CES-based model to predict the river rating curve

Effective control of irrigation schemes and water resources is heavily dependent on the exact river discharge estimates, which are usually estimated by measuring the water level through phase-deviation conditions or rankings. However, the direct measurement of the river flow is often impractical or prohibitively expensive, which reveals the need for a reliable future model. The study focuses on the KUFA River in Iraq and applies the Transport Stimulation System (CES) model to estimate its assessment curve. The CES model integrates hydraulic geometry, channel succession, and flow resistance parameters to generate stage-discharge curves, while its "uncertainty estimates" also stand for underlying uncertainties through the component. Model assumptions were validated against the area measurement collected in several cross sections along the Kufa River. To assess the accuracy of the model, statistical indicators, including prejudice, absolute errors (MAE), and Nash-Sutcliffe Efficiency (NSE) were calculated. The results revealed a strong agreement between CES-PRE-prescribed assessment curves and the observed field data, with most measured values falling within the limit. This river shows the reliability of the CES model to capture complex interactions between river morphology and flow resistance, even under different field conditions. Conclusions suggest that the CES model is a valuable tool for hydraulic engineers and managers of water resources, which enables more informed decisions on the design and operation of river control, irrigation planning, and hydraulic structures. The ability to accommodate changes in channelling and morphology supports its application in the dynamic environment where the functions of the river develop seasonally or are caused by man-made effects. Overall, the CES model increases the future accuracy and supports the use of permanent water in the Al-Kufa River Basin.