<p>Assessment of soil water infiltration through reliable estimation of the infiltration rate is key to informed decision-making for sustainable ecosystem management. This study was conducted to evaluate the performances of the Kostiakov, Modified Kostiakov, Horton, Swartzendruber, Brutsaert and Philip models in estimating cumulative infiltration depth under loam, sandy loam and loamy sand soil textures. The measured infiltration data from the double ring infiltrometer were fitted to the infiltration models and their goodness-of-fit statistics were verified by the Coefficient of Determination (<InlineEquation ID="IEq1"><EquationSource Format="TEX">\({R}^{2}\)</EquationSource></InlineEquation>), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The Goodness-of-fit statistics for all Cumulative infiltration estimating models across the three locations within the study area associated with different soil textures show that the Modified Kostiakov model generally outperformed the other models based on the relatively higher mean <InlineEquation ID="IEq2"><EquationSource Format="TEX">\({R}^{2}\)</EquationSource></InlineEquation> and low RMSEs, MAEs and MAPEs. The estimation accuracy was in the order of Modified Kostiakov &gt; Kostiakov &gt; Swartzendruber &gt; Horton &gt; Brutsaert &gt; Philip models. The influence of soil texture on the model accuracy was also in the order of Loam &gt; Sandy loam &gt; Loamy sand soil textures. The results of this study indicate that the use of the Modified Kostiakov model in hydrological evaluations can improve the accuracy of irrigation system design under verified field conditions.</p>

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Evaluation and comparison of infiltration models under different soil textures in the Mamprusi west district of North East Region, Ghana

  • T. Atta-Darkwa,
  • A. Asare,
  • K. A. Asosega,
  • Y. Seidu,
  • E. T. Atakora,
  • G. A. Akolgo,
  • E. A. Awafo,
  • D. N. D. Quaye,
  • E K Nyantakyi,
  • Ebenezer K. Siabi,
  • J. O.A Akimsah

摘要

Assessment of soil water infiltration through reliable estimation of the infiltration rate is key to informed decision-making for sustainable ecosystem management. This study was conducted to evaluate the performances of the Kostiakov, Modified Kostiakov, Horton, Swartzendruber, Brutsaert and Philip models in estimating cumulative infiltration depth under loam, sandy loam and loamy sand soil textures. The measured infiltration data from the double ring infiltrometer were fitted to the infiltration models and their goodness-of-fit statistics were verified by the Coefficient of Determination (\({R}^{2}\)), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The Goodness-of-fit statistics for all Cumulative infiltration estimating models across the three locations within the study area associated with different soil textures show that the Modified Kostiakov model generally outperformed the other models based on the relatively higher mean \({R}^{2}\) and low RMSEs, MAEs and MAPEs. The estimation accuracy was in the order of Modified Kostiakov > Kostiakov > Swartzendruber > Horton > Brutsaert > Philip models. The influence of soil texture on the model accuracy was also in the order of Loam > Sandy loam > Loamy sand soil textures. The results of this study indicate that the use of the Modified Kostiakov model in hydrological evaluations can improve the accuracy of irrigation system design under verified field conditions.