INTRODUCTION The objective of this task was:
Setting up a simple MIKE 11 Model A network file consisting of two points 5000m apart was implemented. Thereafter, a crosssection file specifying a rectangular crosssection at chainage 0m and 5000m was set up. Two boundaries were specified for the boundary conditions file. At chainage 0 m, a time series of water level, 4m for the entire time was specified, while at chainage 5000m, a constant inflow with Q=0m3/s was specified. A default HD parameter file was used and a simulation run for the period 22/10/10 12:11:38 t0 22/10/10 13:00:38 was carried out using a 30 secs time step. RESULTS
After simulating the time series with ho value of 4m for all times other than the secondtime step which a ho+dh value of 6m is assigned: The theoretical time taken for the wave to travel through 5000m is: (𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 / (√𝑔 ℎ)). Therefore, the theoretical time taken for the wave, h=4m to travel through 5000m is 798 secs=13.30 minutes. From simulation results, the wave starts at 0m at 12:11:37pm and leaves the 5000m section at 12:24:08. This is equal to 12.31 minutes=751 seconds. The difference between the theoretical and simulated time taken for the wave to travel 5000m is: (798−751)𝑠𝑒𝑐𝑜𝑛𝑑𝑠=47 𝑠𝑒𝑐𝑜𝑛𝑑𝑠.
Simulating the time series with ho value of 2m for all times other than the secondtime step which a ho+dh value of 4m is assigned: The theoretical time taken for the wave, h=2m and ho+dh=4m for the secondtime step, to travel through 5000m is 1128.8 secs=18minutes 49 seconds. From simulation results, the wave starts at 0m at 12:11:37pm and leaves the 5000m section at 12:28:38. This is equal to 17:01 minutes=1021 seconds. The difference between the theoretical and simulated time taken for the wave to travel 5000m is: (1128.8−1021)𝑠𝑒𝑐𝑜𝑛𝑑𝑠=107.8 𝑠𝑒𝑐𝑜𝑛𝑑𝑠
Simulating the time series with ho value of 6m for all times other than the secondtime step which a ho+dh value of 8m is assigned: The theoretical time taken for the wave, h=6m and ho+dh=8m for the secondtime step, to travel through 5000m is 651.7 secs=10minutes 52 seconds. From simulation results, the wave starts at 0m at 12:11:37pm and leaves the 5000m section at 12:22:27. This is equal to 11 minutes=660 seconds. The difference between the theoretical and simulated time taken for the wave to travel 5000m is: (660−651.7)𝑠𝑒𝑐𝑜𝑛𝑑𝑠=8.3 𝑠𝑒𝑐𝑜𝑛𝑑𝑠
Simulating the time series with ho value of 8m for all times other than the secondtime step which a ho+dh value of 10m is assigned: The theoretical time taken for the wave, h=8m and ho+dh=10m for the second time step, to travel through 5000m is 564.4 secs=9.24 minutes. From simulation results, the wave starts at 0m at 12:11:37pm and leaves the 5000m section at 12:21:08. This is equal to 9.31 minutes=571 seconds. The difference between the theoretical and simulated time taken for the wave to travel 5000m is: (564.4−751)𝑠𝑒𝑐𝑜𝑛𝑑𝑠=47 𝑠𝑒𝑐𝑜𝑛𝑑𝑠. Summary of Results CONCLUSION Waves propagate faster in deep waters than shallow waters. The relative error between simulated results and theoretical calculations decrease with increasing water level.
