The PM+ model reproduced an eight-day value of ET (denoted as eight-day ET) with R² = 0.741 and RMSE = 5.638 mm/8d, slightly better than the uWUE+ model (R² = 0. 674 and RMSE = 6.275 mm/8d) for a cross-site validation over 17 flux sites of the validation dataset. Site-level validation revealed consistently better performance of PM+ compared to uWUE+ over most flux sites. For the comparisons with six existing models, PM+ can perform better than all these models and uWUE+ is better than five of them. Subsequently, the PM+ (uWUE+) model reasonably reproduced eight-day ET over four sites under a dry climate (Arid Index ≤ 0.5) with site-level R² = 0.691 (0.617) and RMSE = 6.663 (7.906) mm/8d on average, which is better than the six existing models. In addition, the regional mean annual ET varied from 590 mm per year (mm/yr) to 680 mm/yr over NCP with a significant increasing trend of 9.05 mm/yr (p < 0.01), and the ET values in maize growing season were higher than that in wheat growing season. Our results demonstrated that the simply formulated PM+ and uWUE+ models can provide simple and robust approaches to estimate regional and global cropland ET.

摘要

关于农田蒸散 (ET) 的准确信息可以促进有效的农业管理。然而，由于需要难以获取有关限制 ET 的环境因素的信息，现有物理模型在广泛区域的应用可能会受到阻碍。最近开发的植被近红外反射率 (NIR _v ) 可以在不需要额外环境信息的情况下合理地表征生态系统光合作用，对于估计农田 ET 和降低 ET 建模的难度有潜在的帮助。因此，我们提出了两个利用 NIR _{v 的}简单公式化的半经验模型作为制约农田ET的主要因素。第一个模型，称为 Penman-Monteith+ (PM+)，使用 PM 方程计算冠层蒸腾作用以及从 NIR _v衍生的总初级生产力 (NIR _v -GPP)估计的冠层电导值，并使用经验方法计算土壤蒸发。另一个模型，称为潜在用水效率 + (uWUE+)，使用 uWUE 方法和 NIR _v -GPP 来预测 ET。我们校准并验证了 32 个农田通量站点的 PM+ 和 uWUE+，然后将它们与六个复杂模型进行了比较。PM+和uWUE+之间更好的模型被用于估计华北平原（NCP）的区域ET，其中典型的C ₃和C ₄2010-2018 年期间种植了农作物以及遥感和气象数据。结果表明，这两个新模型可以合理地估计农田ET。PM+ 模型再现了 ET 的八天值（表示为八天 ET），R ²  = 0.741 和 RMSE = 5.638 mm/8d，略好于 uWUE+ 模型（R ² = 0. 674 和 RMSE = 6.275 mm/8d) 用于验证数据集的 17 个通量站点的跨站点验证。站点级验证显示，在大多数通量站点上，PM+ 的性能始终优于 uWUE+。与现有的六个模型进行比较，PM+ 的表现优于所有这些模型，而 uWUE+ 优于其中的五个。随后，PM+（uWUE+）模型合理再现了干燥气候（干旱指数≤ 0.5）下四个站点的八天ET，站点级R ²  = 0.691（0.617）和RMSE = 6.663（7.906）mm/8d ，优于现有的六种模型。此外，区域平均年 ET 从 590 毫米/年（mm/yr）到 680 毫米/年不等，在 NCP 上有显着增加的趋势，为 9.05 毫米/年（p< 0.01)，玉米生长季的ET值高于小麦生长季的ET值。我们的结果表明，简单公式化的 PM+ 和 uWUE+ 模型可以提供简单而可靠的方法来估计区域和全球农田 ET。