Dynamic Metabolism Modeling as a Decision-Support Tool for Urban Water Utilities Applied to the Upstream of the Water System in Oslo, Norway

AbstractThe paper presents, first, the ‘Dynamic Metabolism Model’ (DMM), developed by the authors, followed by an application to the city of Oslo, capital city of Norway. The time period considered for the analysis is 2013-2043. The external factors impacting decision-making and interventions are talked about in brief, and some realistic scenarios revolving around these factors are drawn up for testing, after consultation with officials at the Oslo Water and Wastewater Works. Possible interventions that the utility intends to set in motion on the upstream are defined and numerically interpreted for incorporation into the DMM

Urban water system metabolism assessment using WaterMet2 model

12th International Conference on Computing and Control for the Water Industry, CCWI2013, 2013-09-06, 2013-09-09, Perugia, ItalyThis paper presents a new "WaterMet2" model for integrated modelling of an urban water system (UWS). The model is able to quantify the principal water flows and other main fluxes in the UWS. The UWS in WaterMet2 is characterised using four different spatial scales (indoor area, local area, subcatchment and system area) and a daily temporal resolution. The main subsystems in WaterMet2 include water supply, water demand, wastewater and cyclic water recovery. The WaterMet2 is demonstrated here through modelling of the urban water system of Oslo city in Norway. Given a fast population growth, WaterMet2 analyses a range of alternative intervention strategies including 'business as usual', addition of new water resources, increased rehabilitation rates and water demand schemes to improve the performance of the Oslo UWS. The resulting five intervention strategies were compared with respect to some major UWS performance profiles quantified by the WaterMet2 model and expert's opinions. The results demonstrate how an integrated modelling approach can assist planners in defining a better intervention strategy in the future.This work was carried out as part of the ‘TRansition to Urban water Services of Tomorrow’ (TRUST) project. The authors wish to acknowledge the European Commission for funding TRUST project in the 7th Framework Programme under Grant Agreement No. 265122

Decision Support System for the Long-Term City Metabolism Planning Problem

AcceptedArticleA Decision Support System (DSS) tool for the assessment of intervention strategies (Alternatives) in an Urban Water System (UWS) with an integral simulation model called “WaterMet2” is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria (Alegre et al., 2012). The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMet2 model and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A Multi-Criteria Decision Analysis (MCDA) approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive Graphical User Interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life urban water system for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic level sustainability objectives.EU 7th Framework Programm

City Blueprints: Baseline Assessments of Sustainable Water Management in 11 Cities of the Future

