Assessing small hydropower viability in water-scarce regions: environmental flow and climate change impacts using a SWAT+ based tool

Abstract

Water-scarce regions, like the Mediterranean, face worsening conditions due to climate change, intensifying pressure on key economic sectors such as hydropower. Additionally, environmental conservation policies, particularly the implementation of environmental flows, present challenges for hydropower systems. Certainty regarding the impact of these factors on future hydropower production is crucial for informed decision-making in the transition to sustainable energy. This study introduces S + HydPower, a tool coupled with SWAT+ to assess climate change and watershed management effects on small hydropower plant (SHP) systems. In this study, we used this tool to investigate the consequences of implementing environmental flows and climate change on run-of-river SHPs in the Catalan River Basin District (CRBD), in Catalonia. The results show that applying environmental flows would lead to a significant 27% reduction in SHP production. However, this reduction would represent only 0.25% of the region’s current energy demand. Furthermore, the study reveals a potential 38% to 73% reduction in SHP production by the end of the twenty-first century due to the combined effects of environmental flows and climate change. This suggests a substantial decline in run-of-river SHP’s contribution to the CRBD’s electricity supply. These findings emphasize the need to explore alternative and sustainable energy sources to ensure the long-term reliability and resilience of the region’s energy supply.

Background

Countries in the Mediterranean region are highly vulnerable to climate change, particularly concerning changes in rainfall patterns. Future climate projections for this region, under conditions of elevated emissions, indicate significant reductions in rainfall, especially during the summer and in the southern region during winter [9]. These alterations in rainfall patterns could significantly worsen the ongoing issue of water scarcity in the region. With reduced precipitation, the strain on available water resources is likely to intensify, potentially creating challenges for various sectors that rely on adequate water availability [8, 35]. One of the most vulnerable sectors is energy production, which relies extensively on water for cooling, hydropower generation, and other operational processes [16]. On the other hand, the energy production sector is responsible for about 35% of CO₂ emissions [13], due to its current dependence on fossil fuels [33]. According to the 2030 climate and energy framework, which includes European Union (EU)-wide targets and policy objectives for the period from 2021 to 2030, the EU should achieve a minimum of a 32% share of renewable energy in 2030 (EU, 2023). This highlights the need for investigating the reliability of renewable energy technologies under climate change scenarios and their potential to not only mitigate greenhouse gas emissions but also provide a sustainable and resilient energy supply for the future [4].

In recent years, a consensus has emerged indicating that hydropower plants of 10 megawatts (MW) or less are categorized as small [10, 21]. The perception of small hydropower plants (SHP) as environmentally friendly or “green” energy sources has gained traction due to their smaller dams with purportedly reduced ecological impacts, minimal greenhouse gas (GHG) emissions, and potential socio-economic benefits for communities [18, 22, 46]. Consequently, the development of SHP has grown, supported by both public administrations and private investors, and is expected to continue increasing [10]. However, some studies have demonstrated the strong influence that climate change can pose on SHP performance [30, 37, 38]. Based on these findings, it becomes evident that SHP may not exhibit robust climate change resilience, raising questions about its prospective role in effectively decarbonizing the energy sector in the future. Besides this relevant aspect, SHP might not be as “green” as commonly believed in ecological terms. They make significant contributions to the degradation of aquatic habitats and impact the biodiversity and ecological functioning of these vital ecosystems. SHP projects involve mainly dam construction and flow regime alterations, both of which contribute to diminishing river connectivity, thereby hindering the movement of organisms, especially upstream, and causing mortality due to turbines during downstream migrations [25]. The associated dams and alterations in flow patterns may also disrupt sediment and nutrient transport, leading to significant changes in the hydromorphological characteristics of the affected river sections [19]. In fact, there is evidence that indicates the environmental effects of a series of small hydropower projects could be more pronounced than those of a single large hydropower project, particularly with regard to habitat and hydrological changes [23].

