Local-scale maps of the NSGE potential in the Case Study areas
Local-scale maps of the NSGE potential in the Case Study areas
Deliverable D.4.2.1 – Local-scale maps of the NSGE potential in the Case Study areas
16/12/2015 – 01/06/2018: The deliverable will present the work carried out in each Case Study by the relevant project partners, and it will be the input for WPT4 to implement the Near-Surface Geothermal Energy in the energy planning procedures.
Version: Revision 02, 04 September 2018 This document is the third deliverable of the Work Package 4 (or WPT3 according to the EmS numbering of WPs) “Assessment and mapping of the potential of Near-Surface Geothermal Energy (NSGE)”. Politecnico di Torino (POLITO), as responsible partner in the WP4, elaborated this report with the contribution from the involved project partners: TUM, EURAC, ARPA Valle d’Aosta, GeoZS, BRGM, GBA, University of Basel.
This deliverable focuses on the local-scale mapping of the NSGE closed-loop potential (Borehole Heat Exchangers, BHEs) and open-loop potential (Groundwater Heat Pumps, GWHPs) in 6 case-study areas. Among the various existing mapping methods, the G.POT method developed by POLITO was chosen for closed-loop potential while, for open-loop, a method was developed by TUM in collaboration with POLITO and ARPA VdA. The common outputs are closed- and open-loop maps of geothermal potential expressed in MWh/y. Regarding the open-loop potential, maps of technical volume flow potential (l/s) and power (kW) were also realised. All maps in this document are available and downloadable as raster files (tiff), contained in zipped folders, at: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/.
This report serves as a reference guide for the methodology applied, as well as for a better understanding of the outputs of NSGE potential assessment. It is meant to help installers, designers, and public authorities involved in the design, approval and installation of NSGE systems.
GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. Send us an email at [email protected] and see more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
TABLE OF CONTENTS
1 Introduction ...... 5 1.1 Partner´s involvement ...... 6 1.2 Acronyms and definitions referring to NSGE ...... 6 2 Literature review on near-surface geothermal potential assessment methods ...... 7 2.1 Tables of extractable thermal power (BHEs, SHCs) ...... 7 2.1.1 VDI 4640 (BHEs) ...... 7 2.1.2 MIS 3005 (BHEs, SHCs) ...... 11 2.2 Exploitation of Urban Heat Island (GWHPs) ...... 13 2.3 Qualitative methods for the evaluation of shallow geothermal potential (BHEs) ...... 14 2.3.1 Geothermal potential of the province of Treviso (Veneto, NW Italy) ...... 14 2.4 The G.POT (Geothermal POTential) method (BHEs) ...... 15 2.5 Density of closed-loop geothermal systems (BHEs) ...... 16 2.5.1 The Westminster (London) case study (Zheng et alii, 2015) ...... 16 2.5.2 The Barcelona case study (Garcìa-Gil et alii, 2015) ...... 17 2.6 Qualitative open-loop geothermal potential evaluation methods ...... 18 2.6.1 BRGM multi-criteria weighted score systems ...... 19 2.7 Maximum thermal power to be installed in a GWHP ...... 21 2.7.1 The Barcelona case study (Garcìa-Gil et alii, 2015) ...... 21 2.7.2 The Cuneo case study (Casasso and Sethi, 2017) ...... 22 3 Methods adopted for the geothermal potential estimation in the case study areas ...... 25 3.1 Closed loop: G.POT ...... 25 3.1.1 Mathematical method ...... 25 3.1.2 Common modelling assumption and input parameter sets adopted ...... 26 3.1.3 Economic impact of closed-loop geothermal potential ...... 27 3.2 Open loop: assessment of technically feasible flow rates ...... 29 3.3 Access to the geothermal potential maps of the project ...... 31 4 NSGE mapping in Aosta Valley (Italy) ...... 32 4.1 The territory surveyed ...... 32 4.1.1 Existing geothermal installations ...... 32
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4.1.2 Geological setting ...... 33 4.1.3 Hydrogeological setting of the Aosta plain ...... 34 4.2 Closed-loop geothermal potential ...... 39 4.2.1 Thermal properties of the ground ...... 39 4.2.2 Ground temperature ...... 41 4.2.3 Length of the heating season ...... 42 4.2.4 Results ...... 44 4.2.5 Comparison of G.POT with other closed-loop potential mapping methods ...... 45 4.3 Open-loop geothermal potential ...... 46 4.3.1 Methodological remarks ...... 46 4.3.2 Results ...... 47 4.4 Conclusions ...... 51 5 NSGE mapping in Cerkno (Slovenia) ...... 52 5.1 The territory surveyed ...... 52 5.1.1 Geological and hydrogeological setting ...... 55 5.1.2 Existing geothermal installations ...... 56 5.2 Closed-loop geothermal potential ...... 57 5.2.1 Thermal properties of the ground ...... 57 5.2.2 Ground temperature ...... 61 5.2.3 Length of the heating season ...... 63 5.2.4 Results ...... 67 5.3 Conclusions ...... 69 6 NSGE mapping in Oberallgäu (Germany) ...... 70 6.1 The territory surveyed ...... 71 6.1.1 Geological setting ...... 71 6.1.2 Hydrogeological setting ...... 73 6.2 Open-loop geothermal potential ...... 77 6.3 Conclusions ...... 84 7 NSGE mapping in Parc des Bauges (France) ...... 85 7.1 The territory surveyed ...... 85 7.1.1 Geological setting ...... 85 7.1.2 Hydrogeological setting ...... 86
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7.2 Closed-loop geothermal potential ...... 91 7.2.1 Thermal properties of the ground ...... 91 7.2.2 Ground temperature ...... 95 7.2.3 Length of heating season ...... 97 7.2.4 Results ...... 99 7.3 Open-loop geothermal potential ...... 101 7.4 Conclusions ...... 106 8 NSGE mapping in Saalbach-Leogang (Austria) ...... 108 8.1 The territory surveyed ...... 108 8.1.1 Geological and hydrogeological setting ...... 108 8.2 Closed-loop geothermal potential ...... 110 8.2.1 Thermal properties of the ground ...... 110 8.2.2 Ground temperature ...... 112 8.2.3 Length of the heating season ...... 116 8.2.4 Results ...... 118 8.3 Open-loop geothermal potential ...... 120 8.3.1 Hydrogeological setting and open-loop potential of Leogang ...... 120 8.3.2 Hydrogeological setting and open-loop potential of Saalbach-Hinterglemm ...... 124 8.4 Conclusions ...... 128 9 NSGE mapping in Davos (Switzerland) ...... 129 10 Conclusions ...... 134 References ...... 135
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1 Introduction
This deliverable focuses on the local-scale mapping of the Near-Surface Geothermal Energy (NSGE) potential of Borehole Heat Exchangers (BHEs) and Ground Water Heat Pumps (GWHPs) in 6 case study areas, one for each project partners’ country.
Possible negative interferences and legal constraints, as highlighted in the Deliverable 4.1.1 (https://goo.gl/gEud2m), limit the possibility to use NSGE [1]. In addition, the technical and economic feasibility of NSGE systems strongly depends on the local environmental conditions, in particular ground thermal properties (for BHEs) and aquifer hydrogeological properties (for GWHPs). This document is meant to help the reader to better understand the NSGE applicability and limitations depending on the local climatic, geological and hydrogeological features.
The deliverable is structured as follows. Chapter 2 reports a literature review of the existing geothermal potential assessment methods, finding common features, limitations, strengths and weaknesses. Chapter 3 describes the methods adopted for the assessment of closed-loop and open- loop geothermal potential. The other 6 Chapters report the application of the two methods is carried out to assess the near-surface geothermal potential in the 6 pilot areas: Valle d’Aosta (Italy, Chapter 4), Cerkno (Slovenia, Chapter 5), Oberallgäu (Germany, Chapter 6), Parc des Bauges (France, Chapter 7), Saalbach-Leogang (Austria, Chapter 8), and Davos (Switzerland, Chapter 9).
The results of the potential assessment are displayed both in this document and in a downloadable zipped folder at https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/
Table 1: The six pilot areas of the Alpine Space.
Country Pilot area Closed loop potential Open loop potential Italy Aosta valley Entire valley, <2000 m a.s.l. Portion of the Aosta plain Slovenia Cerkno Entire municipality NO (no aquifer present) Germany Oberallgäu Already mapped in Bayern Upper Iller valley with VDI 4640 method (https://goo.gl/ga85qs) France Parc des Bauges 4 municipalities of the park Isère valley bottom between Pontcharra and Gilly-sur-Isère Austria Saalbach/Leogang Both municipalities Saalbach and Leogang valley bottoms Switzerland Davos NO Assessed for a specific utilisation (sport and congress centre)
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1.1 Partner´s involvement
No. Partner Contact E-mail Kai Zosseder [email protected] 1 TUM
Fabian Böttcher [email protected] Pietro Capodaglio [email protected] 2 ARPA VdA Alessandro Baietto [email protected] Magdalena Bottig [email protected] Stefan Hoyer [email protected] 3 GBA Doris Rupprecht [email protected] Gregor Götzl [email protected] Joerg Prestor [email protected] 4 GeoZS
Simona Pestotnik [email protected] Charles Maragna [email protected] 5 BRGM Charles Cartannaz [email protected] Alessandro Casasso [email protected] Rajandrea Sethi [email protected] Alberto Tiraferri [email protected] 6 POLITO Simone Della Valentina [email protected] Arianna Bucci [email protected] Tiziana Tosco [email protected] Pietro Zambelli [email protected] 7 EURAC Chiara Scaramuzzino [email protected] Andrea Vianello [email protected]
8 Uni Basel Peter Huggenberger [email protected]
1.2 Acronyms and definitions referring to NSGE AS: Alpine Space BHE: Borehole Heat Exchanger DHW: Domestic Hot Water FLEH (or FLEQ): Full Load Equivalent hours GSHP: Ground Source Heat Pump GWHP: Ground Water Heat Pump NSGE: Near Surface Geothermal Energy UHI: Urban Heat Island
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2 Literature review on near-surface geothermal potential assessment methods
Geothermal potential is a concept which was first developed for medium and high-enthalpy geothermal resources, i.e. for direct uses and for electricity production. Different definitions are available but, generally speaking, the geothermal potential is the thermal power which can sustainably be abstracted from a reservoir for a long time. The reservoir has a limited extent, and the potential is estimated considering it as a whole.
For low-enthalpy geothermal resources, such a definition of geothermal potential is generally not valid, since the possible supply of heat should meet an on-site demand (i.e. a building), otherwise it will never be exploited. This is a completely different condition compared to the production of electricity, which can be performed in remote areas and transported to users across long distances; to a lesser extent, heat-demanding productions can be installed in geothermal areas to exploit low-cost heat (e.g. a large number of greenhouses, dairy processing activities, breweries are located in the geothermal areas of Larderello and Monte Amiata).
For these reasons, the definitions of “shallow” or “near-surface” geothermal potential usually focused on other aspects such as:
- the economic convenience of geothermal exploitation, e.g. the meters of boreholes to be drilled to satisfy a certain heat demand; - the sustainable density of shallow geothermal installations in urban areas; - the maximum flow rate to be abstracted and reinjected into an aquifer.
This section gives a brief summary of some existing methods for the mapping of near-surface geothermal potential. For each method, we specify whether it can be applied to Borehole Heat Exchangers (BHEs), Groundwater Heat Pumps (GWHPs), Shallow Geothermal Collectors (SHCs). 2.1 Tables of extractable thermal power (BHEs, SHCs) The first methods to be used to determine the shallow geothermal potential are “rule-of-thumb” tables of extractable thermal power per unit length of borehole (W/m). Although these methods were developed for the design of small installations (e.g., below 30 kW according to VDI 4640 [2]), they have also been applied in several shallow geothermal potential mapping projects. Three methods are hereby described: the German standard VDI 4640 with its first version delivered in 2000 [2] and an update in 2015 [3], and the British standard MIS 3005 (2011, [4]).
Unlike the other methods which will be presented in next paragraphs of this chapter, these are design methods which could be applied also for mapping purposes.
2.1.1 VDI 4640 (BHEs) VDI 4640 is a norm developed by the VDI (Verein Deutsche Ingenieure, German Union of the Engineers) to provide a guideline for shallow geothermal installations. Its first version was released in 2000, and the norm is updated every 5 years; the last version was therefore published in 2015. The objective of
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VDI 4640 is to gather in one document the environmental aspects, the feasibility and applicability requisites and the technological aspects.
The norm provides some methods for the design of small BHE fields. According to VDI 4640, BHE fields below 30 kW of thermal power can be sized based on the lithology and on the yearly hours of operation of the plant. The table reported in Figure 1 shows the values of thermal power per unit length (W/m) which can be extracted from the ground considering an operating schedule of 1800 hours and 2400 hours per year. This parameter is also expressed as FLEQ (Full Load EQuivalent) or FLEH (Full Load Equivalent Hours) as it relates the peak power [5] and the heating/cooling need (kWh/year). The shortest operating schedule (1800 hours/year or FLEH) is typical of mild climates (e.g. around 2000 HDD according to ASHRAE or Eurostat), while 2400 hours/year are typical of quite a cold climate (e.g. around 3000 HDD according to ASHRAE or Eurostat).
Let us report an example of sizing procedure, which can also be applied for the MIS 3005 method explained in next paragraph. A single house has a heat demand of 15000 kWh/year and an operating 푘푊ℎ 15000 푦푒푎푟 schedule of 1800 hours/year. Consequently, the power to be installed is ℎ = 8333 푊. For a 1800 푦푒푎푟 8333 푊 dry sediment, the specific heat extraction is of 25 W/m; the length of BHEs to be installed is 푊 = 25 푚 333푚. For normal lithologies, the specific heat extraction is 60 W/m, and hence the BHE length to be 8333 푊 8333 푊 installed is 푊 = 138푚. For highly conductive lithologies (84 W/m), the installed length is 푊 = 60 84 푚 푚 99푚.
Figure 1: Values of extractable specific heat for BHE unit length from VDI 4640 (2000) [2].
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An update of VDI 4640 sizing table was delivered in 2015 [3] and is reported in Figure 2. The VDI (2015) [3] contains several tables of maximum extractable power for BHE unit length, according to two main criteria:
- the use of heat for combination of heating and domestic hot water or for heating-only mode; - the temperature at the outlet of the heat pump.
Another noticeable difference with the 2000 version is the absence of lithologies, which have been replaced by thermal conductivity values. Also, precise values of specific heat extraction are provided, instead of the wide ranges of the previous version: these values have been derived through simulations with Earth Energy Designer (EED) [6]. Different values are provided depending on the number of BHEs (“Anzahl Sonden” in the table) to consider the interference among neighbouring boreholes. Linear interpolation is suggested for intermediate values of thermal conductivity and/or number of hours/year of operation.
Figure 2: Values of extractable specific heat for BHE unit length from VDI 4640 (2015) [3].
The VDI 4640 method, in its first version (2000, [7]), was adopted in a number of NSGE potential mapping methods. Ondreka et alii (2007, [8]) adopted for the mapping of shallow geothermal potential in South-Western Germany. They calculated depth-average values of specific heat extraction, based on the ground stratigraphy, and delivered maps of thermal power for a 50m and 100m-deep borehole, as shown in Figure 3. Gemelli et alii (2011, [9]) applied the VDI 4640 method for the assessment and mapping of closed-loop NSGE potential in the Marche region (Central Italy). They derived the depth of
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BHE to be installed to cover a typical heat demand of a detached house and, based on such depth, they estimated the cost and the payback time of a closed-loop geothermal heat pump, compared to a gas boiler.
Figure 3: Closed-loop NSGE potential in SW Germany, close to the Black Forest. The maps report the thermal power for a 50m and 100m-deep BHE. Source: Ondreka et alii, 2007 [8].
Figure 4: Closed-loop NSGE potential in the Marche region (Central Italy). The map reports the extractable power per unit depth (W/m). Source: Gemelli et alii, 2011 [9].
Regione Lombardia delivered a geo-energetic map of its territory based on the VDI 4640 method, which is available at https://goo.gl/aRUZz9 and is reported in Figure 5.
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Figure 5: Closed-loop NSGE potential in Regione Lombardia (Northern Italy), available at https://goo.gl/aRUZz9 .
The application of VDI 4640, both in its year 2000 and year 2015 version, has a major limitation: the undisturbed ground temperature is not taken into account, thus providing the same specific heat extraction value for a warm ground in the plain (e.g., at 14°C) and a cold ground in the mountains (e.g., 8°C). Such a limitation is overcome by the MIS 3005 method [4], described in next paragraph.
2.1.2 MIS 3005 (BHEs, SHCs) This method is provided by the Department of Energy and Climate Change of Great Britain to assess the geothermal potential of BHEs using tables of extractable power. The input parameters are: duration of the heating cycle, thermal conductivity and soil temperature [4]. The tables are divided by type of system (borehole, horizontal, and slinky heat exchanger) and by duration of the heating cycle (1200, 1800, 2400, 3000, and 3600 hours/year). We hereby report, as a comparison, the tables for 1800 hours/year (Figure 6) and 2400 hours/year (Figure 7). The values of specific heat extraction (W/m) are sorted in rows based on the thermal conductivity of the ground, and in columns based on ground temperature. The upper part of the table reports the hypotheses of the model related to the operation mode (heating only+DHW), the technical and thermal characteristics of the probe, the vector fluid, the ground and the tube [10].
Compared to the VDI 4640 method, the MIS 3005 tables are more flexible since they allow to take the ground temperature into account. The data shown highlight the importance of the underground temperature for the determination of the extractable power.
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Figure 6: Evaluation table for the maximum extractable power for length unit of a BHE for 1800 FLEQ (Full Load Equivalent) running hours [4].
Figure 7: Evaluation table for the maximum extractable power for length unit of a BHE for 2400 FLEQ (Full Load Equivalent) running hours [4].
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2.2 Exploitation of Urban Heat Island (GWHPs) The ground temperature in urban areas is usually higher than the outskirts, due to the presence of many heat inputs. A number of studies has already been published to quantify the subsurface Urban Heat Island (UHI), and to assess the contribution of different heat sources (heat transmission from buildings, sewers, heat absorbed by paved surfaces etc.) [11-16].
Figure 8: Subsurface UHI in Cologne, Germany (left) and Winnipeg, Canada (right) Source: Zhou et alii, 2010 [16].
The UHI is an environmental issue, as it contributes to increase energy consumption for building cooling and may have health impacts. However, the subsurface UHI can also be considered as an opportunity to exploit the higher aquifer temperatures for heating with GWHPs. In this light, Zhou et alii (2010, [16]) define the geothermal potential as the quantity of heat which can be abstracted from a certain aquifer volume (퐴 · 푑) through a temperature reduction Δ푇:
푄 = 퐴 ∙ 푑 · [푛퐶푤 + (1 − 푛) ∙ 퐶푠 ∙] · ∆푇
Equation 1
2 where 퐴 is the aquifer surface (m ) and 푑 is its depth (m), 푛 is the porosity, 퐶푤 and 퐶푠 are the thermal capacity (Jm-3K-1) of the fluid and solid fractions, respectively. According to the estimates reported in the paper, the geothermal potential of the UHI in Cologne (Germany) and Winnipeg (Canada) shown in Figure 8 exceed the heating demand of these cities.
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2.3 Qualitative methods for the evaluation of shallow geothermal potential (BHEs)
2.3.1 Geothermal potential of the province of Treviso (Veneto, NW Italy) A geothermal potential map of the province of Treviso has been provided by University of Padova and the Province administration of Treviso in Veneto, NW Italy [17]. A qualitative criterion was developed, based on thermal conductivity, temperature gradient, and shallow groundwater velocity. The output is a map of the geo-exchange potential. Furthermore, water protection areas have been added to the final map of suitability for the geo-exchange (Figure 9). The document is available at the following link: https://goo.gl/sXSwbG.
Figure 9: Closed-loop NSGE potential map of the Province of Treviso (Veneto, NW Italy). Source: Busoni et alii, 2012 [17].
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2.4 The G.POT (Geothermal POTential) method (BHEs) The G.POT method was developed by Casasso and Sethi in 2016 (Ref. [18]) to estimate the geothermal potential of BHEs, either for heating and cooling. The G.POT method assumes that the application of a cyclic sinusoidal thermal load induces a time-varying thermal alteration of the ground, thus reaching a threshold fluid temperature (minimum or maximum, depending on the use). Since the thermal alteration of the ground is directly proportional to the thermal load exchanged with the ground, the difference between the initial ground temperature and the fluid temperature limit determines the thermal load (geothermal potential) which can sustainably be exchanged by a BHE with a certain length.
The G.POT method was first applied to the territory of the province of Cuneo, as described in Casasso and Sethi (2017, [19]). The depth of evaluation is 100m, i.e. a typical BHE depth. The geothermal potential ranges between 5 and 12 MWh/year, as shown in Figure 10.
Since this method has been adopted for this deliverable, we do not report here the mathematical details and the formulae. Further information is available in Section 3.1 and at https://areeweb.polito.it/ricerca/groundwater/research/shallow-geothermal-energy/gpot/
Figure 10: Closed-loop NSGE potential in the Cuneo province. Source: Ref. [19].
