Difference between revisions of "OR/17/007 Effective knowledge exchange: translating groundwater and geothermal data to city planning - (Gert Laursen and Mitja Janža)"
|[checked revision]||[checked revision]|
m (1 revision imported)
|Line 94:||Line 94:|
| Geothermal potential maps
| Geothermal potential maps
| Barcelona (García-Gil et al., 2015<ref name="García-Gil 2015">García-Gil, A, Vázquez-Suñe, E, Alcaraz, M M, Juan, A S, Sánchez-Navarro, J Á, Montlleó, M, Rodríguez, G, and Lao, J. 2015. GIS-supported mapping of low-temperature geothermal potential taking groundwater flow into account. Renew. Energy 77, 268–278. doi:10.1016/j.renene.2014.11.096</ref>)<br>Basel (Epting and Huggenberger, 2013
| Barcelona (García-Gil et al., 2015<ref name="García-Gil 2015">García-Gil, A, Vázquez-Suñe, E, Alcaraz, M M, Juan, A S, Sánchez-Navarro, J Á, Montlleó, M, Rodríguez, G, and Lao, J. 2015. GIS-supported mapping of low-temperature geothermal potential taking groundwater flow into account. Renew. Energy 77, 268–278. doi:10.1016/j.renene.2014.11.096</ref>)<br>Basel (Epting and Huggenberger, 2013></ref>)<br>Berlin (Kastner et al., 2013<ref name="Kastner 2013">Kastner, O, Sippel, J, Scheck-Wenderoth, M, and Huenges, E. 2013. The deep geothermal potential of the Berlin area. Environ Earth Sci 70, 3567–3584. doi:10.1007/s12665-013-2670-y</ref>)<br>Ludwigsburg (Schiel et al., 2016<ref name="Schiel 2016">Schiel, K, Baume, O, Caruso, G, and Leopold, U. 2016. GIS-based modelling of shallow geothermal energy potential for CO<sub>2</sub> emission mitigation in urban areas. Renew. Energy 86, 1023–1036. doi:10.1016/j.renene.2015.09.017</ref>)<br>Netherlands ([http://www.thermogis.nl/ www.thermogis.nl/)]
Latest revision as of 13:53, 3 December 2019
|Bonsor, H C, Dahlqvist, P, Moosmann, L, Classen, N, Epting, J, Huggenberger, P, Garica-Gil, A, Janźa, M, Laursen, G, Stuurman, R and Gogu, C R. 2017. Groundwater, geothermal modelling and monitoring at city-scale: reviewing European practice and knowledge exchange. British Geological Survey Internal Report, OR/17/007.|
Key words: knowledge and communication gap; closing knowledge and communication gaps for subsurface planning; knowledge exchange practices; decision support tools; translating subsurface knowledge
Fundamental knowledge and communication gaps
The value of good practice to develop robust, systematic, subsurface environmental datasets in urban areas is undermined if the data are not communicated and translated effectively to city municipalities to support environmental management and city planning.
City planners and municipalities face an increasing range of issues and problems in management of the urban environmental. With increasing urbanization, and climatic variability, management of cities, and the people, infrastructure and environment is not just increasingly difficult but also important, and there is increasing need to better utilize available datasets in planning processes. A critical, condition for this is the flow of information between scientists and decision-makers. This is often not always achieved, and rarely in an effective and timely manner for decision making processes. In most cases, this is not a reflection of an absolute lack of information of knowledge of the urban subsurface, but the limited data and knowledge exchange between subsurface specialists and decision makers. The underlying reasons behind this communication gap are many. Often environmental data and hydrological modeling are only communicated as a hard-science numerical approach, which is difficult for non-experts to understand (Jacobs 2002; Rayner et al. 2005; Martínez-Santos et al. 2008; Liu et al. 2008; Molina et al. 2011). Scientific input is often ignored by decision makers because critical information is not presented in a usable form and is therefore not available or accessible to them. There is an obvious need to adapt research results to be more understandable and usable for subsurface planning and the groundwater and geothermal resources held within it.
