Introduction

Since energy demand is constantly increasing, fossil fuel shortages encourage finding substitutional sources. The renewable energy system is a prosperous source that can be used as a substitutional and eco-friendly source for heating and cooling. Aquifer thermal energy storage (ATES) is one of the promising technologies to be used as a renewable source due to its availability, reasonability, and storage capacity (Pellegrini et al. 2019). However, a suitable aquifer must be carefully chosen for constructing the ATES system. Determination of the suitability of aquifers as thermal energy storage is through assessment of the characterizations of the aquifer (Lee 2013 and Stemmle et al. 2022), such as climate, geology, physical properties, flow properties, and water quality.

In China, the early operation of ATES recorded in the 1960s was reported by Morofsky (1994) and Gao et al. (2006). However, the first dominated modeling research was in the 1970s by Kazmann (1971) and Rabbimov et al. (1971).

An overview of ATES studied by Andersson (2007), Dickinson et al. (2009), Morofsky (1994), and Paksoy et al. (2009), ATES system statutes in different countries discussed by Snijders (2005), Desmedt et al. (2006), Desmedt and Hoes (2007), Lottner and Mangold (2000), Schmidt et al. (2004), Sanner et al. (2005) and Allen et al. (2000). A complication of the ATES system is presented by Jenne et al. (1992) and Beek (2010). While the application of the ATES system was studied by Yang et al. (2010), Paksoy et al. (2000), Paksoy et al. (2004), Hendriks et al. (2008), Blum et al. (2010) and Bloemendal and Olsthoorn (2014). ATES-designed studies conducted by Bridger and Allen (2005). Moreover, (Al-Madhlom et al. 2019a, b) studies were conducted to determine the selected site of ATES. Besides that, (Bloemendal et al. 2015 and Lu et al. 2019a, b) studied the global potential of aquifer thermal energy storage.

Multicriteria decision Analysis (MCDA) is the combining technique of several criteria and creating a solitary outcome. Multi-spatial data from different sources can be processed by using ArcGIS; as a result, interconnecting MCDA and ArcGIS have a tremendous benefit for creating an ATES suitability map (Chen et al. 2010). Analytic hierarchy process (AHP) counts as one of the most common methods of the MCDA used by many authors (Saaty 1977, 1980; Carver 1991; Saaty and Vargas 1991; Wu 1998; Malczewski 1999a,b, 2000; Makropoulos et al. 2003; Coyle 2004; Marinoni 2004; Malczewski 2007; Ohta et al. 2007; Marinoni et al. 2009; Drobne and Lisec 2009; Ferretti 2011; Kara and Doratli 2012; Chabuk, et al. 2017; Lu et al. 2019b; Alkaradaghi et al. 2020; Eddouibi et al. 2021; Stemmle et al. 2022).

Although much research has been conducted in the investigation, design, and operation of aquifer thermal energy storage, furthermore has been applied in many countries for cooling and heating. However, this study has a novelty in determining the suitability of ATES in the Iraqi Kurdistan region, as no previous work has been done in the region. Therefore, evaluating and selecting suitable areas is crucial to get an advantage from using renewable energy for heating and cooling. Halabja governorate has productive aquifers and a shortage of electricity. Therefore, it is an excellent area for determining the suitability of ATES based on the GIS-MCDA. This study will help the government and the decision-makers to use the ATES as it is economical and contributes to minimizing the emission of CO2 in the Halabja governorate.

Study area

Halabja-Khurmal sub-basin is situated in the northeastern part of Iraq at the coordinates of 571,545–606,290 East and 3,884,112–3,916,597 North, with the elevation ranging between (455–2609) meters (Fig. 1). The sub-basin is around (488.62 Km2), with a population of around 118,924 in 2021, based on data from Sulaimani Statistical Directorate (Rauf et al. 2022).

