Smart Farming Technologies for Groundwater Conservation in Transboundary Aquifers of Northwestern México

This study evaluated the performance of a smart farming technology (SFT) and a climate-smart agriculture (CSA) approach for improving irrigation management in pecan (Carya illinoinensis) orchards in México through soil moisture monitoring, evapotranspiration estimation, and real-time data integration. Continuous monitoring allowed irrigation to be maintained at field capacity, preventing plant stress while avoiding total soil saturation or permanent wilting point. Calibration of soil moisture sensors showed a very strong correlation (R2 = 0.99) between sensor reverse voltage and volumetric soil water content in predominant sandy loam soils, confirming the reliability of the monitoring system for irrigation scheduling. Seasonal analysis of reference evapotranspiration (ETo) and crop evapotranspiration (ETc) revealed increasing atmospheric water demand during summer months, with crop coefficient (Kc) values ranging from approximately 0.3 during dormancy to 1.0–1.3 during peak vegetative growth. After five years of field implementation of the technology, results showed water savings exceeding 50% compared with traditional flood irrigation practices. The optimized irrigation schedule reduced total seasonal irrigation depth from 216 cm to 128 cm, representing a 59% reduction in applied water while maintaining adequate soil moisture conditions for crop development at field capacity (FC). These results highlight the potential of integrating sensor-based monitoring, evapotranspiration modeling, and IoT platforms to enhance water-use efficiency and support sustainable pecan production under increasing climate variability.

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Publication Details

Journal
Water
Published
2026-03-23
DOI
https://doi.org/10.3390/w18060755
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
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article

Smart Farming Technologies for Groundwater Conservation in Transboundary Aquifers of Northwestern México

Ismael Aguilar Benítez, Christopher J. Brown, Alexander G. Fernald, Felipe Adrián Vázquez Gálvez et al.
Water
Soil Moisture and Remote Sensing
article

Smart Farming Technologies for Groundwater Conservation in Transboundary Aquifers of Northwestern México

Ismael Aguilar Benítez, Christopher J. Brown, Alexander G. Fernald, Felipe Adrián Vázquez Gálvez, Víctor Manuel Salas-Aguilar, W. L. Hargrove, Joam M. Rincon-Zuloaga, Luis C. Alatorre-Cejudo, Alfredo Granados-Olivas, Alfonso Gandara-Ruiz, Victor H. Esquivel-Ceballos, Josiah M. Heyman, Luis C. Bravo-Peña, Richard Heerema
article en

Abstract

This study evaluated the performance of a smart farming technology (SFT) and a climate-smart agriculture (CSA) approach for improving irrigation management in pecan (Carya illinoinensis) orchards in México through soil moisture monitoring, evapotranspiration estimation, and real-time data integration. Continuous monitoring allowed irrigation to be maintained at field capacity, preventing plant stress while avoiding total soil saturation or permanent wilting point. Calibration of soil moisture sensors showed a very strong correlation (R2 = 0.99) between sensor reverse voltage and volumetric soil water content in predominant sandy loam soils, confirming the reliability of the monitoring system for irrigation scheduling. Seasonal analysis of reference evapotranspiration (ETo) and crop evapotranspiration (ETc) revealed increasing atmospheric water demand during summer months, with crop coefficient (Kc) values ranging from approximately 0.3 during dormancy to 1.0–1.3 during peak vegetative growth. After five years of field implementation of the technology, results showed water savings exceeding 50% compared with traditional flood irrigation practices. The optimized irrigation schedule reduced total seasonal irrigation depth from 216 cm to 128 cm, representing a 59% reduction in applied water while maintaining adequate soil moisture conditions for crop development at field capacity (FC). These results highlight the potential of integrating sensor-based monitoring, evapotranspiration modeling, and IoT platforms to enhance water-use efficiency and support sustainable pecan production under increasing climate variability.

WaterVol. 18(6)
New Mexico State University (US), Universidad Autónoma de Ciudad Juárez (MX), El Colegio de la Frontera Norte (MX), The University of Texas at El Paso (US)
Openalex Percentile: Top 12%
Soil Moisture and Remote Sensing
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