Actual evapotranspiration (ET) is an essential variable in linking energy cycles, carbon, and water, yet challenging to measure. Inputs uncertainty and deficiencies in the key elements of hydrologic models are fundamental challenges for optimizing model performance. Furthermore, the performance of land surface model-based ET, reanalysis, and remote sensing products varies with spatiotemporal scales. Here, we evaluate sources of bias in the regional Wisconsin Irrigation and Scheduling Program (WISP) model and develop a correction using eddy covariance (EC) observations. ET, observations were made for five years (2018–2022) using EC systems in agricultural fields in Wisconsin. WISP model ET bias was linked to underestimation of net longwave radiation (LW) that was traced to incorrect specification of effective clear sky atmospheric emissivity (). Applying a correction to the led to reduced WISP model percent bias (pbias) and error for both LW and ET. The calibrated model more accurately represented observed ET. The results indicate that explicit treatment of the LW balance decreases the uncertainty of model parameters and improves the WISP model performance at independent sites. Applying this improved model parameterization reduced the bias of LW radiation from 62.8% to -6.2%, which improved the Nash-Sutcliffe Efficiency (NSE) from -0.08 to 0.52 for ET on training sites. Additionally, overall pbias was significantly reduced ( = 0.035) for validation sites after WISP correction. Hence, WISP performance improved for different crop types when optimal regional parameters were used, confirming the physical parameters' reliability. Our results highlight that model development should focus on energy balance parameterizations to improve ET simulation and the accuracy of hydrologic and climatic simulations for understanding critical processes underlying hydrologic and climatic variability and change over land.

中文翻译：

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利用涡流协方差测量改进区域灌溉调度计划蒸散发估计模型的参数化

实际蒸散量 (ET) 是连接能源循环、碳和水的重要变量，但测量起来却很困难。输入的不确定性和水文模型关键要素的缺陷是优化模型性能的根本挑战。此外，基于地表模型的蒸散、再分析和遥感产品的性能随时空尺度的不同而变化。在这里，我们评估了威斯康星州区域灌溉和调度计划 (WISP) 模型中的偏差来源，并使用涡度协方差 (EC) 观测值进行校正。 ET，使用 EC 系统在威斯康星州的农田中进行了五年（2018-2022）的观察。 WISP 模型 ET 偏差与净长波辐射 (LW) 的低估有关，而净长波辐射 (LW) 的低估可追溯到有效晴空大气发射率 () 的错误规范。对 LW 和 ET 进行修正可减少 WISP 模型百分比偏差 (pbias) 和误差。校准后的模型更准确地代表了观测到的蒸散量。结果表明，LW 平衡的显式处理降低了模型参数的不确定性，并提高了独立站点的 WISP 模型性能。应用这种改进的模型参数化将 LW 辐射的偏差从 62.8% 降低到 -6.2%，从而将训练场地 ET 的纳什-萨特克利夫效率 (NSE) 从 -0.08 提高到 0.52。此外，WISP 校正后验证位点的总体 pbias 显着降低 (= 0.035)。因此，当使用最佳区域参数时，不同作物类型的 WISP 性能得到改善，证实了物理参数的可靠性。我们的结果强调，模型开发应侧重于能量平衡参数化，以提高蒸散模拟以及水文和气候模拟的准确性，以了解水文和气候变化以及陆地变化的关键过程。