The necessity of Urban Water Cycle Services (UWCS) adapting to future stresses calls for changes that take sustainability into account. Megatrends (e.g. population growth, water scarcity, pollution and climate change) pose urgent water challenges in cities. In a previous paper, a set of indicators, i.e., the City Blueprint has been developed to assess the sustainability ofUWCS (Van Leeuwen et al.,Wat Resour Manage 26:2177¿2197, 2012). In this paper this approach has been applied in 9 cities and regions in Europe (Amsterdam, Algarve, Athens, Bucharest, Hamburg, Reggio Emilia, Rotterdam, Oslo and Cities of Scotland) and in 2 African cities in Angola (Kilamba Kiaxi) and Tanzania (Dar es Salaam). The assessments showed that cities vary considerably with regard to the sustainability of theUWCS. This is also captured in the Blue City Index (BCI), the arithmetic mean of 24 indicators comprising the City Blueprint (Van Leeuwen et al., Wat Resour Manage 26:2177¿2197, 2012). Theoretically, the BCI has a minimum score of 0 and a maximum score of 10. The actual BCIs in the 11 cities studied varied from 3.31 (Kilamba Kiaxi) to 7.72 (Hamburg). The BCI was positively correlated with the Gross Domestic Product (GDP) per person, the ambitions of the local authorities regarding the sustainability of the UWCS, the voluntary participation index (VPI) and all governance indicators according to the World Bank. The study demonstrated that the variability in sustainability among the UWCS of cities offers great opportunities for short-term and long-term improvements, provided that cities share their best practices.Van Leeuwen, CJ. (2013). City Blueprints: Baseline Assessments of Sustainable Water Management in 11 Cities of the Future. Water resources management. https://doi.org/10.1007/s11269-013-0462-5Bai X (2007) Industrial ecology and the global impacts of cities. J Industr Ecol 11:1–6Brown RR, Keath N, Wong THF (2009) Urban water management in cities: Historical, current and future regimes. Water Sci Technol 59:847–855De Graaf R, van de Giessen N, van de Ven F (2007a) Alternative water management options to reduce vulnerability for climate change in the Netherlands. Nat Hazards 5:407–422De Graaf RE, van de Giessen NC, van de Ven FHM (2007b) The closed city as a strategy to reduce vulnerability of urban areas for climate change. Water Sci Technol 56:165–173EEA (2010) European Environment Agency. The European environment. State and outlook 2010. Synthesis. Copenhagen, DenmarkEEA (2012) European Environment Agency. Urban adaptation to climate change in Europe. Challenges and opportunities for cities together with supportive national and European policies. Synthesis, Copenhagen, DenmarkEFILWC (2006) First European quality of life survey: participation in civil society. European Foundation for the Improvement of Living and Working Conditions, Dublin. http://www.eurofound.europa.eu/publications/htmlfiles/ef0676.htm . Accessed 21 February 2011Engel K, Jokiel D, Kraljevic A, Geiger M, Smith K (2011) Big cities. Big water. Big challenges. Water in an urbanizing world. World wildlife fund, KoberichEnvironmental Performance Index (2010) http://www.epi2010.yale.edu/Metrics/WaterEffectsOnEcosystem . Accessed 30 March 2012European Commission (2012) Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. A Blueprint to Safeguard Europe’s Water Resources. COM (2012)673 finalEuropean Commission (2013) European Innovation Partnership on water (EIP Water). http://ec.europa.eu/environment/water/innovationpartnership/European green city index (2009) Assessing the environmental impact of Europe’s major cities. A research project conducted by the Economist Intelligence Unit, http://www.siemens.com/press/pool/de/events/corporate/2009-12-Cop15/European_Green_City_Index.pdf . Accessed 20 February 2011Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, Briggs JM (2008) Global change and the ecology of cities. Science 319(5864):756–760Hoekstra AY, Mekonnen MM, Chapagain AK, Mathews RE, Richter BD (2012) Global monthly water scarcity: Blue water footprints versus blue water availability. PLoS ONE 7(2):e32688. doi: 10.1371/journal.pone.0032688IMF (2012) Gross Domestic Product (international dollars) as provided by the International Monetary Fund for 2010–2011: http://en.wikipedia.org/wiki/List_of_countries_by_GDP_(PPP)_per_capita . Accessed October 2012Kaufman D, Kraay A, Mastruzzi M (2010) The worldwide governance indicators. Methodology and analytical issues. World Bank Policy Research Working Paper 5430. World Bank, Washington DCLange P, Driessen PJ, Sauer A, Borneman B, Burger P (2013) Governing towards sustainability – conceptualizing modes of governance. J Environ Policy Planning 15:403–425Makropoulos CK, Butler D (2010) Distributed water infrastructure for sustainable communities. Water Resour Manag 24(11):2795–2816Mekonnen MM, Hoekstra AY (2011) National water footprint accounts: the green, blue and grey water footprint of production and consumption. Volumes 1 and 2. Value of Water Research Report Series No. 50. UNESCO-IHE, Delft, the NetherlandsNorman E, Bakker K, Cook C, Dunn G, Allen D (2010) Water security: A primer. Policy report. Fostering water security in Canada Project www.watergovernance.ca Accessed 20 September 2013Philip R, Anton B, van der Steen P (2011) SWITCH training kit. Integrated urban water management in the city of the future. Module 1. Strategic planning, ICLEI, Freiburg, GermanyPrüss-Üstün A, Bos R, Gore F, Bartram J (2008) Safer water, better health: Costs, benefits and sustainability of interventions to protect and promote health. World Health Organization, GenevaRozos E, Makropoulos C (2013) Source to tap urban water cycle modelling. Environ Model Softw 41:139–150SIWI (2012) Stockholm International Water Institute. Statistics. http://www.siwi.org/sa/node.asp?node=159 Accessed 20 December, 2012Ugarelli R, Pachioli M, Di Federico V (2009) Planning maintenance strategies for Italian urban drainage systems applying CARE-S. In: Allegre H, do Céu Almeida M (eds) Strategic asset management of water supply and wastewater infrastructures. IWA Publishing, London, pp 471–486UN (2012) World urbanization prospects: The 2011 revision. UN, New York, USA. http://esa.un.org/unup/ . Accessed 30 November 2012UNDP (2004) Water governance for poverty reduction. USA, New YorkUNEP (2008) Every drop counts; environmentally sound technologies for urban and domestic water use efficiency. Switzerland, GenevaUNEP (2012) Fifth global environment outlook: Environment for the future we want. Switzerland, GenevaUNESCO (2012) Managing water under uncertainty and risk. Facts and figures from the UN world water development report 4. http://unesdoc.unesco.org/images/0021/002154/215492e.pdf . Accessed 20 December 2012UN-Habitat (2010). Climate change strategy 2010–2013. Urban Environmental Planning Branch, Nairobi, Kenia. http://www.google.nl/search?sourceid=navclient&ie=UTF-8&rlz=1T4MXGB_enNL512NL512&q=Climate+change+strategy+2010-2013 . Accessed 20 December 2012Van Leeuwen CJ (2007) Introduction. In: Van Leeuwen CJ, Vermeire TG (eds) Risk Assessment of Chemicals. An Introduction. 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Displacement of non-Newtonian compressible fluids in plane porous media flow

