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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #385425

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Evapotranspiration estimation and scaling effects on water resources management over a Mediterranean oak savanna in southern Spain

item CARPINTERO, E. - Ifapa Centro Alameda Del Obispo
item Anderson, Martha
item ANDREU, A. - Ifapa Centro Alameda Del Obispo
item HAIN, C. - Nasa Marshall Space Flight Center
item Gao, Feng
item Kustas, William - Bill
item GONZALEZ-DUGO, M. - Ifapa Centro Alameda Del Obispo

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/13/2021
Publication Date: 9/16/2021
Citation: Carpintero, E., Anderson, M.C., Andreu, A., Hain, C., Gao, F.N., Kustas, W.P., Gonzalez-Dugo, M.P. 2021. Evapotranspiration estimation and scaling effects on water resources management over a Mediterranean oak savanna in southern Spain. Agricultural Water Management. 13(18):3701.

Interpretive Summary: The European oak savanna landscape is the most widespread agroforestry system in the continent, occupying more than three million hectares in the Iberian Peninsula. It provides multiple socio-economic uses (livestock, agriculture, hunting, etc.) with an essential role in the economy of rural areas, and it serves as a hotspot of biodiversity. Over the past several decades, however, numerous threats are endangering these savanna agroforestry systems. This paper investigates the utility of a remote sensing indicator of ecosystem health and resilience, quantifying vegetation water use at the management scale (30 m pixels, daily timesteps). Analyses of spatial patterns in ET demonstrated capacity to separate conditions in open grassland, mixed tree/grass systems used in Iberian pig production, and densely treed areas serving as shelter for livestock and wildlife. These high-resolution ET maps show utility for agricultural management decision making related to grazing rotations, and delineating areas with higher water holding capacity and vegetation cover that can sustain a wide diversity of plant and animal species.

Technical Abstract: Mediterranean oak savanna is composed of a mixture of scattered oak trees, crops, pasture, and shrubs. This type of savanna 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 the monitoring of water consumption of a Mediterranean watershed with savanna landscape at different spatial and temporal scales for the years 2013-2015. We used a remote sensing-based energy balance model (ALEXI/DisALEXI approach), and the STARFM 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 a 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 coarser spatial resolution, and may assist management decisions at field and farm scale.