## 1 Introduction
To address this limitation, recent advances in the Noah-MP model have incorporated a dynamic root model that enhances the representation of plant-water interactions, particularly in water-limited regions [26; 37]  
The Chinese Loess Plateau is characterized by a semi-arid to arid climate, with precipitation ranging from 200 mm in the northwest to 800 mm in the southeast [38]. Since 1999, larger-scale afforestation efforts have significantly increased the vegetation cover from 32% in 1999 to 60% in 2013 [39], with the leaf area index rising by 0.01 m\({}^{2}\) m\({}^{-2}\) and gross primary productivity increasing by 17.8 g C m\({}^{-2}\) from 2000 to 2016 [40]. Ecological plantations in this region predominantly develop deep fine root systems (diameter \(<\) 2 mm), enabling deep water uptake to meet transpiration [41; 42]. Previous studies have reported that deep soil water serves as a critical buffer against seasonal and interannual droughs [43; 44]. _Robinia pseudoacacia_ L. (_R. pseudoacacia_), a dominant afforestation species in the Loess Plateau, exhibits rapid root growth, extending fine roots at a rate of 1.0 m yr\({}^{-1}\) and reaching depths more than 20 m within 15 years [45]. However, its rapid growth has led to deep soil water depletion [46; 47]. A significant relationship was found between fine root length and soil water depletion within the 2-10 m soil layers in areas receiving more than 550 mm of annual precipitation [48]. Given the critical role of deep water uptake in sustaining plantation growth, a thorough investigation of its impact on plant-water interactions is essential. Most previous studies on plant-water interactions in the Loess Plateau have relied on statistical analyses using remote sensing or reanalysis data, often focusing on linear relationships between vegetation indicators (e.g., leaf area index, gross primary productivity, enhanced vegetation index) and hydroclimatic factors (e.g., precipitation, terrestrial water storage) [40; 49; 50]. Some studies have examined vegetation responses to drought indices [51; 52]. However, statistical methods cannot fully quantify plant-water interactions. With advancements in remote sensing and numerical modeling, recent studies have explored the impacts of climate, vegetation, and land use changes on the hydrological cycle using models that incorporate vegetation dynamics [53; 54; 55; 56]. For example, ecological restoration reduced terrestrial water storage by 16.6 \(\pm\) 5.0 mm yr\({}^{-1}\) in the Mu Us regions [53], and vegetation changes increased annual evapotranspiration by 11.2% over the loess Plateau [54]. Yet, most of these models assume shallow soil layers, limiting their ability to represent deep-rooting systems. Furthermore, they often neglect root-soil interactions and deep water uptake, leading to unrealistic estimates of soil moisture and evapotranspiration. Incorporating deep root-soil interactions into model simulations is thus essential for accurately evaluating plant-water interactions, particularly in _R. pseudoacacia_ plantations. In this study, we improved the Noah-MP model, developed by the University of Arizona, by integrating actual soil thickness as well as new subsurface and water table schemes. This enhanced model was applied to simulate vegetation growth and the hydrological cycle at an observational site within an _R. pseudoacacia_ plantation. The objectives of this study were to (1) assess the sensitivity of soil stratification and vertical root distribution to vegetation growth and soil water dynamics and (2) quantify the impact of plant-water interactions on long-term simulations.