Osorio-Diaz et al. (2026) Agricultural water balance and variability in Utah irrigation canal companies with OpenET products and spatial data

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Irrigation Science
• Year: 2026
• Date: 2026-08-31
• Authors: Katherine Osorio-Diaz, Alfonso F. Torres‐Rua, Matt A. Yost, Lawrence E. Hipps
• DOI: 10.1007/s00271-026-01172-8

Research Groups

Not explicitly stated in the abstract, but the study focuses on three Irrigation Canal Companies (ICCs) in Northern Utah, suggesting involvement of researchers and practitioners in water management, hydrology, and remote sensing in that region.

Short Summary

This study developed and implemented a satellite-data-driven water balance model for irrigation canal companies (ICCs) in Northern Utah, demonstrating its feasibility for assessing agricultural water depletion and identifying significant water balance residuals under data-limited conditions.

Objective

• To implement a monthly water balance model for three Irrigation Canal Companies (ICCs) in Northern Utah by coupling historical remote sensing data with Geographic Information Systems (GIS) data and agricultural diversion records.
• To determine the change of water depletion at the root zone (∆Dr) and quantify water balance residuals (WBR) at the ICC scale.

Study Configuration

• Spatial Scale: Three Irrigation Canal Companies (ICCs) in Northern Utah, focusing on agricultural fields and canal distribution at the ICC scale.
• Temporal Scale: Monthly water balance calculations over the period 2020–2023, with seasonal analysis (April-October).

Methodology and Data

• Models used:
  • Monthly water balance model (determining ∆Dr with precipitation, irrigation, capillary rise as inflows; and actual crop evapotranspiration, runoff, deep percolation as outflows).
  • Random Forest model (to capture the spatial distribution of ∆Dr).
• Data sources:
  • Historical remote sensing data from OpenET (actual crop evapotranspiration, ETc act).
  • Historical remote sensing data from gridMET (precipitation).
  • Geographic Information Systems (GIS) data (fields/canals distribution).
  • Agricultural diversion records.
  • Local observed data (ETc act and soil water content) for Random Forest model training.

Main Results

• Water balance residuals (WBRs) varied spatially and temporally across the study area from 0.01 to 2.7 cubic hectometers per month between 2020 and 2023.
• The highest WBR values occurred during the peak irrigation season (July-August).
• Seasonally (April-October), WBR represented 5–29% of the sum of all water balance components across the studied ICCs, indicating a significant unresolved portion of the water balance.
• The study successfully demonstrated the feasibility of approximating an ICC-scale water balance, even under data-limited conditions.

Contributions

• Provides one of the few existing water balance approaches at the irrigation canal company (ICC) level, which is critical for agricultural water optimization in arid regions.
• Demonstrates a practical methodology for approximating ICC-scale water balances using readily available remote sensing and GIS data, addressing data limitations.
• Quantifies significant water balance residuals at the ICC scale, highlighting areas for potential water savings and the need for improved monitoring and data collection.

Funding

Not specified in the abstract.

Citation

@article{OsorioDiaz2026Agricultural,
  author = {Osorio-Diaz, Katherine and Torres‐Rua, Alfonso F. and Yost, Matt A. and Hipps, Lawrence E.},
  title = {Agricultural water balance and variability in Utah irrigation canal companies with OpenET products and spatial data},
  journal = {Irrigation Science},
  year = {2026},
  doi = {10.1007/s00271-026-01172-8},
  url = {https://doi.org/10.1007/s00271-026-01172-8}
}