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\begin{document}

\title{Variability Assessment of Soil Water Balance Components in an Almond
Field using Distributed Process-Based Modeling and Electromagnetic
Induction Data}



\author[1]{Tiago Ramos}%
\author[1]{Ana R. Oliveira}%
\author[1]{Hanaa Darouich}%
\author[2]{Mohammad Farzamian}%
\affil[1]{University of Lisbon}%
\affil[2]{INIAV}%


\vspace{-1em}



  
  \date{June 15, 2024}


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\selectlanguage{english}
\begin{abstract}
Accurate estimates of the soil water balance components are critical for
optimizing irrigation water use in agricultural fields. Estimates are
normally obtained using simple water balance models and for
representative areas, not taking into consideration the within
variability of soil properties. In this study, we used the MOHID-Land
distributed process-based model to compute the variability of the soil
water balance components in a 23ha almond field located in southern
Portugal, at a resolution of 5m. The main objective was the possible
assessment of management zones for improving water productivity in that
water-scarce region. An electromagnetic induction survey was carried out
first to obtain electromagnetic conductivity images which provided the
spatial distribution of the real soil electrical conductivity (ff) with
depth. The spatial distribution of ff was then correlated to soil
particle size distribution using an in-situ calibration. Afterward,
pedotransfer functions were applied to define the soil hydraulic
parameters necessary to run the distributed model and map the within
soil variability at the field scale. Irrigation data was monitored
on-site, at two locations, while weather data was extracted from a local
meteorological station. The distributed modeling approach included the
definition of potential evapotranspiration fluxes computed from the
product of the reference evapotranspiration obtained according to the
FAO56 Penman-Monteith equation and a crop coefficient for each stage of
almond's growing season, the variable-saturated flow using the Richards
equation, and root zone water stress following a macroscopic approach.
Modeling results were used to present the maps of the variability of the
seasonal actual crop transpiration and soil evaporation, the mean soil
moisture, seasonal runoff, and seasonal percolation. Then, management
zones for improving irrigation water use in the studied almond field
were proposed.%
\end{abstract}%



\sloppy


\textbf{Variability Assessment of Soil Water Balance Components in an
Almond Field using Distributed Process-Based Modeling and
Electromagnetic Induction Data}

Tiago B. Ramos\textsuperscript{1}, Ana R. Oliveira\textsuperscript{1},
Hanaa Darouich\textsuperscript{2}, Mohammad Farzamian\textsuperscript{3}

\textsuperscript{1} Centro de Ci\selectlanguage{ngerman}ência e Tecnologia do Ambiente e do Mar
(MARETEC), Instituto Superior Técnico, University of Lisbon, Lisbon,
Portugal

\textsuperscript{2} LEAF-Linking Landscape, Environment, Agriculture and
Food-Research Center of the Associated Laboratory TERRA, Instituto
Superior de Agronomia, University of Lisbon, Lisbon, Portugal

\textsuperscript{3} Instituto Nacional de Investigação Agrária e
Veterinária (INIAV), Oeiras, Portugal

Accurate estimates of the soil water balance components are critical for
optimizing irrigation water use in agricultural fields. Estimates are
normally obtained using simple water balance models and for
representative areas, not taking into consideration the within
variability of soil properties. In this study, we used the MOHID-Land
distributed process-based model to compute the variability of the soil
water balance components in a 23ha almond field located in southern
Portugal, at a resolution of 5m. The main objective was the possible
assessment of management zones for improving water productivity in that
water-scarce region. An electromagnetic induction survey was carried out
first to obtain electromagnetic conductivity images which provided the
spatial distribution of the real soil electrical conductivity (\selectlanguage{greek}σ\selectlanguage{english}) with
depth. The spatial distribution of \selectlanguage{greek}σ \selectlanguage{english}was then correlated to soil
particle size distribution using an in-situ calibration. Afterward,
pedotransfer functions were applied to define the soil hydraulic
parameters necessary to run the distributed model and map the within
soil variability at the field scale. Irrigation data was monitored
on-site, at two locations, while weather data was extracted from a local
meteorological station. The distributed modeling approach included the
definition of potential evapotranspiration fluxes computed from the
product of the reference evapotranspiration obtained according to the
FAO56 Penman-Monteith equation and a crop coefficient for each stage of
almond's growing season, the variable-saturated flow using the Richards
equation, and root zone water stress following a macroscopic approach.
Modeling results were used to present the maps of the variability of the
seasonal actual crop transpiration and soil evaporation, the mean soil
moisture, seasonal runoff, and seasonal percolation. Then, management
zones for improving irrigation water use in the studied almond field
were proposed.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/essoar/essoar}

\end{center}
\end{figure}

\selectlanguage{english}
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\end{document}