Due to the pressure that anthropogenic activities exert on aquatic ecosystems, the EU has established a range of policies and initiatives aimed at protecting these valuable environments and preserving biodiversity across its member states [27]. One of the principal regulations is the Water Framework Directive (WFD), which establishes a comprehensive framework for water management, aiming to achieve a “good ecological status” for European water bodies. One of the key measures for restoring and managing river ecosystems, as facilitated by the implementation of the WFD, is the implementation of environmental flows, encompassing the maintenance of the quantity, timing, and quality of water flows [1]. Besides, the EU Biodiversity Strategy for 2030 also seeks the restoration of freshwater ecosystems by “reviewing water abstraction and impoundment permits to implement ecological flows in order to achieve good status” (EU 2020). Regarding SHP, there is also evidence indicating that the implementation of environmental flows could potentially result in a reduction in the performance of SHP production. However, the extent of this performance reduction would vary based on the specific environmental flow method employed [7, 24]. Hence, in addition to the potential impacts of climate change, the implementation of environmental flows across the rivers of Europe could introduce supplementary challenges to the already intricate landscape of SHP development and operation. The interplay between climate change, the demands of environmental flow, and SHP production creates a multifaceted scenario that demands meticulous deliberation and strategic planning. Consequently, there is a need to develop modelling tools capable of comprehensively assessing the effects of climate change, environmental flow requisites, and other watershed management measures on hydropower production. Such tools have the potential to empower stakeholders in making well-informed decisions that incorporate ecological preservation, energy strategies, and long-term sustainability considerations.

The Soil and Water Assessment Tool (SWAT), including its latest version SWAT+ [6, 31], is an ecohydrological modelling tool that has been extensively employed for assessing the environmental consequences of watershed management practices and climate change. SWAT produces a wide range of output variables that can be processed to assess the impact of these in relation to ecosystem services (ES) [14]. Water and food provisioning, as well as sediment and nutrient retention, are among the most common ES assessed based on SWAT [15]. Despite the capability of SWAT to produce required variables to quantify hydropower production, such as daily or hourly flow rates, its utilization in this context remains relatively sparse [12, 17, 40, 44]. Other models such as TOPKAPI [28] or AQUATOOL [39] can be applied to assessing hydropower production, but using SWAT or SWAT+ provides more versatility in the management scenarios that can be simulated and the ES that can be used to assess their impact.

The main purpose of this paper is to develop a modelling approach that couples with SWAT+ to evaluate the impact of climate change and watershed management decisions in terms of hydropower production. To develop it, we use a regional case study, the Catalan River Basin District, and evaluate the impact of the implementation of environmental flows on the hydropower production of multiple SHPs present in their subbasins. Additionally, the results of this socio-environmental modelling approach are used to analyse and shed light on the reliability of this energy source to contribute to the decarbonization objectives of Mediterranean countries within the framework of climate change.

Materials and methods

Figure 1 summarizes the methodological steps of this study. We first develop a combined conceptual and practical approach to link the SWAT+ model with a hydropower production calculation model based on specific catchment system characteristics. This approach is implemented as a QGIS plug-in named S + HydPower. To showcase its functionality and adaptability, we apply it to the basins within the Catalan River Basin District (CRBD), focusing on the system of small run-of-river power plants present there. We then analyze, in detail and comprehensively, the impact of implementing environmental flow requirements and the effects of climate change on short, medium, and long-term hydropower production of this system.

Fig. 1

Methodological framework

Case study: the Catalan River Basin District (CRBD)

The Catalan River Basin District comprises a set of small to medium-sized river basins located in the northeastern part of the Iberian Peninsula, in Catalonia. They encompass all the streams and river basins originating in Catalonia and flowing into the Mediterranean Sea, without draining into any interregional watershed, and therefore they are under the full management of the Catalan Water Agency (CWA). Among the more notable rivers within this district, and the ones included in this study, are the Fluvià, Ter, Tordera, and Llobregat (Fig. 2). These river subbasins within the CRBD have run-of-river SHP facilities installed and operational.

Fig. 2

Map locating the basins considered for this study within the Catalan River Basin District (CRBD). Grey coloured subbasins are those with SHP. Yellow triangles locate the considered SHP

During the latter half of the nineteenth century, numerous SHP were constructed along rivers with sufficient flow and slope, primarily concentrated in the Ter and Llobregat Basins. These installations were primarily established to supply the energy needs of industrial activities situated in close proximity. Over time, the impetus behind this electricity source’s development extended beyond industry to encompass various other sectors, including domestic usage (Tarraubella and Mirabet 2013).

By 2017, the CRBD hosted a total of 410 hydropower plants, of which 248 remained operational. Out of these operational plants, 246 had an installed capacity of less than 10 MW, with a predominant focus on run-of-river designs [3]. The collective installed hydropower capacity within the CRBD region reached approximately 262 MW, of which around 120 MW originated from SHP (ICAEN 2023).