Within Europe, and in many parts elsewhere in the world (Lavoie et al. 2013), the fundamental knowledge and communication gap between subsurface environmental specialists and city planners, generally leads to the subsurface being overlooked in planning processes, and management of the subsurface environment is ad-hoc. Planners are often not aware of the opportunities held by the subsurface for urban development (e.g. sustainable drainage, shallow geothermal energy potential, seasonal heat storage and space), or what data need to be acquired during the planning process to assess these opportunities, and manage groundwater and geothermal resources sustainability (GCC 2012). Equally, there is insufficient awareness and understanding in geological surveys, as to what subsurface data is required by city planners, in what formats, and at what stages in the planning processes.
The effect of these data and knowledge gaps are exemplified by there being no systematic local or national planning guidance for the subsurface environment in the UK, or worldwide. Geological surveys have a key role to play in providing appropriate environmental data and knowledge to underpin city planning and the management of subsurface resources, to ensure they can be utilised effectively, and sustainably, to support future cities. Bridging this current fundamental knowledge gap is increasingly important as the world’s population becomes increasing urban. Indeed, projections estimate more than two-thirds of the world’s population will live in cities by 2050 (UN 2012).
During the last 2–3 decades geological surveys have invested significant focus to developing 3D geological models, ground water models and interpreted maps, at a range of scales, in order to raise the level of knowledge and improve the basis for planning and support decision making. But, despite the development of more maps and models, a significant and fundamental gap in knowledge of the subsurface still exists between the specialists and the planners, decision makers and politicians. The subsurface is very much ‘out of sight and out of mind’.
How might this knowledge gap be bridged?
There is growing recognition of the extent to which the knowledge gaps limits effective management of resources and the city environment (Janža 2015; Lavoie 2015). Different cities within Europe are now beginning to try different approaches bridge the gap, and enable subsurface specialist to better communicate both the content, and relevance, of subsuface data to city planning processes. Within the UK, the National Environmental Research Council (NERC) and Innovate UK have recently funded two Knowledge Exchange Fellowships for 3 years to provide knowledge translators between the different specialisms, and to ensure available UK subsurface data held by NERC are visible and relevant to subsurface planning. Within Ljubljana (Slovenia) an adavanced decision support tool has already been developed between groundwater specialists and city authorities, to assist manaagment of urban contamination and protection of the public water supply from the urban groundwater resource. The Geological Survey of Denmark is also working towards developing more user relevant visualisation and decision support tools with city municipalities and water sector companies. These are discussed in more detail as examples of different good practices to bridge the knowledge gap.
Emerging good practice — case studies
Odense, Denmark — developing cross-specialist working groups within the city municipalities and working groups and visualisation tools.
To help build the communication and knowledge gaps between different specialists (including planning, project design and management, engineering, architecture, geologists) Odense has aspired to develop a SubUrban Infra-Structural Planning-group (SIP-group), which will involve a wide range of specialists within the city municipality. The ultimate aim of the work is that this SIP-group will enable the communication gaps to be properly addressed, and new long-term knowledge exchange pathways to begin to developed between different specialists and city planners, to so that the 3D model does not just become another map or model of subsurface data which is not relevant or accessible to city planners and environmental management.
Specific working groups are also being used to develop shared expertise and understanding between specialists within specific topics. A key example is for greater co-ordination and improved management of groundwater resources in the city — often a resource which is overlooked in planning processes. A working group composed of individuals from Odense city municipality, Geological Survey of Denmark (GEUS), VCS Denmark (public water supply), and Alecta and I-GIS software companies, has been developed to this end, which a specific aim of developing an improved visualisation and communication decision support tool for groundwater. The aim is to develop ‘a 3D geological/hydrogeological model as the basis for understanding the urban water cycle’, and for this model to develop a mechanism or processes which can be emulated for other subsurface datasets and end users. The model developed will be tested by the SIP, and critically in doing this, to begin to bridge the wider connection between the decision makers and the specialists in the SIP-group.
