The development of irrigation and agricultural water management holds significant potential to improve productivity and reduce vulnerability to climactic volatility and land transformation in any country. Although Ethiopia has abundant rainfall and water resources, its agricultural system does not yet fully benefit from the technologies of water management and irrigation. Improved water management for agriculture has many potential benefits in efforts to reduce vulnerability and improve productivity. According to climate change assessments, less precipitation and higher temperatures can be expected in the country. Besides, an increment in drought studies shows high land degradation and nutrient depletion of agricultural land as well. Such climatic and land conditions require an effort to improve agricultural water management efficiency and to optimize irrigation technologies. There are currently available water-use and crop-growth simulation models, which can be combined with climate and land use scenarios in order to recommend, through many simulations, the most reliable irrigation management, as a result, agriculture will have to reduce either its relative water consumption per output by improving usage efficiency or its absolute water demand by decreasing agricultural production. More agricultural output per area and per drop of water used (crop yield and crop water productivity) means achieving more crops per drop. This review was, therefore, targeted at finding a better method for optimal irrigation water management that relies on accurate knowledge of plant water consumption, water flows, and soil moisture dynamics throughout the growing season. The decision-supporting tools should therefore capture the temporal and spatial variability of rainfall, soils, and crops. It is better to model the agricultural water management fully from field measurements or remote sensing using dynamic simulation models. In this paper, it is needed to review the Agro-hydrological model to investigate the agricultural water management. This agro-hydrological model is a good software package for crop water requirement computation as the inputs of the model are based on the real field conditions. As with any model, the reliability of the results depends on the reliability of the input data. The model can generate daily crop water needs (or irrigation requirements), which can assist the user in adjusting irrigation schedules based on weather conditions. On the other hand, with SWAP, an estimation can be made of the losses due to over irrigation.
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Irrigation & Drainage Systems Engineering received 835 citations as per Google Scholar report
