# Drinking water availability from scattered crystalline aquifers: Climatic risks evaluated from production data in France

Alexandre Boisson, Cyril Bourgeois, Noémie Neverre

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Alexandre Boisson, Cyril Bourgeois, Noémie Neverre. Drinking water availability from scattered crystalline aquifers: Climatic risks evaluated from production data in France. Journal of Hydrology: Regional Studies, 2025, 59, pp.102405. 10.1016/j.ejrh.2025.102405. hal-05048869

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# Drinking water availability from scattered crystalline aquifers: Climatic risks evaluated from production data in France

Alexandre Boisson<sup>a, *</sup>, Cyril Bourgeois<sup>b, c</sup>, Noémie Neverre<sup>b, c</sup>

## ARTICLE INFO

**Keywords:**

Drinking water

Drought

Climatic vulnerability

Water production data

## ABSTRACT

**Study region:** Brittany, France.

**Study focus:** Climate change and population growth are increasing pressure on exploited drinking water resources networks. Even in temperate climates, this pressure can become significant, particularly in areas where groundwater resources and storage capacities are limited, such as regions underlain by crystalline rocks. The challenge is further compounded in contexts involving small, scattered, and interconnected production units. Assessing failure risks and supply vulnerability is often challenging due to limited monitoring, insufficient data, and poor coordination among the many stakeholders involved. To address this gap, we developed a framework to quantify the vulnerability of drinking water resources by exploitation type (shallow wells, deep boreholes, surface water) using production data in contexts where resource monitoring is minimal or absent.

**New hydrological insights:** We demonstrate that variations in water production can serve as a proxy for evaluating the state of exploited resources in contexts where direct resource monitoring is lacking — a common limitation for small-scale water resource assessments. The framework allows for the identification of compensation mechanisms between surface and groundwater resources and highlights the risks of shortages related to climatic variations. The study highlights the vulnerability of the area and provides insights for improving the security of drinking water supplies. It underscores the importance of considering productivity variations at monthly time steps, rather than limiting projections to an annual basis.

## 1. Introduction

Climate change and population growth increase pressure on water resources in large parts of the world. Decreasing resources and increasing demand make water management increasingly challenging. On the resource side, sustainability has become a major issue (Thomas et al., 2017). Large groundwater declines are observed in various countries of the world (Famiglietti, 2014; Gleeson et al., 2012; Wada et al., 2010) such as in India (Dangar et al., 2021; Fishman et al., 2011; Rodell et al., 2009), Bangladesh (Shamsuddha et al., 2009), the USA (Famiglietti et al., 2011; Russo and Lall, 2017). Although often less visible, this observation is also true under temperate climates, such as in Europe (Xanke and Liesch, 2022) and droughts are expected to become more frequent and severe

<footnote><sup>a</sup> BRGM, Direction régionale Bretagne, Rennes, France</footnote>

<footnote><sup>b</sup> BRGM, Université Montpellier, Montpellier, France</footnote>

<footnote><sup>c</sup> G-Eau, UMR 183, INRAE, CIRAD, IRD, AgroParisTech, Institut Agro, BRGM, Montpellier, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: a.boisson@brgm.fr (A. Boisson).</footnote>
(Spinoni et al., 2018) with impacts on rivers (Gudmundsson et al., 2021, 2017) and groundwater as in Germany (Wunsch et al., 2022). In France, the decrease of water resources, especially during summer, has long been anticipated (Boé et al., 2009; Habets et al., 2013) but new estimations of global warming depict a situation even worse than previously anticipated (Ribes et al., 2022).

While in temperate regions natural water availability is apparently large, exploitable resources remain limited. The increasingly recognized need to share the resource for human activities (drinking water, agriculture, industry) and environmental requirements (minimum flow in rivers, sustainability of wetlands...) limits resources availability and development. Hence water shortage can also occur in temperate countries. For example, Manoueli et al. (2018) estimate that every area in the UK may face a supply-demand gap by the 2080s.

In temperate climate, regular rainfall reduces the risk for perennial drought. However, the assessment of risks of drought and resilience to drought should not be drawn at an annual time scale but rather at a finer seasonal or monthly resolution (Beek et al., 2011; Wada et al., 2011), which requires sufficient data. Water stress is often assessed at an annual time scale (Alcamo et al., 2003; Arnell, 2004; Vörösmarty et al., 2000). However, as water availability and demand vary over the year, water stress may be underestimated by annual assessments as availability and demand may be out of phase (Beek et al., 2011; Toth et al., 2018). Wada et al. (2011) demonstrate at a global level that climatic variability is often the primary determinant of water stress at a decadal scale. They also show that with a monthly resolution, the number of people experiencing water scarcity increases by more than 40 % compared to conventional annual assessments that do not account for seasonality and inter-annual variability. Beek et al. (2011) and Wada et al. (2011), highlight that this effect is particularly significant in densely populated regions but also show that some temperate regions, as southern United Kingdom, may also experience infrequent but detrimental water stress. Seasonality may be further amplified by tourism (Toth et al., 2018).

Shallow aquifers offer storage capacity that filters out extreme events while remaining vulnerable to long-term changes in climate forcing (Hartmann et al., 2017; Pokhrel et al., 2021; Taylor et al., 2013). This storage capacity depends on the aquifer's properties which can be highly variable. Compared to large sedimentary aquifers, basement aquifers have more limited resources and are more vulnerable (Liesch and Wunsch, 2019). Those aquifers in temperate climate follow an annual cycle of replenishment and discharge. Consequently, drought risk can be particularly important in crystalline rocks areas even under temperate climates due to their limited long-term storage capacity. This is a matter of concern in various countries such as Sweden (Barthel et al., 2021), Norway (Wong et al., 2011) or the northern part of United Kingdom (Barker et al., 2016; Dobson et al., 2020).

