Xie et al. (2026) Practical irrigation scheduling at the sub-field scale: Comparing OpenET and capacitance soil moisture sensors against a TSEB reference in dry edible beans

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-08-31
• Authors: Shuhua Xie, Angie Gradiz, Joseph Oboamah, Wei-zhen Liang, PoNien Su
• DOI: 10.1016/j.agwat.2026.110734

Research Groups

• Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA
• Panhandle Research, Extension, and Education Center, University of Nebraska-Lincoln, Scottsbluff, NE, USA
• Michigan State University, Coldwater, MI, USA
• Department of Chemical & Biochemical Engineering, University of Iowa, Iowa City, IA, USA

Short Summary

This study compared three evapotranspiration (ET) estimation approaches—Two-Source Energy Balance (TSEB), an operational soil water balance (SWB) with capacitance sensors, and satellite-based OpenET—across three management zones in a dry edible bean field. OpenET showed moderate daily agreement with the TSEB reference, while the SWB approach performed poorly, highlighting OpenET's potential for sub-field precision irrigation and limitations of factory-default soil moisture sensor workflows.

Objective

• To quantify daily and cumulative agreement among ground-based TSEB, operational capacitance-sensor SWB, and OpenET ensemble ET estimates within instrumented management zones.
• To assess the performance of an operational capacitance-sensor SWB workflow for daily ET estimation.
• To evaluate whether soil-associated within-field patterns were reflected in OpenET estimates at a scale near its nominal pixel resolution.

Study Configuration

• Spatial Scale: A 50-hectare commercial dry edible bean field near Scottsbluff, Nebraska, USA (41°56′23.6″ N, 103°42′07.5″ W). Three management zones were delineated by apparent electrical conductivity (ECa). Three 23 m × 23 m plots were established per zone, with one representative plot per zone instrumented. OpenET data were extracted from 46 m × 46 m windows centered on instrumented plots, considering its 30 m nominal pixel resolution.
• Temporal Scale: A 47-day period from July 28 to September 12, 2023, covering the reproductive development through physiological maturity stages of dry edible beans (approximately DAP 52–98). Daily ET estimates were compared.

Methodology and Data

• Models used:
  • Two-Source Energy Balance (TSEB) model (Priestley-Taylor formulation)
  • Operational Soil Water Balance (SWB) model
  • OpenET ensemble (mean of ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop models)
• Data sources:
  • Ground-based observations:
    • Ground-installed infrared radiometer thermometers (IRT) for canopy temperature.
    • Sentek Drill and Drop capacitance probes for volumetric water content (VWC) at 10 cm intervals to 120 cm depth.
    • Nebraska Mesonet station (0.9 km away) for meteorological data (air temperature, relative humidity, wind speed, incoming solar radiation, precipitation).
    • Manual measurements of crop height, canopy cover, and dry bean yield.
    • Apparent electrical conductivity (ECa) survey for management zone delineation.
    • Soil samples for texture analysis and pedotransfer estimates of field capacity (FC) and permanent wilting point (PWP).
    • Producer controller logs for nominal irrigation depths.
  • Satellite-based data:
    • OpenET platform API for actual evapotranspiration (ETa) data (30 m spatial resolution).
    • Harmonized Sentinel-2 Multispectral Instrument satellite imagery (10 m × 10 m) for Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE).

Main Results

• The three ECa-delineated management zones exhibited significant differences (p < 0.05) in sensor-derived root-zone water status, vegetation indices (NDVI, NDRE), and yield, confirming distinct growing environments.
• The OpenET ensemble showed moderate daily agreement with the TSEB reference (R² = 0.33–0.52, RMSE = 1.0–1.2 mm/day, Mean Bias Error (MBE) = −0.55–0.06 mm/day).
• The operational SWB, using factory-default calibrated capacitance sensors, showed poor agreement with TSEB (R² = 0.01–0.05, RMSE = 3.1–7.0 mm/day), produced physically implausible daily residuals, and was highly sensitive to the chosen sensor upper threshold in two zones.
• Among individual OpenET models, eeMETRIC achieved the highest temporal correlations with TSEB (R² = 0.38–0.60). SIMS and SSEBop also showed relatively high correlations (R² = 0.35–0.58) and the largest monotonic descriptive gradients across zones.
• On common QA-clear Landsat acquisition dates, the temporal correspondence between OpenET ensemble and TSEB improved (R² = 0.76–0.92, RMSE = 0.54–1.05 mm/day).
• Across 40 complete-case dates, mean ETTSEBIRT descriptively declined from 4.81 mm/day in Zone 1 to 3.86 mm/day in Zone 3. ETOpenETensemble also showed a monotonic descriptive decline from 4.21 mm/day (Zone 1-associated) to 3.80 mm/day (Zone 3-associated).

Contributions

• This study provides a novel within-field, zone-associated evaluation of OpenET in dry edible beans, addressing a critical gap in sub-field scale validation for precision irrigation.
• It offers a direct comparison of satellite-based OpenET with both a ground-based energy balance model (TSEB) and a widely used commercial soil moisture sensor-based soil water balance (SWB) workflow.
• The findings highlight significant limitations of using factory-default calibrated capacitance soil moisture sensors with simplified operational SWB calculations for daily ET estimation.
• It identifies specific OpenET models (eeMETRIC, SIMS, SSEBop) that show promising performance for capturing within-field ET variability, suggesting their potential for sub-field precision irrigation applications where management zones span multiple pixels.
• The research emphasizes the crucial need for validation over larger, contiguous management zones with replicated and scale-matched ground observations, as well as site-specific sensor calibration and independent drainage measurements for robust ET assessment.

Funding

• U.S. Department of Agriculture National Institute of Food and Agriculture (Hatch project NEB-21–177, accession number 1015698)
• National Science Foundation EPSCoR award (#2420405)

Citation

@article{Xie2026Practical,
  author = {Xie, Shuhua and Gradiz, Angie and Qiao, Xin and Oboamah, Joseph and Liang, Wei-zhen and Wang, Jun and Su, PoNien},
  title = {Practical irrigation scheduling at the sub-field scale: Comparing OpenET and capacitance soil moisture sensors against a TSEB reference in dry edible beans},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110734},
  url = {https://doi.org/10.1016/j.agwat.2026.110734}
}