Displacement of non-Newtonian fluid in porous media is of aramount importance in the flow modeling of oil reservoirs. Although numerical solutions are available, there exists a need for closed-form solutions in simple geometries. Here we revisit and expand the work of Pascal and Pascal [4], who analyzed the dynamics of a moving stable interface in a semi-infinite porous domain saturated by two fluids, displacing and displaced, both non-Newtonian of power-law behavior, assuming continuity of pressure and velocity at the interface, and constant initial pressure. The flow law for both fluids is a modified Darcy’s law. Coupling the nonlinear flow law with the continuity equation considering the fluids compressibility, yields a set of nonlinear second-order PDEs. If the fluids have the same consistency index n, the equations can be transformed via a self-similar variable; incorporation of the conditions at the interface shows the existence of a compression front ahead of the moving interface. After some algebra, one obtains a set of nonlinear equations, whose solution yields the location of the moving interface and compression front, and the pressure distributions. The previous equations include integrals which can be expressed by analytical functions if n is of the form k/(k+1) or (2k-1)/(2k+1), with k a positive integer. Explicit xpressions are provided for k = 1, 2; for other values, results are easily obtained via recursive formulae. All results are presented in dimensionless form; the pressure distribution and interface positions are studied and discussed as a function of the self-similar variable for different values of the mobility and compressibility ratios

Comment on \u2018Yamada H, Nakamura F, Watanabe Y, Murakami M and Nogami T. 2005. Measuring hydraulic permeability in a streambed using the packer test. Hydrological Processes 19: 2507\u20132524\u2019

In a recent paper, Yamada et al. (2005) derived an expression to calculate hydraulic permeability under non-Darcy flow conditions using the packer test; their results were obtained via numerical integration of the derived expression. Their findings are extended by providing a closed-form solution to the problem, and its dependence upon key parameters is illustrated

Self-similar solutions for unsteady-state flow of non-Newtonian fluids in porous media

In this paper we study the one-dimensional flow of compressible non-Newtonian power-law fluids generated by fluid withdrawal at the boundary of an infinite reservoir having plane or radial geometry. The withdrawal is effectuated such that the pumped discharge is a prescribed function of time. The power-law fluid flow model is based on a modified Darcy\u2019s law taking into account the nonlinear rheological effects of the fluid behavior. Coupling the flow law with the continuity equation yields a nonlinear second-order partial differential equation in the fluid pressure. The latter equation, with relevant boundary conditions, is amenable to a similarity transformation which reduce the partial differential equation into a nonlinear ordinary differential equation, provided that the injection flow rate as a function of time takes a particular form, depending on the exponent of the flow law and geometry. Solving the nonlinear differential equation yields the pressure distribution in space and time as a function of fluid properties and withdrawal intensity. The resulting integral can be expressed by analytical functions if the fluid consistency index n is of the form (k+1)/k, where k is a positive integer; otherwise, a single numerical integration is required. Explicit expressions are provided for the cases k = 1 and k = 2, while for higher values of k, results can be obtained via recursive formulae. For a Newtonian fluid (n = 1), the self-similar variable reduces to the Boltzmann transformation; in radial geometry, the variable flow rate reduces to a constant one, and the pressure disturbance with respect to the initial condition takes the form of the Theis integral, albeit with pressure replacing hydraulic head