A Novel Approach for Accurate Estimation of Furrow Cross‐Section and Wetted Perimeter Using a Normalized Beta Distribution Function

ABSTRACT Accurate estimation of the cross‐sectional area ( A ) and wetted perimeter ( P ) is vital for analysing furrow irrigation systems. This study introduced a new model based on the normalized beta distribution function to estimate these parameters. Data were collected from 22 furrows in sugarcane fields at the Haft Tappeh Agro‐Industrial Complex in southern Iran using a profilometer. The model's performance was compared to established methods: curve fitting (CF), WinSRFR (SR) and Walker and Skogerboe (WS) for A and Strelkoff and Clemmens (SC) and WS for P . The results demonstrated the new model's superiority. The mean absolute percentage error (MAPE) for estimating A was 5.5%, less than half the error of the CF method and under one‐third of the SR and WS errors. For P , its average MAPE was 5.7%, less than half the error of the SC methods and significantly lower than that of the WS method. The model also showed high accuracy, with low normalized root mean square error values. Boxplot analysis confirmed that it had the smallest error dispersion. These findings highlight the model's superior performance for practical application in designing and managing surface irrigation.