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2.5 Density of closed-loop geothermal systems (BHEs) The studies described above mostly refer to the thermal power per meter length, or per each borehole, which can be abstracted and/or injected into the ground. However, the installation of multiple BHEs need to be installed at a certain distance to minimize their reciprocal thermal interference. For example, Haehnlein et al (2010, [20]) report that European regulations prescribe minimum distances of 3 to 15 m, with most of values in the range 5-7 m. In this section some literature methods are described which provide indications on the geothermal potential assessment according to the density of BHEs. The two methods cited are implemented for urban areas, which more likely undergo issues of high density of geothermal installations.
2.5.1 The Westminster (London) case study (Zheng et alii, 2015) Zheng et al. ([21] and [7]) developed an ArcGIS-based simulation model with embedded GSHP design code to estimate the geothermal potential and to evaluate the allowed GSHP capacity with the land use restrictions for the City of Westminster, London.
The heating demand is first estimated, based on building data, deriving the peak hourly and monthly loads, and the average thermal load.
BHEs are then sized with the ASHRAE method:
푞푎푅푔푎 + (푞푙ℎ − 푊ℎ) · (푅푏푃퐿퐹푚푅푔푚 + 푅푔푑퐹푠푐 ) 퐿ℎ = 푡 + 푡 푡 − 푤푖 푤표 − 푡 푔 푠 푝
Equation 2 where 퐹푠푐 the short-circuit heat loss factor, 푃퐿퐹푚 is the part-load factor during design month, 푞푎 is the net annual average heat transfer to the ground (W), 푞푙ℎ is the building design heating block load (W), 푅푔푎 is the effective thermal resistance of the ground in annual pulse (m K/W), 푅푔푑 is the effective thermal resistance of the ground in daily pulse (m K/W), 푅푔푚 is the effective thermal resistance of the ground in monthly pulse (m K/W), 푅푏 is the thermal resistance of borehole(m K/W), 푡푔 is the undisturbed ground temperature (K), 푡푝 is the temperature penalty for interference of adjacent boreholes (K), 푡푤푖is the liquid temperature at heat pump inlet (K), 푡푤표 is the liquid temperature at heat pump outlet (K), 푊ℎ is the power input at design heating load (W). The relevance of this method consists of introducing the temperature penalty 푡푝 which takes into account the effect of adjacent BHEs.
Considering a maximum depth, the number of BHEs to be installed is then derived. Each BHE occupies 30 m2 of space and, hence, the available space constrains the capacity to demand (퐶/퐷) ratio, i.e. the share of heating demand which could be covered by BHEs. This share can vary depending on the thermal load considered, i.e. the annual load, the peak monthly or the peak hourly load. This means that a backup boiler can be foreseen to cover the remaining thermal load, which cannot be covered by the NSGE system due to the lack of space for BHEs.
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Figure 11: Closed-loop NSGE potential in Westminster (London), expressed as capacity to demand (C/D) ratio to cover the annual heating demand (a) and the peak hourly thermal load (b) of buildings. Source: Zhang et alii, 2015 [7].
2.5.2 The Barcelona case study (Garcìa-Gil et alii, 2015) García-Gil et al. [22] developed another GIS-based method, which involves the two main heat transport mechanisms, advection and conduction. They provide equations to calculate both open-loop and closed-loop potential, resumed by the expression Low-temperature Geothermal Potential (LTGP). The closed-loop geothermal potential is divided into:
- Saturated zone potential, calculated by means of a steady-state analytical solution obtained from the conduction-advection for heat transfer in porous media equation: 2 2 푞푙 푈푥 푈√푥 + 푦 ∆T(x, y) = exp ( ) 퐾 ( ) 2πK 2푎 0 2푎
Equation 3
Where ∆T is the increase in temperature in the x and y horizontal directions; 푞푙 is the heating rate per length of the heat source; K is the thermal conductivity; 퐾0(푧) is the modified Bessel 푘 function of the second kind of order zero; 푎 = is the effective thermal diffusivity and 푈 = 휌퐶 푢푐 휌 푤 푤 is the revised velocity that takes into account the advection velocity 푢, the volumetric 휌퐶
specific heat of water 푐푤휌푤 and the volumetric specific heat of the porous medium 휌퐶 , including both the solid matrix and water in its pores. - Unsaturated zone (or low hydraulic conductivity) potential, calculated by means of a transient solution for the equation of 2-D heat transport in solids with a heating rate along a line perpendicular to the x and y plane:
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2 2 푞푙 4푎푡 푈√푥 + 푦 ΔT(r, t) = ln (( ) ) 2πK 푟2 2푎
Equation 4
Based on a Δ푇 limit of 10°C at the borehole wall (in this paper, 푟 = 0.1푚), the authors calculated the thermal power per unit length 푞푙 (W/m) which can be abstracted by a BHE in the different layers (saturated or unsaturated) which could be crossed by a BHE, which was set equal to 100m. The integral of these values, calculated over the BHE depth of 100m, is the power per BHE which can be exchanged with the ground:
푛 푧푖 · 푞푙푖 퐿퐺푇푃푐푙표푠푒푑 푙표표푝 = ∑ 퐴푝푙푢푚푒 푖=1 𝑖
Equation 5 where 푞푙푖 (W/m) is the thermal power per unit length of the i-th layer, 푧푖 (m) is the layer depth, and 2 퐴푝푙푢푚푒𝑖 (m ) is the plume area in the i-th layer, i.e. the area of the isotherm of 1°C of thermal alteration.
The resulting map is shown in Figure 12 and highlights an extreme variability of the value of LTGP, with values ranging from 3 to 52000 W/m2, mainly correlated to the groundwater velocity. However, the difficulty to get a reliable map of groundwater velocities makes it difficult to map the LTGP with an acceptable precision.
Figure 12: Closed-loop NSGE potential in the area of Barcelona (100m depth). Source: Garcìa-Gil et alii, 2015 [22]. 2.6 Qualitative open-loop geothermal potential evaluation methods 18/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
2.6.1 BRGM multi-criteria weighted score systems The BRGM (the French Geological Service) developed a decision-aid tool for evaluating the very low geothermal energy exploitability of aquifers [23]. The tool is based on an atlas of groundwater resources found within 100 m of depth which are suitable for low enthalpy geothermal use. The atlas consists of a WebGIS tool available at: http://www.geothermie-perspectives.fr/
Since the maps were compiled at 1:50,000 scale, their accuracy is region-wise and their use is not recommendable at project scale, for which detailed site investigations are always required.
The general design principle is a method of index mapping with a weighting criterion. This means that a combination of various parameter (or criterion) maps is used to assess a regional property (here, the geothermal potential of the aquifers) by assigning a numerical index to each parameter. The procedure of multi-criteria processing is performed in GIS environment.
The following four criteria are proposed:
- Productivity of the aquifer or exploitable yield; - Water temperature; - Depth of access to water; - Water quality. The first two criteria are representative of the aquifer’s production yield for geothermal use; the other two criteria are economic-based, since they directly impact a project’s capital and running costs. Each of the four criteria is assigned a score from 1 to 5, where high values mean high potential and vice versa. An example of classification and indexing of three on the four criteria is reported in Table 2.
Table 2: Classification and indexing of the geothermal potential criteria according to Bezelgues et al. [23].
Geothermal potential criterion Criterion classification Indexing Aquifer productivity (Q) < 5 m3/h 1 5-10 m3/h 2 10-50 m3/h 3 50-100 m3/h 4 > 100 m3/h 5 Resource temperature (T) < 10 °C 2 10-15 °C 5 > 15 °C 3 Depth of access to the resource < 5 m 1 5-15 m 2 15-30 m 3 30-100 m 4 > 100 m 5
The water quality criterion takes into account those chemical-physical parameters of water that may affect the use of a heat pump coupled with groundwater because of corrosive power and
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encrusting/plugging capacity: hardness, Eh, pH, electric conductivity, etc. Each physical-chemical parameter is weighted on a qualitative base: good, mediocre, poor, unsuitable.
An index of geothermal potential is calculated by weighted addition of the single criterion potentiality notes assigned to each mesh of the calculation grid. A potentiality index distribution map is then drawn up; this corresponds to the geothermal potential map of the aquifer. The mesh for calculation is 50 m- wide, corresponding to the above mentioned 1: 50,000 scale.
The final output of the method is the atlas of geothermal potential, which is made up of set of thematic maps and a synoptic map of each shallow aquifer of regional interest, as well as a general synthetic map of the regional geothermal potential which corresponds to a compilation of the best potentialities per aquifer. An example for the Franche-Comté region is reported in Figure 13.
The geothermal potential varies between “Faible”, “Moyen” and “Fort” and a class for no data (grey) is also given. The method has been applied in 3 among 4 regions of the Alpine Space (PACA, Rhône- Alpes, Franche-Comté, Alsace excluded).
Figure 13: Example of geothermal potential assessment with the BRGM’s multi-criteria weighted score system (extracted from http://www.geothermie-perspectives.fr/cartographie).
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2.7 Maximum thermal power to be installed in a GWHP As shown in the previous paragraphs, the sizing of BHEs mostly depends on the thermal properties of the ground and on the undisturbed ground temperature. Theoretically, if a sufficient number of BHEs is installed (and a sufficient area is available for this purpose), there is no limit for the thermal power to be delivered by a BHE field.
On the other hand, for open-loop systems, sizing mostly depends on the hydrodynamic properties of the aquifer. In particular, the flow rate (and hence, the thermal power) which can be exchanged with the aquifer through an abstraction-reinjection well doublet is limited by the level variations induced in the wells themselves.
We hereby present two methods developed to calculate the maximum thermal power which can be delivered by a GWHP, depending on the local hydrodynamic properties of the aquifer.
2.7.1 The Barcelona case study (Garcìa-Gil et alii, 2015) Garcìa-Gil et alii, 2015 [25] developed a method for the estimation of the maximum thermal power which can be exchanged by a GWHP, based on the hydraulic impact of the abstraction and injection well(s), calculated with the Thiem’s analytical solution for steady-state pumping tests:
Q 푅 s(r) = 푙푛 ( ) 2휋푇 푟
Equation 6 where 푠 is the drawdown (m) at a radial distance 푟 (m), 푇 is the homogeneous transmissivity (m2/s) of the aquifer, R is the radius of influence (m). The maximum drawdown at the borehole wall (assumed 푟 = 0.25푚) is set to 25% of the saturated thickness, and two values of radius of influence are adopted: 푅 = 250푚 for unconfined aquifers and 푅 = 2500푚 for confined aquifers. The flow rate 푄 (m3/s) is calculated based on this drawdown constraint, and with an upper bound of 0.1 m3/s.
The extractable thermal power from the groundwater is proportional to the maximum flow rate 푄:
푃 = 푄휌푤푐푤 ∆푇
Equation 7
-3 -1 where 푐푤휌푤 is the water heat capacity (4.2 MJm K ) and ∆푇 (°C) is the temperature difference between the groundwater and the air temperature. Such a usual value of Δ푇, which varies depending on the position, makes the value of the open-loop Low Temperature Geothermal Potential (LTGP) vary depending on the season, as shown in Figure 14.
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Figure 14: Open-loop NSGE potential in the metropolitan area of Barcelona. Source: Garcìa-Gil et alii, 2015 [22].
2.7.2 The Cuneo case study (Casasso and Sethi, 2017) Casasso and Sethi (2017, [19]) considered the open-loop NSGE potential as the thermal power which can be exchanged by a well doublet, which is proportional the flow rate 푄 which can be abstracted and injected (i.e., to the lowest of them). The proportionality is the same as reported in Equation 7,
푃 = 푄휌푤푐푤 ∆푇. However, the temperature difference adopted is a fixed one Δ푇 = 5°퐶.
The maximum flow rate 푄 is determined based on two constraints. For the abstraction, the maximum drawdown in the well is:
푠푤(푄푎푏푠) = 훼 · 푏
Equation 8 where 푏 (m) is the saturated thickness of the aquifer and 훼 is a share of such thickness. The authors suggest 훼 = 0.5. For reinjection, the level increase in the well should not exceed the difference between the initial depth of water table 푑 (m) and a minimum threshold 푑푚푖푛:
푠푤(푄푖푛푗) = 푑 − 푑푚푖푛
Equation 9
The drawdown in the abstraction well and the level increase in the injection well are both calculated with the following formula:
푄 푇푡푝푢푚푝 2 푠푤(푄) = · 푙표푔 (2.25 2 ) +퐶푄 4휋푇 푆푟푤
Equation 10 22/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
where 푇 is the aquifer transmissivity (m2/s), 푆 is the storage coefficient (for an unconfined aquifer, it is equal to the effective porosity), 푟푤 is the well radius (m), 푡푝푢푚푝 is the pumping period (s) over which the level variation is calculated (the authors used 푡푝푢푚푝 = 200푑 ), and 퐶 is the quadratic term coefficient (s2m-5) due to turbulent friction losses (according to the Walton’s criterion, the authors used a value 퐶 = 1900 푠2푚−5, which is the acceptability threshold for a well). Figure 15 shows the input data used for the calculation of the open-loop geothermal potential. In particular, Figure 15A highlights that a large portion of the plain has a very small depth to water table, which strongly limits the possibility to reinject water into the aquifer. For this reason, the open-loop geothermal potential is provided both with (Figure 16B) and without (Figure 16A) reinjection. The comparison between the two maps highlights how the disposal into a surface water body can make it possible to install a higher power, in the case of a very shallow water table.
Figure 15: Aquifer properties of the alluvial plain of Cuneo: depth to water table and groundwater levels (A), saturated thickness and transmissivity (B). Source: Casasso and Sethi, 2017 [19].
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Figure 16: Open-loop geothermal potential in the alluvial plain of Cuneo without (A) and with (B) reinjection into the same aquifer. Source: Casasso and Sethi, 2017 [19].
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3 Methods adopted for the geothermal potential estimation in the case study areas
The literature review presented in the previous section highlights that several methods are available for the quantitative assessment of closed-loop potential. On the other hand, open-loop potential has been little addressed. For this reason, the G.POT method is chosen among the available methods for closed-loop NSGE potential mapping, and common modelling assumptions are presented in Section 3.1 (while some area-specific method details are presented in relevant sections). For open-loop systems, a method was developed by TUM, POLITO and ARPA VdA, and is presented in Section 3.2. 3.1 Closed loop: G.POT The G.POT method [18], mentioned in section 2.4, has been used to assess the closed-loop geothermal potential in the pilot areas of Aosta Valley, Cerkno , Parc des Bauges and Saalbach.
The geothermal potential of each area has been calculated in MWh/y, which represents the annual amount of energy sustainably exchangeable with the ground by a single borehole with defined characteristics. This quantity is useful for a preliminary estimation of the installation costs of a closed loop geothermal plant. However, it should not be meant as a replacement of BHE field sizing.
3.1.1 Mathematical method The G.POT method was developed by Casasso and Sethi in 2016 (Ref. [18]) to estimate the geothermal potential of BHEs, either for heating and cooling. The G.POT method is based on the assumption that the application of a cyclic sinusoidal thermal load induces a time-varying thermal alteration of the ground, thus reaching a threshold fluid temperature (minimum or maximum, depending on the use), which is determined by the following parameters:
- ground thermal properties: depth-averaged thermal conductivity 휆 (Wm-1K-1) and thermal capacity 휌푐 (Jm-3K-1);
- undisturbed average ground temperature 푇0 (°C);
- length of the heating or cooling season 푡푐 (s), i.e. the duration of the sinusoidal cycle; - thermal resistance of the borehole 푅푏 (mK/W) as described in Claesson and Eskilson [24]; - threshold temperature for the fluid 푇푙푖푚 (°C), i.e. the minimum temperature (in heating mode) or the maximum temperature (in cooling mode) which can be reached by the heat carrier fluid
circulated into the BHEs. The temperature 푇lim to be used as an input is the average between inlet and outlet;
- the life span 푡푠 (s) considered, i.e. the number of years the plant is expected to operate (e.g., 50 years).
The alteration of the fluid temperature 푇푓(푡) is calculated with the Infinite Line Source solution [25], applying the superposition principle in order to consider the variable thermal load.
The shallow geothermal potential 푄̅퐵퐻퐸 (expressed in MWh/y) is then described by Equation 11:
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′ ̅ 0.0701·(푇0−푇푙𝑖푚)·휆·퐿·푡푐 푄퐵퐻퐸 = ′ ′ ′ 퐺푚푎푥(푢푠,푢푐,푡푐)+4휋휆·푅푏
Equation 11
′ ′ ′ ′ ′ ′ where 퐺푚푎푥(푢푠, 푢푐, 푡푐) is a function of three non-dimensional parameters 푡푐, 푢푐 and 푢푠:
′ ′ ′ ′ ′ 퐺 ′ ′ ′ = −0.619 · 푡 · 푙표푔(푢 ) + (0.532 · 푡 − 0.962) · 푙표푔(푢 ) − 0.455 · 푡 − 1.619 푚푎푥(푢푠,푢푐,푡푐) 푐 푠 푐 푐 푐
Equation 12
′ ′ ′ Where 푢푐, 푢푠, and 푡푐 are three non-dimensional quantities described as follows:
′ 2 푢푐 = 휌푐 · 푟푏 ⁄(4휆푡푐)
Equation 13
′ 2 푢푠 = 휌푐 · 푟푏 ⁄(4휆푡푠)
Equation 14
′ 푡푐 = 푡푐/푡푦
Equation 15
As stated above, G.POT can be used to assess the heating or the cooling geothermal potential. Indeed, the threshold fluid temperature could be set as a minimum one (e.g., 푇lim = +1°퐶) for heating mode, or a maximum temperature (e.g., 푇lim = +27°퐶) for cooling mode. The only limitation is that a single operating mode can be considered and hence, in the presence of both heating and cooling demand, the prevailing one should be considered for mapping.
3.1.2 Common modelling assumption and input parameter sets adopted Due to the typical climate range of the Alpine Space, we investigated the heating use only.
To calculate the geothermal potential of the pilot areas and compare the results, we imposed a common set of BHE parameter values:
- borehole depth 퐿 = 100푚;
- borehole radius 푟푏 = 0.075푚; - time over which the sustainability of the geo-exchange is evaluated 푡푠 = 50 푦푒푎푟푠; - minimum temperature of the carrier fluid during heating mode 푇푙푖푚 = −3°퐶; −1 - thermal resistance of the borehole 푅푏 = 0.1 푚퐾푊 .
On the other hand, several input parameters are spatially variable and has therefore been mapped in each area:
- thermal conductivity 휆; - thermal capacity 휌푐;
- undisturbed ground temperature 푇0 . 26/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
The aforementioned ground parameters have been averaged over the chosen BHE depth, i.e. 100m.
The length of the heating season 푡푐 has also been mapped, since it varies depending on the local climate. The most influential input parameters for the geothermal potential are the ground thermal conductivity (휆) and the undisturbed ground temperature (푇0). The potential (both for heating and cooling) increases with thermal conductivity, since the thermal alteration of the ground diminishes; on the other hand, the geothermal potential increases with 푇0 if the heating mode is considered (since a larger margin is available for cooling the ground), while it diminishes if the cooling mode is assumed for the opposite reason. The length of the heating/cooling season (푡푐) exerts some influence too: the longer 푡푐, the higher the geothermal potential, since the intensity of the thermal load influences the ground thermal alteration much more than its duration. The heating season in the case-study areas is usually very long, ranging between 6 and 10 months. At elevation higher than 2000m, heating may be needed all over the year [26]. The impact of thermal capacity on the geothermal potential, finally, is quite marginal (less than ±5%) in its common ranges of variation (i.e.,휌푐 = 1.5 ÷ 3 푀퐽푚−3퐾−1).
3.1.3 Economic impact of closed-loop geothermal potential The color scale adopted in each pilot area is the same and it is shown in Figure 17.
Figure 17: Geothermal potential colour scale adopted for the G.POT method.
In the Alpine Space, 5 classes can be defined:
- <3 MWh/y very low geothermal potential; - <7 MWh/y low geothermal potential; - <10 MWh/y medium geothermal potential; - <13 MWh/y good geothermal potential; - >13 MWh/y excellent geothermal potential.
The choice on whether the shallow geothermal potential is good or not depends on the payback time it may ensure for a BHE in a detached house. In Table 3, a brief example is provided to explain how the shallow geothermal potential affects the costs of the installation of a closed-loop plant. A block of flats with an annual energetic heating demand of 140 MWh/y is considered. The cost of the heat pump is constant and can be estimated at 55 k€. The cost of each borehole is considered to be 5 k€, and the number of required boreholes depends on the geothermal potential of the area. The total investment for the geothermal plant varies significantly among the cases.
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Table 3: Installation investment of a standard closed-loop geothermal installation, for a heat demand of 140 MWh/y, depending on the geothermal potential of the location.
Total 푃 Number of 퐵퐻퐸 investment Δ cost (MWhy-1) BHE (k€)
20 7 85 -14% 16 8 90 -10% 15 9 100 -5% 14 10 105 0 % 13 11 110 +5% 12 12 115 +10% 11 13 120 +14% 10 14 125 +19% 9 16 135 +29% 8 18 145 +38% 7 20 155 +48% 6 24 175 +67% 5 28 195 +86% 4 35 225 +114%
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3.2 Open loop: assessment of technically feasible flow rates Within the GRETA project, we developed a spatial potential assessment method for the thermal use of groundwater. The key objective is the quantification of technically extractable volume flows with the inclusion of thermal system footprints to allow spatial queries on potential measures.
