Inferring vegetation-infiltration relationships from multitemporal land surface reflectance across gradients of management intensity and forest regeneration in the humid highlands of Veracruz, Mexico

Accurately quantifying soil hydraulic parameters (SHP) improves hydrologic model performance and helps differentiate the ecohydrologic functioning of different land-cover types. However, SHP can vary widely within a single cover type due to site-specific topographic and anthropogenic factors. The effects of these factors on SHP are particularly pronounced and challenging to characterize in mountainous land-cover mosaics. In this study, we sought to develop an approach to the areal estimation of SHP that accounts for heterogeneity within cover types without requiring detailed site-level data. We measured field-saturated hydraulic conductivity (Ksat), a key SHP, at 53 sites in five land-cover types (pasture, row crops, shade coffee agroforest, and pine-alder and cloud forests) in Veracruz, Mexico. To identify predictors of Ksat across the landscape (600 sq. km), we conducted terrain analyses and characterized interannual and seasonal vegetation dynamics with an 18-year time series of surface reflectance that integrates imagery from three multispectral platforms (30-m spatial resolution and finer) to compensate for frequent cloud cover. Across a range of model sophistication (from cover-type means to random forests), the reflectance behavior of vegetation during extreme conditions (i.e., drought and high-productivity years) proved to be a better predictor of Ksat in forests and agricultural cover types than topographic attributes or the use of management intensity or successional status to define more precise cover types. These findings build on studies from semiarid ecosystems by demonstrating that remotely sensed vegetation dynamics can correlate with SHP even in landscapes where water availability is not expected to limit plant growth.