Glasgow, UK — Research Council and Business sector Knowledge Exchange Fellowships to increase awareness of subsurface data and resources in planning and urban development processes.
A similar approach to that of Odense is being taken in the UK to try to address the communication and knowledge gap surrounding subsurface resource utilisation and management within urban development and planning. In the UK, there are increasing efforts to develop cross-discipline working groups to help transfer data and knowledge between disciplines. In Glasgow, work is being undertaken to embed the lessons learnt from these working groups into Supplmentary Planning Guidance, so that subsurface data are reported fully compliant to existing industry best practice to increase interoperability of data, and to increase the utilisation of subsurface data in strategic development planning processes in urban areas, and re-used to much greater effect by different stakeholder in construction and development projects.
The work is being supported by two Knowledge Exchange Fellowships over the next for 3 years by the National Environmental Research Council (NERC) and Innovate UK. The fellows primary aim is to act as knowledge translators between different specialisms, to help identify and forge new knowledge pathways between different subsurface specialists (e.g. construction industry, engineers, geologists, hydrogeologists) and above-ground development and planning specialists (e.g. engineers, archtiects, and planners) — akin to the SIP-group proposed in Odense.
The NERC KE Fellowship work is trialling the development of the UKs first local government fully integrated above and below ground BIM (Business Information Model) to help highlight the available geological and groundwater/geothermal data available to a contruction and urban development projects, within the city of Glasgow, from the planning and design phase right through to the construction and completion stages. This BIM is being developed and trialled by local government, with engagement from key private and public sector stakeholders. Like Odense, the aim is that the 3D BIM will be developed so as to be an effective tool at highlighting subsurface data, and it will be relevant and used to inform city planning and management, rather than be just another 3D model which only bridges the gap half way.
The work is initially being trialled in Glasgow, but the role of the Fellowships is try to transfer the succesful knowledge exchange mechanisms trialled to other cities and national-level stakeholders in the UK.
Ljubljana, Slovenia — developing decision support tools (DSS), incorporating time series monitoring data of key resources.
The city of Ljubljana in Slovenia has been able to develop a specific decision support tool to inform appropriate courses of action in the event of contamination events. This DSS integrates groundwater monitoring data with geological and hydrogeological data, to inform the water utility company and regulators appropriate remediation actions to protect the city’s groundwater-sourced public water supply in the event of a contamination event. The development of this tool was driven from a contamination event which threatened the city’s water supply several years ago and highlighted the need for authorities to have better access to the cities groundwater data; existence of legislative and regulation does not in itself to informed resource management (Jamnik et al. 2012).
The system was developed within the framework of the project INCOME (LIFE07 ENV/SLO/000725; (www.life-income.si/) by Geological Survey of Slovenia in cooperation with project partners (Anton Melik Geographical Institute SRC SASA, and Environmental Agency of the Republic of Slovenia) and end-users (co-financers) Municipality of Ljubljana and Ministry of the Environment and Spatial Planning and Vodovod-kanalizacija, a public company for water supply. The features of the system were defined on the stakeholders meetings and workshops (Janža 2015).
A user-friendly graphical interface enables water managers to utilize the database, numerical modeling techniques and expert knowledge, and thus gives them fast and easy access to supporting information for mitigating groundwater pollution. It consists of three logically interlinked components: the database, hydrological model and decision model.
Database enables the storage, retrieval, display and manipulation of data related to the groundwater resources used for drinking-water supplies to Ljubljana. Through the establishment of an internet application, a larger part of the database is freely accessible through a web viewer (www.akvamarin.geo-zs.si/incomepregledovalnik/). It contains three types of data related to the monitoring, potential sources of pollution and hydrogeological conditions.
The hydrological model is an essential part of the DSS. It is a mathematical representation of the hydrological system of the study area, based on the MIKE SHE/MIKE 11 modeling framework (Graham and Butts 2005; DHI 2011a, b). A transient groundwater/surface water integrated modelling system enables simulation of the groundwater dynamics and the transport of pollutants in the aquifer. The most important feature implemented in the DSS is the simulation of the propagation of pollutants in the aquifer.
