Shallow groundwater is a critical water resource for sustaining vegetation growth in arid and semi-arid environments and affects stand transpiration (T) dynamics. However, it is still difficult to quantify the impact of groundwater on T. Here, we introduced a novel groundwater response function in the Jarvis-type model (referred to as MJSG) and tested its performance using Populus popularis sapflow data over two main growing seasons (2018–2019). The results showed that the performance of the MJSG model depended on groundwater level. Specifically, when groundwater table depth was within 1.2–2.0 m, the precision of daily T simulation by the MJSG model was higher than that by the MJS model without groundwater response function over two years, with an increase in Nash-Sutcliffe Efficiency (NSE) from 0.787 to 0.825. Furthermore, in contrast to the MJS model, the MJSG model could better capture the diurnal course of T in 10:00–16:00, with a significant increase in NSE from 0.592 to 0.706. The improvement allows a more accurately estimate of tree water use under shallow groundwater fluctuations, which will help broaden the ecohydrological application of the Jarvis-type model to similar areas.

中文翻译：

---

将地下水响应函数集成到 Jarvis 型模型中用于 Populus popularis 蒸腾模拟


浅层地下水是在干旱和半干旱环境中维持植被生长的关键水资源，并影响林分蒸腾 （T） 动力学。然而，地下水对 T 的影响仍然难以量化。在这里，我们在贾维斯型模型（简称 MJSG）中引入了一种新的地下水响应函数，并使用 Populus popularis sapflow 数据在两个主要生长季节（2018-2019 年）测试了其性能。结果表明，MJSG 模型的性能取决于地下水位。具体而言，当地下水位深度在 1.2–2.0 m 之间时，MJSG 模型在两年内对日 T 模拟的精度高于没有地下水响应函数的 MJS 模型，Nash-Sutcliffe 效率 （NSE） 从 0.787 提高到 0.825。此外，与 MJS 模型相比，MJSG 模型可以更好地捕捉 T 在 10：00–16：00 的昼夜进程，NSE 从 0.592 显着增加到 0.706。这一改进可以更准确地估计地下水浅层波动下的树木用水量，这将有助于将 Jarvis 型模型的生态水文应用扩大到类似区域。