Michael C. Anderson

Are Single‐Source, Remote‐Sensing Surface‐Flux Models Too Simple?

Both one‐source and two‐source parameterizations of surface sensible heat flux exchange using radiometric surface temperature have been proposed. Although one‐source algorithms may provide reliable heat fluxes, they often require field calibration and hence are unable to accommodate the diverse range of surface conditions often encountered over a landscape. Two‐source models require fewer assumptions and no a priori calibration, and therefore have a wider range of applicability without requiring any additional input data. A one‐source scheme (SEBAL) that performs an “internal calibration” using hydrologic extremes (hot/dry and wet/cool pixels) encountered within a remote sensing scene has been proposed as a way to eliminate a priori calibration and the need for ancillary data. In this paper, some of the key assumptions in SEBAL are evaluated using a two‐source model, field data, and simulations from a complex soil‐vegetation‐atmosphere transfer (SVAT) model, Cupid.

Continuous evapotranspiration monitoring and water stress at watershed scale in a Mediterranean oak savanna

The regular monitoring of the evapotranspiration rates and their links with vegetation conditions and soil moisture may support management and hydrological planning leading to reduce the economic and environmental vulnerability of complex water-controlled Mediterranean ecosystems. In this work, the monitoring of water use over a basin with a predominant oak savanna (known in Spain as dehesa) was conducted for two years, 2013 and 2014, monitoring ET at both fine spatial and temporal resolution in different seasons. A global 5 km daily ET product, developed with the ALEXI model and MODIS day-night temperature difference, was used as starting point. Flux estimations with higher spatial resolutions were obtained with the associated flux disaggregation scheme, DisALEXI, using surface temperature data from the polar orbiting satellites MODIS (1 Km, daily) and Landsat 7/8 (60-120m and sharpened to 30m, 16 days) and the previously estimated coarse resolution fluxes. The results achieved supported the ability of this scheme to accurately estimate daytime-integrated energy fluxes over this system, using input data with different spatio-temporal resolution and without the need for ground observations. Daily ET series at 30 m spatial resolution, generated using STARFM fusion technique, has provided a significant improvement in spatial heterogeneity assessment of the ET series, with RMSE values of 0.56 and 0.68 mm/day for each year, representing an enhancement with respect to interpolated Landsat series. In summary, this approach was demostrated to be robust and operative to map ET at watershed scale with a suitable spatial and temporal resolution for applications over the dehesa ecosystem.

A Multi‐Scale Remote Sensing‐Based Modeling System For Estimating Local And Regional Fluxes

An effective flux‐scaling scheme must be able to bridge the gap between the field scale of interest to agricultural and resource managers (∼100 m) and the regional scale (∼10–100 km), the resolutions used by operational climate and weather forecast models. An approach with operational capabilities is described, which employs a flux disaggregation strategy. Fluxes can be mapped over regional or continental scales in the U.S. at 5–10 km resolution each day using coarse‐scale thermal‐infrared imagery from a geostationary platform such as Geostationary Operational Environmental Satellite (GOES). These coarse‐scale flux estimates can then be spatially disaggregated to finer scales at sites and times of particular interest using higher resolution imagery from satellite sensors such as Landsat. In this way, the temporal sampling power of the geostationary satellites (images every 15 minutes) can be combined with the spatial resolution of polar orbiters (15m – 1km). The disaggregation process serves both as a mea...