Sustainable pumping rates of abstraction and injection wells are defined by three constraining factors:
- Maximum tolerable drawdown of 1/3 of the saturated aquifer thickness - Maximum tolerable rise at the injection well to 0.5 m below the ground surface - Avoidance of thermal recycling by the limit state before a hydraulic breakthrough.
The minimum pumping rate of those three constraints defines the technical volume flow for one well doublet. The dependence between hydrogeological parameters, threshold conditions and the resulting pumping rates was examined by the simulation of well doublets in numerical models. For each of the three constrains, multiple combinations of significant influential parameters, the so-called “Cartesian product”, have been simulated. With the derived dataset, a non-linear regression analysis estimated the following mathematical relations.
Figure 1: Cross section view on the hydraulic head from extraction well (E) to injection well (In) at the limit state before the hydraulic breakthrough occurs with limiting constraints.
3 The pumping rate (푉̇푑푑 (m /s), which generates a drawdown of 1/3 of the saturated aquifer thickness in the extraction well can be calculated by the hydraulic conductivity (퐾푓 (m/s)) and the aquifer thickness (푏 (m)) with Equation 16.
2 푉̇푑푑 = 0.195 퐾푓 푏
Equation 16
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3 The volume flow 푉̇푏푡 (m /s) between a well doublet, which generates the limit state before a hydraulic breakthrough occurs, is given by Equation 17. Significant factors influencing this volume flow are the
Darcy velocity 푣퐷 (m/s), the aquifer thickness 푏 (m) and the distance between the two wells 푥푤 (m).
푉̇푏푡 = 1.6 푣퐷 푏 푥푤 = 1.6 · 퐾푓 · 푖 · 푏 · 푥푤
Equation 17 where 푖 (-) is the hydraulic gradient.
Water infiltration at the injection well leads to a groundwater rise which may even result in 3 groundwater flooding. With a known depth to water 푓 (m), the maximum injection rate 푉̇푖푛 (m /s), which can be injected is:
(0.80 − 푖) 32.8푖 푉̇푖푛 = (푓 − 퐹푂푆) 퐾푓 푏 푒
Equation 18 where 퐹푂푆 (m) is the minimum depth to water table which could be reached in the injection well.
The maximum exchangeable flow rate (푉푚푎푥) will consequently be the minimum between these three resulting values, as shown in Equation 19:
푉푚푎푥̇ = 푀푖푛 (푉̇푑푑, 푉̇푏푡, 푉̇푖푛)
Equation 19
Thus, the resulting maximum power of the heat pump (푃푚푎푥) depends on the temperature difference between injection and abstraction (Δ푇), which usually ranges between 3 and 7°C:
푃푚푎푥 = 푉푚푎푥̇ · 휌푤 푐푤 · ∆푇
Equation 20
−3 −1 where 휌푤푐푤 = 4.2 푀퐽 · 푚 퐾 is the thermal capacity of water. According to Equation 20, the power 푃푚푎푥 is equal to 4.2 kW to be multiplied per every l/s abstracted (and injected) and per every degree of temperature difference Δ푇.
A further factor to be considered is the propagation of thermal plumes, which limits the spatial density of GWHPs which can be installed in a certain area. During the GRETA project, Piga et alii (2017, [27]) studied how the injection rate (푉푡푒푐̇ ℎ), the temperature difference (훥푇), hydraulic conductivity (퐾푓) and the Darcy velocity (푣퐷 = 퐾푓 ∙ 푖), the aquifer thickness (푏), the longitudinal dispersivity (훼퐿) and dispersivity ratio (훼푇/훼퐿) influence the size and the time scales of propagation of thermal plumes.
The spatial evaluation of the available open loop potentials is based on the following datasets:
- Elevation of the groundwater table - Elevation of the aquifer bottom, i.e. the confining geological layer - The digital elevation model 30/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
- The hydraulic conductivity of the aquifer (e.g. from pumping tests) - The groundwater temperature
This spatial data is used in the evaluated case study areas to derive the following information: - Thickness of the saturated groundwater body - The hydraulic gradient - The depth to water - The legally approvable temperature differences for heating & cooling
Through the above described functions, the following outputs will be presented for each processed case study area (Aosta Valley, Upper Iller valley, Saalbach/Leogang): - The qualitative constraints to indicate drawdown limit and flooding risk areas. - The technical volume flow for well pairs with 10 m distance and 100 m distance in 20x20 m resolution. - The maximum extraction at 1/3 drawdown of the aquifer thickness - The maximum injection with a maximum groundwater table rise of 0.5 m below surface - The resulting geothermal extraction power [5] at the legal temperature difference maximum with a spatial aggregation restriction. The spatial assessment also includes a consideration of drinking water protection areas and other potentially harmful risks, which are further examined in the large-scale mapping of the GRETA project.
The presented potential assessment results do not substitute on-site investigations of the local groundwater conditions in the planning phase of a GWHP system. In addition, the potentials are displayed in maps of 20 m resolution, where an aggregation of values for area queries is prohibited. 3.3 Access to the geothermal potential maps of the project The way to access to the information provided by this document is briefly resumed in this paragraph. The access to the geothermal potential maps produced by this Deliverable can be performed in two ways:
1) Offline, by accessing the webpage of Politecnico di Torino reported here and at the beginning of this document: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/. This page hosts zipped folders containing the .tiff files of the maps produced in the context of this Deliverable. The folders are divided following pilot area criteria and type of geothermal potential (closed- or open- loop).
2) Online, by accessing the webpages on the Geonode platform (see Del. 4.1.1 for further detail). 5 different links are available, according to the number of pilot areas of the project which needed geothermal mapping (Davos-CH is excluded). The links are provided in the title of each chapter dedicated to a pilot area, as well as at the end of it (chapters of interest are 4 to 8).
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4 NSGE mapping in Aosta Valley (Italy) 4.1 The territory surveyed The Aosta Valley (NW Italian Alps) is a mountainous region of 3,200 km2 and 128,000 inhabitants surrounded by the highest European massifs (among them the Mt Blanc, the Mt Rose, and the Grand Paradis); the average altitude of the whole territory is about 2100 m a.s.l. and glaciers occupy about 5% of the total area.
The main valley is crossed by the Dora Baltea river, for a length of approximately 100 km. The main towns are all located in the Aosta plain: Aosta (34,777 inhabitants), Sarre (4941), Châtillon (4844), and Saint-Vincent (4742). The majority of Aostan population lives in the bottom valley, between 350 and 700 m a.s.l. However, some famous tourist destinations are located at high elevations: Courmayeur (1224 m a.s.l.), Valtournenche (1528 m a.s.l.) and Cogne (1524 m a.s.l.).
The climate of the region is typically alpine, with cold winter and short summer. Temperatures vary significantly within the territory, due to the big altitude differences. Precipitations are particularly low, if compared to other alpine valleys.
4.1.1 Existing geothermal installations A specific investigation undertaken by Turin Polytechnic together with ARPA VdA found 69 operating systems (see Figure 18), with a cumulate power of almost 4 MW, which makes Valle d’Aosta one of the Italian regions in which shallow geothermal energy is most used. Particularly interesting, some of these systems are located at high altitude (even over 2000 m a.s.l.), in remote areas.
Figure 18: Location of NSGE plants in the Aosta Valley.
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4.1.2 Geological setting Three main tectonic domains of the Alps can be found [28-30] in the Aosta valley, as shown in Figure 19:
- the Helvetic Domain in the north-western portion of the region, which is the only sector not undergone to metamorphism, consisting mainly of granite and migmatites (i.e. the basement of the Mont Blanc massif); - the Austroalpine Domain can be divided in two sectors: o the Sesia Lanzo zone, composed mainly by eclogitic micascists and gneiss with metabasites, located in the south-western portion of the region; o the Dent Blanche unit, composed mainly by kinzingites, amphibolites, and marbles, located in the central part of the region, north and south to Aosta; - the Pennidic Domain is the most diffused one and refers to a broad set of rocks of originally different geological genesis and paleogeographic position, later deformed during the orogenesis. It can be subdivided in: o the Grand Paradis and Mont Rose massifs, mainly composed by gneiss; o the paleo-oceanic Piemontais zone, consisting of ophiolites (mainly serpentinites and metabasalts) and associated metasediments (mainly calceschists); o the Briançonnais zone, consisting of various kind of metasedimentary rocks.
Quaternary alluvial sediments (sandy gravels) host very thick and permeable aquifers, exploited mainly for industrial and drinking use and, in recent years, for geothermal use too. Their recharge is granted by seasonal snowfall melting, in addition to several glaciers covering about 5% of the total regional area.
Figure 19: Simplified tectonic map of the Aosta Valley.
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4.1.3 Hydrogeological setting of the Aosta plain The Aosta plain stretches west–east for about 13.5 km, reaching a width of 2.5 km in the central part, near the town of Aosta, and its elevation ranges from 700 to 530 m above sea level. It is crossed by the Dora Baltea River flowing from west to east, fed also by several tributary streams. The Plain is underlain by a series of Quaternary fluvioglacial, lacustrine, alluvial and fan sediments – whose overall thickness has been estimated of about 250-300 m - laying on a deep crystalline basement which emerges in the mountain slopes bounding the aquifer north and south.
In this sedimentary basin, the exploited shallow aquifer, consisting mainly of heterogeneous alluvial deposits, ranges in thickness from 85 to 90 m in the western part to 50 m in the eastern part. A silty- sandy deposit of lacustrine origin, never completely penetrated by wells and located at the depth of about 50–90 m from the surface is considered to act as a low-permeability basement boundary between the overlying phreatic aquifer used for water supply and a probable deeper sandy-gravel aquifer (of likely glacial origin), not yet investigated nor exploited. In the stretch of the Aosta plain considered in our analysis (Figure 20), the saturated thickness of the aquifer ranges from 50 m in the western part to 15÷20 m in the eastern part, with a clear decreasing trend.
Figure 20: Saturated thickness of the shallow aquifer of the Aosta plain.
As a consequence of the valley shape, the aquifer structure, and the relationships with surface water, the piezometric heads vary from 564 to 526 m a.s.l. from west to east along the valley. The hydraulic gradient is quite discontinuous: it is 1% in the western part of Aosta, 0.3÷0.4% in the eastern part of Aosta and upstream the town, and 0.5÷0.6% elsewhere (Figure 21).
Figure 21: Hydraulic gradient of the shallow aquifer of the Aosta plain.
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The water table depth (Figure 22) decreases longitudinally from west to east and transversely from the valley slopes to the Dora Baltea River, ranging from a maximum of around 20 and 25 m respectively in the western sector and in the alluvial fan of the Buthier Creek, to a minimum of 10 and 4 m respectively in eastern sector, near the Dora Baltea River.
Figure 22: Depth to water table of the shallow aquifer of the Aosta plain.
The hydraulic conductivity of the shallow aquifer (Figure 23) ranges from 5·10-4 m/s to 4·10-3 m/s, with a median value of 1.8·10-3 m/s. These values are typical of sand and gravel sediments and, combined with the large saturated thickness of the aquifer, allow for large flow rates to be abstracted. The Aosta plain aquifer is subjected to intense groundwater exploitation serving both drinking and industrial supplies. Local industries are served by several wells located in the central and in the eastern part of the Aosta plain, whereas the drinking-water supply comprises other wells located in the western part of the plain.
Figure 23: Hydraulic conductivity of the shallow aquifer of the Aosta plain.
In the Aosta plain, where the aquifer geothermal potential has been studied in detail, groundwater temperature has been examined throughout the data collected in the last years by ARPA VdA in 9 monitoring piezometers in which a data logger has been installed (Figure 24) – from a minimum period of 8 months to a maximum of more than 4 years - in order to measure continuously groundwater temperature and depth.
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The location of the piezometers is shown in Figure 25 while results are summarized in Figure 4. Two examples of temperature diagrams in different situations of groundwater depth are shown in Figure 28 and in Figure 27.
Figure 24 : Installation of a data logger inside a piezometer - Data download from the data logger
Figure 25: Location of the piezometers with data logger installed in the Aosta plain.
Figure 26: Measured groundwater temperatures of the shallow aquifer of the Aosta plain.
The main outcome is that groundwater depth affects significantly the seasonal variations of groundwater temperature: it is rather steady (values around 10-12°C during all the year, with
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fluctuations smaller then 1-2°C) with groundwater table deeper than 15-20 m such as Ao61 (shown in Figure 27), Vi6, Jo2. On the other hand, shallower wells such as Br50 (Figure 28) we can observe a seasonal cycle with a certain delay compared to air temperature. In the example reported, the delay is of 3-4 months: maximum temperatures are observed in November instead of July, and minimum temperature are measured in May instead of January.
Table 4: Temperature range resulting from daily measurements in data logger in the Aosta plain, in different groundwater depth conditions.
Piezometer code Data availability Groundwater depth range (m) Temperature range (°C) Vi6 4 years 14.0 – 16.5 10.0 – 11.0 Jo2 3.5 years 12.0 – 22.0 8.5 – 9.5 Ao61 3 years 23.0 – 28.0 11.6 – 12.4 Ch5 3.5 years 8.0 – 16.0 7.6 – 10.5 Po34 4.5 years 2.0 – 4.0 9.5 – 11.0 Po35 1 year 2.0 – 3.5 9.8 – 10.7 Po50 3 years 4.5 – 5.7 10.0 – 14.0 SM7 Some months 2.5 – 5.0 9.5 – 15.3 Br50 Some months 3.0 – 4.0 9.0 – 14.0
Figure 27: Temperature from data logger daily measurements with significant groundwater depth (> 20 m).
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Figure 28: Temperature from data logger daily measurements with small groundwater depth (3-4 m).
The resulting aquifer temperature map of the Aosta plain, is shown in Figure 26.
Most of the above mentioned data loggers, installed since 2010, are not active anymore. In order to continue this monitoring campaigns and to verify the results of the modelling made by Politecnico di Torino, ARPA bought in Autumn 2017 expressly for the GRETA project another data logger featuring the measurement of groundwater electrical conductivity as well.
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4.2 Closed-loop geothermal potential
4.2.1 Thermal properties of the ground 13 rock samples, representative of the main lithologies of bedrock of the Aosta Valley, have been collected to estimate values of thermal conductivity and thermal capacity. These samples were analysed with a thermal conductivity scanner and results are shown in Table 5.
As described in section 3.1, thermal conductivity is a key factor for the estimation of geothermal potential, while the thermal capacity plays a less important role. In particular, values in Table 5 are generally very high (>3.1W/mK, up to 4.0W/mK) and typical of metamorphic rocks, which mainly compose the Aosta valley basement. The alluvial deposits are present in four main lenses in valley bottom (the biggest is the Aosta plain), while glacial deposits are present in smaller lenses in lateral valleys, such as in Val d’Ayas, Valgrisenche and Val Veny.
Thermal properties of the main lithologies of the Aosta valley were assigned according to Table 5 using the map of ISPRA 1:500000; thermal properties of the sediments were estimated according to literature evidences and are reported in Table 6.
Resulting maps of thermal capacity and thermal conductivity are shown in Figure 30 and Figure 29.
Table 5: Thermal conductivity, thermal diffusivity and thermal capacity of the collected samples.
Mean measured Mean measured Calculated Thermal Thermal Thermal Sample Rock type (lithology) Conductivity Diffusivity (10-6 Capacity (Wm-1∙K-1) m2/s) (MJm-3K-1) 1 Mont Blanc granite 3.12 1.62 1.93 2 UltraHelvetic schist 2.82 1.12 2.52 3 Zone Sion Courmayeur flysch 3.23 1.14 2.83 4 Outer Briançonnais micaschist 4.04 1.04 3.88 5 Inner Briançonnais micaschist 3.12 0.94 3.33 6 Piemontais zone calceschist 3.41 1.27 2.68 7 Gneiss minuti 3.42 1.42 2.40 8 Metabasalts 2.46 0.81 3.04 9 Serpentinites 3.41 0.95 3.58 10 Eclogitic Metagranitoids 3.26 1.49 2.19 11 Metagranitoids 3.44 1.82 1.89 12 Grand Paradis gneiss 3.43 1.32 2.60 13 Ortogneiss 3.33 1.51 2.21
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Table 6: Estimated thermal conductivity and thermal capacity of sediments, according to average values of the Italian standard UNI [31]. Thermal Conductivity Thermal Capacity Lithotype Secondary lithologies (Wm-1∙K-1) (MJm-3K-1) Alluvial deposits Silt + Sand + Gravel 1.90 2.00 (considered mainly saturated) Glacial deposits Diamicton + Clay + Silt 1.70 2.50 (considered mainly dry)
Figure 29: Spatial distribution of the average ground thermal conductivity 흀 (Wm-1K-1) in the upper 100m of depth.
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Figure 30: Spatial distribution of the average ground thermal capacity 흆풄 (MJ·m-3K-1) in the upper 100m of depth.
4.2.2 Ground temperature The undisturbed temperature of the soil is related to the annual average temperature of the air, according to Signorelli & Kohl (2004, [32]). The yearly average air temperature recorded over a period of ten years (2006-2016) in 40 meteorological stations (data from ARPA VdA) is linearly related with the altitude, as shown in Figure 31.
Figure 31: Annual average temperature measured in meteorological stations of the Aosta Valley, related to the altitude of each meteorological station.
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The undisturbed soil temperature of the entire Valle d’Aosta has been calculated trough the altitude as in Equation 21. The effect of the geothermal gradient has been considered adding 1°C to the air temperature.
푇0 = 푇푎푖푟 + 1°퐶 = 15.975 − 0.0055 ∗ 퐻
Equation 21
Where 푇푎푖푟 is the the annual average air temperature (°C) and 퐻 is the altitude (m above sea level). Equation 21 does not take into account the effect of the snow presence on ground soil temperature (depending on many factors such as, precipitations, sun exposition…) thus soil temperature over the isotherm line of 5°C were excluded from the mapped area, corresponding to above about 2000 m a.s.l.. Although, this threshold excludes almost inhabited areas. The resulting map is shown in Figure 32.
Figure 32: Estimated ground temperature in the Aosta Valley.
4.2.3 Length of the heating season
According to UNI (1987) [33] the length of the heating season (푡푐) has been estimated as the number of annual days in which the mean temperature is below 12°C. A correlation of this value with the quote (퐻) has been carried out using the data of 38 meteorological stations of the Aosta Valley (Figure 33).
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Figure 33: Correlation between the quote and the length of the heating season.
The resulting Equation 22 has been used for the realisation of the map shown in Figure 34:
푡푐 = 124.5 + 0.094 ∗ 퐻
Equation 22
Figure 34: Calculated map of the length of the heating season in Aosta Valley.
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4.2.4 Results The closed loop geothermal potential of the Aosta Valley has been derived with the G.POT method for a standard BHE 100m deep, and it is shown in Figure 35 for elevations below 2000m a.s.l. (above which the estimation of the ground temperature is nor reliably correlated with the elevation).
The map shows globally high values of geothermal potential, higher than 10 MWh/y in most of the territory (>70%), as a consequence of the good thermal conductivity values, which were derived from laboratory measurements on 13 representative rock samples (see Section 4.2.1). Lower geothermal potential values can be found in the main valley bottom due to the lower thermal conductivity of the alluvial sediments. A few large lenses of glacial deposits, also characterised by low geothermal potential, can be found even in many lateral valleys, such as in Val d’Ayas, Valgrisenche and Val Veny. It should be noted that the estimation of the shallow geothermal potential with G.POT does not take into account the effect of groundwater advection, which may increase the heat exchange rate noticeably, as shown in Refs. [34-36]. The effect of groundwater advection could be taken into account with numerical models such as FEFLOW [37], or with analytical formulae [38, 39].
Concerning the effect of the elevation, geothermal potential values are globally lower in the higher part of the valley, due to the lower ground temperature and despite the longer heating season, imposed in high altitude areas.
Figure 35: Map of the closed-loop shallow geothermal potential 푷푩푯푬 (MWh/y) in the Aosta Valley, calculated with the G.POT method.
The geothermal potential value calculated over the Aosta plain has been compared to a TRT test
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performed in Saint Christophe (550m a.s.l.) (Tagliabue et alii. 2013 [40]) on a BHE 90m depth. During this test, the borehole exchanged 5520 kWh over a period of 1370h, with a mean value of 44.8 W/m of borehole length. Considering a heating period of 2200 Full Load Equivalent Hours (FLEH) and a borehole length of 100m, the exchanged energy that we can derive is 9.9 MWh/y, very close to the obtained value shown in the map, which is 10MWh/y in the plain area of Saint Christophe.
Two other TRT were performed in Etroubles (1326 m asl) and Arvier (726m asl) but data obtained on those installations cannot significantly be compared to this map, because made on much shorter BHE (50m deep).
4.2.5 Comparison of G.POT with other closed-loop potential mapping methods In this pilot area, we have mapped the geothermal potential according to the tables presented in Section 2.1: the MIS 3005 (Figure 7); VDI 4640 version 2000 (Figure 1) and VDI 4640 version 2015 (Figure 2). All these tables provide a range of values expressed in W/m of borehole depth. These tabulated values were multiplied for the borehole length (100m) and the length of heating season expressed in hours to obtain the same geothermal potential scale used in Figure 35. Resulting maps and the cumulative distribution of those values are shown in Figure 36.
