Intact tropical peatlands are globally important carbon stores, yet their hydrology remains poorly understood due to limited accessibility and sparse field measurements. In this study, we evaluate the potential of L-band Synthetic Aperture Radar (SAR) backscatter to monitor above-ground water level variation across diverse lowland peatland ecosystems in Colombia and Peru. Using vegetation structure metrics from GEDI with ancillary remote sensing data, we assess the sensitivity of L-band HH (L-HH) backscatter to water level changes. We observed significant linear correlations between water level and L-HH backscatter in white-sand ecosystems, palm swamp peatlands (open and forested) and seasonally flooded forests. Pole forest peatland water levels showed no correlation with L-HH backscatter. To predict these regressions, we developed ecosystem-specific multiple linear regression models using L-band HV backscatter, NDVI, and GEDI metrics, achieving strong predictive performance (R 2 = 0.8–0.94). We further tested the temporal robustness of these relationships by predicting water levels across different years. Our results demonstrate the potential of combining L-band SAR with vegetation metrics derived from spaceborne data for regional monitoring of peatland hydrology. This provides a methodological pathway for integrating tropical peatland dynamics into carbon cycle models. • L-band SAR HH backscatter correlates with water level in tropical peatland sites. • Vegetation structure controls L-band SAR sensitivity to hydrological changes. • Ecosystems with low vegetation density show strong monitoring potential. • Palm swamps and flooded forests exhibit good monitoring potential with L-band SAR. • Our approach supports the integration of peatland hydrology into carbon cycle models.
Uhde et al. (Tue,) studied this question.