Performance assessment of urban precinct design: a scoping study

Executive Summary: Significant advances have been made over the past decade in the development of scientifically and industry accepted tools for the performance assessment of buildings in terms of energy, carbon, water, indoor environment quality etc. For resilient, sustainable low carbon urban development to be realised in the 21st century, however, will require several radical transitions in design performance beyond the scale of individual buildings. One of these involves the creation and application of leading edge tools (not widely available to built environment professions and practitioners) capable of being applied to an assessment of performance across all stages of development at a precinct scale (neighbourhood, community and district) in either greenfield, brownfield or greyfield settings. A core aspect here is the development of a new way of modelling precincts, referred to as Precinct Information Modelling (PIM) that provides for transparent sharing and linking of precinct object information across the development life cycle together with consistent, accurate and reliable access to reference data, including that associated with the urban context of the precinct. Neighbourhoods are the ‘building blocks’ of our cities and represent the scale at which urban design needs to make its contribution to city performance: as productive, liveable, environmentally sustainable and socially inclusive places (COAG 2009). Neighbourhood design constitutes a major area for innovation as part of an urban design protocol established by the federal government (Department of Infrastructure and Transport 2011, see Figure 1). The ability to efficiently and effectively assess urban design performance at a neighbourhood level is in its infancy. This study was undertaken by Swinburne University of Technology, University of New South Wales, CSIRO and buildingSMART Australasia on behalf of the CRC for Low Carbon Living