Figure 36: Comparison between the G.POT method and other 3 closed-loop geothermal potential estimation methods: MIS 3005 (left up); VDI 4640, version of 2015 (right up); VDI 4640, version of 2000 (right down); values distribution comparison (left down).
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The two VDI 4640 maps, compared to the G.POT method, show limited differences of the geothermal potential, but these two methodologies do not consider the effect of the ground temperature, which varies in wide ranges. Differences between the two VDI 4640 maps are due to the fact than in the 2015 version, measured values of thermal conductivity are implemented, while in the 2000 version, just average values were assigned to each lithotypes, according to given tables. The MIS 3005 system, instead, seems to overestimate the effect of ground temperature, drastically reducing the potential in high altitude areas. On the other hand, in the valley bottom the values of geothermal potential are comparable with the G.POT method.
4.3 Open-loop geothermal potential The quaternary deposits of the main bottom valley host some thick and productive alluvial aquifers. These deposits are present in particular in four main plains: Aosta, Verrès, Pont-Saint-Martin, and Morgex. This work analysed in detail the first of these plains, which has the largest dimensions, the highes wells exploitation, hydrogeological data availability, and the highest population.
4.3.1 Methodological remarks At present, the Region Valle d’Aosta offers an exceptional regulatory feature for the thermal use of groundwater, compared to other Alpine Space Italian regions, since reinjection is not allowed in the subsurface, but only on surface water bodies. A harmonisation towards the typical approach (reinjection in the same aquifer) is foreseen and supported by local environmental organisations for a long time. Therefore, the methodology of assessment for the open-loop geothermal potential was not changed in the case study of Aosta. At present, only the potential estimates for the volume flow based on the maximum drawdown (i.e. less than 1/3 of the saturated thickness) apply to for the current regulatory situation. The reinjection and the thermal breakthrough constraints cannot be applied in the current regulatory framework, but they are deemed to be applied in the future.
The core element of the assessment is the calculation of technically sustainable pumping rates for well pairs in GWHP systems. As presented in Chapter 3.2, the three main limiting factors: no hydraulic breakthrough, a maximum of 1/3 aquifer drawdown and a maximum groundwater rise of 0.5 m below surface at injection, are introduced. At a definite location, the minimum of the three calculated pumping rate values defines the technical volume flow, which offers a sustainable operation of the well pair. Therefore, the results presented in the open-loop potential chapters of this report (Aosta, Oberallgäu, Saalbach-Leogang) are composed of several datasets with different spatial information.
The main result of the potential assessment is the technical volume flow for well distances of 10 m and 100 m (Figure 37 a and b, bottom). The calculated values offer conservative results, where a severe drawdown at the extraction well (drawdown constraint), an extensive groundwater rise (flooding constraint) and efficiency losses due to thermal recycling through prohibiting a hydraulic breakthrough (breakthrough constraint) are excluded. The constraints, which are currently in force, are mapped respectively in yellow, blue and green in the maps in the Figure 37 a and b, top.
The second set of results offers a more specific view on the spatial distribution of the calculated pumping rates for the drawdown constraint and the flooding constraint. In the presence of productive aquifers, the hydraulic breakthrough is usually the main constraining factor (see Figure 37). In 46/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
consequence, the results of the mentioned constraints are hidden in the technically feasible volume flow rate maps. However, they can deliver important information on maximum abstraction estimates, e.g. when the well distance is not known in a planning scenario or only a rough qualitative statement on the general suitability is needed. Hence, the maps of volume flows at the drawdown constraint and at the injection constraint are displayed separately (see Figure 38).
The third and final set of assessment results are maps of extractable geothermal power in kW and MWh/a. The results are derived from the technical volume flow map of 10 m well distance and constant demand estimates, i.e. a temperature difference of 5 K and 2000 full load hours per year (see Figure 39). The values can be used to estimate the coverable heating or cooling demands for initial planning considerations, like energy consultations. Users have to bear in mind that the absolute heating energy for a building has to be calculated with a seasonal performance factor for the heat pump system.
In general, the presented potential assessment results do not substitute on-site investigations of the local groundwater conditions in the planning phase of a GWHP system. In addition, the potentials are displayed in maps of 20 m resolution, where an aggregation of values for spatial queries is prohibited.
4.3.2 Results Figure 37 shows the map of constraining effects (top) and the map of the technical volume flow potential (bottom) for 10 m well distance (a) and 100m well distance (b). Due to the fact that the Aosta valley offers favourable conditions for the thermal use of groundwater, the only constraining factor in this case study area is the hydraulic breakthrough. Throughout the investigated area, moderate (4-8 m east of the airport) to large (15-20 m around the Aosta center) depths to water do not hamper an injection of water even for larger systems. In addition, the aquifer thickness is sufficiently large and hence no drawdown of 1/3 of the saturated thickness does not limit the flow rate even for well pairs at 100 m distance. According to the descriptions in chapter 0, this leads to the result that the volume flows for 100 m wells are 10 times the values of 10 m wells.
The technical volume flows in Figure 37 show influences of aquifer thickness, hydraulic conductivity and hydraulic gradient variations, which have been available in spatially interpolated datasets.
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Figure 37: Technically feasible volume flow rates in the Aosta plain for a) well pairs with 10 m distance and b) well pairs with 100 m well distance.
For further information on the potential, the map of maximum pumping rates at 1/3 drawdown (Figure 38a) and the map of maximum injection rates till the groundwater rises up to 0.5 m below surface (Figure 38b) are displayed. The maps represent the result of an application of Equation 16 and Equation 18, respectively. The calculated volume flows only consider the extraction or the injection well independently from the wells distance to each other and a hydraulic breakthrough limit is not considered.
The extraction rate at the drawdown limit is dependent on the hydraulic conductivity and the square of the aquifer thickness (Equation 16). Among the very high values, this prominent effect of the aquifer thickness can be observed in the eastern section, where rates decline to still high 30-50 L/s (Figure 38, top). The injection potential map on the bottom of Figure 38 shows a similar pattern. However, the calculated values are mainly dependent on the local depth to water. Therefore, the declining values in the eastern section result due to moderate (4-8 m) depths to water east of the airport.
These depths to water values are derived from 58 direct measurements performed in March 2017 by ARPA VdA. The point values were then interpolated as raster file with a resolution of 25 X 25 m.
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Figure 38: Volume flow for an extraction well at a drawdown of one third of the saturated aquifer thickness (left) and volume flow of an injection well with a threshold groundwater table rise of 0.5 m to the surface (right).
The technical volume flow rate results of 10 m well distance are further used to determine a local value of extractable geothermal power and geothermal energy (Figure 39). The geothermal power (Figure 39a) was calculated for a temperature difference at the heat pump of five Kelvin (K) with Equation 20. If the required heating power of a house is known, the displayed geothermal power [kW] can be used with an estimated seasonal performance factor of the heat pump to derive the possible thermal power of the GWHP system. Since the values of the volume flow map are only multiplied with constants, the map shows the same relations as explained for the technical volume flow map for 10-m well distance. In addition, we calculated the extractable geothermal energy for 5K temperature difference and 2000 hours of full load operation per year (Figure 39a). 2000 hours represent an intermediate value taken from the VDI 4640, which suggests a range of 1800 h to 2400 h of full load hours. Figure 40 shows the open-loop potential for a well doublet with 100m of distance between the wells.
Since the thermal recycling is the constraint which always apply, we see that the open-loop potential with 100m distance is exactly 10 times the potential with a well distance of 10m. The “small well doublet” (10m) potential ranges from 10 to 300 kW, with a median value of 91 kW. The highest values are observed just upstream the “Cogne” area, on the SW of the historical centre of Aosta. The “large well doublet” (100m distance) potential ranges between 100 kW and 3 MW.
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Figure 39: Open-loop potential in the Aosta plain for a well doublet with 10 m distance at a 5 Kelvin temperature difference (a) and the resulting geothermal energy for 2000 hours of full load operation per year (b).
Figure 40: Open-loop potential in the Aosta plain for a well doublet with 100 m distance at a 5 Kelvin temperature difference (a) and the resulting geothermal energy for 2000 hours of full load operation per year (b).
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4.4 Conclusions Aosta Valley is the largest of the 6 case-study areas (3263 km2).
The geothermal potential for closed loop systems has been assessed for the areas below 2000m a.s.l. (see Figure 35), while the open-loop potential has been identified for the Aosta alluvial plain (see Figure 39).
The closed-loop geothermal potential map shows value above 10 MWh/year for a 100 m long BHE, which is quite a high value, and it is mainly due to the high thermal conductivity of rocks. Lower values are found in the bottom valleys, due to the lower thermal conductivity of alluvial and glacial sediments; however, since the effect of groundwater advection is not taken into account, thermal loads larger than the G.POT-derived potential can be exchanged. With the values of closed-loop geothermal potential, BHEs may be of interest to replace methane boilers while, in the absence of methane grid, they should be seriously taken into account as an alternative to oil or LPG boilers.
For the thermal use of groundwater, a favourable situation was found in the Aosta plain, since the thick and conductive gravels offer a very suitable porous medium for a highly productive aquifer. Due to the absence of very low depths to water, no negative influences from a critical groundwater level rise could be identified within the analysed system size. For shallow wells near the main river of the valley, the infiltration of cold surface water can lead to very low groundwater temperatures during winter and spring. Apart from this cautionary recommendation, the thermal use of groundwater is possible throughout the analysed area.
All the maps about this pilot area reported in this section can be downloaded from this link: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/ or viewed through this one: http://greta.eurac.edu/maps/177/embed.
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5 NSGE mapping in Cerkno (Slovenia)
This chapter presents geological and geothermal characteristics in the small hilly and mountain municipality of Cerkno (Slovenia). The assessment and mapping of the closed-loop geothermal potential in Cerkno was carried out by GeoZS and POLITO. The mapping of the open-loop geothermal potential was not performed, since Cerkno does not have shallow aquifers with a sufficient productivity for this kind of plants.
The results of this work have been presented at the EGU General Assembly 2017 in Vienna (23-28 April 2017) and are published in an open-access article [41] of the EGU2017 special issue of Energy Procedia: Casasso A., Pestotnik S., Rajver D., Jež J., Prestor J., Sethi R., Assessment and mapping of the closed- loop shallow geothermal potential in Cerkno [42], Energy Procedia, Volume 125, September 2017, Pages 335-344. The article can be downloaded for free at the following web address: https://www.sciencedirect.com/science/article/pii/S187661021733713X
5.1 The territory surveyed Cerkno is a municipality of 4644 inhabitants divided into 30 dispersed settlements (Table 7), among which the largest is Cerkno (1523 inhabitants), with 13 other hamlets of 100 to 300 inhabitants which are shown in the map of Figure 42. The total surface of the municipality is 132 km2, with a population density of 35 inhabitants per km2. Cerkno is located in the Goriška statistical region (SI023), at some 50 km from Gorizia (Italy) and 60 km from Ljubljana, the capital of Slovenia.
Figure 41: Map of the Slovenia, with the position of the municipalities of Cerkno and Ljubljana.
As shown in Figure 42 the SW part of Cerkno is in the plain, while the rest of the territory is mountainous. Ground elevations range between 250 and 1500 m a.s.l., but 90% of the population lives below 700 m a.s.l. and the highest settlement is located at 836 m a.s.l.
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Figure 42: Map of the municipality of Cerkno with the 14 main settlements (exceeding 100 inhabitants each) and elevations.
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Table 7: Main settlements of the municipality of Cerkno, sorted according to their population. The table reports the altitude, the area, and the population of each settlement. The positions are expressed in two different datum: geographical WGS84 (latitude and longitude in decimal degrees) and in the Slovene National Grid (SI-D-48 Gauss-Krueger datum, EPSG:3912).
East North Altitude Area Long Lat Name Population (EPSG: (EPSG: (m a.s.l.) (km2) (°E) (°N) 3912) 3912) CERKNO 332 7.50 1523 13.99 46.13 422078 109743 Šebrelje 639 11.89 289 13.92 46.09 416248 105693 Gorenji Novaki 754 11.17 232 14.06 46.15 427317 112122 Dolenji Novaki 628 4.13 211 14.04 46.15 425857 112312 Zakriž 588 3.66 185 13.97 46.14 420368 110622 Bukovo 709 8.73 179 13.91 46.15 415518 112062 Ravne pri Cerknem 684 5.03 163 13.95 46.12 419198 109072 Podlanišče 789 5.15 148 14.01 46.11 423728 107713 Planina pri Cerknem 601 1.94 135 14.01 46.13 423317 109442 Otalež 598 2.67 133 13.99 46.08 422088 104263 Straža in Želin 252 6.06 119 13.96 46.10 419238 106633 Plužnje 477 2.07 116 13.98 46.09 420948 105033 Lazec 566 2.21 112 13.97 46.09 420588 105603 Jazne 681 5.09 111 14.01 46.07 423747 103283 Labinje 628 1.73 90 14.00 46.14 422838 111302 Trebenče 453 0.98 88 13.99 46.14 421618 111432 Poče 653 6.06 87 13.98 46.15 421538 112572 Gorje 577 4.14 82 13.98 46.15 420848 112232 Reka 253 3.71 79 13.92 46.11 416898 108323 Jesenica 698 3.00 78 13.95 46.15 418988 112212 Čeplez 564 1.74 73 14.00 46.13 422958 109662 Poljane 501 3.76 72 14.01 46.15 423588 111622 Orehek 542 3.88 69 13.94 46.14 418308 111592 Travnik 287 0.49 59 14.00 46.07 422380 103418 Cerkljanski Vrh 836 5.68 58 14.00 46.11 422717 107424 Zakojca 708 7.45 47 13.93 46.17 417208 113942 Laznica 541 0.22 39 13.98 46.15 421238 112132 Jagršče 658 4.59 27 13.94 46.09 418198 105323 Police 550 3.45 22 13.90 46.13 415109 109673 Podpleče 724 3.41 18 14.03 46.13 425007 109572
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5.1.1 Geological and hydrogeological setting The area of the municipality of Cerkno is not yet covered by detailed geological maps, so we first did a research on the existing archive data and maps of which the most useful information we obtained from the framework of Basic Geological Maps’ campaign of the sheets Kranj and Tolmin with Udine (Grad & Ferjančič, 1974 [43]; Buser, 1987 [44]). Thus, the data were collected, reclassified, aggregated and harmonized between individual geological maps. Some additional field validations were also performed.
The largest part of the Cerkno municipality is covered by clastic sedimentary rocks, which in different geological units (formations) exchange very fast in form of different sequences and ratios. In some places, thick layers of carbonate, especially limestone, appear in clastic rocks. The rest of the outcrops is mostly composed of carbonate rocks, dominantly dolomites.
Clastic rocks are mainly represented by alternation of sandstone and claystone (or mudstone if not specified). In the area of Črni vrh, a mountain close to Dolenji Novaki (Figure 42), the alternation is in favour of sandstone, volcanoclastic tuff and tuffite, while claystone and siltstone are present in minor extent. These layers also characterize a part of Cerkno, as well as some other minor neighbouring settlements. Alluvial sediments as gravel, sand and silt are of very limited extent, deposited only along main rivers and creeks, with a few meters of depth. Soils and unconsolidated sediments are generally a thin cover, less than 1m thick.
In predicting lithological conditions that can be expected under the surface, we limited ourselves to geological conditions up to a depth of 100 m. The continuation of rocks from the surface into depth is influenced by the composition of individual geological units and geometry (spatial distribution) of boundaries and contacts between individual units. In the case of a homogeneous composition, similar rocks as on the surface can be expected also deep under the surface, while rocks can change very rapidly in heterogeneous sequences. Changes can be every few centimeters, every few meters or a few dozen meters. Contacts between individual units can be very steep or very flat. In the case of steep contacts, the shallow (100 m) conditions beneath the surface usually do not change significantly. When the contacts are flat, then another unit with completely different rocks lies just below the unit present on the surface. The rocks lying above form a kind of cover.
Clastic and carbonate rocks in Cerkno are mostly of fissured porosity, while karstic porosity is limited to small areas. Dolomites and limestones can be considered as aquifers with a lower permeability. Moderate permeability can be expected in some dolomite layers, especially in tectonized zones. Clastic rocks are mainly aquitards. In particular, sandstones can function as aquifers of weaker permeability while claystones and tuff layers, as a rule, represent hydraulic barriers. The thickness of alternating sandstone layers is usually less than a meter. Generally, groundwater is of favourable quality and weakly mineralized. Thermal water (>20°C) is expected deeper than 600 m unless the ascendant flow from deep aquifer is located.
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5.1.2 Existing geothermal installations Since oil is still the most adopted heating fuel, the municipality of Cerkno is planning a long-term strategy for the gradual transition to carbon-free heating and cooling, and geothermal energy has an important role in this plan. In recent years, a biomass micro-district heating system was implemented, which provides heat to the western part of Cerkno, including two kindergartens, primary school, music school, and a museum (Figure 43). Furthermore, the system is linked to shallow geothermal energy system from 12 BHEs that currently provides heat and cool only to the Centre for School and Outdoor Education. Besides, at least 2 BHEs are in use for heating of individual houses elsewhere in the town. In the central part of the town, a swimming pool and a hotel (space and DHW through the HP) are heated with thermal water from the deep and warm predominantly limestone aquifer, encountered in depths between 856 and 2004 m, with the most abundant part between 856 and 1840 m depth (Prestor et al., 2006 [45]).
In this context, the assessment and mapping of shallow geothermal potential is a useful tool for the planning of future installations.
Figure 43: Map of the geothermal heating systems located in the main settlement of Cerkno.
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5.2 Closed-loop geothermal potential This section reports the sources and the methods adopted to derive the input data for the application of the G.POT method, which has been used to calculate the closed-loop geothermal potential.
5.2.1 Thermal properties of the ground The thermal properties of the shallow underground are mostly influenced by the geological composition (lithology) and by the presence of groundwater. In addition, the BHE's thermal performance (extraction) is also influenced by the mean annual ground surface temperature (GST), the duration of solar irradiation, which also depends on topography, terrestrial heat flux and precipitation (Grunert et al., 2010 [46]). Therefore, factors such as GST, temperatures down to depths of 200 m, thermal conductivities and diffusivities of rocks and soils, groundwater levels and flows as well as aquifer properties should be taken into account (Busby et al., 2009 [47]). The two most important parameters required for designing a BHE are thermal conductivity of rocks and soils in the depth range of BHE and GST at the BHE location. These two parameters have the greatest influence on the dimensioning of closed-loop systems and on the evaluation of the low-temperature sources used by these systems [32, 48]. Both parameters have shown medium to high range of values owing to quite variable surface lithology and surface elevations.
Geological units at the municipal level were converted into 9 lithological categories, on the basis of the lithological characteristics of geological units and internationally established standards of geothermal properties of rocks [2, 31, 48, 49]:
1. Limestone 2. Limestone in alternation with clastic rocks 3. Dolomite 4. Dolomite in alternation with clastic rocks 5. Alternation of clastic rocks of different granularity and carbonate rocks 6. Extrusive (magmatic rocks) and their tuffs 7. Predominantly thick grained volcanoclastic rocks 8. Gravel and pebbles – water saturated (alluvial) 9. Gravel and pebbles - dry (sloping sediments)
Based on the geological maps, rock samples from the most representative geological units were collected in the field, with multiple samples per geologic column in case of very heterogeneous rock successions.
The samples were prepared for the laboratory measurements with the Thermal Conductivity Scanning (TCS) method [50, 51], keeping them as intact as possible and with their pristine water saturation. For the TCS method, at least one flat plane of each piece of rock is required, for which a small tolerance is prescribed for the flatness of the sample (+/- 0.5 mm), and hence samples are cut with a circular saw to cope with this requirement. On each measured piece of rock, a straight line with a black acrylic color of at least 1 cm in width is colored on a flat surface. A precision of ±3% is achieved in the measurement range of 0.2 to 25 Wm-1K-1.
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A total of 16 samples (30 single rock pieces) from the area of the Cerkno town and of 16 samples (23 single rock pieces) from the wider Cerkno municipality were analyzed. Dolomites (massive and layered), quartz sandstones and conglomerates, dolomitic limestones, and certain tuffs (keratophyre, porphire) proved to be the most conductive rocks and therefore have the best potential for dimensioning shallow geothermal systems. Some other types of rock, such as limestones, carbonatic sandstones, siltstones and diabase revealed good thermal properties as well. Lower potential (but again not so bad) for the exploitation of energy is shown by shale claystones, siltstones (mudstones), some marlstones and marly limestones. The observed thermal conductivities matched well with the values in the SIA [48] and VDI 4640 standards [2], as well as to literature values [52]. The thermal capacity values were derived from the mentioned standards.
Figure 44: Scanning of some rock samples (limestone, dolomite, marly limestone) with the TCS meter.
The biggest challenge in predicting geothermal conditions and thermal conductivity values is that different geological units exchange very rapidly and its measured values of thermal conductivity and other geothermal parameters differ significantly. In these cases we used calculations of the average values of thermal conductivity for the entire sequence, taking into account the measured thermal conductivity of the individual key rock types and evaluating the quantity (share) of their occurrence within the entire sequence.
