Evaporative Fraction as an Indicator of Moisture Condition and Water Stress Status in Semi-Arid Rangeland Ecosystems

• Published in: Remote sensing (Basel, Switzerland) Vol. 6; no. 7; pp. 6300 - 6323
• Main Authors: Nutini, Francesco, Boschetti, Mirco, Candiani, Gabriele, Bocchi, Stefano, Brivio, Pietro Alessandro
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2014
• Subjects: Algorithms; Arid environments; Biomass; biomass estimation; Energy balance; Estimates; Evaporative; evaporative fraction; Evapotranspiration; Rangelands; Remote sensing; semi-arid rangeland; Vegetation; Water availability; Water stress
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs6076300

Rangeland monitoring services require the capability to investigate vegetation condition and to assess biomass production, especially in areas where local livelihood depends on rangeland status. Remote sensing solutions are strongly recommended, where the systematic acquisition of field data is not feasible and does not guarantee properly describing the spatio-temporal dynamics of wide areas. Recent research on semi-arid rangelands has focused its attention on the evaporative fraction (EF), a key factor to estimate evapotranspiration (ET) in the energy balance (EB) algorithm. EF is strongly linked to the vegetation water status, and works conducted on eddy covariance towers used this parameter to increase the performances of satellite-based biomass estimation. In this work, a method to estimate EF from MODIS products, originally developed for evapotranspiration estimation, is tested and evaluated. Results show that the EF estimation from low spatial resolution over wide semi-arid area is feasible. Estimated EF resulted in being well correlated to field ET measurements, and the spatial patterns of EF maps are in agreement with the well-known climatic and landscape Sahelian features. The preliminary test on rangeland biomass production shows that satellite-retrieved EF as a water availability factor significantly increased the capacity of a remote sensing operational product to detect the variability of the field biomass measurements.