Smart Water Management towards Future Water Sustainable Networks

[EN] Water management towards smart cities is an issue increasingly appreciated under financial and environmental sustainability focus in any water sector. The main objective of this research is to disclose the technological breakthroughs associated with water and energy use. A methodology is proposed and applied in a case study to analyze the benefits to develop smart water grids, showing the advantages offered by the development of control measures. The case study showed the positive results, particularly savings of 57 GWh and 100 Mm3 in a period of twelve years when different measures from the common ones were developed for the monitoring and control of water losses in smart water management. These savings contributed to reducing the CO2 emissions to 47,385 t CO2-eq. Finally, in order to evaluate the financial effort and savings obtained in this reference systems (RS) network, the investment required in the monitoring and water losses control in a correlation model case (CMC) was estimated, and, as a consequence, the losses level presented a significant reduction towards sustainable values in the next nine years. Since the pressure control is one of the main issues for the reduction of leakage, an estimation of energy production for Portugal is also presentedRamos, HM.; Mcnabola, A.; López Jiménez, PA.; Pérez-Sánchez, M. (2020). Smart Water Management towards Future Water Sustainable Networks. Water. 12(1):1-13. https://doi.org/10.3390/w12010058S113121Sachidananda, M., Webb, D., & Rahimifard, S. (2016). A Concept of Water Usage Efficiency to Support Water Reduction in Manufacturing Industry. Sustainability, 8(12), 1222. doi:10.3390/su8121222Boyle, T., Giurco, D., Mukheibir, P., Liu, A., Moy, C., White, S., & Stewart, R. (2013). Intelligent Metering for Urban Water: A Review. Water, 5(3), 1052-1081. doi:10.3390/w5031052Ritzema, H., Kirkpatrick, H., Stibinger, J., Heinhuis, H., Belting, H., Schrijver, R., & Diemont, H. (2016). Water Management Supporting the Delivery of Ecosystem Services for Grassland, Heath and Moorland. Sustainability, 8(5), 440. doi:10.3390/su8050440Pérez-Sánchez, M., Sánchez-Romero, F. J., & López-Jiménez, P. A. (2017). Nexo agua-energía: optimización energética en sistemas de distribución. Aplicación ‘Postrasvase Júcar-Vinalopó’ (España). Tecnología y ciencias del agua, 08(4), 19-36. doi:10.24850/j-tyca-2017-04-02Howell, S., Rezgui, Y., & Beach, T. (2017). Integrating building and urban semantics to empower smart water solutions. Automation in Construction, 81, 434-448. doi:10.1016/j.autcon.2017.02.004Mounce, S. R., Pedraza, C., Jackson, T., Linford, P., & Boxall, J. B. (2015). Cloud Based Machine Learning Approaches for Leakage Assessment and Management in Smart Water Networks. Procedia Engineering, 119, 43-52. doi:10.1016/j.proeng.2015.08.851Lombardi, P., Giordano, S., Farouh, H., & Yousef, W. (2012). Modelling the smart city performance. Innovation: The European Journal of Social Science Research, 25(2), 137-149. doi:10.1080/13511610.2012.660325Smart Cities: Strategic Sustainable Development for an Urban World. Sweden: School of Engineering, Blekinge Institute of Technology https://www.diva-portal.org/smash/get/diva2:832150/FULLTEXT01.pdfSmart Cities: Ranking of European Medium-Sized. Vienna, Austria: Centre of Regional Science (SRF), Vienna University of Technology http://www.smart-cities.eu/download/smart_cities_final_report.pdfHellström, D., Jeppsson, U., & Kärrman, E. (2000). A framework for systems analysis of sustainable urban water management. Environmental Impact Assessment Review, 20(3), 311-321. doi:10.1016/s0195-9255(00)00043-3Smart Water Grid. USA: Department of Civil and Environmental Engineering, Colorado State University http://www.engr.colostate.edu/~pierre/ce_old/Projects/Rising%20Stars%20Website/Martyusheva,Olga_PlanB_TechnicalReport.pdfSmart Metering Introduction. Obtained on 12 August 2015, from Alliance for Water Efficiency http://www.allianceforwaterefficiency.org/smart-meter-introduction.aspxNtuli, N., & Abu-Mahfouz, A. (2016). A Simple Security Architecture for Smart Water Management System. Procedia Computer Science, 83, 1164-1169. doi:10.1016/j.procs.2016.04.239Britton, T. C., Stewart, R. A., & O’Halloran, K. R. (2013). Smart metering: enabler for rapid and effective post meter leakage identification and water loss management. Journal of Cleaner Production, 54, 166-176. doi:10.1016/j.jclepro.2013.05.018Sharvelle, S., Dozier, A., Arabi, M., & Reichel, B. (2017). A geospatially-enabled web tool for urban water demand forecasting and assessment of alternative urban water management strategies. Environmental Modelling & Software, 97, 213-228. doi:10.1016/j.envsoft.2017.08.009Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and Results.A Guide for Sensor Manufacturers and Water Utilities. Ohio: EPA–Environmental Protection Agency https://www.epa.gov/sites/production/files/2015-06/documents/distribution_system_water_quality_monitoring_sensor_technology_evaluation_methodology_results.pdfSCADA: Supervisory Control and Data Acquision. USA: ISA–The Instrumentation, Systemas and Automation Society https://www.fer.unizg.hr/_download/repository/SCADA-Supervisory_And_Data_Acquisition.pdfCan we make water systems smarter? Opflow http://innovyze.com/news/showcases/SmartWaterNetworks.pdfGurung, T. R., Stewart, R. A., Beal, C. D., & Sharma, A. K. (2015). Smart meter enabled water end-use demand data: platform for the enhanced infrastructure planning of contemporary urban water supply networks. Journal of Cleaner Production, 87, 642-654. doi:10.1016/j.jclepro.2014.09.054Romano, M., & Kapelan, Z. (2014). Adaptive water demand forecasting for near real-time management of smart water distribution systems. Environmental Modelling & Software, 60, 265-276. doi:10.1016/j.envsoft.2014.06.016Samora, I., Franca, M. J., Schleiss, A. J., & Ramos, H. M. (2016). Simulated Annealing in Optimization of Energy Production in a Water Supply Network. Water Resources Management, 30(4), 1533-1547. doi:10.1007/s11269-016-1238-5Sanchis, R., Díaz-Madroñero, M., López-Jiménez, P. A., & Pérez-Sánchez, M. (2019). Solution Approaches for the Management of the Water Resources in Irrigation Water Systems with Fuzzy Costs. Water, 11(12), 2432. doi:10.3390/w11122432Alonso Campos, J. C., Jiménez-Bello, M. A., & Martínez Alzamora, F. (2020). Real-time energy optimization of irrigation scheduling by parallel multi-objective genetic algorithms. Agricultural Water Management, 227, 105857. doi:10.1016/j.agwat.2019.105857Controlo Ativo de Perdas de Água. Lisboa: EPAL–Empresa Portuguesa das Águas Livres http://www.epal.pt/EPAL/docs/default-source/epal/publica%C3%A7%C3%B5es-t%C3%A9cnicas/controlo-ativo-de-perdas-de-%C3%A1gua.pdf?sfvrsn=30Ndirangu, N., Ng’ang’a, J., Chege, A., de Blois, R.-J., & Mels, A. (2013). Local solutions in Non-Revenue Water management through North–South Water Operator Partnerships: the case of Nakuru. Water Policy, 15(S2), 137-164. doi:10.2166/wp.2013.117Romero, L., Pérez-Sánchez, M., & Amparo López-Jiménez, P. (2017). Improvement of sustainability indicators when traditional water management changes: a case study in Alicante (Spain). AIMS Environmental Science, 4(3), 502-522. doi:10.3934/environsci.2017.3.50

Overview of Energy Management and Leakage Control Systems for Smart Water Grids and Digital Water

