Combining Optical and Microwave Remote Sensing for Mapping Energy Fluxes in a Semiarid Watershed

Abstract A dual-source model treating the energy balance of the soil/substrate and vegetation that was developed to use radiometric surface temperature observations is revised to use remotely sensed near-surface moisture from a passive microwave sensor for estimating the soil surface energy balance. With remotely sensed images of near-surface soil moisture, land cover classification, and leaf area index, the model is applied over a semiarid area in the Walnut Gulch Watershed in southern Arizona. The spatial and temporal variation of the Bowen ratio (i.e., the ratio of the turbulent fluxes, sensible, and latent heat) “maps” generated by the model were similar to the changes in near-surface moisture fields caused by recent precipitation events in the study area. The estimated fluxes at the time of the microwave observations (i.e., “instantaneous” estimates) and those simulated over the daytime period are compared with the ground observations within the watershed. Differences between predicted and observed “instantaneous” fluxes were usually comparable to the measurement uncertainties, namely, 5% for net radiation and 20–30% for soil, sensible and latent heat fluxes, except when there was large temporal and spatial variations in solar radiation across the study area. However, by running the model over the daytime period, this variability in solar radiation proved to have a minor effect on computed daytime totals. In fact, differences with observed heat fluxes were significantly less (i.e., around 15%) than when comparing “instantaneous” values. Model predictions of the total soil heat flux over the daytime period were generally higher than measured. An empirical model was developed to reduce this bias, but it is not known how generally applicable it will be. Model sensitivity to typical uncertainties in remotely sensed leaf area index (LAI) and near-surface (0–5 cm) water content, W, was quantified. The variation in flux predictions caused by errors in prescribing leaf area index and W was less than 30%. More tests with this model over different landscapes are necessary to evaluate its potential for predicting regional fluxes. In particular, microwave and radiometric surface temperature observations are needed under drought conditions for evaluating if the model formulation of vegetation transpiration can properly adjust to this extreme and very important environmental condition.Published by Elsevier Science Inc., 1998