Spatiotemporal Analysis and Automated Identification of Manning’s Roughness Coefficient in Lined Canals

This study addresses the problem of inaccurate channel flow simulation and uneven irrigation water distribution caused by the spatiotemporal variability of Manning’s roughness coefficient. The SCE-UA optimization algorithm was applied to calibrate Manning’s roughness coefficients and quantify their spatiotemporal variation patterns using 1728 sets of measured water level–discharge data collected in the Yellow River Irrigation District. Results show that accounting for spatiotemporal variability reduces the mean absolute percentage error (MAPE) for water level simulation by nearly 8%. Based on these findings, an automatic roughness update system specifically designed for grassroots water distribution stations has been developed, which can integrate water demand and gate control to achieve efficient water allocation in canals in the future.