Current and future smart cities are moving towards the zero-net energy use concept. To this end, the built environment should also be designed for efficient energy use and play a significant role in the production of such energy. At present, this is achieved by focusing on energy demand in buildings and to the renewable trade-off related to smart power grids. However, urban water distribution systems constantly carry an excess of hydraulic energy that can potentially be recovered to produce electricity. This paper presents a comprehensive review of current strategies for energy production by reviewing the state-of-the-art of smart water systems. New technologies (such as cyber-physical systems, digital twins, blockchain) and new methodologies (network dynamics, geometric deep learning) associated with digital water are also discussed. The paper then focuses on modelling the installation of both micro-turbines and pumps as turbines, instead of/together with pressure reduction valves, to further demonstrate the energy-recovery methods which will enable water network partitioning into district metered areas. The associated benefits on leakage control, as a source of energy, and for contributing to overall network resilience are also highlighted. The paper concludes by presenting future research directions. Notably, digital water is proposed as the main research and operational direction for current and future Water Distribution Systems (WDS) and as a holistic, data-centred framework for the operation and management of water networks.</jats:p

41st annual hydrology days (2021) - online proceedings

The 41st Annual AGU Hydrology Days event at Colorado State University was hosted online March 30-31, 2021.Includes the schedule and presentation abstracts only. The 41st Annual American Geophysical Union Hydrology Days meeting provides a unique opportunity for students, faculty, staff and practitioners to engage in wide range of water-related interdisciplinary research topics. Unfortunately, the global pandemic has left students with limited opportunities to share their research and satisfy graduation requirements. This year the spotlight focused on students to highlight the interconnections of water and linked systems. The 2021 Student Showcase provides an opportunity for students to exchange ideas, present their research findings and refine their science communication skills

Examples of trends in water management systems under influence of modern technologies

Dobivanje pouzdanih i pravovremenih informacija o trenutačnom i o budućem stanju voda omogućava učinkovito upravljanje vodnogospodarskim sustavima. U ovom se radu prikazuju prednosti i izazovi primjene naprednih tehnologija pri prikupljanju, obradi i integraciji podataka unutar nekoliko primjera sustava gospodarenja vodama. Pokazuje se kako napredne tehnologije imaju izraženu učinkovitost u preciznom praćenju različitih fenomena okoliša, u povećanju sigurnosti vodnih resursa i objekata te omogućavaju smanjenje potrošnje vode i energije uz povećanje kvalitete vode.Reliable and timely information about the current and future condition of water enables an efficient management of water management systems. Advantages and challenges of the use of modern technologies in the collection, analysis, and integration of data, are presented in this paper by means of several examples of water management systems. It is shown how advanced technologies demonstrate a pronounced efficiency in accurate monitoring of various environmental phenomena and in increasing safety of water resources and facilities, while also enabling low water and energy consumption, with simultaneous increase in water quality

Characterization of urban water use and performance evaluation of conservation practices using the Integrated Urban Water Model in São Paulo, Brazil

2018 Fall.Includes bibliographical references.Increasing urban population around the globe has intensified the need for water, food and energy. The residential sector is responsible for the highest water use in urban settings. Understanding the factors affecting water use helps to improve management strategies, incentivize conservation practices, develop public educational events, feed demand forecasting models and support policy creation. Modelling urban water demand in the long-term is a complex process because of incorporation of multiple dynamic components in the urban-environment system. The Integrated Urban Water Model – IUWM – offers capabilities of long-term modelling by using a mass-balance approach for urban water demand predictions and potential demand reductions assessment. A combination of climate anomalies, water resources management practices over the years and watershed conservation contributed to the water shortage in Southeastern Brazil in 2014-2015. In the city of São Paulo, the shortage was worsened by drops in reservoir levels, rise in water use patterns and in number of inhabitants, and the historical tendency to neglect local water sources. Residential water demand, which accounts for 84% of the total water use, faced compulsory reductions through behavioral changes and reuse of graywater and roof runoff harvesting. The goals of this study are to apply IUWM to the city of São Paulo to quantify savings produced by graywater and roof runoff use and to evaluate the potential of conservation practices for demand reduction. The first part of the study focuses on exploring differences in water demand patterns under shortage conditions using a water use time-series from 2013-2017. In this part, IWUM is trained to estimate indoor and outdoor demand through calibration procedures. Determinants of water demand are also investigated through a multiple linear regression, which identified household size and socioeconomic variables as having a significant effect in water use. The second portion focuses on applying IUWM to evaluate reductions during the shortage and performance of graywater, stormwater, roof runoff harvesting and effluent reuse for potable and non-potable purposes. Climate change was added to assess shifts in performances of conservation practices due to future reductions in precipitation. Lastly, a comparison of maximum potential and benefits of fit-for-purpose technology adoption is done using a cost-benefit matrix. The matrix was adapted for required treatment representing cost and percentage reductions in water demand as benefit. The results of this work support decision-making with respect to conservation practices adoption by enhancing the list of options to manage water demand, especially during shortage conditions. Ultimately, these results can encourage development of water reuse policies in Brazil