The decision model comprises a set of logical rules formalizing the knowledge and experiences of water managers and hydrogeologists related to emergency activities. A wide range of possible scenarios for activities to be taken in the case of discovery of pollution in the groundwater was analysed. Upon this basis, conditions and recommended actions or responses were defined. Syntax was developed which enables the easy creation and implementation of changes in the decision model.
The main advantage of presented DSS is reduction of the quantity of input data required and the modelling steps required to achieve an understandable level for water managers. In a similar manner, the model outcomes are presented in the form of a simulated traveling time of the pollution plume to the abstraction well, and the pollutant concentrations in the abstraction wells. In this way, DSS simplifies the use of the model and provides water managers with model outcomes in an understandable form that bridges the often-mentioned gap between science and decision making that hinders more efficient use of hydrogeological data and numerical modelling in water management.
The use and sustainability of the system (or its parts) after the project end have been assured in different ways:
- The project database that is freely accessible through a web viewer has been maintained by geological Survey of Slovenia. The long term maintenance and update of monitoring data is going to be assured by incorporation of the project database into a common environmental data base of Municipality of Ljubljana. The process is in progress at the time.
- The constructed hydrological model is based on the state of the knowledge of hydrogeological conditions in the study area. Recently it was used (by Geological Survey of Slovenia) for groundwater residence time simulations and new delineation of production well catchment areas into protection zones which were implemented in Decree on determining the drinking water protection area for the aquifer of Ljubljansko polje (OG RS, 2015).
- The full form DSS for emergency response to groundwater resource pollution has been used only for the study case scenarios. Luckily no real threatening pollution has occurred after the construction of DSS, but the system and the team of experts of Geological Survey of Slovenia and Vodovod-kanalizacija, a public company for water supply are prepared to use it also in real case scenarios.
The tool is specific to the city of Ljubljana, however, dependent of the city drivers and data availability. As yet, there are no knowledge exchange pathways being developed for other cities to replicate the work, as national tool for city regions. This upscaling of the knowledge and data exchange pathway is the critical next step for Slovenia as in many other countries worldwide, where there are multiple cities with examples of good practice of knowledge translation (see table below) but very few, if any, have transferred and developed these to cities nationally.
Other examples of good practice of integration of groundwater information into decision making for groundwater management:
|Hydrogeological information/tools/methods||City/region (references)|
interpretation and adaptation of
|LOW||Monitoring/Measured data (GW levels, temperature, chemical parameters, hydraulic conductivity, transmissivity…)||database accessible through a web viewer: Amsterdam|
The Hague (https://wareco-denhaag-public.munisense.net/
|Hydrogeological maps/conceptual models/3D models||Bucharest (Serpescu et al., 2015)|
Glasgow (Turner et al., 2014)
Ljubljana (Janža 2009)
Netherlands (Gunnink et al., 2013)
|Numerical GW flow/heat-transport models||Bucharest (Boukhemacha et al., 2015)|
Glasgow (Turner et al., 2014)
Hamburg (Taugs et al., 2014)
Ljubljana (Janža et al., 2011b)
|Vulnerability maps||Ljubljana (Bračič-Železnik et al. 2005)|
Sierra de Canete (Jiménez-Madrid et al., 2012)
|Geothermal potential maps||Barcelona (García-Gil et al., 2015)|
Basel (Epting and Huggenberger, 2013></ref>)
Berlin (Kastner et al., 2013)
Ludwigsburg (Schiel et al., 2016)
|GW contamination risk maps||Multicriteria analysis method: Canada|
(Lavoie et al. 2015)
