# Spatiotemporal Variations in Vegetation Canopy Interception in China Based on a Revised Gash Model
## 1 Introduction  
Vegetation canopy interception is the process by which gross rainfall falling onto plant surfaces is captured, stored, and subsequently lost through evaporation from the canopy [1]. This process represents water loss from ecosystems and water gain for the atmosphere, and as such it plays a critical role in regulating the global hydrological cycle and land-atmosphere interactions [2, 3]. It has been widely reported that canopy interception accounts for more than 20% of the gross rainfall across biomes globally [4], even exceeding 40% in some forest-covered regions [5, 6]. In addition, canopy interception is also the main component of evapotranspiration, with proportion values frequently reaching up to 50% in many ecosystems [7]. Despite its importance, vegetation canopy interceptionhas been traditionally simplified as an underestimated constant or even overlooked in many hydrological models [2], leading to great uncertainties in the modeling results and limiting our understanding of regional hydrological processes. Therefore, how to quantify the magnitude of canopy interception across different vegetation biomes has become an important scientific issue in ecohydrological studies in recent years [8; 9; 10]. Field observations and model simulations are two commonly used methods to estimate the canopy interception of vegetation. The first allows the calculation of interception from the in-situ monitoring throughfall (TF) and stemflow (SF) based on the water balance model, as Ic = P-TF-SF (where P is gross rainfall or precipitation) [11]. Because of its easy operability, the field observation method has been widely used to estimate interception in almost all ecosystems worldwide [4; 12; 13]. However, due to the randomness of precipitation and diversity of vegetation, long-term monitoring periods are generally required, which makes this method time consuming and costly [14; 15]. Model simulations have contributed to addressing this problem, as they allow for estimation of canopy interception based on the available meteorological variables and vegetation canopy parameters [1; 16]. Numerous interception models have subsequently been developed to accurately estimate canopy interception loss in various ecosystems, such as regression models [17], empirical models [18], stochastic models [19], and physically based models [9; 20; 21; 22]. Among them, a simple process-based model proposed by [PERSON] (1979), known as the Gash analytical model, has been widely applied due to its simple calculation process and good simulation ability in different ecosystems [1; 23; 24]. Yet, the original model usually overestimates canopy interception in sparse forests, as it contains a weakness in the description of the canopy cover fraction for this ecosystem [21]. A revised Gash model was therefore reformulated by improving boundary conditions and using evaporation per unit canopy area instead of per unit ground area [21; 25]. This reformulated version of the model has been verified to have a good performance in predicting interception under various canopy coverage conditions, from sparse to closed canopy [10; 26; 27; 28; 29]. However, both the interception results obtained from field observation and simulation models are mostly limited to individual, stand, or ecosystem scales, and it is uneasy to upscale these models to the regional or global scales [30; 31; 32]. This limitation does not allow to include interception into global hydrological models and to consider the spatial and temporal information of interception within the current context of global change. With the development of satellite technology, remote sensing has become a powerful tool to extract spatial and temporal information related to earth surface processes owing to its vast coverage, low costs, and applicability in ungauged areas [32].