Roozbeh MoazenzadehBabak MohammadiMir Jafar Sadegh SafariKwok-wing Chau2025-10-0620221994-20601997-003X10.1080/19942060.2022.2037467http://dx.doi.org/10.1080/19942060.2022.2037467https://gcris.yasar.edu.tr/handle/123456789/7866Soil moisture (SM) is of paramount importance in irrigation scheduling infiltration runoff and agricultural drought monitoring. This work aimed at evaluating the performance of the classical ANFIS (Adaptive Neuro-Fuzzy Inference System) model as well as ANFIS coupled with three bio-inspired metaheuristic optimization methods including whale optimization algorithm (ANFIS-WOA) krill herd algorithm (ANFIS-KHA) and firefly algorithm (ANFIS-FA) in estimating SM. Daily air temperature relative humidity wind speed and sunshine hours data at Istanbul Bolge station in Turkey and soil temperature values measured over 2008-2009 were fed into the models under six different scenarios. ANFIS-WOA (RMSE = 1.68 MAPE = 0.04) and ANFIS (RMSE = 2.55 MAPE = 0.07) exhibited the best and worst performance in SM estimation respectively. All three hybrid models (ANFIS-WOA ANFIS-KHA and ANFIS-FA) improved SM estimates reducing RMSE by 34 28 and 27% relative to the base ANFIS model respectively. A more detailed analysis of model performances in estimating moisture content over three intervals including [15-25) [25-35) and >= 35% revealed that ANFIS-WOA has had the lowest errors with RMSEs of 1.69 1.89 and 1.55 in the three SM intervals respectively. From the perspective of under- or over-estimation of moisture values ANFIS-WOA (RMSE = 1.44 MAPE = 0.03) in under-estimation set and ANFIS-KHA (RMSE = 1.94 MAPE = 0.05) in over-estimation set showed the highest accuracies. Overall all three hybrid models performed better in the underestimation set compared to overestimation set.EnglishANFIS, bio-inspired optimization algorithms, data-driven models, meteorological variables, soil moisture, TurkeyMETAHEURISTIC OPTIMIZATION ALGORITHMS, FUZZY INFERENCE SYSTEM, SOLAR-RADIATION, PREDICTION, MODEL, MACHINE, SIMULATION, MANAGEMENTArticle