EGU21-13739
https://doi.org/10.5194/egusphere-egu21-13739
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Application of SVEN model to estimate evapotranspiration on a coffee plantation using MODIS and Sentinel products.

Ana María Durán-Quesada1, Ioanna Pateromichelaki2, Mónica García3, Sheng Wang4, Yolande Serra5, Marco Gutiérrez6, and Cristina Chinchilla7
Ana María Durán-Quesada et al.
  • 1University of Costa Rica, School of Physics, Center for Geophysical Research, San José, Costa Rica (ana.duranquesada@ucr.ac.cr)
  • 2Department of Environmental Engineering, Technical University of Denmark, Lyngby, Denmark (ioannapater@hotmail.com)
  • 3Department of Environmental Engineering, Technical University of Denmark, Lyngby, Denmark (mgarc@env.dtu.dk)
  • 4College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, USA (shengwang12@gmail.com)
  • 5University of Washington Cooperative Institute for Climate, Ocean, and Ecosystem Studies, Seattle, Washington, USA (yserra@uw.edu)
  • 6University of Costa Rica, Estación Experimental Fabio Baudrit Moreno, Alajuela, Costa Rica (marco.gutierrez@ucr.ac.cr)
  • 7University of Costa Rica, Environmental Pollution Research Center, San José, Costa Rica (marco.gutierrez@ucr.ac.cr)

Warming conditions represent a threat to food security and livelihood in countries in which agriculture is an important share of the national income. Central America is regarded as a climate change hotspot where significant changes in temperature and rainfall have been projected. Coffee is one of the most traditional crops in the area, with Costa Rican coffee recognized worldwide for its quality. However, increasing temperatures and rainfall extremes will likely compromise coffee plantations. A similar challenge has already been faced by farmers on interannual time scales related to the El Niño-Southern Oscillation phenomena, which is associated with yield disruptions and the spread of the coffee rust. A better understanding of the weather and climate dependency of coffee crops is needed to develop water use efficiency strategies for farms. To this end, the present study centers on the integration of long-term meteorological records and a set of measurements that cover the soil-plant-atmosphere continuum. Surface fluxes derived using the eddy covariance technique and the deployment of soil moisture sensors are combined to evaluate the performance of the Soil Vegetation Energy TraNsfer (SVEN) model. One year of micrometeorological and soil measurements in a sun-exposed coffee plantation is used to assess the skills of the SVEN model using a scheme based on MODIS and Sentinel derived products. The aim of this work is to evaluate the skills of the SVEN model to reproduce the intraseasonal seasonal and diurnal variability of evapotranspiration. Given the size of Costa Rica and the scale of the crops, satellite products are often considered of limited use. Nevertheless, given the strong need, the goal of this project is to provide a detailed evaluation of the use of these products in models and support strategies that could expand the use of satellite retrievals in areas currently considered marginal.

How to cite: Durán-Quesada, A. M., Pateromichelaki, I., García, M., Wang, S., Serra, Y., Gutiérrez, M., and Chinchilla, C.: Application of SVEN model to estimate evapotranspiration on a coffee plantation using MODIS and Sentinel products., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13739, https://doi.org/10.5194/egusphere-egu21-13739, 2021.

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