Estimating Evapotranspiration of Mediterranean Oak Savanna at Multiple Temporal and Spatial Resolutions. Implications for Water Resources Management

Abstract

Mediterranean oak savanna is composed of a mixture of scattered oak trees, crops, pasture, and shrubs. It is the most widespread agroforestry landscape in Europe, and its conservation faces multiple threats including water scarcity, which has been exacerbated by global warming and greater climate variability. Evapotranspiration (ET) can be used as a proxy of the vegetation water status and response to water shortage conditions, providing relevant information about the ecosystem stability and its hydrological dynamics. This study evaluates a framework to estimate ET at multiple spatial and temporal scales and applies it to the monitoring of the oak savanna vegetation water consumption for the years 2013–2015. We used a remote sensing-based energy balance model (ALEXI/DisALEXI approach), and the STARFM data fusion technique to provide daily ET estimates at 30 m resolution. The results showed that modeled energy balance components compared well to ground measurements collected by an eddy covariance system, with root mean square error (RMSE) values ranging between 0.60 and 2.18 MJ m−2 d−1, depending on the sensor dataset (MODIS or Landsat) and the flux. The daily 30 m ET series generated by STARFM presented an RMSE value of 0.67 mm d−1, which yielded a slight improvement compared to using MODIS resolution or more simple interpolation approaches with Landsat. However, the major advantage of the high spatio-temporal resolution was found in the analysis of ET dynamics over different vegetation patches that shape the landscape structure and create different microclimates. Fine-scale ET maps (30 m, daily) provide key information difficult to detect at a coarser spatial resolution over heterogeneous landscapes and may assist management decisions at the field and farm scale.

Remote Sensing for Water Resources and Environmental Management

“…Plant water use is critical to the survival, productivity, and spatial distribution of various vegetation functional types. Remote sensing of plant water-use estimation is, therefore, critical in water-controlled ecosystems or dryland areas with limited water resources, as well as in soil moisture dynamics [11,12]. This Special Issue features studies that used multi-source satellite datasets and advanced data analytics techniques to estimate plant water use at various scales.…”

“…This Special Issue features studies that used multi-source satellite datasets and advanced data analytics techniques to estimate plant water use at various scales. Carpintero et al [11] used the ALEXI/DisALEXI model and the STARFM data fusion technique to estimate evapotranspiration (ET) dynamics in a Mediterranean oak savanna at fine spatial and temporal resolution (30 m, daily) from 2013 to 2015. DisALEXI energy fluxes (1 km, daily) and Landsat images (60-100 m, 16 days) were compared to in situ measurements from an eddy covariance flux tower system.…”