This study was aimed to compare estimation methods of crop water requirement and irrigation scheduling for major crops using different models and compare the significance of models for adoption at different situations in Metekel zone. Crop water requirement and irrigation scheduling of maize in selected districts of Metekel zone were estimated using CropWat model based on soil, crop and meteorological data and AquaCrop based on soil, crop and meteorological data including Co2, groundwater, field management, and fertility status. Model performance was evaluated using Normalized Root mean square errors (NRMSE), model by Nash-Sutcliffe efficiency (NSE), Prediction error (Pe), and Model efficiency (MF). It is observed that the maximum reference evapotranspiration in the study area was found to be 7.1 mm/day in Guba and minimum reference evapotranspiration was 2.9 mm/day in Bullen district. In all cases, the maximum ETo in all districts was fund to in March and the lowest in August. The maximum ETc of maize was found to be 702.4 mm in Guba district and minimum ETc was found to be 572.6 mm in Bullen district using CropWat but the effective rainfall (Pe) for maize were determined as 185 mm respectively in Wembera district. However, using AquaCrop model the maximum ETc of 565 mm was recorded in Guba but 425 mm was recorded as minimum in Wembera district for irrigated maize in the study area. The study revealed that the irrigation scheduling with a fixed interval criterion for maize 10 days with 12 irrigation events has been determined. Moreover, furrow irrigation with 60% irrigation application efficiency was adjusted during irrigation water applications for all districts. The performance of the irrigation schedule and crop response was evaluated by the analysis results in the simulation using different models. It has been observed that there was a strong relationship and a significant relation between the simulated and observed values for validation. Hence, Normalized Root mean square errors (NRMSE), model by Nash-Sutcliffe efficiency (NSE), Prediction error (Pe), and Model efficiency (MF) showed that AquaCrop model well simulated in all parameters considered. AquaCrop model is the most suitable soil-water-crop-environment management model, so future studies should suggest a focus on addressing deficit irrigation strategy with different field management conditions to improve agricultural water productivity under irrigated agriculture for the study area for major crops.