|Regulations based on zoning (e.g. GW protection zones)||Methodology: Slovenia (Brenčič et al. 2009)|
Spain (Jiménez-Madrid et al., 2012)
Switzerland (BUWAL, 2004)
UK (Carey et al. 2009)
|HIGH||Decision support tools (e.g. computer tools integrating numerical models||DSS for emergency response to groundwater resource pollution: Ljubljana (Janža 2015)|
DSS for land-use planning:
Monroe County, Michigan (Reeves and Zellner 2010)
Critical knowledge and technical capacity which limit communication and understanding of urban above and below ground resources and interaction in city planning include:
|ID||Current State||Desired State||Gap Description||Gap Reason||Remedies|
|1||scientific input (subsurface information) is often not included within decision making/planning processes.||decision makers/planners use up to date (state-of-the-art) information and knowledge available — and scientists have up to date knowledge of policy needs.||procedures (guidance) for use of subsurface information in planning are not well defined, and lack of awareness of available information.||critical information is not presented in a usable form and is therefore not available or accessible to them.||better communication between different specialists, multidisciplinary working groups, DSS tools.|
|2||Critical knowledge and communication gap between scientists and planning.||Strong two-way communication between both parties, to mutually inform.||Lack of awareness of shared needs and knowledge between the two disciplines, and of the existing data and knowledge within each.||Disciplines have historically worked independently of each other.||Establishment of cross-discipline working groups to discuss on going work within a city, and shared knowledge needs and knowledge/data assests.|
- Rayner, S, Lach, D, and Ingram, H. 2005. Weather Forecasts are for Wimps: Why Water Resource Managers Do Not Use Climate Forecasts. Climatic Change 69 (2–3):197–227. doi:10.1007/s10584-005-3148-z
- Martinez-Santos, P, Llamas, M R, and Martinez-Alfaro, P E. 2008. Vulnerability assessment of groundwater resources: A modelling-based approach to the Mancha Occidental aquifer, Spain. Environ Modell Softw 23 (9):1145–1162. doi:http://dx.doi.org/10.1016/j.envsoft.2007.12.003
- Liu, Y, Gupta, H, Springer, E, and Wagener, T. 2008. Linking science with environmental decision making: Experiences from an integrated modeling approach to supporting sustainable water resources management. Environ Modell Softw 23 (7):846–858. doi:http://dx.doi.org/10.1016/j.envsoft.2007.10.007
- Molina, J-L, García-Aróstegui, J, Bromley, J, and Benavente, J. 2011. Integrated Assessment of the European WFD Implementation in Extremely Overexploited Aquifers Through Participatory Modelling. Water Resour Manag 25 (13):3343–3370. doi:10.1007/s11269-011-9859-1
- Lavoie, R, Lebel, A, Joerin, F, and Rodriguez, M J. 2013. Integration of groundwater information into decision making for regional planning: A portrait for North. J Environ Manage 114:496–504. doi: 10.1016/j.jenvman.2012.10.056
- Glasgow City Council. 2012. City Development Plan, Resource Management 2012–2017.
- UN. 2012. World Urbanization Prospects, the 2011 Revision: Highlights. United Nations, Department of Economic and Social Affairs, Population Division, New York.
- Janža, M. 2015. A decision support system for emergency response to groundwater resource pollution in an urban area (Ljubljana, Slovenia). Environ Earth Sci 73:3763–3774. doi: 10.1007/s12665-014-3662-2
- Lavoie, R, Joerin, F, Vansnick, J-C, and Rodriguez, M J. 2015. Integrating groundwater into land planning: A risk assessment methodology. J Environ Manage 154:358–371. doi: 10.1016/j.jenvman.2015.02.020
- Graham, D N, and Butts, M B. 2005. Flexible, integrated watershed, modelling with MIKE SHE. In: Singh, V P, and Frevert, D K (eds) Watershed Models. CRC Press, Boca Raton, pp.245–272.
- DHI. 2011a. MIKE 1D, DHI Simulation Engine for MOUSE and MIKE 11, Reference Manual.DHI, Horsholm.
- DHI. 2011b. MIKE SHE User Manual Volume 2: Reference Guide. DHI, Horsholm.
- OG RS. 2015. Decree on determining the drinking water protection area for the aquifer of Ljubljansko polje. Official Gazette of the Republic of Slovenia, no.43/15.
