Method for estimating parameter γ in a two-dimensional approximate furrow infiltration model

• Published in: Computers and electronics in agriculture Vol. 235; p. 110403
• Main Authors: Li, Ge, Nie, Weibo, Li, Yuchen, Zhang, Wei
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2025
• Subjects: Adaptive boosting (AdaBoost); agriculture; algorithms; Backpropagation neural network (BPNN); Edge effect; edge effects; electronics; Furrow irrigation; furrows; Gray wolf optimization (GWO); hydraulic conductivity; prediction; regression analysis; soil texture; Furrow irrigation; Gray wolf optimization (GWO); Adaptive boosting (AdaBoost); Backpropagation neural network (BPNN); Edge effect

•The range of parameter γ is 0.60–0.94.•The edge effect’s relative contribution to the total furrow infiltration is 21.0%–41.7%.•A GWO–BPNN–AdaBoost model is proposed for estimating γ. This study expands the analysis of the parameter γ in the approximate furrow infiltration model (FIM) proposed by B...