Fig. 1
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Location map of the Halabja-Khurmal sub-basin

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The studied area is located within the Halabja governorate in the Kurdistan region of Iraq. It is characterized by cold winters and hot summers with an average annual precipitation of 622.6 mm and average annual air temperature ranges between 3.3 and 43.4 °C.

Material and method

The input criteria

The most important criteria for the applicability of ATES are six geo-hydrological and climate parameters combined for assessing the suitability map of ATES in the Halabja-Khurmal sub-basin through aquifer types, groundwater recharge, seepage velocity, type and quality of groundwater, and mean annual temperature. As the effect of each parameter on the suitability of ATES is different, the GIS-based MCDA method is used to approach an accurate decision analysis for each criterion.

A well-known method in the MCDA method is AHP due to its flexibility, simplicity, implementation within a GIS environment, and users' ability to derive the weight of criteria in maps (Malczewski 2007).

AHP is based on a pairwise comparison approach, which deals with comparing the criteria based on the degree of importance with each other (Ishizaka and Nemery 2013).

Many field trips in the studied sub-basin were made to investigate the area's geology, soil, lithology, and hydrogeology. Then, the number of boreholes and springs was selected for groundwater sampling. The samples from the boreholes and springs were collected in clean, sterilized 500-ml bottles. Then, the physio-chemical parameters of the water samples were analyzed by titration method to determine chloride, alkalinity as HCO3−, calcium, and magnesium. Nitrate and sulfate were analyzed using a spectrophotometer. A flame photometer was used to analyze sodium and potassium. The EC, pH, TDS, turbidity, SWL, and temperature were measured in situ. Groundwater recharge was derived by Mehta et al. (2006) using meteorological data for twenty years (2001–2021). Aquifer transmissivity is calculated from many pum** well tests. Data acquisition is collected from different sources to create criteria for assessing ATES's suitability, as shown in Table 1 and Fig. 2. ArcGIS was applied to create the required maps in spatial analysis tools and then converted to a raster (30*30) pixel size.

Table 1 Data source for creating criteria used in the ATES suitability map
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Fig. 2
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Flowchart of creating the ATES suitability map in the Halabja-Khurmal sub-basin

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Type of aquifers

The characterization of aquifers is the most dominant part of the suitability assessment of ATES. Construction of the ATES system needs a suitable aquifer (Lee 2013). This water-bearing geological formation significantly affects the thermal efficiency of the ATES system. Based on (Lu et al. 2019b), complex geological structures are less suitable for ATES applications. The heterogeneity, karstified, and occurrence of fractures and faults negatively impact the thermal efficiency of the aquifer thermal energy storage system due to the lateral loss of thermal energy, and thermal energy is uncontrollable in tilted aquifers due to faults and fractures (Bloemendal et al. 2015). Mainly, it is agreeable that complex hydrological structures are less suitable for ATES application than simpler ones on the base of thermal loss. The studied area is classified into simple, medium, and complex aquifers based on the presence and intensity of the faults and fractures (Fig. 3A).

Fig. 3
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Input maps for the ATES suitability: A Type of aquifers, B Groundwater recharge, C Fresh/Saline groundwater, D Groundwater quality, E Seepage velocity, and F Mean annual temperature

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Groundwater recharge

The yearly percolation of water and rejuvenation into the aquifers' groundwater causes a rise in the water table. Therefore, a higher groundwater recharge corresponds to a higher suitability of the ATES system (Lu et al. 2019b). This criterion is fundamental in characterizing ATES suitability; the more groundwater recharge, the more productive the wells will be, and the higher the probability that ATES can be applied (Fig. 3B).

Fresh/saline groundwater

A suitable aquifer with fresh water for ATES application is cheaper and less maintenance sensitive than saline water (Lee 2013). Therefore, freshwater aquifers are preferable. The study area is characterized by freshwater based on TDS analysis of wells and springs samples ranging between (120–630 ppm). It can be classified as freshwater based on the classification of Drever (1997), which is a suitable criterion for the ATES system. (Fig. 3C).

Groundwater quality

ATES is performed superior in high-quality groundwater for maintaining longer system life. However, when groundwater from a variable depth of aquifer is discharged from the extraction well and then recharged in the injection well, as a result of the mixing, the different water quality may cause chemical reactions and produce chemical precipitation. It will lead to corrosion and clogging in the well's screen (Zuurbier et al. 2013; Beek 2010). Shallow aquifers are more vulnerable to contamination, so mixing any contaminated shallow water into a deep aquifer can cause severe damage to groundwater resources. Consequently, groundwater quality is one of the critical points to be considered. The water quality of the Halabja-Khurmal sub-basin is classified as excellent and good (Rauf et al. 2022), which is suitable for the ATES technique (Fig. 3D).

Seepage velocity

The velocity of flowing groundwater within the aquifer's pores influences the storage of thermal energy in the groundwater. Although groundwater flow is generally slow (EU Commission SAVE Programme and Nordic Energy Research 2004) suggested a prerequisite rate to suit ATES to be less than 3 cm/day and 11 cm/day for small and big projects, respectively.

The aquifers with higher groundwater flow rates are less suited to store thermal energy. The reason for that is the advection of the thermal energy stored in it may cause a loss of efficiency of ATES systems due to potential substantial heat energy loss (Sommer et al. 2014; Bloemendal and Olsthoorn 2018). Therefore, seepage velocity is one of the criteria regarding the suitability of ATES for having an essential impact on thermal storage.

In the study area, groundwater seepage velocity was calculated through ArcGIS-Darcy velocity by the input rasters of groundwater head elevation, effective formation porosity, saturated thickness, and formation transmissivity. The seepage velocity magnitudes map of the study area is mostly less than 0.03 m/day, suited to store thermal energy (Fig. 3E).

Mean annual temperature

Climate conditions impact the energy demands for cooling and heating any building systems. However, outside conditions are closely related to temperature as well as the stability between cooling demand in summer and space heating demand in winter. Therefore, this criterion is used for driven the suitability of ATES application in the area (Fleuchaus et al. 2020). Very high or very low temperature negatively impacts the ATES system’s application. The mean annual temperature in the study area is 21.2 °C for the twenty years (2001–2021) (Fig. 3F).

Determination of criteria rating and weighting

The AHP method has been used in MCDA to create the ATES suitability area concerning the criteria comparison. The AHP developed by Saaty (1980) provides a flexible and easily understood way of analyzing complicated problems. The MCDA technique allows subjective and objective features to be considered in decision-making (Taherdoost 2017; Manguri and Hamza 2022). In AHP, all criteria are prioritized by their degree of importance based on the expert's opinion for the ATES suitability indicator between the criteria based on the same scale (Eddouibi et al., 2021). The current study used six criteria in the computation process. Firstly, the selected six criteria are set side by side to finalize the criteria assigned weights that reflect the importance of ATES in the area of interest. Then, the weights calculated for criteria were the results of a pairwise comparison of criteria based on their relative importance to ATES. Finally, each criterion was classified into sub-criterion with assigned suitable rating values from zero to ten (Saaty 1980; Saaty 1977; and Malczewski 2000), with rates closer to ten representing a favorable condition to ATES suitability and rates closer to zero being an unsuitable condition. The rating and prioritizing of criteria were specified based on priorities, expert decision-making, and relying on many works of literature (Table 2).

Table 2 Criteria class, rating, and weighting used in the ATES suitability map
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The weighting of each criterion is determined based on pairwise one-on-one comparisons between classes of individual criterion through the degree of importance of each class over the others following AHP from the MCDA approach to generate a hierarchical order from one to nine from expert decision-making (Stemmle et al. 2022 and Saaty 1980) by using ArcGIS-spatial MCDA-AHP. In this study, the pairwise comparison of the six criteria based on their priority is shown in Table 3.