- Serpescu, I, Gogu, C R, Boukhemacha, M A, Gaitanaru, D. 2015: 3D geological model to support the management of urban subsurface environment: Bucharest City case study. 8th European Congress on Regional Geoscientific Cartography and Information Systems (EUREGEO), Barcelona
- Turner, R J, Mansour, M M, Dearden, R, Ó Dochartaigh, B É, and Hughes, A G. 2014. Improved understanding of groundwater flow in complex superficial deposits using three-dimensional geological-framework and groundwater models: an example from Glasgow, Scotland (UK). Hydrogeol. J. 493–506. doi:10.1007/s10040-014-1207-0
- Janža, M. 2009. Modeliranje heterogenosti vodonosnika Ljubljanskega polja z uporabo Markovih verig in geostatistike. 233–240.
- Gunnink, J L, Maljers, D, Gessel, S F, Van, Menkovic, A, and Hummelman, H J. 2013. Digital Geological Model (DGM): a 3D raster model of the subsurface of the Netherlands. Netherlands J. Geosci. 92, 33–46. doi:10.1017/ S0016774600000263
- Taugs, R, Moosmann, L, Classen, N, and Meyer, P. 2014. Groundwater monitoring and modelling of the urban groundwater system of Hamburg: Sub-Urban/WG1: Case study of Hamburg.
- Janža, M, Meglič, P, Šram, D, and Slovenia, G S of (2011b) Numerical hydrological modelling (project INCOME action report). Geological Survey of Slovenia, Ljubljana.
- Unraveling the heat island effect observed in urban groundwater bodies — Definition of a potential natural state. J. Hydrol. 501, 193–204. doi:10.1016/j.jhydrol.2013.08.002
- García-Gil, A, Vázquez-Suñe, E, Schneider, E G, Sánchez-Navarro, J Á, and Mateo-Lázaro, J. 2014. The thermal consequences of river-level variations in an urban groundwater body highly affected by groundwater heat pumps. Sci. Total Environ. 485–486, 575–87. doi:10.1016/j.scitotenv.2014.03.123
- Bračič-Železnik, B, Frantar, P, Janža, M, and Uhan, J. 2005. Groundwater vulnerability. In: Rejec Brancelj I, Smrekar A, Kladnik D (eds) Groundwater of Ljubljansko polje. Založba ZRC, Ljubljana, pp.61–72.
- Jiménez-Madrid, A, Carrasco-Cantos, F, Martínez-Navarrete, C. 2012. Protection of groundwater intended for human consumption: A proposed methodology for defining safeguard zones. Environ Earth Sci 65, 2391–2406. doi:10.1007/s12665-011-1494-x
- García-Gil, A, Vázquez-Suñe, E, Alcaraz, M M, Juan, A S, Sánchez-Navarro, J Á, Montlleó, M, Rodríguez, G, and Lao, J. 2015. GIS-supported mapping of low-temperature geothermal potential taking groundwater flow into account. Renew. Energy 77, 268–278. doi:10.1016/j.renene.2014.11.096
- Kastner, O, Sippel, J, Scheck-Wenderoth, M, and Huenges, E. 2013. The deep geothermal potential of the Berlin area. Environ Earth Sci 70, 3567–3584. doi:10.1007/s12665-013-2670-y
- Schiel, K, Baume, O, Caruso, G, and Leopold, U. 2016. GIS-based modelling of shallow geothermal energy potential for CO2 emission mitigation in urban areas. Renew. Energy 86, 1023–1036. doi:10.1016/j.renene.2015.09.017
- Brenčič, M, Prestor, J, and Kompare, B, et al. 2009. Integrated approach to delineation of drinking waterprotection zones. Geologija 52:175–182. doi: 10.5474/geologija.2009.017
- BUWAL, 2004. Wegleitung Grundwasserschutz. Bern.
- Carey, M, Hayes, P, Renne, A, and Agency, E. 2009. Groundwater Source Protection Zones –Review of Methods. Environment Agency, Bristol.