For example, within the geological unit Pseudozilje formation, tuffite, sandstone and mudstone are in alternation at the level of individual layers. Thermal conductivity (휆) was measured on each of the three rock types, the ratio of the rocks or the proportion of each rock within the formation was determined, and the average thermal conductivity for the entire sequence of the Pseudozilje formation was estimated. Similar calculations were also made for values of the volumetric heat capacity (휌푐) of the rocks.
The lithology was interpreted down to a depth of 100 m, which is a typical value for BHEs. With this respect, the geometry of geological unit boundaries and tectonic contacts were taken into account as well as relations between different lithologies. Values of thermal conductivity and capacity were
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therefore estimated as the depth-weighted average values of thermal conductivity 휆 and thermal capacity 휌푐 for each rock type, according to a simplified lithological distribution.
The measured values of thermal conductivity are summarized in Table 8 by types of rocks in the Municipality of Cerkno. The measured thermal conductivity for individual rock types in certain geological units is not enough for planning the extraction of NSGE. Because of the rapid alternation in lithological variations within a single unit, we must take into account the thermal conductivity of all the rock types that occur in sequence or that may be drilled by the planned BHE. Volumetric heat capacity values were derived from the mentioned standards. Generally this parameter does not show large ranges, since the values are between 1.8 and 2.9 MJm-3K-1 for all present rock sequences (Table 8).
Table 8: Measured thermal conductivity of rock samples from the Cerkno area with associated volumetric heat capacity.
Mean Calculated measured Thermal Rock type Thermal Location Capacity Conductivity (MJm-3K-1) (Wm-1∙K-1) Cerkno and immediate surroundings dolomite 3.758 2.4 – 2.9 Košec dolomite 5.598 2.4 – 2.9 Magajna dolomite 5.329 2.4 – 2.9 W of Homec hill dolomitized limestone 3.034 2.5 – 2.6 Hotel Cerkno limestone 2.637 2.1 – 2.4 Rače, along the creek marl to limestone, tectonized 1.968 2.2 – 2.3 Rače, along the creek limestone 2.360 2.1 – 2.4 Saint Jernej black limestone, marly, coalish 2.007 2.1 – 2.4 Saint Jernej limestone, tectonized 2.508 2.1 – 2.4 along road to Labinje marly limestone 2.818 2.2 Na mlin black limestone 2.961 2.2 Homec hill tuff, seriticized & lithocryst. 3.181 2.22 Maketon tuff, of keratophyre & porphyre 4.044 2.2 Maketon sandstone & siltstone 1.954 1.8 – 2.5 Strana siltstone to mudstone 1.952 1.7 – 2.3 Brdca sandstone 2.746 1.8 – 2.6 Brdca, at monument shaly claystone 1.843 1.7 – 2.4 Kacan quartz conglomerate 4.830 2.1 – 2.3 Mlin quartz sandstone w. conglomerate 3.908 2.0 – 2.3 Mlin Wider Cerkno municipality area shaly claystone 1.892 2.1 – 2.4 Jesenica siltstone & shaly claystone 1.775 1.8 – 2.4 Črni Vrh siltstone 3.428 1.7 – 2.4 Otalež tuff sandstone 2.447 2.25 Črni Vrh quartz sandstone 5.304 2.14 – 2.26 Črni Vrh tuff 2.999 2.2 Gorenji Novaki tuff 2.320 2.2 Ravne
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Mean Calculated measured Thermal Rock type Thermal Location Capacity Conductivity (MJm-3K-1) (Wm-1∙K-1) diabase 2.948 2.1 – 2.4 Zakriž limestone 2.755 2.1 – 2.4 Jesenica dolomite, thin-bedded 4.119 2.4 – 2.9 Kojca dolomite, massive crystal. 5.593 2.4 – 2.9 Žabče dolomite, bedded 4.837 2.4 – 2.9 Želin
The results of the measurements of the ground thermal properties are reported in Figure 45 (thermal conductivity) and Figure 46 (thermal capacity).
Figure 45: Map of the thermal conductivity (흀) in Cerkno.
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Figure 46: Map of the thermal capacity (흆풄) in Cerkno.
5.2.2 Ground temperature For the ground-surface temperature map, temperatures profiles from 458 boreholes in Slovenia were processed. The boreholes’ temperature profiles (T-z) they were classified according to their position (continental and coastal region of Slovenia) and to their exposition to solar irradiation (S - sunny location, facing south, open space, and T - facing north, dark-shadow position, in the woods).
Linear correlations with the altitude were found (Figure 47), with the GST (soil temperature at 2 cm depth) about 1°C higher than the annual mean air temperature, and a high resolution GIS layer (25 x 25 m) was derived based on a DTM.
The resulting spatial distribution of undisturbed ground temperature (푇0) is reported in Figure 48.
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Figure 47: Dependence of temperatures from thermograms (black), GSTs (red) and air temperatures (green) in continental Slovenia on ground elevation.
Figure 48: Map of the undisturbed ground temperature (푻ퟎ) in Cerkno.
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Typical mean annual soil temperatures are between 5.6°C at an altitude of about 1250 m (Črni Vrh) to 10°C at an altitude of 263 m at Želin. In the Ravne area (712 m) it is 8°C, at Kojca (639 m) 8.3°C, and at the Cerkno Hotel (316 m) it is 9.8°C. The surface heat-flow density q was calculated correctly only at the location of the Ce-2/95 deep well with a value of 0.054 W/m2. The value of q is probably slightly reduced from Cerkno towards higher areas (0.050 W/m2), but this is only a prediction based on a reduced geothermal gradient in the upper 500 to 1000 m of rock, where it is affected by the penetration of meteoric water, especially in more fractured rocks.
5.2.3 Length of the heating season Due to the cold climate of the area, HVAC systems are expected to operate only (or mostly) in the heating mode. For this reason, the length of the heating season was estimated based on local climate data, in particular with Heating Degree Days (HDD). There are different definitions of HDD, depending on the maximum threshold of temperature (e.g., 12°C for the Italian norm) and on the reference indoor temperature (e.g. 20°C for the Italian norm and 65°F=18.3°C for the ASHRAE [53]).
A previous study by the Meteorological Office of ARSO (Environmental Agency of Slovenia) [26], was based on calculating the Heating Degree Days (HDD) according to the Slovenian norm. The results are reported in Table 9, and ASHRAE HDD are reported too. The warmest town in Slovenia is Portorož, in Istria, with 1955 HDD (according to ASHRAE) and a heating season length of 191 days (28th October – 6th May), while the coldest site is Kredarica at 2515 m a.s.l., with 7386 HDD which makes it necessary to keep heating plants always switched on. The main settlement of Cerkno (2764 HDD) is located in an intermediate climate zone, similar to Maribor (2848 HDD), for which a heating season of 242 days (25th September – 24th May) is foreseen.
Figure 49: Map of the Heating Degree-Days (with reference to 20°C) in Slovenia. Edited from Ref. [26].
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Table 9: Climatic data of some Slovenian towns and cities. Modified from Ref. [26].
Beginning End HDD Duration HDD (ref. heating heating Location ASHRAE (ref. heating 20°C) season season 18.3°C) season (d) (mm/dd) (mm/dd) Ljubljana 3301 2878 234 01/10 22/05 Kredarica 7877 7386 365 01/07 01/06 Rateče 4737 3552 327 30/07 21/06 Maribor 3341 2848 242 25/09 24/05 Murska Sobota 3501 2832 250 21/09 28/05 Novo Mesto 3381 2819 244 24/09 24/05 Postojna 3705 3029 285 02/09 13/06 Portorož 2109 1955 191 28/10 06/05
A clear correlation is observed between the duration of the heating season and the number of HDD according to the ASHRAE norm, as reported in Figure 50. According to this correlation, all locations with HDD>4157 (ASHRAE) have a heating season of 365 days, i.e. the heating system has to be switched on throughout the year.
Figure 50: Scatterplot of the correlation of the heating season duration (풕풄) with the number of Heating Degree Days (ASHRAE).
As it commonly occurs, HDD and ground elevation in the settlements of Cerkno municipality show a strong correlation (Table 10). For this reason, we assigned the duration of the heating seasons according to altitude was set:
- 푡푐 = 240푑 for elevations below 500 m a.s.l.; - 푡푐 = 270푑 for elevations between 501 and 700 m a.s.l.; - 푡푐 = 300푑 for elevations above 700 m a.s.l.
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As it commonly occurs, HDD and ground elevation in the settlements of Cerkno show a strong correlation (Table 10). For this reason, we assigned the duration of the heating seasons according to the altitude:
- 푡푐 = 240푑 for elevations below 500 m a.s.l.; - 푡푐 = 270푑 for elevations between 501 and 700 m a.s.l.; - 푡푐 = 300푑 for elevations above 700 m a.s.l.
Table 10: Heating Degree Days in the main settlements of Cerkno, calculated with the Eurostat and the ASHRAE method.
HDD HDD Name Altitude Eurostat ASHRAE CERKNO 332 2976 2764 Šebrelje 639 3235 3314 Gorenji Novaki 754 3319 3283 Dolenji Novaki 628 3124 3308 Zakriž 588 3103 3189 Bukovo 709 3101 3389 Ravne pri Cerknem 684 2997 3513 Podlanišče 789 3475 3735 Planina pri Cerknem 601 3399 3129 Otalež 598 2703 3059 Straža in Želin 252 2620 2381 Plužnje 477 2705 2850 Lazec 566 3061 2974 Jazne 681 2765 3068 Labinje 628 3038 3247 Trebenče 453 3100 2928 Poče 653 3425 3350 Gorje 577 3212 3189 Reka 253 2699 2311 Jesenica 698 2994 3389 Čeplez 564 3084 3150 Poljane 501 3155 3062 Orehek 542 2994 3092 Travnik 287 2966 2402 Cerkljanski Vrh 836 3754 4136 Zakojca 708 3490 3429 Laznica 541 3100 3116 Jagršče 658 3075 3341 Police 550 2887 3141 Podpleče 724 3483 3450
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Figure 51: Duration of the heating season (풕풄) in Cerkno: 240 days/year (violet); 270 days/year (green); 300 days/year (red).
Figure 52: Duration of the heating season (풕풄) in Cerkno: 240 days/year (violet); 270 days/year (green); 300 days/year (red).
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5.2.4 Results The spatial distribution of the closed-loop geothermal potential is shown in Figure 53. The geothermal potential 푃퐵퐻퐸 ranges from 8 to 15 MWh/year, and most of settlements have a potential between 8 and 10 MWh/year. Higher values are found in the area covered by highly conductive dolomite (4 to 4.8 Wm-1K-1) in the villages of Bukovo (15 MWh/year), Orehek and Reka (14 MWh/year), Jagršče, Police and Jazne (12 MWh/year). Generally speaking, the high thermal conductivity of the ground compensates the effect of the relatively low ground temperature, and hence the shallow geothermal potential has quite high values for this mountain area.
Table 11:Values of geothermal potential estimated in the 30 settlements of Cerkno municipality.
Name Population Potential (MWh/year) Cerkno 1523 9.5 Šebrelje 289 8.1 Gorenji Novaki 232 8.7 Dolenji Novaki 211 9.7 Zakriž 185 8.5 Bukovo 179 15.0 Ravne pri Cerknem 163 8.7 Podlanišče 148 8.3 Planina pri Cerknem 135 10.1 Otalež 133 9.8 Straža in Želin 119 10.1 Plužnje 116 10.7 Lazec 112 10.1 Jazne 111 12.1 Labinje 90 8.7 Trebenče 88 10.6 Poče 87 9.6 Gorje 82 9.3 Reka 79 14.0 Jesenica 78 9.2 Čeplez 73 9.6 Poljane 72 8.8 Orehek 69 14.1 Travnik 59 10.7 Cerkljanski Vrh 58 8.1 Zakojca 47 8.8 Laznica 39 9.8 Jagršče 27 12.7 Police 22 12.5 Podpleče 18 7.9
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Figure 53: Map of the closed-loop shallow geothermal potential 푷푩푯푬 (MWh/y) in Cerkno.
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5.3 Conclusions Presented is the assessment and mapping of closed-loop shallow geothermal potential in the municipality of Cerkno, a mountain town in Slovenia. The shallow geothermal potential is here defined as the quantity of heat which can be efficiently exchanged using a BHE with a certain length, depending on the ground thermal properties and on the utilization profile. The input distributions of ground thermal conductivity and capacity were derived from detailed geological maps and on laboratory measurements on field samples. A length of 100 m was considered for the BHE, and ground thermal properties were therefore evaluated for the same depth.
The resulting map highlights that the closed-loop geothermal potential is quite high for a mountain area, since it ranges between 8 MWh/year and 10 MWh/year with even higher values, i.e. up to 15 MWh/year, observed in the western part of the municipality which is covered by a highly conductive dolomite, here and there only seldom in exchange with other rock types down to 100 m depth.
All the maps about this pilot area reported in this section can be downloaded from this link: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/ o viewed through this one: http://greta.eurac.edu/maps/179/embed.
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6 NSGE mapping in Oberallgäu (Germany)
In this section, the German case study area is presented. In the beginning, the surveyed area is introduced geographically. Then, the derived input data for the open-loop potential assessment is presented. This section is thematically divided into the geological modelling of the valley sediments and the results of the hydrogeological measurement campaign. The main section will display the open loop potential assessment results in the valley, followed by conclusions.
The closed-loop geothermal has not been mapped since it is already assessed in the entire state of Bayern (see also Figure 54) and it is available at: http://www.umweltatlas.bayern.de/mapapps/resources/apps/lfu_angewandte_geologie_ftz/index.h tml?lang=de&layers=service_ageo_18
Figure 54: Screen shot of the Bavarian "Umweltatlas", which displays the thermal conductivity for different depth zones and serves as major planning basis for BHE systems in Bavaria.
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6.1 The territory surveyed The Upper Iller valley is located in the south-west of Bavaria in the administrative district “Oberallgäu”. As displayed in Figure 55, the surveyed parts of the valley extent from Immenstadt im Allgäu (14,207 population) in the north, over Sonthofen (21,529) and Fischen (3,151) to Oberstdorf (9,697) in the south. The geography of the project area is determined by the river Iller and extents 20 km in length and 1 to 3 km in width. The shape of the project area (approx. 30 km2) comprises the extent of the valley’s shallow aquifer. It’s topographic surface declines from 850 m a.s.l. south of Oberstdorf to 720 m a.s.l. at Immenstadt. In Oberstdorf at an altitude of 813 m a.s.l the precipitation counts 1742 mm at a mean temperature of 6.6°C.
Figure 55: Geographical overview of the Oberallgäu and the Upper Iller valley.
6.1.1 Geological setting Geologically, the Upper Iller valley is located on the northern fringe of the Allgäu Alps. In the Alpine and pre-alpine area of the Oberallgäu, two major geological layers, a deeper and an upper layer, can be differentiated. The deeper layer consists of consolidated sedimentary rocks from the Triassic, Jurassic, Cretaceous and Tertiary period. On top of this bedrock layer the Quaternary sediment layer can be found, which filled the glacier carved erosion surface of the valley.
The main interest of the conducted 3D geological modelling was to distinguish the hydro-geologically relevant units within the Pleistocene and post-Glacial deposits of the Quaternary valley filling. The Quaternary deposits reach from well-sorted glaciofluvial gravels to glacial-lacustrine sediments that can be silt, clay, marl and sand. The mostly loosely bedded gravels that, which were deposited by meltwaters, provide excellent supplies of groundwater. Hence, the glacial and fluviatile gravel deposits in the Alpine valley are of local and regional importance for the water resource management and the public drinking water supply. On the contrary, the Glacial-lacustrine sediments are the main groundwater confining units in the valley and a spatial knowledge on their extent and depth is crucial for potential evaluations.
In the 3D modelling, spatial information on bedrock, older gravel, older clay, younger gravel and younger clay was processed (Figure 56). The older deposits are pre-Würm glacial sediments, which are
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predominantly from the Riß-age. The younger sediments were deposited from the Würm-Glacial to the young Holocene. As the cross-section in Figure 56 displays, the Quaternary valley fillings can reach remarkable thickness. The bedrock in the northern basin near Sonthofen, for example, is 150 m below surface. In the basin relief lakes formed and silted up accompanied by typical sequences of delta deposits. A characteristic of this sedimentation process is the interlocking of lacustrine clays, delta forest beds and fluviatile deposits. However, due to a lack in spatial resolution of the geological data, this interlocking is not resolved in the 3D model.
The northern drainage of the valley is hampered by Molasses sediments, the so-called “Greggenhofner Molasseriegel”, which is located northeast of Immenstadt and acts like a confining barrier. Therefore, the northern part of the valley sediment is dominated by lacustrine deposits. In the south end of the valley, instead, the proximity to the Glacier’s delivery area, causes the gravel units thickness increase.
The creation of the geological surfaces was based on borehole logs, profiles from seismic refraction surveys, geological maps and Diploma mapping campaigns by TUM students (Figure 57). The interpolation was performed with the Discrete Smooth Interpolation (DSI) in SKUA GOCAD. The surface of the older and younger clay layers was used to derive saturated groundwater thickness for the assessment of open loop potentials in the first groundwater storey.
Figure 56: Geological cross section through the Upper Iller valley from south to north.
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Figure 57: Hydrogeological characterisation of the valley’s surrounding bedrock and seismic cross sections for the 3D modelling.
6.1.2 Hydrogeological setting On the 10th of August 2017, the Chair of Hydrogeology carried out a reference date measurement in the Upper Iller valley aquifer. Previously, an exhausting database update of registered wells was conducted. All 196 investigated wells have been visited and at 148 groundwater wells a water level and temperature measurement was possible (see Figure 58 b). In the hole valley the river Iller has a very good connection to the groundwater. Discharge measurements of the Iller proved that highly heterogeneous and variable infiltration and exfiltration processes strongly influence the hydraulic conditions in the aquifer [54]. In sections, the Iller changes from 1760 ls-1m-1 infiltration to 555 ls-1m-1 exfiltration within 3 km distance. This displays the relevance of surface water measurements. We integrated the hydraulic influences from surface water interactions by adding 53 surface water points to the measurement campaign. Other rivers, like the Ostrach north of Sonthofen, have a clogged river bed and infiltrate from an elevated position through the vadose zone. A similar situation is present at the river Stillach west of Oberstdorf.
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Figure 58: a) Groundwater contours and hydraulic gradient and b) saturated groundwater thickness in the Upper Iller Valley aquifer.
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Figure 59: a) Depth to water and b) groundwater temperature in the Upper Iller Valley aquifer.
The results of the measurements are shown in Figure 58. 75/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
The saturated groundwater thickness given by the subtraction of the groundwater table, shown in Figure 58 a, and the elevation of the first clay layer, as described in section 6.1.1. The results show, that the groundwater thickness in most parts of the upper Iller valley are above 10 m. Especially in the southern part around Oberstdorf, where no separating clay layer exists between younger and older gravels, aquifer thickness rises up to 100 m (see Figure 56). Low aquifer thickness values can be observed north of Sonthofen, because the lacustrine clay has been deposited in the former Pleistocene lake at this location. However, a layer of Holocene fluviatile gravel accumulated on top of the thick clay layer and serves as a thin aquifer (see Figure 56).
In addition, we calculated the depth to water with the groundwater table and the DEM (digital elevation model) in the resolution of 25 m. Due to few available measurement points in the area of Oberstdorf, the results of the southern parts are not very resilient. This knowledge gap was discussed with local geologists and the available measurement points have been integrated into a hydraulic model concept of the area. Users of the maps should pay attention to the varying data basis and the related uncertainties. However, in most parts of the upper Iller valley, enough wells have been measured to interpolate the groundwater table in a sufficient way. The valley’s groundwater table shows gradients within typical ranges: 1st Quartile of 0.37 %, 3rd Quartile of 0.69 % and a median of 0.50 %, which leads to Darcy velocities of approximately 0.5 m/d.
Supplementary to the surface water and well measurements, the inflow of conductive fissured, karstic and porous aquifers from the consolidated rocks at mountain slopes have been accounted in the hydraulic model concept (c.f. Figure 57). The interpolation of the groundwater contour map was performed with universal kriging. A spherical function with a sill of 50, range of 4000 and anisotropy factor of 0.8 in 25° direction was fitted in a variogram analysis. A cross validation showed a mean deviance of -0.16 m to the measured points.
Figure 57 a displays the groundwater temperature distribution. In wide areas, a typical groundwater temperature range of 8°C to 11°C was measured. In proximity to the Iller the temperature increases according to the surface water temperature of 11.4 to 11.6 °C. Thus, the aquifer’s temperature reflects the partially strong surface water infiltration. Noticeable are also elevated temperatures downstream of bigger lakes. Due to the strong thermal interaction of surface water and groundwater, designers of open loop systems should pay attention to potentially low temperatures near the river Iller in winter and spring. Shallow wells and missing technical adaptions may even cause heat pump failures.
