Mapping Maize Evapotranspiration at Field Scale Using SEBAL: A Comparison with the FAO Method and Soil-Plant Model Simulations

Remote Sensing

Francesco Morari¹  Marco Martello¹  Ilaria Piccoli¹  Pietro Teatini²  YannH. Chemin³  DiegoH. Pons⁴  Gabriele Manoli⁵  Carla Grosso⁶ 

[1] Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020 Legnaro PD, Italy;Department of Civil, Environmental and Architectural Engineering, University of Padova, 35131 Padova, Italy;Harvesting, Silicon Valley, CA 94027, USA;INTA EEA Manfredi, 5988 Córdoba, Argentina;Institute of Environmental Engineering, ETH Zurich, 8093 Zurich, Switzerland;Mario Gulich Institute, National Agency of Spatial Activities (CONAE), X5000 Córdoba, Argentina;

关键词: surface energy balance algorithm for land (SEBAL);    evapotranspiration;    yield;    remote sensing;    heterogeneous conditions;   

DOI  :  10.3390/rs10091452

来源: DOAJ

【 摘 要 】

The surface energy balance algorithm for land (SEBAL) has been successfully applied to estimate evapotranspiration (ET) and yield at different spatial scales. However, ET and yield patterns have never been investigated under highly heterogeneous conditions. We applied SEBAL in a salt-affected and water-stressed maize field located at the margin of the Venice Lagoon, Italy, using Landsat images. SEBAL results were compared with estimates of evapotranspiration by the Food and Agriculture Organization (FAO) method (ETc) and three-dimensional soil-plant simulations. The biomass production routine in SEBAL was then tested using spatially distributed crop yield measurements and the outcomes of a soil-plant numerical model. The results show good agreement between SEBAL evapotranspiration and ETc. Instantaneous ET simulated by SEBAL is also consistent with the soil-plant model results (R2 = 0.7047 for 2011 and R2 = 0.6689 for 2012). Conversely, yield predictions (6.4 t/ha in 2011 and 3.47 t/ha in 2012) are in good agreement with observations (8.64 t/ha and 3.86 t/ha, respectively) only in 2012 and the comparison with soil-plant simulations (8.69 t/ha and 5.49 t/ha) is poor. In general, SEBAL underestimates land productivity in contrast to the soil-plant model that overestimates yield in dry years. SEBAL provides accurate predictions under stress conditions due to the fact that it does not require knowledge of the soil/root characteristics.

【 授权许可】

Unknown