No abstract

Different approaches for quantification of pollution loads discharged from combined sewer networks into surface water bodies have been observed over the last few years and decades, but a large number of unresolved problems still remain. Many monitoring campaigns have been based on manual or automated spot sampling - with the long known limitations of this method such as sampling errors and errors due to sample conservation, transport and preparation. On the other hand, only recently have sensors became available which are suitable for continuous application in sewer networks. A large number of practical problems still have to be solved before continuous monitoring in sewer networks will be successful. Additionally, most of the applicable sensors are based on surrogate methods which results in a considerable effort for reference measurements for sensor calibration. Finally, it has to be considered that, depending on the sewer network topography, deposition and remobilisation of pollutants varies considerably, which limits the generality of monitoring results and, subsequently, their applicability as a base for the design of storm water tanks or combined sewer overflows (CSO). A monitoring station for continuous monitoring of load discharges from a CSO has been installed and operated for more than one year. The design and equipment of the measurement station, operational experiences and results are given in this paper.

Within the last years a trend towards in-situ monitoring can be observed, i.e. most new sensors for water quality monitoring are designed for direct installation in the medium, compact in size and use measurement principles which minimise maintenance demand. Ion-sensitive sensors (Ion-Sensitive-Electrode--ISE) are based on a well known measurement principle and recently some manufacturers have released probe types which are specially adapted for application in water quality monitoring. The function principle of ISE-sensors, their advantages, limitations and the different methods for sensor calibration are described. Experiences with ISE-sensors from applications in sewer networks, at different sampling points within wastewater treatment plants and for surface water monitoring are reported. An estimation of investment and operation costs in comparison to other sensor types is given.

An explosion-proof UV/VIS sensor has been available even in sewer systems for some years for simultaneous measurement of COD eq , filtered COD eq , TSS eq and nitrate eq . This sensor allows in-situ real-time measurements with no sampling, no sample preparation and no reagents. Three case studies are presented in this paper using this UV/VIS sensor for longterm sewer monitoring issues whereby two different installation strategies are applied. The pros and cons of both different installation solutions are compared and different calibration results during dry and wet weather conditions and long-term operational sewer monitoring experiences are given in this paper.

Rainfall runoff models are frequently used for design processes for urban infrastructure. The most sensitive input for these models is precipitation data. Therefore, it is crucial to account for temporal and spatial variability of rainfall events as accurately as possible to avoid misleading simulation results. This paper aims to show the significant errors that can occur by using rainfall measurement resolutions in urban environments that are too coarse. We analyzed the spatial variability of rainfall events from two years with the validated data of 22 rain gauges spread out over an urban catchment of 125 km2. By looking at the interstation correlation of the rain gauges for different classes of rainfall intensities, we found that rainfall events with low and intermediate intensities show a good interstation correlation. However, the correlation drops significantly for heavy rainfall events suggesting higher spatial variability for more intense rainstorms. Further, we analyzed the possible deviation from the spatial rainfall interpolation that uses all available rain gauges when reducing the number of rain gauges to interpolate the spatial rainfall for 24 chosen events. With these analyses we found that reducing the available information by half results in deviations of up to 25% for events with return periods shorter than one year and 45% for events with longer return periods. Assuming uniformly distributed rainfall over the entire catchment resulted in deviations of up to 75% and 125%, respectively. These findings are supported by the work of past research projects and underline the necessity of a high spatial measurement density in order to account for spatial variability of intense rainstorms.