Subsequently, the data of 38 valid pumping tests was gathered from archives of local geological offices. The tests, mainly conduced in the valley’s alluvial gravel, have been analysed and classified with a quality rating. The evaluations were carried out with five different evaluation methods. The data from the drawdown is evaluated with Theis for confined aquifers and with Theis with Jacob correction for unconfined aquifers. The data under steady state condition was evaluated in confined aquifers with Thiem with Sichardt and for unconfined aquifers with the Dupuit Thiem with Sichardt method. Regarding the data from the recovery the Theis & Jacob method was used. Considering the quality classification and the spatial and geological categorisation a representative mean hydraulic conductivity was calculated as 2.69∙10-3 m/s with a standard deviation of 8.25∙10-3 m/s. The calculated hydraulic conductivities serve as an important basis for the following potential assessment. 76/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
Unfortunately, the evaluated pumping tests have been locally clustered around the area of Sonthofen. Therefore, we abstained from a spatial interpolation of the conductivities and applied a conservative global value of 1∙10-3 m/s in the potential analysis. Given the mentioned standard deviation and mean, the value reflects our evaluation results and is further in line with the conservative value published by the Bavarian environmental agency for this area [55]. 6.2 Open-loop geothermal potential The open loop potential of the upper Iller valley has been calculated for well pairs with a distance from extraction to injection well of 10 m and 100 m. The main result of the potential assessment is the technical volume flow. The calculated volume flows offer sustainable and conservative values, where a severe drawdown (extraction well), a groundwater rise (injection well) and efficiency losses due to thermal recycling (thermal breakthrough) are excluded. These areas are mapped respectively in yellow, blue and green in the maps in Figure 61. As described in Chapter 3.2, the potential assessment uses the conservative event of a hydraulic breakthrough to prevent thermal recycling.
In general, the presented potential assessment results do not substitute on-site investigations of the local groundwater conditions in the planning phase of a GWHP system. In addition, the potentials are displayed in maps of 20 m resolution, where an aggregation of values for spatial queries is prohibited.
Figure 61 shows the map of constraining effects and the map of the technical volume flow potential for 10 m well distance (see Figure 61a) and 100m well distance (see Figure 61b). Since a well distance of 10 m is not far, interflow of groundwater between the pair of wells would occur soon. For this reason, the hydraulic breakthrough threshold constraints the technical volume flow nearly everywhere in the upper Iller valley for this low well distance (see Figure 61a, left). Only in a small sector in the north, where the aquifer thickness is very thin, a drawdown of 1/3 of the thickness occurs before the hydraulic breakthrough. This effect is amplified for well distances of 100 m (see Figure 61b, left). The greater distance of the wells leads to higher values before a hydraulic breakthrough would happen. Therefore, the drawdown threshold constraints a larger area. In addition, the injection threshold prohibits a further rise of the groundwater table in areas of low depth to water. In the central part of the upper Iller valley and in northern parts this threshold becomes the limiting factor. Especially in swampy regions, technical measures to distribute infiltration or injection (i.e. discharge into rivers, if allowed, or multiple injection wells) can help to prevent a harmful groundwater table rise for larger open loop systems.
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Figure 60: a) The locally active constraints and b) technical volume flow potentials of the upper Iller valley for well pairs with 10 m distance.
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Figure 61: a) The locally active constraints and b) technical volume flow potentials of the upper Iller valley for well pairs with 100 m distance.
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In general, Figure 61 displays that the upper Iller valley provides quite suitable hydrogeological conditions for open loop systems. Only in the area near Blaichach (northern sector), where the Quaternary deposits change from gravel to clay, thin Holocene gravels might prevent the installation of larger uses.
Figure 62: Volume flow for an extraction well at a drawdown of one third of the saturated aquifer thickness (left) and volume.
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A more detailed view on the open-loop potential is provided in Figure 62, representing the maps of maximum pumping rates at 1/3 drawdown (Figure 62, left) and the map of maximum injection rates till the groundwater rises up to 0.5 m below surface (Figure 62right). In this representation, the volume flows are calculated independently from the wells distance and a hydraulic breakthrough limit is not considered.
The extraction rate at the drawdown limit (Figure 62, left) is dependent on the hydraulic conductivity and the square of the aquifer thickness (Chapter 3.2). As described in section 6.1.2, a global hydraulic conductivity value was used. Thus, only the influence of the aquifer thickness becomes spatially visible. Except for the clay-dominated area in the north, thick saturated zones lead to very high values for a maximum extraction. This result is covered by pumping tests at the drinking water well of Ortwang (in the drinking water protection area north of Sonthofen), which is capable of delivering sustainable extraction rates of up to 200 L/s. Since, the applied hydraulic conductivity was set to a conservative value of 1∙10-3 m/s, on-site investigation will always provide a refined information and may lead to improved extraction rates.
The right map of Figure 62 shows the injection potential, which is mainly dependent on the local depth to water. Around Oberstdorf (south) and around the river Ostrach in Sonthofen (east), very high depths to water prevent problems with injection limits. Lower depths to water have been observed in the central part of the valley and near Blaichach (north). In those areas, the designer of open loop systems should be aware of the naturally high fluctuations in the groundwater table. Especially in spring with an increased runoff, due to snow melting, and a still high heating demand, an increased rise of the groundwater table should be considered for injection wells of larger open loop systems. It is worth a note that a remaining uncertainty in the calculated depth to water value results from the used 25-m resolution DEM, which can have biases in woodlands or densely build areas.
The technical volume flow rates of 10 m well distance are further used to determine a local value of extractable geothermal power and geothermal energy (c.f. Figure 63). The geothermal power (c.f. Figure 63, left) was calculated for a temperature difference at the heat pump of five Kelvin (K) with Equation 20. If the required heating power of a house is known, the displayed geothermal power [kW] can be used with an estimated seasonal performance factor of the heat pump to derive the possible thermal power of the GWHP system. Since the values of the volume flow map are only multiplied with constants, the map shows the same relations as explained for the technical volume flow map for 10- m well distance.
In addition, we calculated the extractable geothermal energy for 5K temperature difference and 2000 hours of full load operation per year. 2000 hours represent an intermediate value taken from the VDI 4640, which suggests a range of 1800 h to 2400 h of full load hours.
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Figure 63: a) Geothermal power of a well pair with 100 m distance at a 5 Kelvin temperature difference and b) the resulting geothermal energy for 2000 hours of full load operation per year.
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Figure 64: a) Geothermal power of a well pair with 100 m distance at a 5 Kelvin temperature difference and b) the resulting geothermal energy for 2000 hours of full load operation per year.
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6.3 Conclusions For the case study area of the Upper Iller valley, a quite suitable situation for the use of shallow geothermal energy with open loop systems was found. The prevalent Pleistocene and Holocene gravels offer a very conductive porous medium for a highly productive aquifer. During and after the ice-ages, thick layers of gravel have been deposited, which nowadays contain a thick saturated zone of groundwater. Except for areas where the drainage was obstructed and lakes formed, as in the Blaichach area, groundwater is available for medium and large heating and/or cooling uses.
However, the open loop potential mapping also revealed areas, where installers of open loop systems have to pay attention to possible issues. The infiltration of cold surface water near rivers, a severe groundwater drawdown and an excessive rise of the groundwater table are among the identified issues. At locations, remote from surface water influences, the groundwater showed a typical temperature range of 8°C to 11°C, which is suitable for the operation of GWHP systems.
All the maps about this pilot area reported in this section can be downloaded from this link: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/ or viewed through this one: http://greta.eurac.edu/maps/183/embed.
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7 NSGE mapping in Parc des Bauges (France) 7.1 The territory surveyed The parc naturel régional du Massif des Bauges is a regional natural park, located in the northern western Alps of France, both on Savoie and Haute-Savoie Departments. It encompasses 64 local communes that make up about 70,000 inhabitants. The Park territory covers diverse areas: from rural communes located in the park heart to urban and residential areas on outer edges of the park, with stronger links to the major agglomerations of Chambéry and Annecy (see Figure 65). Along with these two agglomerations, the park is committed in a TEPOS (positive energy territory) process aiming a local production of renewable energy greater than the energy consumption by 2050. Therefore, mapping geothermal potential in this area is a useful activity for the implementation of renewable energy resources maps. In particular, the geothermal potential has been assessed in four of the most populated municipalities of the park: Sévrier (4156 inhabitants), Faverge-Seythenex (7592 inh.), Saint- Pierre-d’Albigny (3936 inh.) and Montmelian (4112 inh.), making up almost 20,000 inhabitants.
Figure 65: Bauges regional natural park. Source: http://wiki.coop-tic.eu/wikis/rezozh73/wakka.php?wiki=PagePNRMB
7.1.1 Geological setting The Bauges massif is one of the subalpine massifs that exists along the western edge of northern French Alps. It is mainly made of folded and faulted, carbonated sedimentary rocks, with an increase of deformation to the east. In its western part (Revard, Semnoz and Margériaz chains), the Bauges
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massif reveals asymmetric reliefs (west steep slopes, east regularly dipped ones) induced by the geological structure of Jurassic and Cretaceous formations in folds recumbent to the East. In its eastern part, the Bauges massif presents steeper reliefs in relation to more intense rock deformation (more folds, numerous faults) induced by the vicinity of the alpine thrust front. The Bauges massif is bounded by obvious physical features. To the West, an important scarp, more than 1000 m in height, marks the boundary with the molassic foreland and its low altitudes (200 to 300 m above sea level). It represents the front of Bauges Cretaceous and Jurassic formations thrusting on the Oligo-Miocene perialpine molassic infilling. To the East, the Bauges massif is recognized up to the Isère valley that corresponds to the western boundary of external crystalline units of the western Alps (Lauzière and Belledonne massifs). Northern and southern boundaries of the Bauges massif are located in transverse valleys that are strongly incised: to the North, the Annecy valley that marks the boundary with the Bornes massif; to the South, the Chambéry valley that marks the boundary with the Chartreuse massif.
7.1.2 Hydrogeological setting The Isère course runs along the southern edge of the Massif des Bauges. The average monthly flow (calculated over 41 years) of the Isère at Chamousset increases from 86.9 m3/s in January to 304 m3/s in June (Source: Banque Hydro - MEDDE). This variation reflects that the Isère is predominantly influenced by snowmelt.
During the last phases of the Quaternary, the glacial periods allowed the alpine glaciers to advance and over-dig the valleys. The warming/receding phases resulted in the formation of lakes, and the filling of these over-dug valleys. Laterally, many alluvial fans (cones) came to feed the valley with more or less coarse materials. The size of these cones varies: more than 2 km at Gilly-sur-Isère or St-Pierre- d'Albigny, 300 m at Chamousset. Their thickness can sometimes reach several tens of meters (eg. 60m at St-Pierre-d'Albigny or Jean-de-la-Porte, cf. Figure 66 a), forming deltaic deposits. These cones can nest in paleo-channels of Isere, or cover them. Depending on the deposit environment, the current subsoil has been reworked several times, notably by the Isère river, and is today composed of various sedimentary horizons, ranging from clay to pebbles, with sometimes the presence of peat and plant elements [56]. In the valley floor, the thickness of these sediments may exceed 100m. In the last years, the Isère river bed was lowered by human activity (agriculture and flood prevention). This lowering had an important impact on the aquifer flows and on the water exchange with the river. Furthermore, the aquifer is influenced by the presence of several active gravel quarry and quarry lakes.
The Isère valley has been the subject of several geophysical studies since the 1970’s. Important resistivity contrasts shown by these studies show the alternation of clay and sand-gravelly horizons, caused by the channelings of the old Isère river. As part of a master work Laroche & Tardy, 2006 [57] these old studies have been combined to propose a mapping of the gravelly paleo-channels thickness, thus potentially interfere with the ground water flow. Many reservations are though indicated by the authors of the report: heterogeneity of the practices in electrical geophysics according to the companies, different types of equipment used, different topography conditions. Furthermore, some results (for instance in Montmélian) appear to be incoherent with regard to the meanders that could have formed the Isère. This cartography is also incomplete in several urbanized sectors (e.g. above
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Montmélian center) and in geological locks (zones of tightening where the Isère was channelled by the presence of limestone and crystalline massifs).
The available information on hydrogeology in the area from Albertville to Montmélian is numerous but heterogeneous. This is the reason why some parts of the valley are not covered and are missing in the following figures. The last piezometric map of the entire area was made on data collected in September 1987 [58]. More recent maps are available, but only on portions of the Isére valley, therefore the 1987 map was used in the hydraulic gradient and depth to water table reconstruction of the valley (Figure 66b and Figure 68a). The aquifer flows globally along the axe of the valley, with a hydraulic gradient close to 2‰. The map shows that the Isère tends to drain the aquifer, even if local deviations are present (eg. at the confluence of Isère and Arc rivers).
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Figure 66: a) Saturated thickness and b) hydraulic gradient with groundwater contour lines of the shallow aquifer of the Isère Valley.
In the paleo-channels, characterised by thick gravel deposits, the wells productivity can be excellent (eg. more than 400 m3/h at Montailleur), as well as near certain alluvial fans (eg. an authorization for a 900 m3/h well in St-Jean-de-la-Porte). Outside these areas, the aquifer productivity drops drastically, as in Francin, where 6 parallel wells could not reach a total flow of 500 m3/h [59]. The transmissivity is therefore largely variable on a very local scale. Figure 67 shows the hydraulic potentiality of the aquifer, investigated since 2015 in order to identify the protection perimeters around drinking water wells. 3 classes are showbn in the map, according to Table 12, and a mean transmissivity value has been assigned to each one, according to the productivity of 15 wells of the area. The hydraulic conductivity (cf. Figure 68b) is then obtained by dividing the transmissivity by the aquifer thickness
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(Figure 66 a). Interpretations of slug tests, carried out in Grésy-sur-Isère, confirm the average values shown in this area of the map (2×10-3 m/s).
Yellow Green Blue
-3 -2 Value range Qexploitation < 25 10 < T < 10 m²/s or T > 10-2 m²/s ou Qexploitation 3 3 3 m /h Qexploitation > 25 m /h > 50 m /h Meaning Low High Really high Transmissivity value used for 10-3 m2.s-1 5 × 10-3 m2.s-1 10-2 m2.s-1 GRETA mapping Table 12: Hydraulic potentiality of the Isère Valley.
Figure 67: Spatial distribution of hydraulic potentiality of the Isère Valley.
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Figure 68: a) Depth to water and b) hydraulic conductivity table of the shallow aquifer of the Isère Valley.
Figure 69 shows the interpolation of the mean aquifer temperature measured in almost 800 wells of the surroundings (location shown in Figure 72), stored in the ADES database. The groundwater temperatures, ranging from mostly 10°C to locally 14°C, indicate natural conditions without an anthropogenic influence.
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Figure 69: Measured groundwater temperatures of the shallow aquifer of the Isère Valley.
7.2 Closed-loop geothermal potential
7.2.1 Thermal properties of the ground A cartography of the mean ground thermal conductivity between 0-100 m deep, was carried out in the four municipalities of the pilot area. The most important geological units were sampled on the study areas. 17 samples within limestones and a molassic formation could be easily sampled, unlike marls which are very poorly exposed and whose low induration prevents the preservation of the sample (Figure 70). Sample rocks are mostly limestones and marls of Jurassic and Cretaceous ages. Clay-rich or poorly indurated geological formations such as alluvium, scree or moraine were not sampled for thermal conductivity measurements. The values are taken from the bibliography including those used in the Swiss standard (SIA384/6).
Thermal conductivity and thermal diffusivity were measured by GeoZS with a thermal conductivity scanning (TCS) instrument. Sawing some of the 18 rough samples resulted in 31 samples. One interesting result is that, except for sample 6, the conductivity is rather high (> 2,3 Wm-1K-1, see Table
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13). The thermal conductivity map created according to these measures and to further geological considerations in shown in Figure 71.
Excepted for two out-layers (sample 6 and 8), values of thermal capacity of the rock samples have a really small range of variation (see Table 13) and a marginal impact on the final geothermal potential of the pilot area. Due to this very limited variation, the value of thermal capacity (ratio between thermal conductivity and thermal diffusivity), were fixed to the average value of 3.00 MJm-3K-1 in the entire pilot area.
Figure 70 : Digital Elevation Model of the park, location of 4 municipalities covered by the geothermal potential mapping an position where the 17 rock samples were collected. 92/137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
Table 13: Results of thermal conductivity and thermal diffusivity measurements.
Calculated Measured Thermal Measured Thermal mean Sample Conductivity Diffusivity thermal Rock type (lithology) Age no. (Wm-1K-1) (mm2s-1) capacity (MJm-3K-1) Mean Min Max Mean Min Max - 1 Molasse sandstone Ol2 3.263 2.858 3.737 1.140 0.479 1.939 2.86 1 2 Limestone K2 2.766 2.478 3.079 0.885 0.517 1.578 3.13 2b Limestone K2 2.937 2.733 3.370 0.952 0.596 1.295 3.09 5-6 3 Limestone with sand K1 3.255 2.811 3.618 0.965 0.516 2.009 3.37 4-5 4 Limestone K1 3.338 3.100 3.584 1.026 0.473 1.815 3.25 2 5 Limestone 1J3 2.828 2.596 3.027 1.160 0.828 1.585 2.44 1-2 6 Marl & marly K1 1.262 0.917 1.417 0.971 0.756 1.136 1.3 limestone 2- 7 Limestone 1J3 2.721 2.531 2.921 1.229 0.851 1.749 2.21 3 1-2 8 Marl & marly K1 2.365 2.210 2.494 0.559 0.350 0.796 4.23 limestone 1-2 9 Limestone J3 2.856 2.737 3.005 1.008 0.795 1.215 2.83 3-4 10 Limestone/marl with K1 3.482 3.110 3.793 0.965 0.607 1.247 3.61 sand 3-5 11 Limestone K1 3.379 3.134 3.731 1.079 0.529 1.901 3.13 1-2 12 Limestone with slight K1 2.682 2.559 2.854 0.851 0.569 1.506 3.15 clay 3 13 Limestone J3 2.837 2.583 3.121 1.005 0.440 1.725 2.82 1 14 Limestone 3J3 2.932 2.467 3.284 0.935 0.640 1.627 3.14 3 15 Marl/limestone K1 3.044 2.629 3.241 1.118 0.715 1.497 2.72 3 16 Marl K1 2.837 2.490 3.381 0.888 0.579 1.244 3.19 3 17 Marl K1 2.938 1.483 4.229 0.690 0.412 1.708 3.06 average 3.0
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Figure 71 : Map of average thermal conductivity for 100m of depth.
Taking into account the results of conductivity measurements and estimation, the geological units of the harmonized geological map were classified into four major groups of thermal conductivity, 0.4, 2.0, 2.8 and 3.4 Wm-1K-1. A simplified evaluation of the thickness (not based on a 3D geological model) of each unit with the same thermal conductivity value was carried out from expert estimates (geological section and BSS) on the depths of 50, 100 and 200 m. Weighted average values according to the thickness of the unit were placed on all the sectors and the maps were obtained by carrying out a triangular interpolation.
Uncertainties of various kinds remain and must be kept in mind as part of any subsequent interpretation of the results. The uncertainty in the results is the sum of several uncertainties which are the uncertainty in the geological formations, the uncertainty in the choice of the thermal conductivity for each lithological formation and the deep projection of these geological formations.
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The geological contours used are those of the 1:50 000 cartography, some of which are obsolete and would require mapping in the field. It is therefore necessary to take into account both the accuracy of the 50 000 (50 m) and the accuracy of the geological formations that corresponds to the difference between the cartographic model transcribed on paper and the reality of the terrain. This value is unknown but it can in some cases exceed the hundred meters. In addition, the boundary between some geological formations, alluvium for example, is not just a single feature in space, it is more of a progressive transition zone between alluvial deposits and colluviums or deposits of slopes. like screes. The deposits are in fact more or less bevelled depending on the sedimentation conditions.
The choice of thermal conductivity values, although it is argued by field sampling and thermal conductivity analysis, remains a mean indicator of the geological formation. The large geological units that have been cut off from the study areas are heterogeneous when studied in detail. Similarly, a characterization of all the lithologies was impossible with regard to the large number of different rocks. Finally, the loose formations could not be sampled for laboratory measurement. This shows a high degree of uncertainty about the value of the thermal conductivities, in particular the value of 0.4 W/(mK). The hard or soft nature of the ground is very difficult to evaluate. The values chosen are average values and it is not impossible that a value coming from the map is different from the real thermal conductivity encountered in reality.
Finally, a very high degree of inaccuracy is attributed to the extension of the formation in depth because there is no three-dimensional geological model of the Bauges massif. Thus, the variation in thickness of the lithological unit with the same characteristic of thermal conductivity is purely controlled by the choice of the interpolation method of the points between them (here a triangular interpolation). In some cases, we have considered the thickness of the geological unit as homogeneous (by default the round values like 10, 20, 50 and 100 m were chosen), which does not correspond to the reality, especially for scree, moraine deposits and alluvium, etc.
The result can therefore only be taken statistically over a large area and by homogeneous geological unit. These maps cannot be used at a cadastral scale. It is up to the expert to decide the accuracy and validity of the values provided by these cards. As it stands, the characterization of accuracy has not been the goal of this work and has not been realized and cannot be achieved without a three- dimensional geological model.
7.2.2 Ground temperature Around Parc des Bauges, many different ground temperature measurements were available, in 209 different observation points (see Figure 72). In 159 of these locations, more than 3 different measurements are available. A correlation between the ground temperature and the elevation were carried out in these 159 locations and it shown in Figure 73. The resulting temperature map is shown in Figure 74.
