Département Gestion des eaux urbaines

The sewer-based paradigm for wastewater management at the global scale is not successful neither from a humanitarian nor from an environmental perspective. The systems are too expensive for the largest part of the global population. Source separation and resource recovery offer an alternative for sanitation and water pollution control. This chapter illustrates the importance but also the challenges of urine source separation for efficient nutrient removal and recovery.

Urban pluvial flood models need to be calibrated with data from actual flood events in order to validate and improve model performance. Due to the lack of conventional sensor solutions, alternative sources of data such as citizen science, social media, and surveillance cameras have been proposed in literature. Some of the methods proposed boast high scalability but without an on-site survey, they can only provide proxy measurements for physical flooding variables (such as water level). In this study, the potential value of such proxy measurements was evaluated by calibrating an urban pluvial flood model with data from experimental flood events conducted in a 25 × 25 m facility, monitored with surveillance cameras and conventional sensors in parallel. Both ideal proxy data and actual image-based proxy measurements with noise were tested, and the effects of measurement location and measurement noise were investigated separately. The results with error-free proxy data confirm the theoretic potential of such measurements, as in half of the calibration configurations tested, ideal proxy data increases model performance by at least 70% compared to sensor data. However, image-based proxy data can contain complex correlated errors, which have a complex and predominantly negative effect on performance.

One third of the global carbon emissions are emitted by the building sector. Over the last decades, space heating loads have decreased in modern buildings, and domestic hot water (DHW) is now oftentimes the largest energy consumer in the household. We developed the WaterHub modeling framework to assess the potential of technologies or measures targeting DHW energy demand. The framework combines process-based technological models and stochastic water demand modeling in a modular way to allow for holistic simulations of complex DHW systems. In two rigorous tests of the modeling framework, we demonstrated the importance of water consumption dynamics in the modeling of DHW systems, showing that static modeling leads to underestimated heat losses and wrong energy consumption predictions. In an exemplary case study, we identified and quantified the synergistic interactions between water boiler temperatures and a drain water heat recovery device, demonstrating the strength of this methodology for optimizing strategies targeting DHW systems. With its modular structure, this open-source modeling framework can be extended to include any DHW-related technology, providing a useful common platform for collaboration between technology developers and water experts.

To provide access to sustainable sanitation for the entire world population, novel technologies and systems have been developed. These options are often independent of sewers, water, and energy and therefore promise to be more appropriate for fast-growing urban areas. They also allow for resource recovery and and are adaptable to changing environmental and demographic conditions what makes them more sustainable. More options, however, also enhance planning complexity. Structured decision making (SDM) can help balance opposing interests. Yet, most of the current research focuses on the selection of a preferred option, assuming that a set of appropriate options is available. There is a lack of reproducible methods for the identification of sanitation system planning options that can consider the growing number of available technology and the many possible system configurations. Additionally, there is a lack of data, particularly for novel options, to evaluate the various sustainability criteria for sanitation.To overcome this limitation, we present a novel software supported approach: the SANitation sysTem Alternative GeneratOr (Santiago). To be optimally effective, Santiago is required to be integrated into an SDM approach. In this paper, we present all the elements that such an integration requires and illustrate these methods at the case of Arba Minch, a fast growing town in Ethiopia. Based on this example and experiences from other cases, we discuss the lessons learnt and present the advantages potentially brought by Santiago for sanitation planning The integration requires four elements: a set of technologies to be looked at, decision objectives for sustainable sanitation, screening criteria to evalute technology appropriateness, and about the technologies and the casea. The main output is a set of sanitation system options that is locally appropriate, diverse in order to reveal trade-offs, and of a manageable size. To support the definition of decision objectives, we developed a generic objective hierarchy for sustainable sanitation. Because one of the main challenges lies in the quantification of screening criteria, we established the data for 27 criteria and 41 technologies in a library.The case studies showed, that if the integration is successful, then Santiago can provide substantial benefits: (i) it is systematic and reproducible; (ii) it opens up the decision space with novel and potentially more appropriate solutions; (iii) it makes international data accessible for more empirical decision making; (iv) it enables decisions based on strategic objectives in line with the sustainable development goals; (v) it allows to prioritise appropriate and resource efficient systems right from the beginning (vi) and it contributes to a more citywide inclusive approach by birding strategic objectives with an area-based appropriateness assessment. The here presented approach enables the prioritisation of appropriate and resource efficient sanitation technologies and systems in strategic planning. Thereby this approach contributes to SDG 6.2, 6.3, and 11, sustainable sanitation for all.