Assessing tradeoffs of urban water demand reduction strategies

2019 Fall.Includes bibliographical references.In many cities across the World, traditional sources of potable water supply can become susceptible to shortage due to increased water demands from rapid urbanization and more frequent and extreme drought conditions. Understanding impacts of city-scale conservation and water reuse is important for water managers to implement cost effective water saving strategies and develop resilient municipal water systems. Innovative water reuse systems are becoming more cost effective, technologically viable and socially accepted. However, there is still a need for comparative assessment of alternative sources; graywater, stormwater and wastewater use along with indoor and outdoor conservation, implemented at the municipal scale. This study applies the Integrated Urban Water Model (IUWM) to three U.S. cities; Denver, CO; Miami, FL; and Tucson, AZ. We assess the tradeoffs between cost and water savings for a range of solutions composed of up to three strategies; to understand interactions between strategies and their performance under the influence of local precipitation, population density and land cover. A global sensitivity analysis method was used to fit and test model parameters to historical water use in each city. Alternative source and conservation strategies available in IUWM were simulated to quantify annual water savings. Alternative source strategies simulate collection of graywater, stormwater and wastewater to supplement demands for toilet flushing, landscape irrigation and potable supply. A non-dominated sorting function was applied that minimizes annual demand and total annualized cost to identify optimal strategies. Results show discrete strategy performance in demand reduction between cities influenced by local climate conditions, land cover and population density. Strategies that include use of stormwater can achieve highest demand reduction in Miami, where precipitation and impervious area is large resulting in larger generation of stormwater compared to other study cities. Indoor conservation was frequently part of optimal solutions in Tucson, where indoor water use is higher per capita compared to other study cities. The top performing strategies overall in terms of water savings and total cost were found to be efficient irrigation systems and stormwater for irrigation. While use of stormwater achieves large demand reduction relative to other strategies, it only occurred in non-dominated solutions that were characterized by higher cost. This strategy can be very effective for demand reduction, but is also costly. On the contrary, efficient irrigation systems are frequently part of low-cost solutions across all three study cities. Overall, this study introduces a framework for assessing cost and efficacy of water conservation and reuse strategies across regions. Results identify optimal strategies that can meet a range of demand reduction targets and stay within financial constraints

Infrastructure systems modeling using data visualization and trend extraction

“Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction. This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions. Four distinct contributions are made in this work and divided equally across the two cases. The first contribution identifies trends and flood characteristics that must be included as part of model development. The second contribution uses trend extraction to create a traffic management data visualization system based on the flood influencing factors identified. The third contribution creates a data visualization framework for energy portfolio analysis using a genetic algorithm and fuzzy logic. The fourth contribution develops a sustainability assessment model using trend extraction and time series forecasting of state-level electricity generation in a proposed transition setting. The data visualization and trend extraction tools developed and validated in this research will improve strategic infrastructure planning effectiveness”--Abstract, page iv

Bridging the Geospatial Education-Workforce Divide: A Case Study on How Higher Education Can Address the Emerging Geospatial Drivers and Trends of the Intelligent Web Mapping Era

The purpose of this exploratory collective case study is to discover how geospatial education can meet the geospatial workforce needs of the Commonwealth of Virginia, in the emerging intelligent web mapping era. Geospatial education uses geographic information systems (GIS) to enable student learning by increasing in-depth spatial analysis and meaning using geotechnology tools (Baker & White, 2003). Bandura’s (1977) self-efficacy theory and geography concept of spatial thinking form an integrated theoretical framework of spatial cognition for this study. Data collection included in-depth interviews of twelve geospatial stakeholders, documentation collection, and supporting Q methodology to determine the viewpoints of a total of 41 geospatial stakeholders. Q methodology is a type of data collection that when used as a qualitative method utilizes sorting by the participant to determine their preferences. Data analysis strategies included cross-case synthesis, direct interpretation, generalizations, and a correlation matrix to show similarities in participants\u27 preferences. The results revealed four collaborative perceptions of the stakeholders, forming four themes of social education, technology early adoption, data collaboration, and urban fundamentals. Four strategies were identified for higher education to prepare students for the emerging geospatial workforce trends. These strategies are to teach fundamentals, develop agile faculty and curriculum, use an interdisciplinary approach, and collaborate. These strategies reflect the perceptions of stakeholders in this study on how higher education can meet the emerging drivers and trends of the geospatial workforce