Anthropogenic and natural alterations of shallow groundwater temperatures

Shallow subsurface temperatures are influenced by various processes. In particular, the thermal environment under urban areas is profoundly changed by anthropogenic activities and under several cities a permanent increase in groundwater temperatures is observed, which is driven by site-specific factors. Also in rural areas atmospheric temperatures exhibit an increasing trend due to climatic changes and influence the development of groundwater temperatures in economically important aquifers

Potential of low-temperature aquifer thermal energy storage (LT-ATES) in Germany

More than 30% of Germany’s final energy consumption currently results from thermal energy for heating and cooling in the building sector. One possibility to achieve significant greenhouse gas emission savings in space heating and cooling is the application of aquifer thermal energy storage (ATES) systems. Hence, this study maps the spatial technical potential of shallow low-temperature ATES systems in Germany. Important criteria for efficient ATES operation considered in this assessment encompass suitable hydrogeological conditions, such as aquifer productivity and groundwater flow velocity, and balanced space heating and cooling demands. The latter is approximated by the ratio of heating and cooling degree days, which is incorporated as a time-dependent criterion to also evaluate the impact of climate change on the ATES potential. The hydrogeological and climatic criteria are combined within a spatial analysis revealing that, regarding the upcoming decades, about 54% of the investigated German area are very well or well suitable for ATES applications, largely concentrating on three regions: the North German Basin, the Upper Rhine Graben and the South German Molasse Basin. Considering time-dependent climatic conditions, the very well or well suitable areas will increase by 13% for the time period 2071–2100. This is mostly caused by a large relative area increase of the very well suitable regions due to an increasing cooling demand in the future. The sensitivity of the very well and well suitable regions to the criteria weightings is relatively low. Accounting for existing water protection zones shows a reduction of the country-wide share of very well or well suitable areas by around 11%. Nevertheless, the newly created potential map reveals a huge potential for shallow low-temperature ATES systems in Germany

Meeting the demand: geothermal heat supply rates for an urban quarter in Germany

Abstract Thermal energy for space heating and for domestic hot water use represents about a third of the overall energy demand in Germany. An alternative to non-renewable energy-based heat supply is the implementation of closed and open shallow geothermal systems, such as horizontal ground source heat pump systems, vertical ground source heat pump (vGSHP) systems and groundwater heat pump systems. Based on existing regulations and local hydrogeological conditions, the optimal site-specific system for heat supply has to be identified. In the presented technical feasibility study, various analytical solutions are tested for an urban quarter before and after building refurbishment. Geothermal heat supply rates are evaluated by providing information on the optimal system and the specific shortcomings. Our results show that standard vGSHP systems are even applicable in older and non-refurbished residential areas with a high heat demand using a borehole heat exchanger with a length of 100 m or in conjunction with multiple boreholes. After refurbishment, all studied shallow geothermal systems are able to cover the lowered heat demand. The presented analysis also demonstrates that ideally, various technological variants of geothermal systems should be evaluated for finding the optimal solution for existing, refurbished and newly developed residential areas

Shallow subsurface heat recycling is a sustainable global space heating alternative

Despite the global interest in green energy alternatives, little attention has focused on the large-scale viability of recycling the ground heat accumulated due to urbanization, industrialization and climate change. Here we show this theoretical heat potential at a multi-continental scale by first leveraging datasets of groundwater temperature and lithology to assess the distribution of subsurface thermal pollution. We then evaluate subsurface heat recycling for three scenarios: a status quo scenario representing present-day accumulated heat, a recycled scenario with ground temperatures returned to background values, and a climate change scenario representing projected warming impacts. Our analyses reveal that over 50% of sites show recyclable underground heat pollution in the status quo, 25% of locations would be feasible for long-term heat recycling for the recycled scenario, and at least 83% for the climate change scenario. Results highlight that subsurface heat recycling warrants consideration in the move to a low-carbon economy in a warmer world

