ABSTRACT

Relative soil water content (RSWC) is widely used to characterize the impact of water stress (WS) on vegetation. In bi-layer ecosystems, such as olive groves, this impact must be primarily estimated for the tree component, which, having greater rooting depth, responds more slowly to WS than understory grass. This complicates the application of methods for RSWC prediction, which must be properly adapted to consider the deeper soil layer influential on olive trees. The current study investigates the modification of a recently proposed RSWC simulation method based on a combination of meteorological and satellite-derived normalized difference vegetation index (NDVI) data. The application of the method to an olive grove in Central Italy requires the estimation of both weather and NDVI contributions affecting solely olive trees, which is carried out through the use of appropriate data processing techniques. The RSWC estimates obtained reasonably reproduce the ground RSWC observations referred to the 1 m soil layer, which are representative of the WS affecting olive trees (r² = 0.795, RMSE = 0.15 and MBE = −0.09). The limits and prospects of this method are finally discussed with particular reference to the possible integration of the RSWC estimates within more complex ecosystem models.

摘要

相对土壤含水量 (RSWC) 广泛用于表征水分胁迫 (WS) 对植被的影响。在双层生态系统中，例如橄榄树，必须主要针对树木成分估计这种影响，树木成分具有更大的根深，对 WS 的响应比林下草更慢。这使 RSWC 预测方法的应用变得复杂，必须适当调整以考虑对橄榄树有影响的更深土壤层。目前的研究调查了最近提出的基于气象和卫星衍生的归一化差异植被指数 (NDVI) 数据的组合的 RSWC 模拟方法的修改。将该方法应用于意大利中部的橄榄树需要估计仅影响橄榄树的天气和 NDVI 贡献，这是通过使用适当的数据处理技术进行的。获得的 RSWC 估计合理地再现了参考 1 m 土壤层的地面 RSWC 观测值，这代表了影响橄榄树的 WS（r²  = 0.795，RMSE = 0.15 和 MBE = −0.09）。最后讨论了这种方法的局限性和前景，特别是在更复杂的生态系统模型中可能整合 RSWC 估计。