Automatic classification of aerial imagery for urban hydrological applications

In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order to assess whether the capacity of the sewers is sufficient to avoid surcharge within certain return periods, precipitation is transformed into runoff. The transformation of precipitation into runoff requires knowledge about the proportion of drainage-effective areas and their spatial distribution in the catchment area. Common simulation methods use the coefficient of imperviousness as an important parameter to estimate the overland flow, which subsequently contributes to the pipe flow. The coefficient of imperviousness is the percentage of area covered by impervious surfaces such as roofs or road surfaces. It is still common practice to assign the coefficient of imperviousness for each particular land parcel manually by visual interpretation of aerial images. Based on classification results of these imagery we contribute to an objective automatic determination of the coefficient of imperviousness. In this context we compare two classification techniques: Random Forests (RF) and Conditional Random Fields (CRF). Experimental results performed on an urban test area show good results and confirm that the automated derivation of the coefficient of imperviousness, apart from being more objective and, thus, reproducible, delivers more accurate results than the interactive estimation. We achieve an overall accuracy of about 85% for both classifiers. The root mean square error of the differences of the coefficient of imperviousness compared to the reference is 4.4% for the CRF-based classification, and 3.8% for the RF-based classification

Integrated sensor and management system for urban waste water networks and prevention of critical situations

[EN] This work describes the design and implementation of improvements to the monitoring system of an urban waste water network, resulting in more efficient management of the system. To achieve this objective, the latest communications technology has been incorporated into heterogeneous networks and sensor systems. This technology includes mobile systems, which take measurements and transmit images in real time, an intelligent platform for processing and management of variables, and the implementation of wireless sensor networks (WSNs) designed with specific protocols and tools that allow the rapid deployment of the network and allow measurements to be taken in emergency situations. The sensors in this type of installation are extremely important for the management of the system as they allow us to collect information and make decisions with sufficient time to deal effectively with critical situations such as flooding or overloading of the waste water system, or environmental problems such as dumping of possible pollutants, as well as to make the best use of the water cycle. The solution presented here automates large portions of the processes, minimizing the possibility of human error, and increasing the frequency and accuracy of the measurements taken, ensuring a robust communication system covering all the elements involved to provide ubiquity of information, and finally gives an application layer to manage the system and receive alerts. © 2011 Elsevier Ltd.This work was supported by the MCyT (Spanish Ministry of Science and Technology) under the projects PET2007-0316 and TIN2010-21378-C02-02, which are partially funded by ERDF (European Regional Development Fund).Sempere Paya, VM.; Santonja Climent, S. (2012). Integrated sensor and management system for urban waste water networks and prevention of critical situations. Computers, Environment and Urban Systems. 36(1):65-80. https://doi.org/10.1016/j.compenvurbsys.2011.07.001S658036

Erregung und Lähmung 3 )

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Criteria for assessment of the operational potential of the urban wastewater system

Application of real-time control (RTC) is one possible measure to increase the performance of the urban wastewater system. However, the potential and the benefits of control depend strongly on the characteristics of the individual site under question. Conventionally, to evaluate this potential, a detailed feasibility study had to be carried out. In some cases, such a study may well conclude that, for the given site, real-time control does not have any significant potential, thus resulting in unnecessarily having spent precious resources for a detailed study. It would be desirable to have a methodology that allows simple, and cost-effective, screening of sites for which the analysis of real-time control may be beneficial. Earlier research led to the provision of an easy-to-apply scoring system which allows a quick assessment of the RTC potential of controlling flow in sewer systems. However, since this procedure does not take into account water quality aspects, or the treatment plant or the receiving water body, it cannot be used for assessing the potential of RTC of the complete system, let alone for integrated RTC. This paper describes the first part of an on-going project which aims at establishing an enhanced procedure for assessing the real-time control potential for the entire urban wastewater system. After providing a definition of the term “RTC potential”, a large number of (partly hypothetical) case studies (varying a number of key parameters of the wastewater system) is simulated, using the simulation tool SYNOPSIS. For each of these sites, a number of real-time control algorithms are developed and optimised, following a general procedure, which allows for local, global and integrated scenarios to be considered. Analysis of the results reveals those system parameters which are of particular significance to the RTC potential of urban wastewater systems. These are discussed and assessed in this paper. Furthermore, the results of a simulation study are provided which indicate a clear potential of integrated control even for many case studies for which local control provides hardly any benefits. Subsequent studies will complement the simulation study by comparison with a number of real case studies in various countries.</jats:p

Runoff modelling using radar data and flow measurements in a stochastic state space approach

In urban drainage the estimation of runoff with the help of models is a complex task. This is in part due to the fact that rainfall, the most important input to urban drainage modelling, is highly uncertain. Added to the uncertainty of rainfall is the complexity of performing accurate flow measurements. In terms of deterministic modelling techniques these are needed for calibration and evaluation of the applied model. Therefore, the uncertainties of rainfall and flow measurements have a severe impact on the model parameters and results. To overcome these problems a new methodology has been developed which is based on simple rain plane and runoff models that are incorporated into a stochastic state space model approach. The state estimation is done by using the extended Kalman filter in combination with a maximum likelihood criterion and an off-line optimization routine. This paper presents the results of this new methodology with respect to the combined consideration of uncertainties in distributed rainfall derived from radar data and uncertainties in measured flows in an urban catchment within the Emscher river basin, Germany.</jats:p