Groundwater temperature anomalies in Central Europe

As groundwater is competitively used for drinking, irrigation, industrial and geothermal applications, the focus on elevated groundwater temperature (GWT) affecting the sustainable use of this resource increases. Hence, in this study GWT anomalies and their heat sources are identified. The anthropogenic heat intensity (AHI), defined as the difference between GWT at the well location and the median of surrounding rural background GWTs, is evaluated in over 10 000 wells in ten European countries. Wells within the upper three percentiles of the AHI are investigated for each of the three major land cover classes (natural, agricultural and artificial). Extreme GWTs ranging between 25 °C and 47 °C are attributed to natural hot springs. In contrast, AHIs from 3 to 10 K for both natural and agricultural surfaces are due to anthropogenic sources such as landfills, wastewater treatment plants or mining. Two-thirds of all anomalies beneath artificial surfaces have an AHI > 6 K and are related to underground car parks, heated basements and district heating systems. In some wells, the GWT exceeds current threshold values for open geothermal systems. Consequently, a holistic management of groundwater, addressing a multitude of different heat sources, is required to balance the conflict between groundwater quality for drinking and groundwater as an energy source or storage media for geothermal systems

Heat supply by shallow geothermal energy in Karlsruhe

By employing shallow geothermal systems, heat is extracted from the subsurface and utilized for space heating and domestic hot water (DHW). In built-up areas the available thermal energy is even larger, if the subsurface urban heat island (UHI) effect is also considered. Increased surface temperatures combined with underground anthropogenic heat sources, such as basements and sewage systems, can raise urban groundwater temperatures by 3 K to 7 K above those in rural areas. Previous studies calculated the annual average anthropogenic heat flux into the ground by means of a spatially resolved heat transport model (Benz et al., 2015). In this study, the geothermal potential is compared to the energy demand for space heating as well as DHW for the urban quarter “Rintheimer Feld” in Karlsruhe, Germany. In this quarter the housing association (Volkswohnung GmbH) is proprietor of 30 multifamily-houses with about 70,000 m² of living space. These houses were built in the 1950/60s and meanwhile have been refurbished (Rink and Kuklinski, 2015). The calculation is based on the consumption data of space heating and DHW of all buildings before and after the refurbishment. By merging the anthropogenic heat flux and the energy stored underground we obtain the geothermal potential. Based on these results and considering space availability as well as (hydro)geological boundary conditions, we determine the required number of open and closed geothermal systems. Furthermore, we determine how much of the energy demand – before and after refurbishment, respectively – can be covered by one of the three following geothermal systems: (1) horizontal ground heat exchangers (HBHE), (2) ground source heat pump (GSHP) systems with vertical borehole heat exchangers (BHE) and (3) ground water heat pump (GWHP) systems. Our results show that energy supplied by the HBHE is not sufficient, since the area required for the system installation is too small. Totally 90% of the heating energy demand can be covered. Assuming a BHE length of 100 m and a spacing of 5 m, the energy demand before and after refurbishment can be fully covered by GSHP systems. GWHP systems can only partly cover the demand, due to the higher space demand, which is required to avoid thermal interaction between the wells. In case of a conservative assumption (1 K plume isotherm), 6% of the energy demand can be obtained before and 13% covered after refurbishment. Assuming a 3 K plume isotherm, an entire coverage of the demand is possible after and at 76% before refurbishment. To conclude, GSHP systems can cover the energy demand before and after refurbishment in the “Rintheimer Feld” and are therefore also the preferred geothermal system varian

Multi-fidelity approach to Bayesian parameter estimation in subsurface heat and fluid transport models

The increased use of the urban subsurface for competing purposes, such as anthropogenic infrastructures and geothermal energy applications, leads to an urgent need for large-scale sophisticated modelling approaches for coupled mass and heat transfer. However, such models are subject to large uncertainties in model parameters, the physical model itself and in available measured data, which is often rare. Thus, the robustness and reliability of the computer model and its outcomes largely depend on successful parameter estimation and model calibration, which are hampered by the computational burden of large-scale coupled models. To tackle this problem, we develop a novel Bayesian approach for parameter estimation, which allows us to account for different sources of uncertainty, is capable of dealing with sparse field data and makes optimal use of the output data from expensive numerical model runs. This is achieved by combining output data from different models that represent the same physical problem, but at different levels of fidelity, e.g. reflected by different spatial resolution. By applying this new approach to a 1D analytical heat transfer model and a large-scale semi-3D numerical model while using synthetic data, we show that the accuracy and precision of parameter estimation by this multi-fidelity framework by far exceeds the standard single-fidelity results. The consideration of different error terms in the Bayesian framework also allows assessment of the model bias and the discrepancy between the different fidelity levels. These are emulated by Gaussian Process models, which facilitate re-iteration of the parameter estimation without additional model runs

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand