Abstract
The topic of this Ph.D. thesis is adjustment of weather radar rainfall measurements for urban drainage applications by the use of in-situ stormwater runoff measurements. It is possible to obtain the high spatiotemporal resolution rainfall data desired for advanced distributed urban drainage applications by the use of weather radars. Rainfall data representing the spatiotemporal distribution is a necessity for accurate modelling and real-time control of distributed urban drainage systems.
Weather radar measurements are indirect measurements of the rainfall in the atmosphere, which poses some challenges for using the data in urban drainage applications. There are discrepancies between radar-rainfall measured in the atmosphere and the “true” rainfall at ground level. Consequently, radar-rainfall estimates are usually adjusted to rainfall observations at ground level from rain gauges. When radar-rain gauge adjusted data is applied for urban drainage models, discrepancies between radar-estimated runoff and observed runoff still occur. The aim of urban drainage applications is to estimate flow and water levels in critical points in the system. The “true” rainfall at ground level is, therefore, of less importance as long as the estimated flow and water levels are correct. It makes sense to investigate the possibility of adjusting weather radar data to rainfall-runoff measurements instead of rain gauge measurements in order to obtain better predictions of flow and water levels.
This Ph.D. study investigates how rainfall-runoff measurements can be utilised to adjust weather radars. Two traditional adjustments methods based on rain gauges were used as the basis for developing two radar-runoff adjustment methods. The first method is based on the ZR relationship describing the relation between radar reflectivity (Z) and radar rainfall rate (R). A Z-Q relationship were developed to describe the relation between radar reflectivity (Z) and radar rainfall runoff (Q). The second method is based on the radar-rain gauge mean field bias adjustment approach. A radar-runoff bias adjustment approach was developed. The second method is less computationally heavy and easier to implement in larger complex urban catchments since the method does not require a runoff model to describe the transfer function between rainfall and runoff.
The two radar-runoff adjustment methods were tested under real practical conditions using two different case study sites. Both methods performed similar to the radar-rain gauge adjustment methods when comparing radar predicted rainfall-runoff against observed rainfallrunoff. However, the performance of the radar-rain gauge adjustment methods decreases when only based on rain gauges located outside the given catchment. This Ph.D. study has proved that it is possible to adjust weather radar measurement using measured rainfall-runoff.
The main challenge of using radar-runoff adjustment methods is to close the rainfallrunoff mass-balance. In complex combined sewer catchment with CSOs, basins, pumps, etc. it can be very difficult to close the rainfall-runoff mass-balance. A great effort of the Ph.D. project was dedicated to developing methods for closing the rainfall-runoff mass-balance. A closed mass-balance is also important for accurate calibration of the urban drainage models used of the analyses and real-time control. Hence, some of the work performed during this Ph.D. can also be used for improving calibration of urban drainage models.
Weather radar measurements are indirect measurements of the rainfall in the atmosphere, which poses some challenges for using the data in urban drainage applications. There are discrepancies between radar-rainfall measured in the atmosphere and the “true” rainfall at ground level. Consequently, radar-rainfall estimates are usually adjusted to rainfall observations at ground level from rain gauges. When radar-rain gauge adjusted data is applied for urban drainage models, discrepancies between radar-estimated runoff and observed runoff still occur. The aim of urban drainage applications is to estimate flow and water levels in critical points in the system. The “true” rainfall at ground level is, therefore, of less importance as long as the estimated flow and water levels are correct. It makes sense to investigate the possibility of adjusting weather radar data to rainfall-runoff measurements instead of rain gauge measurements in order to obtain better predictions of flow and water levels.
This Ph.D. study investigates how rainfall-runoff measurements can be utilised to adjust weather radars. Two traditional adjustments methods based on rain gauges were used as the basis for developing two radar-runoff adjustment methods. The first method is based on the ZR relationship describing the relation between radar reflectivity (Z) and radar rainfall rate (R). A Z-Q relationship were developed to describe the relation between radar reflectivity (Z) and radar rainfall runoff (Q). The second method is based on the radar-rain gauge mean field bias adjustment approach. A radar-runoff bias adjustment approach was developed. The second method is less computationally heavy and easier to implement in larger complex urban catchments since the method does not require a runoff model to describe the transfer function between rainfall and runoff.
The two radar-runoff adjustment methods were tested under real practical conditions using two different case study sites. Both methods performed similar to the radar-rain gauge adjustment methods when comparing radar predicted rainfall-runoff against observed rainfallrunoff. However, the performance of the radar-rain gauge adjustment methods decreases when only based on rain gauges located outside the given catchment. This Ph.D. study has proved that it is possible to adjust weather radar measurement using measured rainfall-runoff.
The main challenge of using radar-runoff adjustment methods is to close the rainfallrunoff mass-balance. In complex combined sewer catchment with CSOs, basins, pumps, etc. it can be very difficult to close the rainfall-runoff mass-balance. A great effort of the Ph.D. project was dedicated to developing methods for closing the rainfall-runoff mass-balance. A closed mass-balance is also important for accurate calibration of the urban drainage models used of the analyses and real-time control. Hence, some of the work performed during this Ph.D. can also be used for improving calibration of urban drainage models.
| Original language | English |
|---|---|
| Place of Publication | Aalborg |
| Publisher | |
| Publication status | Published - 2015 |
Keywords
- Rainfall estimates
- Weather radars
- Drainage sensors