Baiamonte et al. (2025) Exploring the impact of average water content on wetting bulb expansion from a buried point source

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-10-14
• Authors: Giorgio Baiamonte, Loris Franco, Girolamo Vaccaro
• DOI: 10.1016/j.agwat.2025.109889

Research Groups

• Department of Agricultural, Food and Forest Sciences (SAAF), University of Palermo, Palermo, Italy
• IRRITEC S.p.A., Capo d’Orlando, Messina, Italy

Short Summary

This study investigates the influence of the average volumetric water content (θavg) on the expansion of the wetting bulb from a buried point source in a subsurface drip irrigation (SDI) system. By calibrating a k parameter for θavg within Philip's analytical model using six years of experimental data, the study significantly improved the accuracy of wetting front travel time (tt) estimations, reducing the standard error from 15012 seconds to 1560 seconds.

Objective

• To investigate the impact of the average volumetric water content (θavg) on the expansion of the wetting bulb from a buried point source in a subsurface drip irrigation (SDI) system.
• To calibrate Philip's simplified analytical model by introducing a k parameter for θavg, aiming to improve the accuracy of wetting front travel time (tt) estimations.

Study Configuration

• Spatial Scale: An experimental citrus orchard (38°4′53.4′′ N, 13°25′8.2′′ E, 35 m above sea level) in Sicily, Italy, covering approximately 1000 square meters. The soil is classified as sandy-clay-loam or sandy loam. A subsurface drip irrigation (SDI) system with emitters buried at 0.30 meters depth and spaced 0.5 meters apart was used. A 1-meter-long "Drill & Drop" probe was installed 0.3 meters from an emitter, measuring soil water content and temperature at 0.1-meter intervals.
• Temporal Scale: Six years of continuous monitoring from January 2018 to November 2023. Soil moisture and temperature data were recorded every 1200 seconds (20 minutes). The study analyzed 141 recorded irrigation events, yielding a total of 832 paired travel time (tt) and initial soil moisture content (θ0) measurements.

Methodology and Data

• Models used:
  • Philip (1984) simplified analytical model for wetting front travel time from a buried point source.
  • Gardner (1958) exponential hydraulic conductivity function.
  • BEST-steady algorithm for estimating saturated hydraulic conductivity (Ks).
  • Power law relationships (k = m * d^n) were developed to model the intra-seasonal variability of the k parameter.
• Data sources:
  • In-situ measurements: Volumetric soil water content (θ) and temperature from a 1-meter "Drill & Drop" probe (Sentek Pty Ltd.) with 10 sensors at 0.1-meter depth intervals.
  • Emitter characteristics: Nominal emitter flow rate (qn) of 5.83 × 10⁻⁷ m³ s⁻¹ (2.1 L h⁻¹) from self-compensating Multibar™ C emitters.
  • Soil hydraulic properties: Determined from 15 Beerkan infiltration experiments and six undisturbed soil cores, yielding parameters like dry soil bulk density (ρb = 1269 kg m⁻³), initial gravimetric soil water content (w0 = 0.094 kg kg⁻¹), initial volumetric soil water content (θ0 = 0.119 m³ m⁻³), saturated volumetric soil water content (θs = 0.521 m³ m⁻³), and Gardner's α parameter (8.6 m⁻¹).
  • Meteorological data: Half-hourly precipitation, solar radiation, wind speed and direction, air temperature, and relative humidity from a WatchDog 2000 Series weather station.

Main Results

• The common simplified assumption of θavg being the mean between initial and saturated volumetric water content (k = 0.5) led to significant overestimations of travel times, with a standard error of the estimate (SEE) of 15012 seconds (4.17 hours). This assumption was found to be reasonable only at the deepest soil layers.
• The introduction and calibration of a k parameter, which allows θavg to vary between θ0 and θs, substantially improved the accuracy of travel time (tt) estimation. The SEE was reduced from 15012 seconds to 1560 seconds (26 minutes), which is moderate considering the 1200-second (20-minute) data acquisition resolution.
• The calibrated k parameter exhibited a regular increasing trend with soil depth, indicating a progressive enrichment of water in the wetting bulb as it moves downward.
• Analysis of intra-seasonal variability showed that k values generally increase over an irrigation season, reflecting a soil moisture memory effect where retained water from previous events contributes to a wetter bulb. This dynamic behavior was well-described by power law relationships (k = m * d^n).
• The parameter 'm' (k value after one day) was strongly correlated with the initial soil moisture content (ISMC) at the start of the first irrigation (θ0|d=0). The parameter 'n' (shape of the power law) showed an inverse relationship with θ0|d=0, suggesting less temporal variability of k at higher ISMCs.

Contributions

• Introduced a novel k parameter to accurately represent the average volumetric water content (θavg) within Philip's analytical model, accounting for the model's inherent simplified assumptions.
• Demonstrated that a dynamic, calibrated θavg is crucial for accurate wetting bulb expansion prediction, significantly outperforming static assumptions (e.g., k=0.5).
• Provided a robust methodology for calibrating Philip's model using long-term field data, leading to a substantial improvement in travel time estimation accuracy (from hours to minutes).
• Characterized the depth-dependent and intra-seasonal variability of θavg, revealing the influence of soil moisture memory and initial conditions on wetting front dynamics.
• Offers practical implications for optimizing subsurface drip irrigation system design and water management by enabling more precise prediction of water distribution in the root zone.

Funding

• CN_00000022 “National Research Centre for Agricultural Technologies (Agritech)”, D.R. n. 1032 on 17.06.2022, PNRR MUR – M4C2 – 1.4 - “Centri Nazionali” - D.D. n. 3138 on 16/12/2021, CUP: B13D21011580004. Spoke 3 Enabling Technologies and sustainable strategies for the smart management of agricultural system and their environmental impact.
• PRIN 2022, “Smart Technologies and Remote Sensing methods to support the sustainable Agriculture WAter Management of Mediterranean woody Crops (SWAM4Crops)”, CUP: B53D23018040001.

Citation

@article{Baiamonte2025Exploring,
  author = {Baiamonte, Giorgio and Franco, Loris and Vaccaro, Girolamo},
  title = {Exploring the impact of average water content on wetting bulb expansion from a buried point source},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.109889},
  url = {https://doi.org/10.1016/j.agwat.2025.109889}
}