INTRODUCTION Rivers like other water systems are complex and dynamic, they are always changing in response to human intervention and changing climatic, geologic, and hydrological regime. Reliable analysis of river problems requires recognition and understanding of the governing processes in the river system (Timbe, 2007). By carrying out numerical computations that give a better understanding of the behaviour of rivers and other water systems, phenomena such as flooding investigated. Several river modelling tools are available be used for such purposes. One of such tools is DHI’s MIKE11, a fully dynamic 1D modeling package, that has capabilities to carry out complex modelling of rivers, channels, lakes and reservoirs, producing several userdefined outputs/ results that are visualized on MIKE View (DHI Water and Environment, 2007). The MIKE 11 HD module solves the nonlinear Saint Venant equations and was used in the tasks that make up this report. MIKE 11 files that had been prepared for the Var river were downloaded. It is important to note that these files have been adapted to run on MIKE 11 demo mode and therefore are not an accurate representative of the Var river. TASK 1: SETUP OF A BASIC MODEL FOR NORMAL FLOW CONDITIONS The objective of this task were to run the downloaded MIKE 11 files provided and present results of the simulation viewed on MIKE View.
The length of the river simulated is 24012.50 m long, with 9 crosssections at chainages 0m, 1894.98, 4500m, 7500m, 10000m, 15000m, 16000m, 18300m and 24012.50m. The upstream and downstream boundary conditions specified were:
In the hydrodynamic parameters file, the initial conditions were set to 0 m for water level and 0 m3/s for discharge. The model’s default values for all other HD parameters such as wave approximation and default values were retained. A simulation covering the period 04/11/1994 12:00:00 to 07/11/1994 13:30:00 was carried out, with a time step of 30 seconds and the steady state initial condition HD parameter specified.
TASK 2: SETUP OF A BASIC UNSTEADY MODEL FOR THE FLOOD EVENT 1994 The objectives of this task were:
Model Domain Other than the boundary conditions file, all other model files (Network, Crosssections, HD Parameter) remained as in task 1. The change in the boundary conditions file involved changing the discharge time series from a constant Q of 300m3/s as in task 1 to a QFlood obtained from the HECHMS exercise for the 1994 flood event.
Locations on the left bank of crosssection at chainage 0m, are inundated, while the locations on the right bank of crosssection 7500m and areas close to the downstream end of the river are faced by an inundation threat if the discharge levels are higher. All other parts of the river are safe from flood risk, considering Q_flood used for simulations. TASK 3: PARAMETER STUDY  BED RESISTANCE The objectives of this task were:
The task 2 model with changes to the manning values in the HD parameter file was used. Manning values 15, 30, 60 and 80 were used for the bed resistance analysis.
From the results shown above, a lower manning’s number results to higher water levels and vice versa. This follows the manning equation, 𝑄=𝐴 𝑅2/3𝑆𝑜1/2𝑛, whereby smaller values of 𝑛, will result to higher values of Q. Consequently, as per the Qh relations, higher values of Q will lead to higher h levels. Lower manning values mean that the channel is smoother. Therefore, it can be concluded that the rougher the channel, the lower the water levels and vice versa. TASK 4: WEIR IMPACT The objectives of this task were: To add a broad crested weir at chainage 15200m To run the model with different weir values (width, lower level) compare the results by graphs and numbers
The task 2 model with a broad crested weir added at chainage 15200m was used for this task. A rectangular broad crested weir having the following lengthwidth geometry relation was added: Thereafter, subsequent simulations were run with different weir values.
Figure 11: Longitudinal profile at chainage 15000m after adding weir After changing for the second time weir dimensions to: Figure 14: Crosssection profile at 15000m after changing weir dimensions Figure 15; Crossesection profile at 15000m after changing weir dimensions Figure 16: Crosssection profile at 15000m after changing weir dimensions at above By varying the weir dimensions, it is observed that weirs with a width smaller than 50 m and lower lengths than the original levels result to higher water levels at crosssection 15000m. With this river, the type of weir which can modify significantly the discharge. So a weir with a small width and a high height. Whereas a weir with a big width and a small height doesn’t change the discharge. CONCLUSION This study shows the importance of parameters in a model. Parameters change and specify min and max values. In hydrology, it’s important to know the max values, so the peak values in order to model a flood. With a correct peak, we obtain the max water level, and with this max water level, people can prevent any risk of destruction of infrastructure. They can decide budget in protection and take decisions to fight against flood.

5. Results >