Understanding the interaction of vegetation and hydrology and determining the changes in this relationship across spatial and temporal domains is critical for modeling landscape hydrology. Trees release water into the atmosphere via stomatal pores in exchange for carbon dioxide and play an important role in landscape hydrology. Our objective was to investigate the coupled spatial and temporal dynamics of vegetation and hydrological properties in a forested catchment covering 7900 m2 in central Pennsylvania at the Shale Hills Critical Zone Observatory. During 2010, We measured leaf area index (LAI) and canopy closure to characterize vegetation properties and soil water content, soil water potential and water table depth to characterize hydrological properties at a spatial grid of 70 sampling points across an entire watershed at 15-day intervals. We used geostatistical techniques to quantify spatial structure (semi-variograms) and visualize spatial patterns (Kriging) of vegetation and hydrological properties and their relationship to each other (cross-variograms). Our results show an
exponential increase (90 - 600 m) in the range of spatial autocorrelation and decrease in noise-to-signal ratio of LAI from April to August, which also coincides with exponential increase in LAI (1 - 5 m2m-2) and exponential decline in soil water content (0.3 - 0.1 m3 m-3) at a 10 cm soil depth. Results from this study suggest increasing spatial dependence from leaf onset till maturity and that the landscape canopy area and soil water become more homogenized and coupled from spring to summer. Our results provide insight into tight coupling between vegetation and hydrology across space and time; incorporating these spatial and temporal feedbacks in hydropedological models will improve current and future landscape modeling of temperate forests.
Naithani, K.J., Gaines, K., Baldwin, D., Lin, H., Eissenstat, D.M. (2010): Spatial and Temporal Dynamics of Vegetation and Hydrological Properties at Shale Hills Critical Zone Observatory in Central Pennsylvania. AGU Annual Fall Conference Proceedings.
This Paper/Book acknowledges NSF CZO grant support.