Center for Advanced Water Research

This work starts from the hypothesis that water quality in a drainage basin is determined by dominant flow paths, travel time distributions and the associated transport and conversion of material which are primarily controlled by specific functional structures. They can be the geographical arrangement of the water networks and the entry points of anthropogenic matter inputs. With regard to urban systems there is a long lasting and ongoing debate about the “optimal degree” of centralized or decentralized wastewater treatment with regard to technical, economic and environmental criteria. However, in central Europe the urban water infrastructures and networks have been fully developed with emphasis on centralized systems and following the emission principle with uniform effluent standards. The consequence of this approach is an effective reduction of loadings to the aquatic environment, but not necessarily a minimisation of water quality impacts from a network perspective.
The alternative approach of water quality management would therefore be to follow a principle of minimum emissions and optimisation of the functionality of river networks with the aim of achieving tolerable overall immissions and optimum water quality for the ecosystems in a networks perspective.
The questions addressed are the following:

• Are there characteristic temporal and spatial patterns of pressures and water quality impacts in developed natural and anthropogenic water networks in Central Europe?
• How do recovery paths in term of eutrophication look like?
• How is the effect of measures for eutrophication abatement in Europe?
• How should discharge points and retention zones be distributed in the catchment to minimise the impacts upon river networks?
• What is the optimal management option for load reduction at a catchment outlet in relation to the best achievable water quality of the upstream river network?

References

• Bloeschl, G., Viglione, A., Montanari, A., 2013. Emerging Approaches to Hydrological Risk Management in a Changing World, in: Climate Vulnerability: Understanding and Addressing Threats to Essential Resources. Academic Press, pp. 3–10.

• Duarte, M.C., D.J.Conley, J. Carstensen, M. Sanchez-Camacho (2008) Return to Neverland: Shifting Baselines Affect Eutrophication Restoration Targets. Estuaries and Coasts. 32 : 29–36.

• Park, J., Rao, P.S.C., 2014. Regime shifts under forcing of non-stationary attractors : Conceptual model and case studies in hydrologic systems. J. Contam. Hydrol. 169, 112–122. doi:10.1016/j.jconhyd.2014.08.005

• Park, J., Seager, T.P., Rao, P.S.C., Convertino, M., Linkov, I., 2013. Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems. Risk Anal. 33, 356–367. doi:10.1111/j.1539-6924.2012.01885.x

• Rinaldo, A., Rigon, R., Banavar, J.R., Maritan, A., Rodriguez-Iturbe, I., 2014. Evolution and selection of river networks: statics, dynamics, and complexity. Proc. Natl. Acad. Sci. U. S. A. 111, 2417–24. doi:10.1073/pnas.1322700111

• Scheffer, M., Carpenter, S., Foley, J.A., Folke, C., Walker, B., 2001. Catastrophic shifts in ecosystems. Nature 413, 591–596.

In a growing and increasingly urbanizing world, cities are faced with challenges to the reliable provision of public services, which are provided by critical infrastructure systems (CIS). These include: transportation, water, energy, and IT networks. Many cities in developing countries (Asia, Africa and South America) are faced with rapid population growth through rural-urban migration or influx of refugees from neighboring regions that experience crises. As CIS age, they degrade, and they need to continuously grow and adapt, in order to provide services to the increasing population. Furthermore, many of these cities already have to contend with water scarcity issues and inequality of access within the urban communities, and environmental changes and emerging competition for resources may further exacerbate both types of problems. While these cities often have restricted financial and technological resources, they need to find effective ways in order to adapt to system changes without making decisions that may lead to cascading effects and put the system at risk of failure of the socio-technical system in the medium-term or collapse of the environment it draws its resources from. Much of the engineering analysis of CIS resilience to date is centered on empirical metrics derived on CIS response to a single “shock” (i.e., loss of service, and recovery to initial state). Urban services are often regarded as single-sector processes as regulated by segmented regulatory and decision-making bodies, and management is grounded on a normative ideal of the formal sector being the main, if not the only player in providing urban services, and keeping social adaptive capacity, together with the informal sector as a black box at best.
While it is recognized in the scientific literature that the informal sector plays an important role in the resilience of complex systems, as it can act quickly and effectively when needed (Salt and Walker, 2012), a quantification of this role remains absent. Also lacking is an understanding of the role played by the informal social structures and the social capital that is derived from them, and the role of such networks in developing coping strategies to contend with the dysfunctional or unreliable CIS and formal institutions.
Improvements in the level of service are often measured as an average rate (over a certain time period and certain neighborhood), neglecting aggravating inequalities in time and space, and for different social groups affected by insufficiencies in urban water services. Topology (structure) and services (functions) of CIS networks are determined by a set of procedures and decision-making cascades embedded in social networks on different levels among 1) decision makers, 2) service-providers and 3) service users. Interdependent social and technical networks of CIS are embedded into their environment, and hence are subject to external shocks originating in their environment (e.g. droughts, in-migration, or other international dynamics), as well as to non-linear effects and inter-relations of processes taking place on different space and time scales within the different urban sectors and on the different levels of the social networks. We will extend the analysis of single shocks to recovery from emerging (e.g., climate change), persistent (population shocks), and multiple shocks.

• Anderies, J.M., Janssen, M. a, Ostrom, E., 2004. A Framework to Analyze the Robustness of Social- Ecological Systems from an Institutional Perspective. Ecol. Soc. 9, 1–18. doi:18
• Gawel, E., Sigel, K., Bretschneider, W., 2013. Affordability of water supply in Mongolia: Empirical lessons for measuring affordability. Water Policy 15, 19–42. doi:10.2166/wp.2012.192
• Muneepeerakul, R., Qubbaj, M.R., 2012. The effect of scaling and connection on the sustainability of a socio-economic resource system. Ecol. Econ. 77, 123–128. doi:10.1016/j.ecolecon.2012.02.017
• Obrist, B., Pfeiffer, C., Henley, R., 2010. Multi-layered social resilience: a new approach in mitigation research. Prog. Dev. Stud. 10, 283–293. doi:10.1177/146499340901000402
• Park, J., Rao, P.S.C., 2014. Regime shifts under forcing of non-stationary attractors: Conceptual model and case studies in hydrologic systems. J. Contam. Hydrol. 169, 112–122. doi:10.1016/j.jconhyd.2014.08.005
• Park, J., Seager, T.P., Rao, P.S.C., Convertino, M., Linkov, I., 2013. Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems. Risk Anal. 33, 356–367. doi:10.1111/j.1539-6924.2012.01885.x
• Walker, B., Holling, C.S., Carpenter, S.R., Kinzig, A., 2004. Resilience, Adaptability and Transformability in Social – ecological Systems. Ecol. Soc. 9.