In the context of basement aquifers, this resource is particularly limited in time and space. The structure of basement aquifers depends mainly on the alteration properties of the rocks. In the case of crystalline basement regions, groundwater resources are considered to be limited to weathered and fissured horizons (Acworth, 1987; Dewandel et al., 2006; Lachassagne et al., 2021; Mougin et al., 2008; Wyns et al., 2004), large faults and densely fractured zones (Leray et al., 2013; Roques et al., 2016; Schroëtter et al., 2020). As a result of this structure, a decrease in productivity is observed with depth (Boisson et al., 2015; Guihéneuf et al., 2014), which can lead to the sudden drying up of wells or boreholes when the main productive fractures are no longer supplied. In this type of environment, the seasonal drop in water table levels therefore leads to a drop in productivity or even a drying up of the exploited resource. This is observed in arid environments (Guihéneuf et al., 2014) with dramatic consequences (Maréchal, 2010) but is often neglected in temperate climates. While the phenomenon is known, it remains insufficiently quantified to be used in resources management. These mechanisms need to be integrated into the global and interconnected management of the resources, especially in a context of climate change.

Future water management will shift from building new water supply systems to better operating existing ones (Harou et al., 2009). The problems linked to water management are complex and the parameters to be taken into account are numerous, including: climatic, geological, geomorphological (Price, 2011; Taylor et al., 2013), economic and human factors (Rinaudo et al., 2012; Scanlon et al., 2007), but also technical factors such as the interconnection of water supply networks.

The diversity and intricacy of human, geological, and climatic factors, along with their interconnections and the operational demands of drinking water networks, pose significant challenges for effective management. This complexity makes large-scale phenomena, such as droughts, difficult to interpret (Van Loon, 2015). To address these multifaceted parameters, management and optimization models are being developed (Harou et al., 2009). As decision making grows increasingly demanding, tailored tools are required to support decision making (Girard et al., 2015; Harou et al., 2009; Lanini et al., 2004), ensuring robust collaboration among diverse parties (Montginoul and Rinaudo, 2009; Neverre, 2024; Rinaudo and Garin, 2005). The number of these model remain limited due to the lack of data to examine the effects of spatial variability of droughts on the reliability of water supply (Dobson et al., 2020).

Lack of data and accurate monitoring is a regular issue in groundwater management, both at the global scale (Taylor et al., 2013) or local scale. It is especially true in a context of multiple small exploited resources as in crystalline aquifers where means for monitoring are limited. Also, in the case of small scattered resources the lack of communication and interaction between multiple operators at different levels limits regional and local management possibilities and fragmentation can become a source of vulnerability (Boholm and Prutzer, 2017; Garnier and Holman, 2019; McFarlane and Harris, 2018; Mullin, 2020).

Although groundwater hydrology is a well-established field, the unknown repercussions of variations in natural water resources on specific infrastructures (such as boreholes and dams) make it challenging to accurately determine the amount of water that can be safely withdrawn on any given day (Dobson et al., 2020). Numerous studies exist on human impact on water resources (Wada et al., 2017) but little information is available on climate impact on water production systems, especially on small production units, which is a need for water agencies (Boholm and Prutzer, 2017; Subak, 2000) and water producers.

The objective of this study is to develop a methodology to quantify the impact of seasonal and inter-annual climatic variations on drinking water production capacity in a context of limited underground resources and scarce data availability. The aim is to evaluate, on a monthly timescale, the vulnerability of drinking water supply systems and test their capacity to further support population
growth, industrial expansion, and tourism development.

The study is conducted in a crystalline rock region in Brittany, France, where significant annual rainfall masks the risk of summer droughts and the lack of resilience to extreme events. This threat is further aggravated by limited knowledge of water resources (in terms of both volume and dynamics) due to complex geology, inadequate resource monitoring, and the disparity in water withdrawals by various operators. Despite a temperate climate and relatively moderate impacts of climate change compared to other regions (Gudmundsson and Seneviratne, 2015; IPCC, 2021), summer droughts are expected to become more intense and frequent in this area (Dubreuil et al., 2018; Lamy, 2013). These challenges are shared with other crystalline regions in France with limited storage capacity, including the Armorican Massif, Central Massif, Corsica, and Vosges. In these areas, drought conditions may lead municipalities to rely on water transported by tankers as observed in 2022. These challenges also resonate with those observed in other regions with similar geology, such as parts of Sweden (Barthel et al., 2021; Nygren et al., 2022, 2020), Norway (Wong et al., 2011), and the northern United Kingdom (Barker et al., 2016).

Local insights from this study not only enhance the understanding of these issues at a regional scale but also provide valuable information that can be applied to other regions. The results underscore the need for diversifying water resources in such contexts. Additionally, the study offers opportunities for improved drinking water network design and modeling to optimize drinking water resources management.

## 2. Site description

### 2.1. Drinking water system

The study area is located in the western part of Brittany (France), downstream of the Aulne watershed (Fig. 1). The area spans 63 municipalities grouped into six local authorities (EPCIs) which are interconnected through a drinking water supply network. The 6 EPCIs use mostly their own local water resources when sufficient for their needs. When their own resources are insufficient they buy water from the Syndicat mixte de l'Aulne (SMA) that pumps in the river Aulne, which is one of Brittany's major rivers and benefits from low-flow support from a reservoir. Hence the SMA has a securing role at the scale of the territory.

Diverse water exploitation types are present in the territory with direct pumping from rivers, dams, shallow wells, boreholes, drains. Some sites use a conjunction of shallow wells and boreholes. Those will thereafter be referred to as mixed resources.

The survey of the local resources show that on the territory, drinking water comes from 81 sites exploited with 50 wells, 19 boreholes, 2 dams, 6 river surface water resources, 2 drains and 6 springs operated by 6 different local authorities (EPCIs) (Fig. 1). The

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Map of the area with drinking water abstraction sites. The study area is composed of 6 EPCIs (in orange) and detailed investigations were conducted on the DzCo and Crozon EPCIs (in red). Geology is composed of plutonic and metamorphic rocks (in pink) and schists (mostly Paleozoic, in dark green).</figcaption></figure>
exploitation potential of the resources is 111 500 m³/day. The allocation by resource type is dominated by the surface water with a volume of 64 500 m³/d (58 % of the total capacity), 35 450 m³/d for the shallow wells (31 % of the total capacity), and boreholes represent only 6.5 % with a volume of 7 250 m³/d. Others resources as springs or drain represent around 4.5 % of the total capacity. The Aulne resource (SMA), which secures the area has a theoretical capacity of 38 000 m³/d (34 % of the uptake capacity, and half of the surface water total capacity) when no natural restriction exists (low flow). Hence, apart from this major surface resource, the resources from the shallow wells and surface water are balanced.

