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The process of infiltration plays a vital role in hydrological cycle and replenishing the ground water resources. The associated infiltration data helps to estimate various components of hydrological cycle. The natural phenomenon of infiltration is influenced by several factors such as nature of soil, bulk density of soil, hydraulic conductivity, catchment terrain etc. The experimental procedure with double ring infiltrometer provides the field infiltration values extended over a time duration. However, due to tedious efforts and continuous human intervention required for on field process, researchers rely on mathematical models of such as physical models, empirical model and semi-empirical models. The work elaborates the potential of various commonly adopted infiltration models and reliability analysis of such models with field data using statistical parameters coefficient of correlation, coefficient of determination, root mean square error and decision factor. Further a Multi Linear Regression Model was developed by incorporating various factors like soil parameters and moisture content that governs the infiltration behavior of terrain and suggest an empirical equation for the process of infiltration which can be extended to catchment area similar terrain and soil properties. This study presents a comprehensive methodology for identifying the most suitable infiltration model based on field data and statistical evaluation. Various influencing factors were considered to develop a regression-based empirical model that accurately characterizes the infiltration process. Statistical parameters were employed to assess model performance and ensure robustness. The resulting regression equation demonstrates strong predictive capability and provides a practical tool for estimating infiltration in similar terrains. The novelty of this work lies in the application of the developed empirical model to areas with comparable geological and hydrological characteristics, offering a reliable approach for regional-scale hydrological assessments.

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Development of Empirical Equation for Infiltration Measurement Over a Catchment Area Using Statistical Methods

  • 会议论文

  • 发表日期：

    2026年

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  • Sunith John David,
  • K. U. Abdu Rahiman,
  • Subha Vishnudas

摘要

The process of infiltration plays a vital role in hydrological cycle and replenishing the ground water resources. The associated infiltration data helps to estimate various components of hydrological cycle. The natural phenomenon of infiltration is influenced by several factors such as nature of soil, bulk density of soil, hydraulic conductivity, catchment terrain etc. The experimental procedure with double ring infiltrometer provides the field infiltration values extended over a time duration. However, due to tedious efforts and continuous human intervention required for on field process, researchers rely on mathematical models of such as physical models, empirical model and semi-empirical models. The work elaborates the potential of various commonly adopted infiltration models and reliability analysis of such models with field data using statistical parameters coefficient of correlation, coefficient of determination, root mean square error and decision factor. Further a Multi Linear Regression Model was developed by incorporating various factors like soil parameters and moisture content that governs the infiltration behavior of terrain and suggest an empirical equation for the process of infiltration which can be extended to catchment area similar terrain and soil properties. This study presents a comprehensive methodology for identifying the most suitable infiltration model based on field data and statistical evaluation. Various influencing factors were considered to develop a regression-based empirical model that accurately characterizes the infiltration process. Statistical parameters were employed to assess model performance and ensure robustness. The resulting regression equation demonstrates strong predictive capability and provides a practical tool for estimating infiltration in similar terrains. The novelty of this work lies in the application of the developed empirical model to areas with comparable geological and hydrological characteristics, offering a reliable approach for regional-scale hydrological assessments.