Performance assessment of infiltration models for varying soil textural classes

Authors

  • Xiufang Yang 1. School of Transportation Engineering, Yangzhou Polytechnic Institute, Yangzhou 225127, Jiangsu, China
  • Shoukat Ali Soomro 2. Faculty of Agricultural Engineering and Technology, Sindh Agriculture University, Tandojam 70050, Pakistan
  • Vikash Kumar Rajani 2. Faculty of Agricultural Engineering and Technology, Sindh Agriculture University, Tandojam 70050, Pakistan
  • Bin Li 3. College of Optical, Mechanical and Electrical Engineering, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China
  • Rajesh Kumar Soothar 2. Faculty of Agricultural Engineering and Technology, Sindh Agriculture University, Tandojam 70050, Pakistan
  • Muhammad Uris Mirjat 2. Faculty of Agricultural Engineering and Technology, Sindh Agriculture University, Tandojam 70050, Pakistan
  • Sher Ali Shaikh 2. Faculty of Agricultural Engineering and Technology, Sindh Agriculture University, Tandojam 70050, Pakistan
  • Farman Ali Chandio 2. Faculty of Agricultural Engineering and Technology, Sindh Agriculture University, Tandojam 70050, Pakistan 4. Yellow River Delta Intelligent Agricultural Machinery Equipment Industry Academy, Dongying 257300, Shandong, China

DOI:

https://doi.org/10.25165/ijabe.v18i6.9603

Keywords:

infiltration models, infiltration rate, texture, predictions

Abstract

Field experiments were carried out to investigate the soil infiltration rates in different soil textures (clay loam, clay, and silty clay loam) with five infiltration models (Kostiakov, Modified Kostiakov, Philip, Horton, and Green-Ampt). Field experiments were conducted at the experimental stations of Sindh Agriculture University, Tandojam (Station No. 1, Faculty of Agricultural Engineering; 25°25′28′′N, 68°32′24′′E), (Station No. 2, Latif Experimental Farm; 25°26′14′′N, 68°32′30′′E) and Agriculture Research, Tandojam, (Station No. 3, Barley and Wheat Research Institute, 25° 24′ 59′′ N 68° 32′ 40′′ E), Sindh, Pakistan. These stations were selected to meet the need of three different soil textures. The composted soil samples were collected at the depth of 0-30 cm, and their textural classes were determined with the Bouyoucos hydrometer method. Field infiltration rates were measured using a double ring infiltrometer method. The results showed that the initial infiltration rates were high and gradually decreased until they reached a steady state. Using statistical parameters (NSE, RMSE, CC, and R2), the measured infiltration rates were compared with the predicted infiltration rates of the selected infiltration models. For clay loam soil, Philip’s model had the lowest RMSE and highest NSE, CC, and R2 values, followed by Horton’s model. For both clay and silty clay loam soils, Horton’s model was the most accurate in predicting the infiltration rate with lowest RMSE and highest NSE, CC, and R2 values, followed by Philip’s model. The other three models (Kostiakov’s, Modified Kostiakov’s, and Green-Ampt’s) performed poorly with higher errors and lower agreements compared to Horton’s and Philip’s models. In conclusion, Horton’s model demonstrated the highest accuracy and agreement for clay and silty clay loam soils, while Philip’s model showed the best performance for clay loam soil. These findings contribute to understanding the behavior of soil infiltration rate and provide valuable insights for land and water management practices in the studied area. Key words: infiltration models; infiltration rate; texture; predictions DOI: 10.25165/j.ijabe.20251806.9603 Citation: Yang X F, Soomro S A, Rajani V K, Li B, Soothar R K, Mirjat M U, et al. Performance assessment of infiltration models for varying soil textural classes. Int J Agric & Biol Eng, 2025; 18(6): 175–181.

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Published

2025-12-26

How to Cite

Yang, X., Soomro, S. A., Rajani, V. K., Li, B., Soothar, R. K., Mirjat, M. U., … Chandio, F. A. (2025). Performance assessment of infiltration models for varying soil textural classes. International Journal of Agricultural and Biological Engineering, 18(6), 175–181. https://doi.org/10.25165/ijabe.v18i6.9603

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Section

Natural Resources and Environmental Systems