Evaluation of Ecosystem Water Use Efficiency Based on Coupled and Uncoupled Remote Sensing Products for Maize and Soybean
Evaluation of Ecosystem Water Use Efficiency Based on Coupled and Uncoupled Remote Sensing Products for Maize and Soybean
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DOI：
10.3390/rs15204922
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发表时间：
2023-10
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通讯作者：
Lingxiao Huang;Meng Liu;Na Yao
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作者：
Lingxiao Huang;Meng Liu;Na Yao
农业生态系统水分利用效率（eWUE）的准确量化对于水资源管理和粮食安全保障至关重要。目前，非耦合的中分辨率成像光谱仪（MODIS）产品是最广泛应用的数据集，用于模拟不同植物功能类型的本地，区域和全球eWUE。然而，很少有人研究偶联产物在特定C4和C3作物物种的eWUE估计中是否优于非偶联产物。在这里，利用8天尺度和年尺度的实测资料，对非耦合的MODIS产品和耦合的Penman-Monteith-Leuning version 2（PMLv2）产品的eWUE、总初级生产力（GPP）和蒸散量（ET）进行了评价（包含1902个8天和61个年度样本）的C4玉米和C3大豆在来自FLUXNET2015和AmeriFlux数据集的5个农田站点。研究结果表明：（1）在GPP估测中，PMLv2产品对C4玉米的估测值有显著提高，而对C3大豆的估测值则略有提高。(2)对于ET估计，两种产品对两种作物的表现相似。(3)对于eWUE估计，耦合PMLv2产品实现了更高的精度eWUE估计比未耦合的MODIS产品在八天和年度尺度。以8天尺度的结果为例，与MODIS产品相比，PMLv2产品可以将C4玉米的均方根误差（RMSE）从2.14 g C Kg − 1 H2O降低到1.36 g C Kg − 1 H2O，并将决定系数（R2）从0.06提高到0.52，C3大豆的RMSE从1.33 g C Kg − 1 H2O降低到0.89 g C Kg − 1 H2O，R2从0.05增加到0.49。(4)尽管PMLv2产品在eWUE估计中表现出色，但这两种产品在其模型校准和验证过程中未能区分C4和C3作物物种，导致eWUE估计存在一定程度的不确定性。本研究不仅为应用遥感产品获得可靠的农田eWUE估计提供了重要参考，而且还表明了未来对C4和C3作物物种的现有遥感模型的修改。
Accurate quantification of ecosystem water use efficiency (eWUE) over agroecosystems is crucial for managing water resources and assuring food security. Currently, the uncoupled Moderate Resolution Imaging Spectroradiometer (MODIS) product is the most widely applied dataset for simulating local, regional, and global eWUE across different plant functional types. However, it has been rarely investigated as to whether the coupled product can outperform the uncoupled product in eWUE estimations for specific C4 and C3 crop species. Here, the eWUE as well as gross primary production (GPP) and evapotranspiration (ET) from the uncoupled MODIS product and the coupled Penman–Monteith–Leuning version 2 (PMLv2) product were evaluated against the in-situ observations on eight-day and annual scales (containing 1902 eight-day and 61 annual samples) for C4 maize and C3 soybean at the five cropland sites from the FLUXNET2015 and AmeriFlux datasets. Our results show the following: (1) For GPP estimates, the PMLv2 product showed paramount improvements for C4 maize and slight improvements for C3 soybean, relative to the MODIS product. (2) For ET estimates, both products performed similarly for both crop species. (3) For eWUE estimates, the coupled PMLv2 product achieved higher-accuracy eWUE estimates than the uncoupled MODIS product at both eight-day and annual scales. Taking the result at an eight-day scale for example, compared to the MODIS product, the PMLv2 product could reduce the root mean square error (RMSE) from 2.14 g C Kg−1 H2O to 1.36 g C Kg−1 H2O and increase the coefficient of determination (R2) from 0.06 to 0.52 for C4 maize, as well as reduce the RMSE from 1.33 g C Kg−1 H2O to 0.89 g C Kg−1 H2O and increase the R2 from 0.05 to 0.49 for C3 soybean. (4) Despite the outperformance of the PMLv2 product in eWUE estimations, both two products failed to differentiate C4 and C3 crop species in their model calibration and validation processes, leading to a certain degree of uncertainties in eWUE estimates. Our study not only provides an important reference for applying remote sensing products to derive reliable eWUE estimates over cropland but also indicates the future modification of the current remote sensing models for C4 and C3 crop species.