This pattern is contrary to the partition at national scale in France, where most of the drinking water comes from groundwater through the exploitation of large aquifers. This partition is in line with what is observed at the regional scale (Brittany), where almost 75 % of the drinking water comes from surface water while only 25 % comes from groundwater. On the studied area these resources are used by a population of around 200 000 people. At the regional level (Brittany), the population is 3.3 million people.

The survey conducted among the drinking water producers show that individual resources exploited by the different operators are all exploited following the same pattern. Exploitation of the local resources of the EPCIs being cheaper, all EPCIs use their own local resources first and when their resources are insufficient they use the resource from the SMA. This behavior is driven by economic rules. Based on 2022 data provided by water producers, the cost of groundwater abstraction is 0.38€/m³, while surface water exploitation comes at 0.68€/m³ due to larger treatment costs. Water from the SMA is more expensive with a cost of 0.68€/m³ and a surplus of 0.38€/m³ in the period from June to October. Hence the SMA has a securing role in the configuration. However, the SMA has no regulation role, and there is no coordination between the EPCIs.

## 2.2. Climatic context

The area has a temperate oceanic climate with a mean temperature of 12°C and annual precipitations superior to evapotranspiration potential (ETP). For precipitations an annual mean of 1214 mm/y is recorded at Quimper (Météo-France). Precipitations occur all year long with a maximum between October to February (monthly mean 138 mm/m) and a minimum in summer June to August (monthly mean 63 mm/m). Yearly ETP, determined by Météo-France following Penman-Monteith method, is 770 mm with a maximum in summer (116 mm/m).

## 2.3. Geological context

The geology of the area is composed of plutonic and metamorphic rocks and schists which are mostly Paleozoic. In such a context, the aquifer properties are inherited from weathering and can be highly heterogeneous. The aquifer development follows the classical model for hard rock aquifers (Acworth, 1987; Dewandel et al., 2006; Wyns et al., 2004) with a decrease of permeability with depth (Boisson et al., 2015; Dewandel et al., 2006). Historical development of the production sites was based on a conceptual model of discontinuous aquifers and prioritized saprolite exploitation (i.e. shallow wells) while current developments go toward deeper boreholes.

# 3. Materials and methods

## 3.1. Data collection

### 3.1.1. Local data availability

Complexity, cost and time required for monitoring often leads to limited information on resources especially for small and scattered production units. Often the collected data (water levels, pumping rates) are not monitored enough or without sufficient precision (collection of relative levels without a clear reference, gaps in data, short time series...). Available data is often insufficient to produce a clear model of the resource's variations over time. This is especially true in heterogeneous media as crystalline aquifers and scattered exploitation resources where information is scattered due to numerous water production sites and producers.

From the EPCIs the available water level from exploitation sites were limited to 3-year water levels time series on 3 sites and 2-year water levels time series on 2 sites, over the 78 exploitation points of the area. This dataset is too limited to build a resource vulnerability assessment.

Although natural resource monitoring (water level) can be limited, production volumes are more often available at the monthly time step. Hence we use site production data as a proxy to assess evolution of water resources. Information on site production was available from public yearly reports made by the water producers. From those reports, 23 times series of monthly site production volumes (representing 1/3 of the sites) was available. Monthly volumes time series length ranges from 3 to 10 years. All time series are continuous (no data gap). This data set was completed by the monthly produced volumes by the SMA on the period 1973 – 2024 with the delivery partition at the local authority scale.

The interpretation of local data was cross-checked with local knowledge before being validated through a participatory approach involving several collective meetings with all water producers and numerous bilateral meetings. These exchanges are essential to guarantee the completeness and accuracy of the data, as well as the representation of production patterns. They must ensure that no significant changes in production modes occur during the period. This includes modifications such as alterations in pumping capacity, well rehabilitation, or the development of site interconnections. Additionally, these exchanges help monitor for any major shifts in demand, such as the establishment of a new industrial plant or changes in the surrounding environment, including noticeable transformations or the implementation of new pumping systems. These exchanges are crucial for validating the stability of exploitation
conditions, demand, production capacity, and the site's surroundings, and are essential for interpreting data in relation to climatic variations. This knowledge sharing and validation process are mandatory for further data interpretation of production data. Those meetings also raise awareness about the lack of information sharing between the different water producers of the area.

Despite the interaction with drinking water managers of the area and their involvement, the data are available on a limited number of sites, highlighting the lack of monitoring and informative elements on the water withdrawals capacities. This lack of data for model calibration prevents from building a resource assessment based on a physical flow model of the territory.

### 3.1.2. General data

In addition to the production site data, natural piezometric levels are monitored by 5 piezometers from the French national network operated by the BRGM (French geological survey - www.ADES.fr). Stream flows are monitored by the French national network (www.hydroportail.fr) with 20 monitoring stations on the study area including 5 on the Aulne river. The climatic informations (precipitation and ETP) are obtained from the French meteorological survey (Météo France). The data collected and validated by these dedicated national organizations do not present major gaps. The few missing days were corrected by linear interpolation.

### 3.2. Data treatment

The data analysis is performed to draw the typical yearly and multi-year production distribution and decipher the processes of interaction between resources and distribution patterns between independent operators on an interconnected network to identify system vulnerability. We use statistical analysis, signal decomposition and statistical correlation for data comparison.

#### 3.2.1. Monthly analysis

Monthly analysis of the production data is made based on classical statistical analysis using means, median and quantiles calculated over the reconstructed production time series for the different sites. All production data is available at the monthly time step. This analysis is performed to assess the impact of seasonality.

#### 3.2.2. Multi-year assessment

A long-term analysis of the data is conducted to identify trends over multiple years, excluding seasonal variations. The goal is also to standardize the data so that the magnitude of their variations can be compared. Multi-year evolution of the resources is assessed based on production variations over 10-year time-series to account for variability. The long-term evolution of production is assessed by calculating at a monthly time scale the difference with the monthly mean over the 10-year period, normalized by the standard deviation. A 12-month moving average is then applied over the monthly anomalies to smooth the signal. This technique attenuates the short-term fluctuations and accentuates the long-term fluctuations and allows for comparing signals of different types in a homogeneous manner. This procedure has been previously used by some authors to analyse the long term evolution of natural resources (Boutt, 2018; Weider and Boutt, 2010).

The anomalies are calculated according to the following equation:

$$A_i = \frac{m_i - \bar{m}}{\sigma_m} \qquad (1)$$

With, $m_i$ the monthly value, $\bar{m}$ the mean for this same month over the entire 10-year period, and $\sigma_m$ the standard deviation for this same month over the entire time series. Correlation on long term trends of production data other variables is quantified using Spearman correlation.

#### 3.2.3. Computation on the securing resource

For securing resources (SMA), we break down the data to separate the seasonal patterns from the long-term trends. The goal is to determine how much of the volume is due to regular, cyclical consumption and how much is influenced by larger, long-term changes. Long term and seasonal decomposition of production values is performed by seasonal additive decomposition which is a time series analysis technique used to break down a time series into its constituent components: trend, seasonal, and residual (or noise). This method assumes that these components combine additively to the observed data. The trend component represents the long-term progression or direction in the data, such as an upward or downward trend over time. The seasonal component captures regular, repeating patterns that occur at consistent intervals, such as monthly or quarterly cycles while the residual component represents the random fluctuations or noise that cannot be explained by the trend or seasonal components. The additive model can then be expressed as:

$$Observed\ Data = Trend + Seasonal + Residual \qquad (2)$$

Calculation were made using R package ggplottimeseries (Edullantes, 2019). This decomposition is used to extract the long-term trend of the signal and assess its significance over the complete series.

#### 3.2.4. Exploitation cost calculation

Exploitation cost calculations are estimated from the produced volumes based on the exploitation cost given by the EPCI and the contract agreement between the SMA and the EPCIs. The exploitation cost for groundwater, whether by wells or boreholes, has been estimated by the EPCI to be 0.38€/m³ throughout the year. For surface water, this cost is higher due to larger treatment requirements
and is estimated as an annual average of 0.68€/m³. Purchases from the SMA have an evolving price. The base cost is fixed by the SMA at 0.68€/m³, but it adds a surplus of 0.38€/m³ during the period of high demand (June to October), resulting in a cost of 1.06€/m³ during this period. The same values will be applied for all sites.

This methodology can be applied when water production data spans a sufficient period (a minimum of 5 years) with no or limited gaps, and when the stability of the production pattern has been validated by local stakeholders. In the following section we present the resource use for two EPCIs on a yearly time scale, one with enough local resources for its own needs and a second with insufficient local resources. Then we generalize the impact of climate on productivity by exploitation type and look at the impact on the securing resource (SMA) to assess the vulnerability of the area.

# 4. Results

## 4.1. Monthly evolution of resources productivity

Examples of water demand (distributed volumes) evolution at the scale of EPCI during the year and production by individual site are presented in Fig. 2. Those examples are representative of the other EPCIs, with in one case an EPCI (DzCo) whose resources are sufficient to meet the drinking water needs, while for the second (Crozon), resources are insufficient during summer and they resort to the SMA to fill their resource-needs gap. Mean monthly production and water needs are shown Fig. 2. For both EPCIs, shallow wells (in blue Fig. 2) are the primary water sources during winter. Since they are cheaper (0.38€/m³), those resources are always exploited at their maximum capacities. During summer the decrease in productivity and the increase in demand is compensated by either local surface water (for DzCo – cost: 0.68€/m³) or purchases from the SMA (for Crozon – cost 0.68–1.06€/m³). Despite a more limited water production capacity, boreholes on DzCo are more resilient in summer and production remains constant all year long. Hence, as shown by the example, the increase of water resources import from the SMA should not only compensate the increase in water demand but also the decrease in other resources productivity. Hence the evolution of water demand between winter and summer in Crozon (+23 %), mostly related to tourism, is accompanied by a large increase in water imports from the SMA (+450 %).

The generalization of the monthly production by exploitation type is made using the average annual variability for each resource type. Complete production data was available on 16 water production sites (5 wells, 3 mixed resources, 3 boreholes, 5 surface water sites). Data are normalized by their authorized production capacity (Fig. 3). Although conducted on a limited number of sites, the analysis shows the decrease of production of the wells in the summer period (June-September) by almost 50 % of their capacities on average. Monthly evolutions show a decrease in production in summer for all wells, at the same time when the water demand is the highest. This decrease is hence not related to a decrease in the water demand but rather a limit on the resource's productivity. This

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Mean water demand and individual exploitation site production for DzCO (top) and Crozon (bottom) (Based on the monthly means over the 2011–2020 period).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Annual evolution of the resources production by type normalized by their authorized production capacity (SMA, Wells, surface water, boreholes and mixed resources) based on 16 water production sites (5 wells, 3 mixed resources, 3 boreholes, 5 surface water sites).</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Boxplot of the summer production evolution by resource type.</figcaption></figure>
element has been confirmed by the water managers. The wells do not become dry but often less productive with in certain cases a drastic decrease of the productivity. Surface waters are not used during winter due to larger exploitation costs (0.68€/m³) than groundwater (0.38€/m³). Boreholes are used all year long with a slight increase during summer to meet the demand. Mixed resource sites (well and boreholes) where abstracting from the deeper borehole compensates for the decrease in shallow well productivity during summer appear to be more resilient. The annual analysis shows the dependency of the shallow well resources to climate and its compensation by drinking water producers by using surface water as well as deeper groundwater, which displays a better resilience than shallow wells. In complement, decreases in production between September and February by resource type are shown in boxplot Fig. 4 and highlight a decrease in production of shallow wells, a small decrease for mixed resources (shallow wells and boreholes). On the other hand, production is slightly higher for boreholes and largely increased for surface water. In this context surface water resources are used not only to compensate the increase in demand, but also the decrease in the wells productivity.

## 4.2. Inter-annual impact on local resources

The inter-annual evolution of productivity is evaluated against groundwater levels on the area of DzCO where data on produced volumes is available on the period 2010–2021. During this time scale, the driest year was observed in 2011 while the most humid year was 2012. The monthly production data can be compared to the piezometric levels available from an uninfluenced monitoring piezometer from the national monitoring network (www.Ades.fr) in the same plutonic formation. Locally crystalline aquifers are ruled by annual periodicity meaning that the aquifer replenishes and discharges almost completely on a yearly basis with almost no pluri-annual cycles visible on the water levels. On the area and its close surroundings, 5 piezometers are available (Fig. 1). The comparison between drinking water needs, groundwater level, and the production from each resource for DzCO is displayed in Fig. 5 with the mean, median, as well as the driest (2011) and wettest (2012) years.

The comparison shows that for the year 2011, when the water levels were the lowest, during the period May to December the production of the wells (Kergaouledan site) were also at their lowest; while for the same period in 2012, when the piezometric levels were at their historic highest, this site production was also at its historic maximum. These changes in production are directly related to the resource availability since May-November corresponds to the highest water needs period and wells are always exploited at their full capacity when needed due to lower costs. In 2012, due to a late recharge in April, the levels during the beginning of the year were low as well as the production level on shallow wells site, while after the recharge period the increase in water level induced an increase in production. On the other hand, the surface water (Keratry site) was more used in the 2011 dry year than in the 2012 wet year. Deep boreholes (Botcarn site) keep a relatively constant production rate. The low production in winter is related to lower water needs (less tourism).

Identical observations can be made on the Crozon area (Fig. 6), with a decrease in well productivity which is in this case compensated by imports from the SMA (Fig. 6, bottom right). The surface water site on the Crozon area does not allow withdrawals

CCDzCo

Drivers

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

Production per resources

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

**Fig. 5.** Comparison between water needs and piezometric levels (at Landrevarzec) versus production by sites on the 2010–2021 period on DzCo. The year 2011 (in green) is the driest year of the period while the year 2012 (orange) is the wettest in summer. Red and blue lines are median and means over the whole period.
CROZON

Drivers

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

Production per ressources

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /><figcaption>**Fig. 6.** Comparison between water needs and piezometric levels (at Landrevarzec) versus production by sites on the 2010–2021 period for the Crozon sites. The year 2011 (in green) is the driest year of the period while the year 2012 (orange) is the wettest in summer. Red and blue lines are median and means on the period.</figcaption></figure>

during summer and is used only in extreme cases with derogations (as in 2011). Hence, without a derogation for not respecting target low flows, which are critical for biodiversity, the surface water production site is not used.

The observed decrease in well productivity affects both the exploitation distribution and the costs for the utilities. To assess the impact, the produced volumes are converted to monthly exploitation costs following the rules described in Section 2, "Exploitation cost calculation." These cost evolutions are presented in Fig. 7. The transposition from volume to cost shows that on the DzCo territory, a relative increase of 16 % in volume in August induces an increase of 65 % in the total cost. In the case of the Crozon area, the variation

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /><figcaption>**Fig. 7.** Monthly mean production cost for DzCo (left) and CROZON (right) areas. On top: comparison of produced volumes (m³) in black against production cost (€) of the total area (in black) and specific sites and cost per m³ (dashed red line) on right axis. Bottom: relative variation against January of the total costs (in black), total volumes (in blue) and cost per m³ (in red).</figcaption></figure>
is even worse, with a 219 % cost increase for only a 38 % increase in volume. This drastic increase mainly comes from SMA purchases. For both territories, while the demand and the produced volume decrease at the end of August (end of the touristic season), the costs remain high since the well capacity does not recover until the recharge period occurring around November. This transposition to cost confirms that the main driver of resource solicitation is the groundwater level.

To assess the impact of climate on resource productivity in the long term as well as the regularity of the compensation mechanisms between the different resources types used in the DzCo area, anomalies in production levels and water levels are displayed in Fig. 8. For a comparison with climatic variations, precipitations anomalies are also displayed.

The anomalies in production levels at the wells site (in blue) follows the anomalies in precipitations (black) and piezometric levels (dashed blue). The production from the surface resource (red) is anti-correlated with the wells site production, highlighting the compensation mechanism between resources to ensure drinking water supply. The boreholes production follows a different trend, which is probably more impacted by water demand and production rules. Fig. 8 shows that in a crystalline context, climatic variations directly influence the resource availability and distribution. Precipitations anomalies transpose directly to the surface and groundwater resources as well as to the exploited resources productivity, firstly on shallow groundwater which further affects surface water production.

The comparison of the production in August between the typical dry and wet years as well as the ratio between those two years is displayed in Table 1. It shows a production decrease close to 40 % for the wells (a site out of DzCo and Crozon but in their vicinity has also been added to increase the quantity of data analysed). Mixed resources show a lower decrease in production during a dry year. It shows that the drier the summer is, the lower is the shallow water production capacity and higher the use of surface water.

To assess the impact of the inter-annual climatic variation on the securing resource (SMA surface water) and hence the vulnerability of the area against climate change and intense drought the assessment was also performed on the securing resource of the SMA. Availability of data on the period 1983-2020 allows for a broader interpretation of the variation on this resource.

## 4.3. Inter-annual climate variability on securing resources (SMA - AULNE)

The time series on individual resources are restricted to a limited number of sites and on a limited period of ten years (2010–2020). To assess the long-term relation between local withdrawals and resource availability on the area the only long time series available are from the rivers and for the monthly production of the SMA which is the resource that has been used for securing the area for the period 1983–2020. By its securing role, the variations in production from the SMA resource integrate the variations in production of all the other resources of the area. Variations in volumes produced by the SMA as well as the anomalies are presented in Fig. 9.

Anomalies in production variations of the SMA (Fig. 9, bottom) show no clear increasing or decreasing trend over the whole period. Over the period the demographic growth has been mostly compensated by water savings as generally observed at the regional scale and by the individual EPCIs. Peaks of production appear in the years 1989, 2003, 2011 and 2017, which are the years of the most important droughts in the area over this period. While those peaks in production may partially come from an increase in water demand, from the previous observation they are mostly influenced by the failure of individual subsurface resources.

### 4.3.1. Links between produced volumes and water levels

To compare those variations in production with the subsurface resource availability, the anomalies variations in production are compared to the piezometric levels (Fig. 10) for the period 1993–2020. For an easier comparison of the phase and amplitude, the inverse of the SMA production (production * –1) is also shown on the figure.

<figure><img src="image_19.png" /><figcaption>**Fig. 8.** Normalized anomalies with precipitation (dashed black), piezometric levels (dashed blue), production on sites: well site (Kergaouledan – solid blue), surface water (Keratry - solid red) and Water demand (Dashed orange) and boreholes (Botcarn F1 and F2 – dashed green).</figcaption></figure>
<table><caption>**Table 1**
Production ratio by site and type in August between a dry summer (2011) and a wet summer (2012).</caption><thead><tr><th>Type</th><th>EPCI NAME_Site Name</th><th>Production: August 2011 (m3)</th><th>Production: August 2012 (m3)</th><th>Ratio</th></tr></thead><tbody><tr><td>Wells</td><td>DzCO_Kergaouledan</td><td>12643</td><td>23610</td><td>0.54</td></tr><tr><td>Wells</td><td>CROZON_Kernagoff</td><td>32067</td><td>50614</td><td>0.63</td></tr><tr><td>Borehole</td><td>DzCo_Botcarn_F1</td><td>10152</td><td>10986</td><td>0.92</td></tr><tr><td>Borehole</td><td>DzCo_Botcarn_F2</td><td>11041</td><td>11477</td><td>0.96</td></tr><tr><td>Mixed</td><td>CCHPB_Kermaget</td><td>13683</td><td>16841</td><td>0.81</td></tr><tr><td>Mixed</td><td>CCHPB_St-Ronan</td><td>34826</td><td>42500</td><td>0.82</td></tr><tr><td>Surface</td><td>CROZON_Poraon</td><td>19570</td><td>0</td><td>-</td></tr><tr><td>Surface</td><td>DzCO_Keratry</td><td>66960</td><td>52808</td><td>1.27</td></tr></tbody></table>

<figure><img src="image_20.png" /><figcaption>**Fig. 9.** Top: Monthly distributed volume by the SMA; Bottom: Anomalies extracted from the production data (Large production upward, low production downward) with highlighted minimums and maximums dates.</figcaption></figure>

The comparison of the water levels and the production from the SMA show a very strong anticorrelation. Note that withdrawals by the SMA (in the Aulne river) have no influence on the groundwater levels. The inverse of the distributed volumes (in dotted blue) allows for a comparison of the amplitude of the signal, showing that both anomalies signals have not only the same phase but also the same relative amplitude. This highlights the strong link between local resources availability (especially shallow groundwater) and the volumes requested to the SMA.

The Spearman correlation was used to quantify the relationship between the different variables in the study. Values of these correlations are provided in Table 2. This assessment highlights, as expected, that for DzCo the strongest correlation is between groundwater levels and the wells (0.9). A strong anti-correlation is also observed with surface water (-0.88) and, to a lesser extent, with boreholes (-0.65), which are used to compensate for the decrease in well productivity. No clear correlation appears between water demand and water production on the site. For Crozon, the strongest correlation is obtained between groundwater levels and the wells (0.84) and in a lower extend with the Crozon site (0.6), which is unable to produce in summer. Purchases from the SMA, which is the securing resource, are anti-correlated with groundwater levels (-0.81), as it is used to compensate for the decrease in local resource capacities. From this analysis, no strong correlation is observed between water demand and water production on individual sites.

### 4.3.2. Quantification of the climatic impact on produced volumes

To quantify the changes in distributed water volumes by the SMA related to long term climatic variations, a seasonal additive decomposition of the signal was performed (Fig. 11). The extracted trend represents 20 % of the produced volume in average, with an influence up to 50 % in 1989 and 29 % in 2011 and 2017 in comparison to a wet year. The extracted trend is identical to the previously mentioned anomalies but without normalization. This important part of the climatic variable on the requested volumes shows that
<figure><img src="image_21.png" /><figcaption>Fig. 10. Comparison of the anomalies in distributed volumes by the SMA and anomalies in piezometric levels on the nearest piezometer.</figcaption></figure>

<table><caption>**Table 2**

Correlations between the variables (Groundwater levels, water demand, site production and climatic factors).</caption><thead><tr><th>Site</th><th>Variable 1</th><th>Variable 2</th><th>Spearman Correlation</th><th>Spearman p-value</th></tr></thead><tbody><tr><td rowspan="10">DzCO</td><td rowspan="5">Groundwater Level</td><td>Water demand (Total Production)</td><td>-0.229</td><td>1.179E-02</td></tr><tr><td>Production Kergaouledan (Wells)</td><td><strong>0.906</strong></td><td>8.951E-46</td></tr><tr><td>Production Keratry (Surface W.)</td><td><strong>-0.885</strong></td><td>4.863E-41</td></tr><tr><td>Production Botcarn (Boreholes)</td><td>-0.651</td><td>5.931E-16</td></tr><tr><td>Production Keryanes (Surface W.)</td><td>-0.392</td><td>9.379E-06</td></tr><tr><td rowspan="5">Water demand (Total Production)</td><td>Production Kergaouledan (Wells)</td><td>-0.039</td><td>6.728E-01</td></tr><tr><td>Production Keratry (Surface W.)</td><td>0.373</td><td>2.651E-05</td></tr><tr><td>Production Botcarn (Boreholes)</td><td>0.248</td><td>6.379E-03</td></tr><tr><td>Production Keryanes (Surface W.)</td><td>-0.014</td><td>8.785E-01</td></tr><tr><td>Precipitations</td><td>-0.152</td><td>9.747E-02</td></tr><tr><td rowspan="10">CROZON</td><td rowspan="5">Groundwater Level</td><td>ETP</td><td>0.459</td><td>1.329E-07</td></tr><tr><td>Water demand (Total Production)</td><td>-0.322</td><td>3.299E-04</td></tr><tr><td>Production Kernagoff (Wells)</td><td><strong>0.845</strong></td><td>8.369E-34</td></tr><tr><td>Production Poraon (Surface W.)</td><td>0.620</td><td>4.494E-14</td></tr><tr><td>SMA Purchase (Sercuring ressource)</td><td><strong>-0.811</strong></td><td>3.436E-29</td></tr><tr><td rowspan="5">Water demand (Total Production)</td><td>Production Kernagoff (Wells)</td><td>-0.099</td><td>2.798E-01</td></tr><tr><td>Production Poraon (Surface W.)</td><td>-0.123</td><td>1.800E-01</td></tr><tr><td>SMA Purchase (Sercuring ressource)</td><td>0.451</td><td>2.290E-07</td></tr><tr><td>Precipitations</td><td>-0.422</td><td>1.540E-06</td></tr><tr><td>ETP</td><td>0.597</td><td>6.445E-13</td></tr></tbody></table>

