Now and in the future, many countries expect to face inadequate water resources to fulfil their recent environmental, industrial, domestic and agricultural water needs. The world population is expected to grow about 30% at the year 2025, getting 8 billion persons. The living standards are also anticipated to increase as a result of improving urbanization, communications and globalization. So, competition on water among the domestic, industrial, agricultural and other users will rise in unprecedented levels.The researcher studied feasibility study and records that were generated during the life of the Hilla – Kifl irrigation project so as to get some perception into the planning and implementation processes. The researcher made field visits concentrating on direct observation of unending and completed project activities. During the field visits, group discussions and interviews with project staff, farmers and resident engineer were held.The objective of this research is to define the extent to which the feasibility study aims and objectives of Hilla – Kifl irrigation project were met. It was also significant to find best lessons and practices learned so as to improve the design, planning and implementation of future irrigation projects.
Since evapotranspiration typically makes up the largest portion of the terrestrial water cycle, it is one of the most crucial factors in determining how much water is available. This study evaluated four models (Penman-FAO-24(PF), Penman-Monteith -FAO-56(PM), Penman-Kimberly(PK), and Jensen-Haise (JH)) utilized frequently to calculate monthly reference crop evapotranspiration (ET_0) values for Ramadi irrigation project (fourth stage). The statistical indicators considered were the root mean square error (RMSE), Mean Absolute Error (MAE), Relative Error (RE), Correlation Coefficient (R^2) and mean bias error (MBE), models were used to estimate evapotranspiration, and by calculating evapotranspiration for Al-Ramadi city according to the climate data available to us, The (PF) model had the lowest MBE = 0.02945, greatest RMSE = 29.369, and highest R = 0.9641 values among the four models, demonstrating that it is the best. The JH model, which achieved the highest values of MBE = 0.00978 and RSME = 58.509, was the least accurate of the models.. The study's conclusions may be useful to farmers, decision-makers, and local water organizations in assessing irrigation water requirements, planning, and effective use of water resources.