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Figure 72: Spatial distribution of ground temperature measurements.
Figure 73: Correlation between the measured average ground temperature and the altitude in Parc des Bauges.
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Figure 74: Estimated ground temperature in the French pilot area.
7.2.3 Length of heating season Using the Photovoltaic Geographical Information System (PVGIS) as data source, a linear correlation between the altitude (퐻) and the heating degree days referred to 18°C (HDD) was developed using 20 different location around Parc des Bauges (Figure 75). Later, a correlation between the length of the heating season (푡푐) and the number of HDD was implemented. The result is shown in Equation 23 and it is very similar to the Equation 22 adopted for the Aosta Valley, with a sligthly lower influence of the altitude and a higher fix value, probably due to the higher latitude and the consequent colder climate of the area. Resulting map is shown in Figure 76.
푡푐 = 156 + 0.093 ∗ 퐻 Equation 23
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Figure 75: Calculated relation between HDD and the altitude.
Figure 76: Map of the estimated length of the heating season.
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7.2.4 Results The map of the closed-loop geothermal potential of the four selected municipalities of Parc des Bauges is shown in Figure 77 (general view) and in Figure 78 (municipality level). The range of values shown in this map is quite big, if compared to the limited surface. This is mainly due to the detailed analysis of the mean Thermal Conductivity, especially over the alluvial deposits. Over these deposits, in fact, values are lower than 10 MWh/y, while on the valley slopes, values rise up to 15 MWh/y. Lower values (5.5÷7 MWh/y) are reached over the Isére plain in the municipalities of Montmelian and Saint-Pierre- d’Albigny.
Figure 77: Geothermal potential referred to BHE of 100m in the municipalities of Montmelian, Saint-Pierre-d’Albigny, Sevrier, Faverger-Seythenex.
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A B
Figure 78: Geothermal potential in Sevrier (A),Faverges-Seythenex (B), Montmelian and Saint-Pierre-d’Albigny (C).
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7.3 Open-loop geothermal potential The structure and relevance of the different potential assessment results are explained in detail in section 4.3 (open loop mapping of the Aosta valley). In line with the other case study areas, the technical volume flow potential of the Isère Valley has also been calculated for well pairs with a distance from extraction to injection well of 10 m and 100 m. The spatially active volume flow constraints are mapped respectively in yellow (1/3 aquifer drawdown reached), blue (groundwater rise to 0.5 m below surface reached) and green (hydraulic breakthrough reached) in the maps (see Figure 79 a). As described in section 3.2, the potential assessment uses the more conservative event of a hydraulic breakthrough to prevent thermal recycling.
Figure 79: a) The locally active constraints and b) the technical volume flow potentials of the Isère Valley for well pairs with 10 m distance.
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Figure 80: a) The locally active constraints and b) the technical volume flow potentials of the Isère Valley for well pairs with 100 m distance.
Like in the Aosta valley and the Upper Iller Valley, constraining effects and technical volume flows have been calculated for a well distance of 10 m (see Figure 79) and a well distance of 100 m (see Figure 80). Since lower well distances lead to an earlier hydraulic breakthrough, also the related constraints become differently active. Figure 79 a (10 m well distance) shows a similar pattern compared to the results of the Aosta and the Iller valley. Since the saturated thickness and the hydraulic conductivity are rather high, the hydraulic breakthrough threshold entirely constraints the technical volume flow. For well distances of 100 m, areas of lower saturated thickness and hydraulic conductivity are constrained by a drawdown limit (see Figure 80 a). Additionally, pumping rates in areas with a lower depth to water are limited by the injection threshold.
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In consequence, the technical volume flows in Figure 79 b show influences of aquifer thickness, hydraulic conductivity and hydraulic gradient variations. Especially the combination of higher hydraulic gradients and saturated thickness leads to elevated volume flow potentials in the channelling structures of the valley. This is also the case for the larger well distances (cf. Figure 80 b). It can be concluded that the Isère Valley provides suitable hydrogeological conditions for the thermal use of groundwater, also for larger system sizes.
Figure 81: a) The volume flow for an extraction well at a drawdown of one third of the saturated aquifer thickness and b) the volume flow of an injection well with a threshold groundwater table rise of 0.5 m to the surface.
A more detailed view on the potential is provided by the map of maximum pumping rates at 1/3 drawdown (Figure 81 a) and the map of maximum injection rates till the groundwater rises up to 0.5 m below surface (Figure 81 b). The maps represent the result of an application of Equation 16 and 103/ 137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
Equation 18, respectively. The calculated volume flows only consider the extraction or the injection well independently from the well distance and a hydraulic breakthrough limit is not considered.
The drawdown constraint is related to the hydraulic conductivity and the square of the aquifer thickness (c.f. section 3.2). As anticipated, for Isère Valley those values are comparatively high and therefore also the related pumping rate estimations. The injection potential map, shown in Figure 81 b, is mainly influenced by the depth to water variation. Most of the evaluated area has sufficient depth to water values of 2-5 m.
The technical volume flow rate results are further used to determine a local value of extractable geothermal power and geothermal energy (c.f. Figure 82 and Figure 83). The geothermal power was calculated for a temperature difference at the heat pump of five Kelvin (K) with Equation 20. If the required heating power of a house is known, the displayed geothermal power [kW] can be used with an estimated seasonal performance factor of the heat pump to derive the possible thermal power of the GWHP system. In addition, we calculated the extractable geothermal energy for 5K temperature difference and 2000 hours of full load operation per year(c.f. Figure 82 b and Figure 83 b). 2000 hours represent an intermediate value taken from the VDI 4640, which suggests a range of 1800 h to 2400 h of full load hours.
In general, the presented potential assessment results do not substitute on-site investigations of the local groundwater conditions in the planning phase of a GWHP system. In addition, the potentials are displayed in maps of 20 m resolution, where an aggregation of values for spatial queries is prohibited.
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Figure 82: a) The geothermal power of a well pair with 10 m distance at a 5 Kelvin temperature difference and b) the resulting geothermal energy for 2000 hours of full load operation per year.
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Figure 83: a) The geothermal power of a well pair with 100 m distance at a 5 Kelvin temperature difference and b) the resulting geothermal energy for 2000 hours of full load operation per year.
7.4 Conclusions The closed-loop geothermal potential map, shown in Figure 77, is based on data collected by the geological survey of France [60]. The approximations adopted for the G.POT method application are the following:
- Undisturbed soil temperature has been estimated , with a linear correlation between altitude and mean measured ground temperature values according to Figure 73; - Length of heating season is linearly related with the quote (Equation 23);
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- Thermal conductivity has been assessed according to laboratory measurements and a detailed study of the thickness, and direction of geological units and superficial deposits - Thermal capacity has been considered constant all over the territory (3.0 MJ/(m3K))
The maps of Figure 78 show a deep influence of the sediment cover thickness on the closed-loop geothermal potential. In high altitude areas, where this cover is very reduced, the good thermal conductivity values of the rocks allow to reach very good geothermal potential values. In particular, in Saint-Pierre-d’Albigny this difference is evident: over the lateral valley slope, values are almost double than in the bottom.
Globally, in this area, where higher values are present in high altitude areas, we can observe how the effect of a longer heating season and good thermal conductivity has a greater impact on the geothermal potential than the ground temperature, which is in contrast lower in these areas than in the valley bottom.
The Isère Valley offers suitable conditions for the thermal use of groundwater. The combination of a conductive porous medium and generally a high (>10 m) saturated groundwater thickness support the extraction of groundwater. In addition, the Isère Valley has low but for injection still adequate depths to water. This makes the resource groundwater accessible in an economic way. At locations, remote from potentially unwanted surface water influences, the groundwater showed a typical natural temperature of 9°C to 11°C, which is suitable for the operation of GWHP systems. An excessive drawdown or groundwater table rise could affect larger systems only in minor parts of the area (see Figure 80 a).
All the maps about this pilot area reported in this section can be downloaded from this link: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/ o viewed through this one: http://greta.eurac.edu/maps/178/embed.
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8 NSGE mapping in Saalbach-Leogang (Austria) 8.1 The territory surveyed Leogang and Saalbach-Hinterglemm are two municipalities located in the far west of the province of Salzburg, bordering Tyrol. Both municipalities are located in west – east oriented valleys, to the north lies the Leogang valley with the river Leoganger Ache and to the south the Glemmtal with the river Saalach, in which the Leoganger Ache flows into.
Settlements are located in altitudes of about 800-1.000 m and host roughly 6000 inhabitants. The region belongs to the Kitzbüheler Alps with the highest peak, the “Birnhorn”, at 2,634 m altitude and hosts one of the largest skiing resort in Austria. Considering that the two municipalities record more than 2 million guest nights every year, it is clear that tourism is an important economic factor for the whole region.
8.1.1 Geological and hydrogeological setting The Case Study area is located in the geological unit of the Austroalpine. The E-W striking Leogang valley represents the geological boundary between the Northern Calcareous Alps with their sandstones, conglomerates and carbonates to the north and the Greywacke Zone the with its sand-, silt- and claystones to the south.
The valleys are filled with Quaternary sediments and bear multiple narrow aquifers used both for thermal use and for drinking water supply. The identified aquifer bodies are characterized by fine- to coarse grained Quaternary gravels and reach thicknesses of up to 20 m. The hydraulic conductivity values range between 0.0001-0.0025 m/s and the average annual temperature is in the range of about 8 °C. Up to date, only scattered groundwater heat pumps are installed in these two valleys.
A simplified geological map reporting bedrock lithologies is shown in Figure 84. This map represents a compilation of available geological and lithological information from maps of the region with scales between 1:200.000 (geological map of Salzburg) [61] and 1:50,000 (geological map of Zell am See [62] and Kitzbühel) [63]. Units comprising lithologies with similar thermal rock properties were grouped to receive a simplified but realistic distribution of thermal conductivity values [63].
Figure 85 shows the boundaries of the alluvial cover and the spatial distribution of their thicknesses. The Glemmtal (valley of Glemm) is very narrow, with a sedimentary cover of about 15-20 m of depth with a few areas where such cover gets thicker, close to Hinterglemm and between Saalbach and Jausern. The Leogang Ache has a wider alluvial plain and, downstream the main settlement of Leogang, the deposits reach thicknesses of up to 180 m.
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Figure 84 : Simplified geological map reporting bedrock lithologies.
Figure 85: Sediment thickness (푺푻).
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Only a few information is available about the character of the narrow aquifer bodies in the case study area. The thickness of the sediment cover was modelled using the dip of the hillslope (from a 10 m digital elevation model) in combination with a compiled sediment distribution boundary from geological maps and scattered borehole information to extrapolate the base of the sediment basin. The next step was to identify aquifers and their characteristics within this sediment body, though only scarce boreholes, wells and groundwater monitoring stations give indications about the top and bottom of the aquifer. As a result of this study, 10 aquifer bodies with different thicknesses, depth to water table, temperature and kf-values were identified. Important to state is, that the data situation, especially due to the lack of wells, is poor. Nevertheless, these aquifers were modelled in all conscience using all available data, and thus represent a sound basis for the calculation of the open loop potential. 8.2 Closed-loop geothermal potential
8.2.1 Thermal properties of the ground The area of Saalbach-Leogang is composed of two main kind of rocks: alluvial sediments along the narrow valleys of Saalbach-Hinterglemm and of Leogang, and the underlying bedrock, which outcrops over most of the mapped territory. For the areas where the alluvial cover is absent, a unique value was adopted for the thermal conductivity (휆) and thermal capacity (휌푐), based on literature references as reported in Table 14. For the areas covered by alluvial sediments, depth-averaged value was calculated considering a value for the alluvial cover (according to the map of the sediment thickness 푆푇 reported in Figure 85 and a value for the bedrock (according to the map reported in Figure 84):
푚푖푛(푆푇, 100) [100 − min(푆푇, 100)] 휆 = 휆 · + 휆 · 푠푒푑 100 푟표푐푘 100
Equation 24 -1 -1 where 휆푠푒푑 and 휆푟표푐푘 are, respectively, the thermal conductivities (Wm K ) of the sediments and of the underlying rock. The same approach was adopted for the evaluation of the thermal capacity (휌푐):
푚푖푛(푆푇, 100) [100 − min(푆푇, 100)] 휌푐 = 휌푐 · + 휌푐 · 푠푒푑 100 푟표푐푘 100
Equation 25 Table 14: Thermal parameter values assigned to different lithologies.
Lithology Thermal conductivity 흀 Thermal capacity 흆풄 (·106 Jm-3K-1) References (Wm-1K-1) Sandstone 2.8 2.2 Dolomite 3.5 2.6 Limestone 2.7 2.25 VDI 4640 Metabasite 2 2.6 Conglomerate/ breccia 2.5 2 Alluvial sediments 2 2.2
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Figure 86: Spatial distribution of the average ground thermal conductivity 흀 (Wm-1K-1) in the upper 100m of depth, estimated with the method described in this chapter.
Figure 87: Spatial distribution of the average ground thermal capacity 흆풄 (MJ·m-3K-1) in the upper 100m of depth, estimated with the method described in this chapter.
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8.2.2 Ground temperature The underground temperature is one crucial parameter for the evaluation of operational criteria and constraints for shallow geothermal systems (Section 2). Hence, a profound geothermal potential assessment needs a good temperature layer as input to deliver accurate results. The approximation of underground temperature as linear function of the elevation is a widely accepted standard workflow. Within this study area, a more sophisticated workflow is presented that also takes the influence of the solar exposure into account. Derivation of the dependency of ground temperature is carried out through multi-regression analysis: first, a linear approximation of ground temperature with altitude is calculated based on the data from five ground temperature monitoring stations (four GRETA stations in Leogang + one station run by the Austrian weather service ZAMG in Saalbach). In the second step, the deviation of the linear fit to the measured values is compared to the solar exposure, another linear fit is calculated. Finally, ground temperature is calculated based on two grids: A digital terrain model and the mean of solar exposure 2006 – 2016.
Necessary input data for the calculation of the multi-regression analysis includes measured underground temperature at different elevations, expositions and solar exposure. Four temperature logging stations had been deployed by the end of 2016, ZAMG upgraded their station in Saalbach with underground temperature logging equipment. At least one year of monitoring is necessary to calculate annual mean temperatures that can then be compared to the mean solar exposure evaluated within the same timeframe. Solar exposure data is available in Austria from the Austrian weather service ZAMG as daily radiation sum, rasterised with a spatial resolution of 100 x 100 m. For the calculation of the temperature grids with the derived formula, only a digital elevation model is necessary. A collection of the derived formulae is presented in Table 16 and Table 17.
A B C Figure 88: Drilling activities in 10/2016 (A); servicing and data readout in 10/2017 (B); finished station, with solar panel, datalogger & battery (C).
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Table 15: Input data description. Raw Data Type and Unit Provider Description, Resolution Spatial Temporal Availability coverage coverage Digital elevation Raster data - 100 m World-wide model [m] Solar exposure Raster data ZAMG APOLIS dataset: At least 100 m Austria- On-going [kWh/d/m2] hourly values for the wide since sum of irradiation 1980 available either onto the real or user- specified inclined surface. Daily sum onto the real surface (DTM) is used for this study. Underground Measured data GBA, Data from the four Pointwise sparse On-going temperature ZAMG station deployed by since GBA as well as from the Nov. ZAMG station 2016 - “Saalbach” are used for the calculation of the annual mean temperature.
Table 16: Calculated data description – intermediate steps. Calculated Data Symbol and Unit Calculation Source Mean ground Mean of measured temperature values Own data and TGND [°C] temperatures (One year from Nov. 2016 – Oct. 2017) ZAMG Daily sum and monthly mean values ZAMG data, 풌푾풉 Mean solar exposure TSE [ ] Annual mean values for 2006 – 16 modified by 풎ퟐ풅풂풚 Total mean for 2006 – 16 GBA Linear approximation of Linear fit of TLIN(elev) [°C] 푻푳푰푵 = ퟏퟐ. ퟐퟔ − ퟎ. ퟎퟎퟑퟐ ∗ 풆풍풆풗 ground temperature TGND over elev Temperature deviation TDEV [°C] 푻푫푬푽 = 푻푳푰푵(풆풍풆풗) − 푻푮푵푫 Temperature correction Linear fit of TDEV ΔT[64](TSE, #5537) [°C] 휟푻 = −ퟏퟎ. ퟕퟕퟐ + ퟑ. ퟎퟏퟖ ∗ 푻푺푬 term for exposure (푻푺푬) over TSE
Table 17: Resulting raster calculation. Result layer Symbol and Unit Calculation Source Mean ground Own data and TCALC [°C] 푻 = 푻 + 휟푻 temperatures 푪푨푳푪 푳푰푵(풆풍풆풗) (푻푺푬) ZAMG
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Mean ground temperatures 11.00
10.50 Neuhäusl
10.00
C] ° 9.50 Sonnberg y = -0.0032x + 12.26 9.00 Hirnreith Temperature deviation 8.50 (used for the next calculation step) Saalbach 8.00
7.50
Ground temperature [ temperature Ground 7.00
6.50 Bergbahn
6.00 600 700 800 900 1000 1100 1200 1300 1400 1500 Elevation [m]
Figure 89: Mean ground temperatures, derived from the own monitoring stations (Hirnreith, Neuhäusl, Sonnberg and Bergbahn) as well as from the ZAMG weatherTemperature station Saalbach. deviation One year of anddata was available for this calculation (from 6.0 exposureNov. correction 2016 – Oct. 2017 )term. ΔT
5.0 C]
° 4.0
3.0 y = 3.018x - 10.772
2.0 Sonnberg 1.0 Neuhäusl
0.0 Saalbach
-1.0 Hirnreith
-2.0 Bergbahn Temperature deviation [ deviation Temperature -3.0
-4.0 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Mean solar exposure TSE2016/17 [kWh/m²/day]
Figure 90: Deviation between measured temperature and the linear approximation. The linear fit in this diagram represents the Temperature correction for solar exposure. The solar exposure used for this calculation is the mean solar exposure Nov. 2016 – Oct. 2017; the same time interval as the measured ground temperature values.
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Mean ground temperatures 11 measured vs calculated 11 Neuhäusl
10
C] ° 10 Sonnberg y = -0.0032x + 12.26 9 Hirnreith 9 Saalbach 8
8 measured ground temperature TGND calculated ground temperature TCALC(2016/17)
Ground temperature [ temperature Ground 7 TCALC(2006-16) Bergbahn 7 Linear approximation TLIN
6 600 700 800 900 1000 1100 1200 1300 1400 1500 Elevation [m]
Figure 91: Comparison between measured and calculated ground temperatures. The measured values are the mean temperatures measured between Nov. 2016 and Oct. 2017. The calculated values « TCALC(2006-16)» are based on mean solar exposure 2006–2016 (the total available timeframe) are used for the raster calculation and potential mapping.
Figure 92: Spatial distribution of the depth-averaged undisturbed ground temperature 푻ퟎ (°C).
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8.2.3 Length of the heating season The length of the heating season was considered as long as the number of days with average temperature below 12°C. This parameter was estimated based on data from 7 local meteorological stations, with elevations ranging between 622 m a.s.l. and 1956 m a.s.l. (Figure 93). As reported in Table 18, the days with temperature below 12°C range from 210 days/year in Lofer to 318 days/year in Schmittenhoehe. A correlation between the heating season length (푡푐) and the altitude (푧) was derived from these data (see Figure 94):
푡푐 = 0.0814푧 + 160.16
Equation 26
Figure 93: Weather stations used to estimate the number of heating days in the case-study area of Saalbach-Leogang.
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Table 18: Number of days with daily-average air temperature below 12°C.
YEAR Hochfilzen Lofer Loferer Alm Maria Alm Saalbach Schmittenhoehe Zell am See 2006 n.a. 205 285 233 235 306 220 2007 n.a. 213 286 219 231 327 208 2008 246 227 293 240 241 311 227 2009 228 200 294 221 238 319 212 2010 257 225 306 236 262 321 227 2011 226 199 287 211 233 n.a. 205 2012 245 209 288 221 250 n.a. 217 2013 248 219 292 228 247 317 217 2014 245 197 298 220 254 325 207 2015 249 n.a. n.a. n.a. n.a. n.a. n.a. AVERAGE 243 210 292 225 243 318 216 Elevations 962 622 1620 792 975 1956 770 AVG TEMP 7.22 9.26 5.20 8.12 7.05 3.44 8.83
Figure 94: Correlation between the altitude and the length of the heating season 풕풄 (d), assumed as the number of days/year with daily-averaged air temperature below 12°C.
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Figure 95: Length of the heating season 풕풄 (d).
8.2.4 Results The spatial distribution of the closed-loop NSGE potential is reported in Figure 96. The effect of ground temperature is quite clear, as southward-oriented slopes exhibit ground temperatures of about 8÷10°C, while northward-oriented slopes are much colder (about 2÷7°C) (see Figure 92). On the other hand, the thermal conductivity (Figure 86) exhibit a much lower spatial variability, with most of the surface lying in the range 2÷2.8 W/(mK).
For this reason, the highest values of geothermal potentials are found in the lower, southward- oriented side of the valleys of Saalbach (12÷13 MWh/y) and of Leogang (9÷12 MWy). Much lower values are found in the northward-oriented slopes, ranging between 4 and 9 MWh/y.
