Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 558626
Title Generalizing multi-reward functions aimed at identifying the best locations to install flow control devices in sewer systems
Author(s) Muñoz, David F.; Simões, Nuno E.; Sousa, Luís M. de; Maluf, Lucas; Sá Marques, Alfeu; Leitão, João P.
Source Urban Water Journal 16 (2019)8. - ISSN 1573-062X - p. 564 - 574.
Department(s) ISRIC - World Soil Information
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) in-sewer flow control device - multi-criteria decision models - reward function - sewer overflow - Spearman rank correlation coefficient - Urban flood control

Multi-criteria decision models have been recently implemented in many urban flood risk management schemes due to the increasing demand of low-cost and reliable solutions to prevent and control overflow from sewer systems. Based on specific targets, these decision models encompass multiple reward (or objective) functions according to socio-economic requirements, vulnerability assessments and physical constraints on existing sewer systems. In this study, we present a simple algorithm to generalize reward functions aimed at locating the best sites to install in-sewer flow control devices, and thus controlling sewer overflow. The algorithm uses the mathematical structure of reward functions previously established, and adjust them based on hydraulic simulation results of two real sewer networks. Our results indicate that a single generalized reward function can efficiently identify strategic locations to guarantee (i) maximum in-sewer storage, (ii) minimum impact of possible flow control device failures and (iii) maximum flow discharge reduction upstream flood-prone urban areas.

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