Abstract
High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper presents a way of updating conceptual rainfall-runoff models using Maximum a Posteriori estimation to determine the most likely parameter constellation at the current point in time. This is done by combining information from prior parameter distributions and the model goodness of fit over a predefined period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior standard deviations and lengths of the auto-calibration period on the resulting flow forecast performance are evaluated. We were able to demonstrate that, if properly tuned, the method leads to a significant increase in forecasting performance compared to a model without continuous auto-calibration. Delayed responses and erratic behaviour in the parameter variations are, however, observed and the choice of prior distributions and length of auto-calibration period is not straightforward.
Highlights
Combined urban drainage systems are built to convey sewage as well as stormwater, which often results in very complex hydrological behaviour as many factors influence the quantity and quality of the water that is discharged from urban areas
On the parameter ranges during the ML calibration on a dry obtained without any constraints on the parameter ranges during the ML calibration on a dry weather weather period. This resulted in a dry weather flow (DWF) model that was used during the calibration of the mean period
This resulted in a DWF model that was used during the calibration of the mean values for the values for the effective area and transport time
Summary
Combined urban drainage systems are built to convey sewage as well as stormwater, which often results in very complex hydrological behaviour as many factors influence the quantity and quality of the water that is discharged from urban areas. Computer based dynamic operation of urban drainage systems in real-time is an attractive tool to avoid combined sewer overflows, minimise the risk of pluvial flooding, achieve better wastewater treatment during wet-weather and to optimise the. Recent examples of implementations of such schemes have been documented by [1,2,3,4,5]. In these types of control schemes, forecast models can be an essential part of the model predictive real-time decision making processes as they provide valuable lead time to act on. Hutton et al [11,12] and
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
