Seasonal variability of throughfall spatial pattern under a natural Fagus orientalis stand using geostatistical method

The spatial heterogeneity of throughfall (TF) is a critical component of the hydrological cycle. The aim of this study was to identify TF spatial pattern variability for leaf-out seasons in a natural beech (Fagus orientalis L.) stand located in the Caspian forests using geostatistical method. The rain-collectors used for measuring TF (n= 122) were distributed in a stratified simple random sampling design under the canopy. Measurements were carried out in 2016, and 2017; spring, summer, and autumn. Variograms indicated strong structure of spatial continuous TF pattern beneath the canopy for all seasons when the trees are in leaf. The spherical model was the best fitted model to empirical variograms for summer and fall and exponential model for spring season. The effective range of variogram for spring, summer, and fall were 2, 8, and 7 m, respectively. The leaf area index (LAI) of summer (6 m2/m2) was significantly higher than spring (4.5 m2/m2) and fall (5 m2/m2) seasons. The number of hotspot points was estimated to be the highest in summer (10) and lowest in spring (6). TF spatial variability was attributed to the climate variability and changeability of LAI characteristics, in particular. The LAI increasing may be a claim to increase the spatial continuity of TF and hotspot points observed in summer. This research properly displays the spatial pattern of TF for different seasons by geoestatistical method that could be successfully applied for predicting and mapping the changes in the behavior of rainfall affected by LAI under the canopy of a natural beech stand. Fully understanding the spatial distribution of rainfall within forests will definitely help the managers to optimize the management of these stands in terms of soil water and nutrition availability. The outcomes of this study would help future investigators for providing the appropriate sampling strategies in the beech stand under similar climate conditions.