impact of climate on water demand is not only related to an increase in needs but also highly dependent on the status of the general subsurface resource availability. Hence as a 30 % increase in needs is evaluated in dry years (e.g: years 2011, 2017; Fig. 11), the impact in years of limited resource availability will be larger than an increase of needs related to water demand only and may create unexpected pressure on the drinking water network as observed in 2017.

### 4.3.3. Vulnerability of the area to water shortage

This decrease in local water production capacity is of little impact if the securing resource is large enough to compensate for it. However, while being the most abundant resource on the territory the Aulne has still a limited capacity. As a main river it also fills other upstream needs as well as environmental requirements. To maintain environmental requirements a minimum flow should be maintained during summer. Unit hydrograph of the river compared to the minimum flow required for environmental needs Qmin (in red) show that the Qmin is close to the median and above the bottom 25 percentile in summer. Hence the river is often in a stressed situation. The monitoring station is located upstream of the pumping site and hence is not influenced. Over the data availability period (1983–2020) the region experienced severe droughts during the years 1989–90; 2011; 2017. The comparison of the securing resource with the Qmin flow (Fig. 12), taking in account that most of the surrounding resources may not be able to provide more water, shows the vulnerability of the area and a tense situation even under a temperate climate.
<figure><img src="image_22.png" /><figcaption>Fig. 11. Quantification of the long term trend in the volumes distributed by the SMA.</figcaption></figure>

<figure><img src="image_23.png" /><figcaption>Fig. 12. Unit hydrograph of the Aulne at Chateauneuf-du-Faou with the minimum environmental flow in red. When river flow is below the minimum objective flow (dashed red line), pumping is forbidden.</figcaption></figure>

## 5. Discussion

The risk of drought and water shortages in temperate regions like Brittany is often underestimated due to regular rainfall and the perception that climate change will have less impact there compared to northern or southern Europe (Gudmundsson et al., 2017; IPCC, 2021). This perception obscures the urgency of taking adaptive measures. In Brittany, pressures on water resources are often attributed to economic and demographic growth rather than climate. However, dry summers and droughts have become increasingly frequent, with significant water stress recorded in 1976, 1989, 2003, 2017, 2019, and 2022. Future projections (IPCC, 2021; Ribes et al., 2022) indicate that such events will grow more frequent and severe, heightening pressure on the drinking water supply system. While drought intensity in Brittany may be lower than in other regions, the area's limited groundwater reserves and current resource exploitation methods make it highly vulnerable. In 2022, severe drought left some municipalities reliant on trucking or alternative water sources like quarries. This underscores that even in a temperate climate with minimal irrigation demand, Brittany faces significant summer water stress due to the low resilience of shallow groundwater resources. The temperate climate and prevailing perceptions mask the growing risk of droughts and their impact on water supply.

This study highlights a critical lack of monitoring and coordination among water resources stakeholders. Given that subsurface water resources function as a flow rather than a fixed stock, tracking their yearly drainage is essential especially in low-capacity aquifers as crystalline rocks. As noted by other researchers (Boholm and Prutzer, 2017; Garnier and Holman, 2019; McFarlane and Harris, 2018; Mullin, 2020), fragmentation and poor information sharing are major vulnerabilities in securing drinking water supply.
The involvement of numerous stakeholders and unintentional information gaps obscure both local challenges and global risks. This study underscores the importance of using at least monthly data, rather than annual averages, to assess critical summer water stress.

Yearly decreases in water resources productivity are locally acceptable but their cumulative effects which are further enhanced on a multi-year scale may become critical. The decrease induces a large increase in cost for the EPCIs and the consumers. Moreover, the resulting concentration of production on a single resource (SMA) is a strong vulnerability factor and a major challenge at the scale of the whole territory. Small shallow aquifers are known to be particularly vulnerable to climatic variations (Hartmann et al., 2017; Liesch and Wunsch, 2019) however this risk is further extended by the resource exploitation mode. With such exploitation mode, the pressure on certain resources do not come only from the demand increase and the impact of climate on that given resource, but also from the failure of small local resources which are not monitored and hence difficult to predict. The drinking water supply system primarily relies on dams and river water abstraction. These dams serve multiple purposes: drinking water production, maintaining minimum river flows, and sometimes hydroelectricity generation, which can lead to conflicts of use. Climate forecasts predict slightly higher rainfall intensity but with concentrated and erratic temporal patterns. Regional forecasts on water resources for the region highlight increasing risks of resource replenishment issues for dams which are the cornerstone of the drinking water system (Abhervé, 2022).

Incomplete resource replenishment during winter (both dams and aquifers) intensifies the strain on limited resources, forcing tough choices between drinking water supply and environmental needs. Increasingly frequent exceptions to low-flow standards underscore this tension. For instance, heavy reliance on SMA resources often extends until December with impact on water costs. Brief but intense rainfall events can mask winter droughts from public awareness and hinder timely action, as these events create short-lived river flow spikes without significantly recharging aquifers. Additionally, cooler temperatures and scattered rain from September onward obscure the extended low-flow periods. Both winter droughts and prolonged low-water periods are significant but largely hidden risks.