Table 3 Pairwise comparison matrix with AHP method for calculating the ATES suitability
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In order to validate the outcomes of the AHP, the consistency ratio is calculated using the following equation:

$$CR = \frac{CI}{{RI }}$$
(1)

where the CR is a consistency ratio and the RI is a random index depending on a number of criteria (Saaty 1980 and Lu et al. 2019a, b). The CI is the consistency index, in turn, calculated through the following equation:

$$CI=\frac{{\lambda }_{max}-n}{n-1}$$
(2)

where the n is the number of criteria and the \({\lambda }_{max}\) is the principle eigenvalue of the matrix calculated as:

$$\lambda_{max} = \frac{1}{n}\mathop \sum \limits_{i = 1}^{n} C_{i}$$
(3)

where the \({C}_{i}\) is the consistency measure calculated by dividing entries (vi) of the consistency vector (v) by the corresponding entries (wi) of the weighting vector (w).

Calculation of ATES suitability map

The suitability of the ATES system in the Halabja-Khurmal sub-basin is calculated via a weighted linear combination using six criteria and their corresponding weighting factors based on the following equation:

$$S_{ATES} = \mathop \sum \limits_{i = 1}^{n} \left( {(w_{i} x_{i} } \right) n = 6$$
(4)

where the SATES represents the ATES suitability, wi is the weighting factors, xi is the normalized rates for each criterion, and n represents the number of criteria.

Result and discussion

The matrix of pairwise comparisons with the AHP in the study area has been calculated based on Eqs. (1,2, and 3). RI value is (1.24), \({\lambda }_{max}\) value is (6.05), CI value is (0.01), and a consistency ratio of 0.008, indicating a very reasonable consistency level in the pairwise comparison (Sólnes 2003). To detect the most suitable location for ATES, all criteria mentioned in this study are considered, and the weights of each criterion are determined by using AHP. All the layers are overlaid with their weights in the ArcGIS weight overlay tool, and the final map of suitability based on AHP-MCDA is created. The final map depicts the suitability for the aquifer thermal energy storage system in the Halabja-Khurmal sub-basin, divided into four categories: not suitable, weakly suitable, suitable, and strongly suitable areas, as shown in Fig. 4.

Fig. 4
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The ATES suitability map

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In the suitability map, the suitable areas are simple aquifer types with high groundwater recharge, good groundwater quality, and low seepage velocity. Conversely, the regions where the conditions are unavailable tend to receive lower suitability scores.

Conclusion

This study used the MCDA-AHP technique with the ArcGIS method to create the suitability map of the aquifer thermal energy storage system in the Halabja-Khurmal sub-basin. For this aim, six hydrogeological and climatic data were combined based on the degree of their influence on ATES suitability. The hydrogeological and climate criteria spatial analysis combination have a consistency ratio of 0.008 in the AHP. The final map has been categorized into four classes with calculated area using the pixel calculation in ArcGIS. The specific value of each category depends on the weighting assigned for each criterion during the calculation of the ATES suitability map. As a result, the ATES suitability map in the Halabja-Khurmal sub-basin displays a surface area of 62.1% as strongly suitable, 7.7% as suitable in northern and southern parts, 29.2% as weakly suitable in southwestern, east, southeast, and northeast, and 1% as not suitable for aquifer thermal energy storage technology. The suitable areas are simple aquifer types with high groundwater recharge, good groundwater quality, and low seepage velocity. Conversely, the regions where the conditions are unavailable tend to receive lower suitability scores.

In this study, new criteria are proposed to evaluate the ATES suitability. Therefore, this study will help the government and the decision-makers to use the ATES as it is economical and contributes to minimizing the emission of CO2 in the Halabja governorate.

Further studies are in progress to evaluate another side of this study by comparative analysis of different data, applying different indicators. In addition, the evaluation results are also expected to be improved by taking more detailed information about the ATES applicability into account.