MP
M. Pleij
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2 records found
1
The design of an early warning system for floods in Dar Es Salaam, Tanzania
A case study for the local bus company
With climate change increasing its mark on all aspects of the hydrological cycle, societies all over the world living in flood-prone areas are increasingly exposed to flood hazards. In many parts of the world, especially in less developed areas, societies lack knowledge and data to predict future flood events. By predicting a future flood event, an organization creates a time frame in which it can implement a mitigating action that reduces the financial damage inflicted. In recent years, development in new measuring techniques has significantly lowered the cost of collecting data and information on different aspects of the hydrological cycle. These developments enable organizations in regions restrained of knowledge and data to establish methods to analyze aspects of the hydrological cycle and thereby predicting the probability of a flood hazard several hours or days in advance. This thesis explores various possibilities of designing and implementing an \ac{EWS} for the \ac{BRT} in Dar es Salaam. The EWS design is based on the forecasting requirements, investigated with the BRT-system. Several operational forecasting methods are available. The EWS designed in this thesis makes use of rainfall data obtained from rainfall stations located in the Dar es Salaam region, installed and managed by the \ac{TAHMO}. This forecasting data is chosen because it provides the needed lead-time with the lowest margin of error. This forecasting data is processed and analyzed by the designed EWS and subsequently produces a probability level on a flood event. It thereby provides an advice on if the BRT-system should implement a mitigating action based on the principle of pursuing an optimal economic outcome. The designed EWS produces the flood probability in real-time, updated every hour with a lead time of one hour. This time frame enables the BRT-system to implement a mitigating action, thereby reducing the inflicted cost.
The probability level of a flood event is determined by training the EWS with historic flood and rainfall data. In addition, the implementation of both a hydrological and relational model in the EWS was tested. The results show that the hydrological model is the better option. The results also show that the implementation of an EWS ensures a decrease in financial damage endured by the BRT-system. The produced outcome of the EWS was validated by a 'leave one out' method. This validation was done by consecutively leaving one flood event out of the historical data frame and analyzing the variability of the resulting outcome. Finally, the designed EWS is best implemented in the BRT-system alongside the EWS-systems currently in place.
...
The probability level of a flood event is determined by training the EWS with historic flood and rainfall data. In addition, the implementation of both a hydrological and relational model in the EWS was tested. The results show that the hydrological model is the better option. The results also show that the implementation of an EWS ensures a decrease in financial damage endured by the BRT-system. The produced outcome of the EWS was validated by a 'leave one out' method. This validation was done by consecutively leaving one flood event out of the historical data frame and analyzing the variability of the resulting outcome. Finally, the designed EWS is best implemented in the BRT-system alongside the EWS-systems currently in place.
...
With climate change increasing its mark on all aspects of the hydrological cycle, societies all over the world living in flood-prone areas are increasingly exposed to flood hazards. In many parts of the world, especially in less developed areas, societies lack knowledge and data to predict future flood events. By predicting a future flood event, an organization creates a time frame in which it can implement a mitigating action that reduces the financial damage inflicted. In recent years, development in new measuring techniques has significantly lowered the cost of collecting data and information on different aspects of the hydrological cycle. These developments enable organizations in regions restrained of knowledge and data to establish methods to analyze aspects of the hydrological cycle and thereby predicting the probability of a flood hazard several hours or days in advance. This thesis explores various possibilities of designing and implementing an \ac{EWS} for the \ac{BRT} in Dar es Salaam. The EWS design is based on the forecasting requirements, investigated with the BRT-system. Several operational forecasting methods are available. The EWS designed in this thesis makes use of rainfall data obtained from rainfall stations located in the Dar es Salaam region, installed and managed by the \ac{TAHMO}. This forecasting data is chosen because it provides the needed lead-time with the lowest margin of error. This forecasting data is processed and analyzed by the designed EWS and subsequently produces a probability level on a flood event. It thereby provides an advice on if the BRT-system should implement a mitigating action based on the principle of pursuing an optimal economic outcome. The designed EWS produces the flood probability in real-time, updated every hour with a lead time of one hour. This time frame enables the BRT-system to implement a mitigating action, thereby reducing the inflicted cost.
The probability level of a flood event is determined by training the EWS with historic flood and rainfall data. In addition, the implementation of both a hydrological and relational model in the EWS was tested. The results show that the hydrological model is the better option. The results also show that the implementation of an EWS ensures a decrease in financial damage endured by the BRT-system. The produced outcome of the EWS was validated by a 'leave one out' method. This validation was done by consecutively leaving one flood event out of the historical data frame and analyzing the variability of the resulting outcome. Finally, the designed EWS is best implemented in the BRT-system alongside the EWS-systems currently in place.
The probability level of a flood event is determined by training the EWS with historic flood and rainfall data. In addition, the implementation of both a hydrological and relational model in the EWS was tested. The results show that the hydrological model is the better option. The results also show that the implementation of an EWS ensures a decrease in financial damage endured by the BRT-system. The produced outcome of the EWS was validated by a 'leave one out' method. This validation was done by consecutively leaving one flood event out of the historical data frame and analyzing the variability of the resulting outcome. Finally, the designed EWS is best implemented in the BRT-system alongside the EWS-systems currently in place.