Given the complexity of drinking water management—including rivers, dams, wells, boreholes, and interlinked infrastructure networks managed by various operators — rationalization through efficient hydro-economic modeling (HEM) is essential (Dobson et al., 2020; Harou et al., 2009). However, HEM requires accurate data, often lacking for both resource availability (stock and dynamics) and monitoring (e.g., water levels in natural and exploited sources). The methodology of the present study can be used to inform in a HEM the resource part of the model. This study demonstrates that, despite these gaps, resource status can be partially inferred from analyzing production capacity evolutions. When physically based groundwater modelling is not available or not possible to develop due to data limitations this approach based on production data can be a relevant alternative. Working from production data to predict production capacities from long-term time series makes it possible to take into account the effect of seasonality but also the effect of larger events as droughts. This approach ensures realistic information for an accurate representation of the evolution of exploited resources, with the advantage of bypassing the need for detailed groundwater descriptions and model calibration from natural resources to exploited resources. In Brittany's temperate climate, water production partition between resources is primarily driven by demand in winter when resources are plentiful, while in summer, both demand and availability influence production patterns, with local water availability becoming a significant constraint. For example, municipalities relying heavily on SMA imports highlight these limitations. When interpreted with input from local stakeholders, water production data can serve as a valuable proxy for resource availability and status. As a "resource with invoice," production volumes are monitored, verified, archived, and are often the only reliable information available, particularly for small, unmonitored resources.

The information gathered using the procedure developed in this paper can be applied to predict productivity decreases due to resource availability in relation with climatic variations through numerical modelling. Yet, climate forecasts on water resources rarely account for productivity decline. Non-exploited groundwater resources are typically monitored at the national level (e.g., in France through the national monitoring network (www.ades.fr)) with hydrogeological modelling developed for forecasting. Since water levels and well productivity are closely linked, those hydrogeological models can be adapted following the relation between groundwater levels and production obtained from this methodology to local scales to predict not only water levels but also productivity decreases on shallow resources and possible impacts to surface exploitation sites. While this method may be less precise than detailed models used for large sedimentary aquifers (e.g., Saltel et al., 2021), where substantial resources are allocated and data and monitoring exist, it remains valuable in areas with shallow resources, limited data, and many small water production sites where detailed monitoring and modelling are not feasible.

Shallow resources like wells are the most vulnerable to annual and multi-year production declines, making this mode of exploitation poorly resilient in the region. Other resource types show greater resilience, which can be further enhanced by adding boreholes to well fields without increasing overall extraction rates. While this does not increase total water availability, it can sustain productivity during summer. Mixed-resource systems have demonstrated the value of such adaptations, with only a 10 % average productivity decrease in summer (Fig. 4). The region's crystalline substratum limits the development of large new resources, though moderate-scale exploitation remains possible. Implementing new resources requires significant time for both installation and regulatory approvals, which in France can take several years. Despite these limitations, such solutions are cost-effective and faster to implement in a region already facing critical challenges. During the summer of 2022, nearly the entire area faced water usage restrictions. This study demonstrates that, even without considering climate change, the current situation in temperate climates over crystalline aquifers is precarious due to low resilience. This methodology can facilitate such identification in other data-scarce areas with scattered exploited resources. This approach can be applied in other contexts involving shallow unconfined resources that are directly influenced by climatic variations. This method can be particularly valuable in headwater catchments, which are often poorly characterized. Careful management, emphasizing monitoring, data sharing, and collaboration among stakeholders, is crucial.

This approach can be utilized in future work to provide information on water resource productivity to hydro-economic models (Neverre, 2024), thereby forming the "hydro" component of the model. This will enable the development of an effective
decision-support tool for water management and planning, especially in contexts with limited data.

## 6. Conclusions

The study proposes a framework which allow to highlight the high vulnerability to drought of drinking water supply in areas with low-resilience aquifers (small volumes, annual discharge), even under a temperate climate. It demonstrates that, in data-scarce contexts, production volume data, when analyzed with local stakeholders, can serve as a useful proxy for water resource status and help identify vulnerability factors. This data can also help assess the impact of annual and multi-year climatic changes on water resource productivity. This approach offers a methodology that can help build decision-support models in areas with limited natural resource data, by providing key information on the resource part for building integrated hydro-economic models assessing climate change impact on drinking water supply.

From this study, we identified various vulnerability factors which hide the existing risks of water shortage. The first one is the perception of a temperate wet climate. The others are related to the low resilience of the exploited water resources to face climatic variations, resulting from both aquifer properties and exploitation modes. The least resilient exploitation mode (wells) represents 1/3 of the production capacity of the area and faces a severe productivity decline in summer. This situation induces, during extreme events, a concentration of water production to a few resources, with major vulnerability in case of pollution or shortage. The use of multiple small resources is often an advantage for securing supply. However, without cooperation and proper management tools, it may be critical when productivity and failure risks are not adequately reported and anticipated. Altogether, the combination of these factors may have locally critical consequences.

Local insights from this study not only enhance the understanding of these issues at a regional scale but also provide valuable information applicable to other regions facing low-resilience aquifers and data-scarce conditions. Future developments of this approach will focus on forecasting exploited resource capacity at the scale of exploitation site and integrating the approach into hydro-economic modeling, in areas where complete hydrogeological modeling is not feasible.

## CRediT authorship contribution statement

**Alexandre Boisson:** Writing – original draft, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.
**Cyril Bourgeois:** Writing – review & editing, Resources, Methodology, Data curation, Conceptualization.
**Noémie Neverre:** Writing – review & editing, Project administration, Funding acquisition, Conceptualization.

## Funding

This work benefited from the financial support of the Agence de l'Éau Loire-Bretagne (Water agency) and the Region Bretagne through the project "De l'eau pour Demain" and European Interreg France (Channel) England program, co-funded by the European Regional Development Fund (Water for Tomorrow project).

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

The authors would like to thank the water producers from the EPCIs of the area for their dedication in data collection and knowledge sharing. The authors thank also the three anonymous reviewers for their thoughtful comments which improves the quality of the manuscript.

## Data availability

Data will be made available on request.

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