In this paper, a methodology based on a new heuristic evolutionary game is developed to determine evolutionary stable equilibrium (ESE) strategies for conjunctive surface and groundwater allocation to water users with conflicting objectives. The methodology provides reasonable and realistic framework to illuminate noncooperative behaviors of water users in the joint usage of surface and groundwater resources. The developed heuristic evolutionary game theoretic approach can be used for finding equilibrium in asymmetric n-person games with continuous strategies. The penalty function is provided in a way that it can control groundwater table drawdown at monitoring points. It is also shown that applying the proposed penalty function may inhibit the water users' excessive exploitation and can consequently avoid the tragedy of commons. As the methodology needs to run water allocation optimization and groundwater simulation models for several times, an optimization model based on genetic algorithms is linked with MODFLOW groundwater simulation model. Furthermore, a computational cost reduction method has been used to reduce the computation time caused by several consecutive computational steps in the proposed Water Resour Manage

No abstract

Given the importance of pressure gradients in driving secondary flow, it is worth studying how the modelled flow structures in a natural river bend can be impacted by the assumption of hydrodynamic pressure. In this paper, the performance of hydrostatic versus nonhydrostatic pressure assumption in the three-dimensional (3D) hydrodynamic modelling of a tortuously meandering river is studied. Both hydrostatic and nonhydrostatic numerical models were developed using Delft3D-Flow to predict the 3D flow field in a reach of Stillwater Creek in Ottawa, Canada. An acoustic Doppler velocimeter was employed to measure the 3D flow field at a section in a sharp bend of the simulated river at two flow stages. The results of the Delft3D hydrostatic model agreed well with the acoustic Doppler velocimeter measurements: The hydrostatic model predicted reasonably accurately both the streamwise velocity distribution across the section and the magnitude and location of the primary secondary flow cell. The results of the Delft3D nonhydrostatic approximation showed that the model was not conservative and could not accurately generate either the secondary flow or the streamwise velocity distribution. This study illustrated the superior performance of the hydrostatic over nonhydrostatic 3D modelling of the secondary flow using Delft3D. Several possible reasons for unfavourable performance of the nonhydrostatic version of Delft3D are discussed, including the pressure correction technique employed in Delft3D. Considering the uncertainties that may arise in both modelling and field measurements, the 3D hydrostatic Delft3D model was capable of reasonably predicting the river bend flow structures in the studied meandering creek. KEYWORDS 3D hydrodynamic modelling, Delft3D, field-based data, hydrostatic versus nonhydrostatic modelling, natural meandering river, secondary flow

No abstract

This study aims at hydrodynamic modelling of Bow River, which passes through the City of Calgary, Canada. Bow River has a mobile gravel bed. Erosion and deposition processes were exacerbated by a catastrophic flood in 2013. Channel banks were eroded at various locations, and large gravel bars formed, which could lead to water level changes and accordingly more flooding. This study investigates the performance of Delft3D-Flow and MIKE 21 FM to simulate the hydrodynamics of the river during the 2013 flood. MIKE 21FM employs unstructured triangular mesh while Delft3D-Flow model uses curvilinear structured grids. Performance of each model was evaluated by the available historical water levels. The results of this study demonstrated that, with approximately the same averaged grid resolution, MIKE 21 FM resulted in more accurate results with a higher computational cost compared to the Delft3DFlow model. It was shown that Delft3D-Flow model may require higher grid cell resolution to result in comparably same depth-averaged velocities throughout the study area. However, considering the balance between the computational cost and the accuracy of the results, both models were capable to adequately replicate the hydrodynamics of the river during the 2013 flood. Results of statistical KS and ANOVA test analysis showed that the model predictions were sensitive to the horizontal eddy viscosity and the Manning roughness. This confirms the necessity of an appropriate calibration of the generated numerical models. The findings of this study shed light on the Bow River flood modelling, which can guide flood management.