Hydraulic models have been widely used to facilitate the design, management, and operation of water distribution systems (WDS). However, model parameters including pipe roughness coefficients (PRCs) and nodal demands (NDs) must be calibrated before practical applications, and the calibration accuracy and efficiency is important to enable their wide uptake in practice. This therefore motivates intensive studies to develop approaches for model calibration focusing on either optimization algorithms or numeric methods. Although these previous studies have advanced this research area, the calibration efficiency and effectiveness need to be further improved, especially when dealing with real-world problems. To attain this objective, this paper proposes an efficient numerical approach to simultaneously calibrate PRCs and NDs for WDS. Within this method, the calibration objective function is formulated as a least-square equation, followed by the derivation of iterative formulas according to a local sensitivity analysis. These formulas allow PRCs and NDs to be iteratively updated in an efficient manner until the given convergence criteria are met. To further improve the efficiency, the pipes and nodes are grouped according to their physical properties, which allows the calibration dimensions to be significantly reduced. Additionally, within the calibration process, values of PRCs and NDs are restricted into specified ranges to ensure the calibrated results are practically meaningful. Two case studies are used to demonstrate the utility of the proposed method, and results show that this approach is able to simultaneously calibrate PRCs and NDs efficiently, with the modeled hydraulic parameter values (pipe flows and nodal pressures) matching well with observations.

A new shaft spillway composed of an inlet structure that includes inlet swirling-flow-generating piers, an annular weir, a vertical shaft, and an outlet structure is presented. Major factors influencing the inlet’s discharge coefficient, including the number of piers, pier weir angle, weir head, and pier height are discussed. An empirical discharge coefficient equation using a relative dimensionless weir head is presented in order to provide design guidance. Model experiments and numerical simulations are conducted regarding the flow behavior of the proposed inlet and vortex drop structure performance. Hydraulic characteristics such as the flow pattern, air core distribution, annular hydraulic jump position, pressure profiles, and water profiles of the outlet tunnel are obtained and agree well with the measured experimental data. Results show that the flow around the inlet is divided into a free-flow swirling region near the piers and submerged-flow region at the piers. The flow rate grows nearly linearly with the relative dimensionless weir head in the submerged region, and the discharge coefficient is approximately constant at 0.223. Experiments and simulations reveal the rotational flow movement mechanism of the self-regulating underwater swirl piers and the energy dissipation of the new vortex drop shaft spillway. Analytic calculations for the resultant velocity and water course thickness of the shaft sections correlate well with the results of a numerical simulation.

Forecasting of ice jams and their breakup is crucial to prevent or reduce flooding risk in cold regions. A back propagation (BP) neural network model improved by the Levenberg-Marquardt clustering method has been developed with air temperatures and precipitation as inputs and applied for ice-jam forecasting in a given year in the upper reaches of the Heilongjiang River (Amur River), where ice flooding occurs frequently during spring. The accuracy rate achieved was 85%, higher than that obtained using the conventional statistical method (62% accuracy), for ice-jam breakup forecasting. The BP model has a forecast period of 10 days with a maximum error of two days and a qualified rate of 100% for national standards breakup date forecasting. The forecast on the ice-jam breakup, which was released 24 days ahead, provided accurate results for the breakup date and the occurrence of ice jams in the spring of 2017.

A piano key weir (PKW) is a new type of labyrinth weir that increases the unit discharge at the unregulated spillway inlet of the weir. It is considered to be an important structure in water supply and drainage systems. However, its complex geometry makes it difficult to achieve an optimal hydraulic design, and only a few design equations and criteria are available. This study investigates the discharge capacity of a PKW and evaluates the characteristics of its discharge using various sources of experimental data from a database. First, previously proposed discharge capacity formulas are summarized and analyzed. Then, a new formula that integrates the existing test data with the results of dimensional analysis and multiparameter optimization is proposed. The weir characteristics are evaluated using the proposed formula and a mathematical model. The results show that both the proposed formula and numerical model are promising approaches to evaluate the discharge capacity of an A-type PKW and can guide its design.