Evapotranspiration (ET) is a crucial component of the soil–plant-atmosphere system. In semi-arid Mediterranean regions, most land water loss occurs through ET, encompassing both evaporation from the earth's surface and plant transpiration. A comprehensive understanding of the actual ET spatiotemporal dynamics is critically important for hydrological modelling and effective water resource management. This significance is further pronounced considering the growing stress on water resources and the potential influence of climate change on water fluxes. Remote sensing (RS) provides long-term, high-resolution data that can contribute to the monitoring and management of natural ecosystems. Surface energy balance (SEB) methods relying on satellite remote sensing have proven effective in measuring actual evapotranspiration (ET) across different scales. However, their applicability may be constrained by interruptions in image acquisition caused by cloud cover and/or the spatio-temporal resolution limitations of satellites. In this research, a model-based methodology is suggested for simulating the dynamics of the soil–plant-atmosphere system and for estimating the daily actual evapotranspiration (ET) of a Mediterranean Maquis ecosystem in northwest Sardinia. The model integrates ET estimates obtained from the SEBAL model utilizing Landsat-8 data, satellite-derived vegetation indices, on-site measurements of potential evapotranspiration, and the mono-dimensional transient flow Richards equation for simulating soil moisture within the root zone. By combining these elements, the proposed model provides a more comprehensive and accurate estimate of the ET between Landsat acquisitions. The SEBAL model showed satisfactory performance in estimating actual evapotranspiration (ET) on satellite acquisition days, with an average error of 17 % compared to Eddy Covariance measurements. In addition, the integrated modelling approach yielded an ET average estimation error of ± 37 % in the whole studied period. The soil moisture simulation by the model had a notable accuracy with an average error of 7.1 %. Temporal analysis showed that the model effectively simulated ET and soil moisture under both dry and wet conditions, exhibiting similar monthly and daily variations as observed data. Furthermore, a sensitivity analysis revealed that the stress index significantly improved the model's accuracy, while vegetation dynamics had a lower impact. Overall, the proposed model is a valuable tool for estimating ET in semi-arid Mediterranean regions, providing important information for water resource management and conservation efforts. Further application and validation of the model are recommended as new data becomes accessible, especially in areas characterized by cropped and irrigated agriculture. In future work, we aim to spatialize the Richards equation and integrate a multi-dimensional water balance hydrologic model.

中文翻译：

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模拟土壤湿度和每日实际蒸散量：集成遥感表面能量平衡和一维理查兹方程

蒸散量（ET）是土壤-植物-大气系统的重要组成部分。在半干旱的地中海地区，大多数陆地水损失是通过蒸散发生的，包括地球表面的蒸发和植物蒸腾。全面了解实际的蒸散时空动态对于水文建模和有效的水资源管理至关重要。考虑到水资源日益增加的压力以及气候变化对水通量的潜在影响，这一重要性更加明显。遥感（RS）提供长期、高分辨率的数据，有助于自然生态系统的监测和管理。事实证明，依靠卫星遥感的地表能量平衡（SEB）方法可以有效测量不同尺度的实际蒸散量（ET）。然而，它们的适用性可能会受到云层覆盖和/或卫星时空分辨率限制引起的图像采集中断的限制。在这项研究中，提出了一种基于模型的方法来模拟土壤-植物-大气系统的动态并估计撒丁岛西北部地中海马基斯生态系统的每日实际蒸散量（ET）。该模型集成了利用 Landsat-8 数据从 SEBAL 模型获得的蒸散估计值、卫星衍生的植被指数、潜在蒸散量的现场测量以及用于模拟根区土壤湿度的单维瞬态流理查兹方程。通过结合这些要素，所提出的模型可以对 Landsat 采集之间的 ET 进行更全面、更准确的估计。 SEBAL 模型在估算卫星采集日的实际蒸散量 (ET) 方面表现出令人满意的性能，与涡流协方差测量相比，平均误差为 17%。此外，综合建模方法在整个研究期间产生的 ET 平均估计误差为 ± 37%。该模型对土壤湿度的模拟精度较高，平均误差为7.1%。时间分析表明，该模型有效地模拟了干燥和潮湿条件下的蒸散和土壤湿度，表现出与观测数据相似的月和日变化。此外，敏感性分析表明，应力指数显着提高了模型的准确性，而植被动态的影响较小。总体而言，所提出的模型是估算半干旱地中海地区蒸散发的宝贵工具，为水资源管理和保护工作提供了重要信息。随着新数据的出现，建议进一步应用和验证该模型，特别是在以种植和灌溉农业为特征的地区。在未来的工作中，我们的目标是空间化理查兹方程并整合多维水平衡水文模型。