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Figure 96: Spatial distribution of the closed-loop shallow geothermal potential 푷푩푯푬 (MWh/y) of the upper 100m of depth of the ground in Saalbach and Leogang, estimated with the G.POT method [18].
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8.3 Open-loop geothermal potential Within the municipalities of Leogang and Saalbach, the open loop geothermal potential has been assessed in the aquifers of the two valley bottoms, as shown in Figure 97. The following sections are divided to present each valley separately.
Figure 97: Location of the two assessed aquifers
In general, the presented potential assessment results do not substitute on-site investigations of the local groundwater conditions in the planning phase of a GWHP system. In addition, the potentials are displayed in maps of 20 m resolution, where an aggregation of values for spatial queries is prohibited.
8.3.1 Hydrogeological setting and open-loop potential of Leogang The structure and relevance of the different potential assessment results are explained in detail in section 4.3 (open loop mapping of the Aosta valley). In line with the other case study areas, the technical volume flow potential of the Leogang valley has also been calculated for well pairs with a distance from extraction to injection well of 10 m and 100 m. The spatially active volume flow constraints are mapped respectively in yellow (1/3 aquifer drawdown reached), blue (groundwater rise to 0.5 m below surface reached) and green (hydraulic breakthrough reached) in the maps (see Figure 99, top). As described in chapter 0, the potential assessment uses the more conservative event of a hydraulic breakthrough to prevent thermal recycling.
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Figure 98: The locally active constraints (top) and the technical volume flow potentials (bottom) of the Leogang valley for well pairs with 10 m distance.
Figure 99: The locally active constraints (top) and the technical volume flow potentials (bottom) of the Leogang valley for well pairs with 100 m distance.
Like in the Aosta valley and the upper Iller valley, constraining effects and technical volume flows have been calculated for 10 m well distance (see Figure 99a) and 100m well distance (see Figure 99b). Since lower well distances lead to an earlier hydraulic breakthrough, also the related constraints become differently active. The top map of Figure 99a (10 m well distance) shows a similar pattern in comparison with the Aosta and the Iller valley. Here the hydraulic breakthrough threshold constraints the technical volume flow nearly everywhere. Only in a small sector in the north, where high hydraulic gradients elevate the volume flows till a hydraulic breakthrough occurs, a drawdown of 1/3 of the thickness is
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generated before the breakthrough. This effect is amplified for well distances of 100 m (see Figure 99b, top). Consequently, a larger area is constraint by the drawdown threshold.
The technical volume flows in Figure 99 show influences of aquifer thickness, hydraulic conductivity and hydraulic gradient variations. The hydraulic gradient was spatially calculated from the groundwater levels, whereas hydraulic conductivity and aquifer thickness was considered through the assignment of constant values in different sections of the aquifer. This approach of conductivity and aquifer thickness assignment significantly influences the result ranges between the sections (Grießen: 3 m & 1∙10-4 m/s, West-Leogang: 7 m & 7∙10-4 m/s, East-Leogang: 20 m & 2∙10-3 m/s). This leads to the high volume flows levels in the East-Leogang section and low values in the Grießen section. Since the hydraulic gradient is the only spatially varying parameter, its distribution pattern can be directly observed in the results. In general, the gradient is very high in this Alpine valley (approx. 1–6 %) and supports higher volume flows, until the event of a hydraulic breakthrough occurs. Except for the Grießen section, Figure 100 displays that the Leogang valley provides suitable hydrogeological conditions for the thermal use of groundwater. However, most parameters in this case study area are derived from a sectional assignment of constant values, which might vary and considerably change the hydrogeology at on-site investigations.
Figure 100: Volume flow for an extraction well at a drawdown of one third of the saturated aquifer thickness (top) and volume flow of an injection well with a threshold groundwater table rise of 0.5 m to the surface (bottom).
A more detailed view on the potential is provided by the map of maximum pumping rates at 1/3 drawdown (Figure 100, top) and the map of maximum injection rates till the groundwater rises up to 0.5 m below surface (Figure 100, bottom). The maps represent the result of an application of Equation 16 and Equation 18, respectively. The calculated volume flows only consider the extraction or the injection well independently from the wells distance to each other and a hydraulic breakthrough limit is not considered.
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The drawdown constraint is related to the hydraulic conductivity and the square of the aquifer thickness (c.f. chapter 0). As anticipated, for Leogang and Saalbach-Hinterglemm those values are set constant per aquifer section. Consequently, the pumping rates, displayed in the top map of Figure 100, show no spatial variation, but reflect the interaction of the two parameters in the distinct sections. The injection potential map on the bottom of Figure 100 is mainly influenced by the depth to water variation. The highest values of 10-20 m can be found in the section east of Leogang, whereas the remaining area has moderate values of 2-7 m.
The technical volume flow rate results of 10 m well distance are further used to determine a local value of extractable geothermal power and geothermal energy (c.f. Figure 101). The geothermal power (c.f. Figure 101, top) was calculated for a temperature difference at the heat pump of five Kelvin (K) with Equation 20. If the required heating power of a house is known, the displayed geothermal power [kW] can be used with an estimated seasonal performance factor of the heat pump to derive the possible thermal power of the GWHP system. Since the values of the volume flow map are only multiplied with constants, the map shows the same relations as explained for the technical volume flow map for 10- m well distance. In addition, we calculated the extractable geothermal energy for 5K temperature difference and 2000 hours of full load operation per year (Figure 101, bottom). 2000 hours represent an intermediate value taken from the VDI 4640, which suggests a range of 1800 h to 2400 h of full load hours.
Figure 101: Geothermal power of a well pair with 10 m distance at a 5 Kelvin temperature difference (top) and the resulting geothermal energy for 2000 hours of full load operation per year (bottom).
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Figure 102: Geothermal power of a well pair with 100 m distance at a 5 Kelvin temperature difference (top) and the resulting geothermal energy for 2000 hours of full load operation per year (bottom).
8.3.2 Hydrogeological setting and open-loop potential of Saalbach-Hinterglemm Please refer to the introductory data and assessment strategy descriptions given in the previous chapter and the section 4.3 (open loop mapping of the Aosta valley). Congruent with the other case study areas, the technical volume flow potential of the Saalbach-Hinterglemm valley was calculated for well pair distances of 10 m and 100 m (see Figure 103).
Like explained in the previous section, the related constraints become differently active at changing well distances. The top map of Figure 103a (10 m well distance) shows that the drawdown constraint is already limiting the pumping rates in larger areas. At 100 m, well distances it became the only constraining factor. Different to the other surveyed case study areas, the hydraulic gradient in this narrow Alpine valley is very high (approx. 1–6 %), which elevates the volume flow results of the hydraulic breakthrough constraint.
Like in the Leogang valley, hydraulic conductivities and aquifer thickness were assigned constant in sections (West of Saalbach:3 m & 2.5∙10-3 m/s, East of Saalbach: 5 m & 1∙10-3 m/s). Since the hydraulic gradient is the only spatially varying parameter, its distribution pattern can be seen in Figure 103a. Active drawdown constraints indicate areas of very high gradients.
In conclusion, Figure 103 displays that the Saalbach-Hinterglemm valley may only provide moderate suitability for the thermal use of groundwater for larger GWHP systems. Due to relatively low aquifer thickness values, the groundwater availability might hamper a sustainable operation of the extraction
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well. Smaller GWHP systems (one or two family houses) can find suitable conditions in the valley aquifer.
Figure 103: The locally active constraints (top) and the technical volume flow potentials (bottom) of the Saalbach valley for well pairs with 10 m distance.
Figure 104: The locally active constraints (top) and the technical volume flow potentials (bottom) of the Saalbach valley for well pairs with 100 m distance.
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Analogous to the other case study areas, the map of maximum pumping rates at 1/3 drawdown (Figure 105, top) and the map of maximum injection rates till the groundwater rises up to 0.5 m below surface (Figure 105, bottom) are displayed.
As anticipated, those values are set constant per aquifer section. Like for the Leogang valley, the pumping rates, displayed in the top map of Figure 105, show no spatial variation, but reflect the interaction of the hydraulic conductivity and the aquifer thickness in the distinct sections. The injection potential map on the bottom of Figure 105 is mainly influenced by the depth to water variation, which ranges from 2-7 m.
Figure 105: Volume flow for an extraction well at a drawdown of one third of the saturated aquifer thickness (top) and volume flow of an injection well with a threshold groundwater table rise of 0.5 m to the surface (bottom).
The technical volume flow rate results of 10 m well distance are further used to determine a local value of extractable geothermal power and geothermal energy (c.f. Figure 106). The geothermal power (c.f. Figure 106, top) was calculated for a temperature difference at the heat pump of five Kelvin (K) with Equation 20. If the required heating power of a house is known, the displayed geothermal power [kW] can be used with an estimated seasonal performance factor of the heat pump to derive the possible thermal power of the GWHP system. Since the values of the volume flow map are only multiplied with constants, the map shows the same relations as explained for the technical volume flow map for 10- m well distance.
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Figure 106: Geothermal power of a well pair with 10 m distance at a 5 Kelvin temperature difference (top) and the resulting geothermal energy for 2000 hours of full load operation per year (bottom).
Figure 107: Geothermal power of a well pair with 100 m distance at a 5 Kelvin temperature difference (top) and the resulting geothermal energy for 2000 hours of full load operation per year (bottom).
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In addition, we calculated the extractable geothermal energy for 5K temperature difference and 2000 hours of full load operation per year (Figure 106, bottom). 2000 hours represent an intermediate value taken from the VDI 4640, which suggests a range of 1800 h to 2400 h of full load hours. 8.4 Conclusions The closed-loop geothermal potential map of Saalbach and Leogang, shown in Figure 96, is based on data collected by the geological survey of Austria. The approximations adopted for the G.POT method application are the following:
- Undisturbed ground temperature has been estimated considering the quote and the orientation of the slope according to Figure 92; - Length of heating season is linearly related with the quote (Figure 94); - Thermal conductivity and thermal capacity values have been imposed according to literature references.
Thermal conductivity values of the area are lower than the Aosta case study area (except from the small area of Dolomite) and the impact of the ground temperature plays a more important role. In particular, the slopes characterised by a south orientation has much higher values of geothermal potential. In general, the variability within the territory is very important, varying from 3 up to 17 MWh/y.
Open loop potential has been assessed in the two valley bottoms of Saalbach-Hinterglemm and Leogang. In the narrow valley of Saalbach-Hinterglemm, only 100 to 300 m wide aquifer could develop. Thus, the potential is quite reduced for larger GWHP systems, due to the narrow aquifer body and a low aquifer thickness of 3-5 m. In the larger valley of Leogang the western section of Grießen offers only a low suitability for thermal use of groundwater, due to a low aquifer thickness of 3 m and a hydraulic conductivity of only 1∙10-4 m/s. The section west of Leogang provides moderate conditions for the thermal use of groundwater. Especially larger systems would be limited by the significant drawdown in the 7 m thick aquifer. The section east of Leogang provides the best hydrogeological conditions within the Austrian case study area. A high aquifer thickness of 20 m and good hydraulic conductivity of 2∙10-3 m/s is combined with a high hydraulic gradient and therefore offers quite suitable conditions also for larger GWHP systems.
However, most parameters in this case study area are derived from a sectional assignment of constant values, which might vary significantly. Thus, on-site investigations can have a considerable bias from the observations used for the open-loop potential assessment.
All the maps about this pilot area reported in this section can be downloaded from this link: https://areeweb.polito.it/ricerca/groundwater/zip/GRETA_NSGE_potential/ or viewed through this one: http://greta.eurac.edu/maps/180/embed.
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9 NSGE mapping in Davos (Switzerland)
The innovative aspect of the GRETA pilot study Davos (Switzerland, canton of Grisons) is the development of methods for the estimation and exploitation of the geothermal utilization potential of deeper alpine aquifers. Methods include the development of model-based scenarios of the exploitation of the deep aquifers and approaches for a computer-aided optimization of use. A major challenge is the integration of complex geological geometries from a geological 3D model (GOCAD) at different scales into a numerical groundwater flow model (COMSOL Multiphysics). Starting point is a geological 3D model representing a regional tectonic system of the Eastern Alpine and Pennine system of the Davos area. The developed geological 3D model is then transferred into regional and local scale groundwater flow models.
In particular, in this area, the open-loop potential has been assessed in order to fulfil the energy demand of the local hockey stadium and congress palace (Figure 108).
Figure 108: Conference and sports facilities, which are the main energy-user in Davos.
There are some limits with respect to the number of shallow geothermal systems which could be installed in aquifers in general. Reasons are groundwater protection issues and critical temperature declines in the surroundings of geothermal heat pumps (GHPs). However, in the Alps the distribution of regional aquifer and aquitard systems is not restricted to the shallow subsurface. Due to the complex tectonic structure of the different nappe systems, Triassic evaporitic and dolomitic units often separate
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individual nappes. These units represent regional aquifers characterized by recharge areas, which are hydraulically connected to deep aquifers below the valley bottoms Figure 109.
Figure 109: Geological model and cross section from the local study area. Both figures show the position of an exploration drilling (German: “Erkundungsbohrung”).Target horizon is the Arosa-Dolomite with a change of hydraulic conductivity (dashed line, position is based on information from the drilling).
Starting point was a very conceptual approach by using the hydrogeological 3D model of the Davos area and defining hydraulic boundary conditions. The driving forces of regional groundwater flow systems are largely controlled by the configuration of the water table, which under most conditions is a subdued replica of the topography [65] and which determines the hydraulic head distribution. Consequently, the regional flow in mountain areas can be regarded as driven by variations in the hydraulic head. This concept also leads to the idea of exploring aquifers at greater depth, in the artesian confined Arosa-dolomite at about 100 m to 400 m depth.
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The availability of data on the hydraulic properties and the hydraulic boundary conditions of the subsurface is generally very limited in Alpine areas. Developing regional groundwater flow models, based on geological 3D conditions that determine the large-scale groundwater circulation systems, are the greatest challenge for using the energy of deep aquifer systems in the Alps.
The geological-hydrogeological 3D model allows evaluating pumping tests in the 400 m deep exploration well and to understand the dynamic character of capture zones of pumping wells as well as to test how different boundary conditions and the hydraulic property distribution influence calculated flow regimes. In addition, the model allows testing the effects of hydraulic regime changes at different scales. In the year 2016, the focus was laid on the development of the geological 3D model and in 2017 on the hydraulic model for understanding the dynamics of deeper confined and artesian aquifers, including the interaction with near surface groundwater resources in the unconsolidated rocks of valley fills. Results of the regional flow can be seen in Figure 110 and Figure 111, where the arrows represent the flow direction and the density of the arrows is based on a Gaussian distribution and is not to be equated with a volume or a velocity. ±
Figure 110: Result of regional scale groundwater modelling. This figure shows the view from the north, where the influence of the topographical and tectonic structures on the groundwater-flow field is clearly visible.
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Local-scale maps of the NSGE potential in the Case Study areas
±
Figure 111: Result of regional scale groundwater modelling from the south.
In Davos, they have already drilled an exploratory well (EKB) in 2012 down to 400 m, whereby artesian groundwater, with a free discharge of about 1200 l/min, was found. By installing a pump, the yield could be increased to 1760 l/min, while lowering the groundwater level by 31 m. Without groundwater extraction, the groundwater level recovers quickly, which suggests abundant inflows. A measure±ment program (GNAMA) around the exploration well at the Davos Kurpark served to study the sustainable operation of production and to monitor potential negative impacts on existing geothermal applications. By connecting the heat extraction system of the exploratory well with the existing heat supply systems of the congress-centre and the ice hockey-centre, it was possible to increase heat generation from 1200 MWh to 1600 MWh per year. This increased the heat supply of the congress- centre and the indoor pool from 12 hours to more than 20 hours per day. Extensive previous and current investigations in Davos due to the use of GHPs are listed in Table 19.
Table 19: Investigations of the three different project that assessed the geothermal potential of the pilot area of Davos.
SFOE/ANU/Geotest AG Exploration Drilling 400 m Hydraulics Artesian conditions: 2.6 bar 1200 l/min Aquifer lithology Dolomites (Arosa Dolomite) Depths of Water inflow 150-270 m Temp. 14 °C Pumping Test max 1760 l/min GW decline 31 m 3 Groundwater uptake (2012) 100 000 m Goal: Groundwater uptake 2000 l/min Estimated GW decline 40 m 2014 70-80 % from Arosa Dolomite and Origin of pumped water 30% from the southern valley
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Bachelor Thesis 2015 (C. Eisenring) Isotope analysis 70-80% young groundwater
to determine the balance of GNAMA (Geothermal use of Alpine Implementation by Geotest AG usable water and heat potential Aquifers) and ISSKA with good data 2014 Set-up of 3 observation wells 140-170 m
Geologic 3D model – GRETA Project hydraulic model
The success of geothermal energy in Davos largely depends on whether or not the water resources permit sustainable use. The model scenarios based on the groundwater model should help answer this question. A comprehensive measuring program (GNAMA) during a large scale pumping test in the exploration borehole in the Kurpark of Davos (400 m deep) served to examine a sustainable operation of the production well and to monitor potential negative impacts on existing geothermal applications. The pumping tests allowed to derive the hydraulic properties of the subsurface and to calibrate the hydraulic models. In a second phase the productivity of the well, possible interference with other or planed uses of the aquifer system and the 3D evolution of the capture zone of wells could be derived. Further hydrogeological data concentrate on the Landwasser-valley of the Davos area, which are the basis for the setup of the models and the hydraulic calibration.
According to the groundwater protection legislation, reinjection of the sulphate rich water from the Arosa-dolomite into the same aquifer is obligatory. Since this would be very (energy-) consuming, it would almost represent a killer argument for using the Arosa-dolomite as an energy resource. A possible solution would be the reinjection into the Quaternary aquifer. The water from the Triassic dolomite already infiltrates into the Quaternary aquifer and the introduction of the mineralized water into the surface waters only leads to negligible change of the chemical composition of the surface water. Thereupon a re-infiltration of the water from the Triassic aquifer into the surface waters can be envisaged under certain constraints with respect to the infiltration.
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10 Conclusions
This document describes the activities performed, in the framework of WP4, to assess and map the shallow geothermal potential in the 6 case-study areas of GRETA: Valle d’Aosta (Italy), Parc des Bauges (France), Oberallgäu (Germany), Saalbach-Leogang (Austria), Cerkno (Slovenia), and Davos (Switzerland). It is widely acknowledged that the technical and economic feasibility of Ground Source Heat Pumps strongly depends on the in situ underground properties. The concept of geothermal potential has been applied for a long time for deep geothermal resources, for which it indicates the thermal power which can sustainably be extracted from a reservoir. On the other hand, shallow geothermal energy has different constraints, since the objective is to satisfy a certain demand with the resource available on site. For this reason, the shallow geothermal potential is defined with different indicators, which are also differentiated between closed-loop (mainly borehole heat exchangers and, in a few cases, horizontal collectors) and open-loop (groundwater heat pumps) systems. The closed-loop geothermal potential has been often defined as the thermal power per unit length of borehole, which can be abstracted and/or injected into the ground with a certain schedule (e.g. full- load hours per year) Most of the methods are based on the thermal conductivity, which depends on its lithology and, for sediments, on the water saturation. However, a main issue in mountainous areas is the high variability of the ground temperature, which is a major factor influencing the ability of the ground to provide heating (or, in warmer areas, cooling). The G.POT method was developed in recent years to overcome this limitation. G.POT allows to take into account ground thermal parameters, ground temperature, operating schedule, and other plant parameters. For this reason, we adopted this method to perform the closed-loop mapping in the areas in the areas of Valle d’Aosta, Parc des Bauges, Saalbach-Leogang, and Cerkno. The other two areas (Oberallgäu in Germany and Davos in Switzerland) were not mapped since similar mapping was already available. It is interesting to notice that in each pilot area, the detail of available data is different and results are coherent. For example, for the Austrian pilot area, particular attention was put on the ground temperature and on the thickness of alluvial sediments; in France on the influence of quaternary deposits on the average thermal conductivity; in Italy and Slovenia on the thermal conductivity and thermal capacity of main substrate lithotypes. This shows how the G.POT method is versatile and can be adopted in different conditions, with different data sets. The open-loop potential is far less studied in literature. The studies in literature agree it mostly depends on the hydraulic properties of the aquifer and, to a far lesser extent, on the groundwater temperature. In our work we identified 4 main limiting factors, which correspond to the 4 main design aspects of GWHPs, namely i) the drawdown in the abstraction well(s), ii) the level increase in the reinjection well(s), iii) thermal recycling between the reinjection and the abstraction well(s), and iv) the propagation of thermal plumes. The first three factors limit the flow rate, and hence the thermal power, which can be exchanged with the aquifer. In this version of the report, we present the flow rates and the thermal power which can be exchanged through a well doublet. Further developments are needed to estimate the thermal plume area and, from this, the maximum density (installed power per unit surface) which can be installed.
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135/ 137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta. Local-scale maps of the NSGE potential in the Case Study areas
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137/ 137 GRETA is co-financed by the European Regional Development Fund through the Interreg Alpine Space programme. See more about GRETA at www.alpine-space.eu/projects/greta.