Remote sensing indicators to assess riparian vegetation and river ecosystem health

Abstract

Environmental managers need information to quickly detect which stressor combinations should be addressed to reverse river degradation across large study areas. The pivotal role of riparian vegetation in regulating thermal regimes and inputs of light, nutrients and organic matter has made it a major target of stressor-mitigation and conservation actions. However, due to the dendritic and extensive nature of river networks, field-based monitoring of local riparian conditions is expensive and time-consuming. Ongoing developments in remote sensing offer an unparalleled opportunity to address this challenge. Nonetheless, there is still a limited understanding of the capacity of remote sensing indicators to predict changes in local riparian and river conditions, urging for local calibration with in situ measurements. This study aims to evaluate the capacity of remote sensing to detect impacts on quality elements commonly used in river biomonitoring: riparian vegetation, abiotic river condition and macrophyte biomass. To this end, four remote sensing metrics were tested against field-based indicators in 50 stream locations from four river basins across the Northwest of Portugal: i) the lateral riparian continuity at reach scale (riparian forest buffer width), ii) the riparian vegetation density at reach scale (Normalized Difference Vegetation Index, NDVI100m), and iii) the land use intensification at both reach (LUI100m) and iv) segment (LUI500m) scales. We found that the combination of remote sensing variables (riparian forest buffer width and the land use intensification index) correlated with riparian vegetation quality and dissolved inorganic nitrogen concentrations. We also found that the riparian vegetation density was able to predict changes in vascular plant biomass except for bryophytes. Our study provides new insights on the capacity of satellite-based indicators to assess riparian and river health, illustrating their utility for land and water managers, to identify and monitor, at a reduced cost and time, po