Abstract

Mediterranean oak savannas (known as dehesas in Spain) are exposed to numerous threats from natural and economic causes. A close monitoring of the use of water resources and the status of the vegetation in these ecosystems can be useful tools for maintaining the production of ecological services. This study explores the estimation of evapotranspiration (ET) and water stress over a dehesa by integrating remotely sensed data into a water balance using the FAO-56 approach (VI-ETo model). Special attention is paid to the different phenology and contribution to the system’s hydrology of the two main canopy layers of the system (tree + grass). The results showed that the model accurately reproduced the dynamics of the water consumed by the vegetation, with RMSE of 0.47 mm day−1 and low biases for both, the whole system and the grass layer, when compared with flux tower measurements. The ET/ETo ratio helped to identify periods of water stress, confirmed for the grassland by measured soil water content. The modeling scheme and Sentinel-2 temporal resolution allowed the reproduction of fast and isolated ET pulses, important for understanding the hydrologic behavior of the system, confirming the adequacy of this sensor for monitoring grasslands water dynamics.

Highlights

  • Water availability is the main climate factor limiting the primary production of Mediterranean agroforestry systems

  • Xu et al [38] found a linear relationship between Normalized Difference Vegetation Index (NDVI) and dead cover in grasslands, with a variable contribution to NDVI depending on the dead cover fraction

  • The spectral data were taken on 7 July 2015 over 20 sampling points, and this information was later integrated into the Landsat Operational Land imager (OLI) sensor bandwidths, using the spectral response function for those wavelengths in order to compute the broadband vegetation indices (VIs)

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Summary

Introduction

Water availability is the main climate factor limiting the primary production of Mediterranean agroforestry systems. Remote sensing is widely used in agricultural areas to assist in the computation of crop water requirements, using an adaptation of the Food and Agriculture Organization (FAO) Irrigation and drainage paper -56 approach [21,22] This model estimates crop evapotranspiration (ET) as being the product of reference evapotranspiration (ETo ), representing the atmospheric evaporative demand, and a crop coefficient (Kc ) used to account for crop factors, such as crop type, developmental stage, ground cover, or soil water content. Xu et al [38] found a linear relationship between Normalized Difference Vegetation Index (NDVI) and dead cover in grasslands, with a variable contribution to NDVI depending on the dead cover fraction This study uses both measurements and models to explore the factors influencing the estimation of ET and water stress over a dehesa ecosystem in an attempt to provide effective vegetation parameters to model the water balance with the assistance of remote sensing.

Methods
Ground Validation Measurements
Remote-Sensing-Based Soil–Water Balance Model
Tree–Grass Cover Fraction during the Dry Season
Satellite Remote Sensing Dataset
Meteorological Information and Soil Properties
Tabulated and Measured Soil and Vegetation Parameters
Calibration of Vegetation Parameters
Results and Discussion
Performance
Dead Grass Impact on ET Estimations during the Dry Season
Conclusions
Full Text
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