An improved approach to estimating the infiltration characteristics in surface irrigation systems

Area of Science:

• Agricultural Engineering
• Soil Science
• Hydrology

Background:

• Estimating soil infiltration functions is crucial for efficient irrigation management.
• Traditional methods like double-ring infiltrometers (DRI) and empirical models often suffer from data scatter and accuracy issues.
• Soil water content variability and measurement errors impact infiltration function reliability.

Purpose of the Study:

• To present a novel methodology for calibrating soil infiltration functions.
• To enhance the accuracy and reliability of infiltration function estimation.
• To investigate the effect of data scatter on infiltration function estimation.

Main Methods:

• Conducted furrow irrigation experiments to collect infiltration data.
• Combined double-ring infiltrometer (DRI) measurements with changes in soil water content.
• Utilized empirical models (Kostiakov model) for comparison.
• Observed furrow elevations, advance/recession times, and inflow rates.

Main Results:

• DRI-estimated infiltration depths were lower than observed depths.
• Empirical model (Kostiakov) estimated infiltration depths were higher than observed depths.
• The proposed combined method yielded more accurate and reasonable infiltration function estimates.

Conclusions:

• The new methodology offers a more accurate approach to estimating infiltration functions than DRI or empirical models alone.
• The proposed method effectively reduces data scatter caused by soil variability and measurement errors.
• This approach can potentially reduce the number of measurements needed during irrigation events.