Entropy theory applied to hydrometric measurements enables establishing a relationship between the maximum and the mean velocities of flow passing a river section. In many developing countries, river discharge is still estimated by the velocity‐area method following the procedure established based on the point‐velocities measured at 0.6D depth from the water surface of many verticals of flow section. This study explores the establishment of a relationship between the maximum point‐velocity estimated at 0.6D depth of the vertical located at or nearer to the deepest flow depth, and the maximum point‐velocity occurring somewhere along the same vertical which in turn can be linked to the sectional mean flow velocity based on the established entropy theory. The appropriateness of the proposed two‐steps based approach of discharge estimation is first verified on the Tiber River and the Po River of Italy. The study finds that the values of the maximum point‐velocity estimated using the proposed approach closely matches with the recorded maximum flow velocity values along the same flow‐depths. After this verification, the proposed method was applied for discharge estimation at two Indian river gauging stations, where only the point‐velocity measurements at 0.6D depth locations of the verticals are recorded. The study finds that the discharges estimated by both the proposed approach and the velocity‐area method closely match with each other with the estimated Nash‐Sutcliffe Efficiency (NSE) values greater than 0.99. Thus the proposed two‐steps approach involving the entropy concept based relationship for discharge estimation enables to replace the tedious and time‐consuming velocity‐area approach.

Streamflow measurements during high floods is a challenge for which the World Meteorological Organization fosters the development of innovative technologies for achieving an accurate estimation of the discharge. The use of non-contact sensors for monitoring surface flow velocities is of interest to turn these observed values into a cross-sectional mean flow velocity, and subsequently, into discharge if bathymetry is given. In this context, several techniques are available for the estimation of mean flow velocity, starting from observed surface velocities. Among them, the entropy-based methodology for river discharge assessment is often applied by leveraging the theoretical entropic principles of Shannon and Tsallis, both of which link the maximum flow velocity measured at a vertical of the flow area, named the y-axis, and the cross-sectional mean flow velocity at a river site. This study investigates the performance of the two different entropic approaches in estimating the mean flow velocity, starting from the maximum surface flow velocity sampled at the y-axis. A velocity dataset consisting of 70 events of measurements collected at two gauged stations with different geometric and hydraulic characteristics on the Po and Tiber Rivers in Italy was used for the analysis. The comparative evaluation of the velocity distribution observed at the y-axis of all 70 events of measurement was closely reproduced using both the Shannon and Tsallis entropy approaches. Accurate values in terms of the cross-sectional mean flow velocity and discharge were obtained with average errors not exceeding 10%, demonstrating that the Shannon and Tsallis entropy concepts were equally efficient for discharge estimation in any flow conditions.

A multilinear stage-hydrograph routing method based on time distribution scheme is analyzed. The framework of the multilinear method is based on the Muskingum-type routing method, which is used as the linear submodel. The proposed method can implicitly model the nonlinear dynamics of the flood wave propagation by varying the model parameters at each routing time step. The suitability of this flood routing method is verified using a set of laboratory experimental data and the field data of the Tiber River in central Italy.