PDAM Tirtawening
Investigating flow problems in the supply pipeline of PDAM Tirtawening.
The drinking water company PDAM Tirtawening has two pipelines that supply raw water to the treatment plant. The pipelines stretch out for 31 kilometers from Chikalong(small nearby town) to the treatment plant in Badaksinga in Bandung. For one of those pipelines the current flow to the treatment plant is well below the design flow. The original design flow of the pipeline is 850 liters per second, currently the pipeline transports roughly 580-650 liters per second. This is not a critical problem at the moment because the treatment plant does not have the capacity to treat and distribute more water, but in the nearby future PDAM Tirtawening wants to increase its capacity and supply more water to the people of Bandung. This means that the supply of raw water to the treatment plant also needs to be increased. From the study it can be concluded that the flow drop was caused by human decisions to throttle the flow, based on the fact that there was severe burst (“explosion”) of the pipeline somewhere in the year 2005. The burst was caused by a water hammer incident, occurring during maintenance. During this maintenance period the water flow was stopped and a water body was standing stagnant in the lower end of the pipeline. When the operators opened valve again at the intake point, to start up the flow in the pipeline, the water mass accelerated downwards towards the stagnant water body below. The air trapped between these two water bodies could not escape in time thereby being compressed causing peak pressures. These pressures where of a much higher magnitude than the pressure which the pipeline was designed for, causing the “explosion” of the pipe. The reason why the trapped air could not escape through the air valves is because they are sealed to reduce the chance of locals stealing water. To avoid air entrapment and thereby reducing the risk on water hammer the following three throttling locations along the pipeline where investigated. • keep regulating the inflow at the intake point at Chikalong. • regulate inflow at the first intersection (OVS1) 3 kilometres downstream of Chikalong. • regulate inflow downstream at Badaksinga at the outflow point of the pipeline. From these three options throttling at OVS1 is preferred. The peak pressures along the pipeline stay well below the design pressure. However, throttling at preset at Chikalong has gone ’sufficient’ looking at PDAM’s standards for more than 25 years already. Regulating at Badaksinga (throttling and closing) is not feasible. Very high pressures and problems with cavitation of the intake valve will increase the chance on pipe bursts and damage to the valve. Also, it is recommended to PDAM to slowly open the valve at the intake point after maintenance in order to slowly increase the volume of the flow. This action will insure that the pipeline will slowly fill up with water thereby giving the trapped air the chance to escape, this will decrease the chance on peak pressures and “explosions” in the future.
...
The drinking water company PDAM Tirtawening has two pipelines that supply raw water to the treatment plant. The pipelines stretch out for 31 kilometers from Chikalong(small nearby town) to the treatment plant in Badaksinga in Bandung. For one of those pipelines the current flow to the treatment plant is well below the design flow. The original design flow of the pipeline is 850 liters per second, currently the pipeline transports roughly 580-650 liters per second. This is not a critical problem at the moment because the treatment plant does not have the capacity to treat and distribute more water, but in the nearby future PDAM Tirtawening wants to increase its capacity and supply more water to the people of Bandung. This means that the supply of raw water to the treatment plant also needs to be increased. From the study it can be concluded that the flow drop was caused by human decisions to throttle the flow, based on the fact that there was severe burst (“explosion”) of the pipeline somewhere in the year 2005. The burst was caused by a water hammer incident, occurring during maintenance. During this maintenance period the water flow was stopped and a water body was standing stagnant in the lower end of the pipeline. When the operators opened valve again at the intake point, to start up the flow in the pipeline, the water mass accelerated downwards towards the stagnant water body below. The air trapped between these two water bodies could not escape in time thereby being compressed causing peak pressures. These pressures where of a much higher magnitude than the pressure which the pipeline was designed for, causing the “explosion” of the pipe. The reason why the trapped air could not escape through the air valves is because they are sealed to reduce the chance of locals stealing water. To avoid air entrapment and thereby reducing the risk on water hammer the following three throttling locations along the pipeline where investigated. • keep regulating the inflow at the intake point at Chikalong. • regulate inflow at the first intersection (OVS1) 3 kilometres downstream of Chikalong. • regulate inflow downstream at Badaksinga at the outflow point of the pipeline. From these three options throttling at OVS1 is preferred. The peak pressures along the pipeline stay well below the design pressure. However, throttling at preset at Chikalong has gone ’sufficient’ looking at PDAM’s standards for more than 25 years already. Regulating at Badaksinga (throttling and closing) is not feasible. Very high pressures and problems with cavitation of the intake valve will increase the chance on pipe bursts and damage to the valve. Also, it is recommended to PDAM to slowly open the valve at the intake point after maintenance in order to slowly increase the volume of the flow. This action will insure that the pipeline will slowly fill up with water thereby giving the trapped air the chance to escape, this will decrease the chance on peak pressures and “explosions” in the future.