Drawing from annual data spanning 2013 to 2020 at the local level (GENCAT 2023), estimations reveal that the electricity demand within the CRBD municipalities stands at 37,006.8 GWh per year. This accounts for roughly 93% of Catalonia’s annual demand, which amounts to 39,642.9 GWh. The average total hydropower production in Catalonia within this timeframe hovers around 4620 GWh. As a result, approximately 11.7% of Catalonia’s demand is met through hydropower resources. However, it is important to note that the hydropower production from plants with an installed capacity below 50 MW amounts to around 874 GWh, contributing merely 2.2% to Catalonia’s total electricity demand. The fluctuation in this percentage is influenced by shifts in demand and variations in hydropower production.

In summary, the initial industrial drive in this European region, coupled with the necessity to harness hydropower to facilitate the operations of industrial settlements, spurred the proliferation of numerous small hydropower plants along these rivers of the CRBD. This factor lends significance to the region as a case study, showcasing a comprehensive implementation of this type of renewable energy resource within a water-scarce context, characteristic of the Mediterranean region.

Definition of the CRBD environmental flows

To ensure the ecological health of rivers in the CRBD, the CWA has followed a sequential criterion to determine environmental flow requirements [11]. Initially, the CWA considered existing environmental flow studies conducted by competent authorities, administrations, or research centres. These studies were carefully examined and validated by the CWA prior to implementation. When specific studies are unavailable, the CWA analysed ecological status analysis protocols, encompassing biological, hydromorphological, and physicochemical characteristics, to determine if existing flow regimes support a favourable ecological status. In these cases, the results of hydraulic methods such as the sequential pulse hydrograph method (abbreviated as QBM in Spanish) [34] were adjusted to align with the specific river section. For river sections lacking specific studies or environmental quality information, or where a good ecological status has not been achieved, the CWA employed the QBM method to calculate the environmental flows.

Development and description of the S + HydPower tool

We developed a modelling approach that uses hydrological SWAT+ simulated outputs to estimate the hydropower generated and evaluate the socioeconomic impact of watershed management measures, that can be modelled with SWAT+ (hereinafter S + HydPower). Besides, this modelling approach allows us to test other scenarios based on the functioning and characteristics of the hydropower system. To enhance accessibility, we have designed the tool as a QGIS plug-in written in Python, making it available to a broader audience.

S + HydPower data requirements

As mentioned previously, S + HydPower is designed to work in conjunction with SWAT+, therefore, it requires data created on the framework of a SWAT+ simulation. Specifically, it requires the use of the channels line vector layer and daily simulated streamflow data (flo_out, m³/s), which should be imported into a SQLite database using SWAT+ Editor. The required SWAT+ output files are channel_sd_day for the run-of-river hydropower plants and the reservoir_day for those relying on a reservoir.

In addition to the SWAT+ datasets, S + HydPower depends on other data and parameters that need to be incorporated into the model. Concretely, two-point vector layers indicating the location of the (1) run-of-river hydropower plants, (2) and the reservoir-based hydropower plants, and (3) another point vector layers indicating the location of the derivation points for the run-of-river hydropower plants. Finally, by default, the S + HydPower tool aggregates the total annual results of the benefits provided by all the hydropower stations included in the program, aggregated by the desired administrative limits where the stations are located (watershed, municipality, county, state, etc.). Table 1 provides a list of these required datasets and the key variables that must be included in the model.

Table 1 List of datasets required for the S + HydPower model

S + HydPower equations

The equations integrated in the S + HydPower tool to calculate the economic impact of the watershed measures or climate change are the following. First in relation to the annual benefits (in the currency chosen by the user) produced in each run-off-river hydropower station ${(EVHP}_{ror hps})$, and then regarding the benefits of each reservoir-based hydropower plants ${(EVHP}_{res hps})$.

$${EVHP}_{ror hps}= \sum_{d=1}^{365}G\times Ft{}_{d}\times H{F}_{hps}\times HL\times Rt\times Rg\times Rs\times {OpDay}_{d} \times EP\times 24$$

(1)

${OpDay}_{hpsd}=1$ si Ft_d > Ftm_hps; otherwise is 0

$$Ft_{d} = {\text{MIN }}\left( {Fmac_{p} ;\left( {{\text{MAX }}\left( {0;flo\_out_{p} - Fmef_{mp} } \right)} \right)} \right)$$

$${EVHP}_{res hps}= \sum_{d=1}^{365}G\times Ft{}_{d}\times H{F}_{hps} \times HL\times Rt\times Rg\times Rs\times {OpDay}_{d} \times EP\times 24$$

(2)

${OpDay}_{hpsd}=1$ si $Ft{}_{d}$ > Ftm_hps; otherwise is 0

$$Ft_{d} = {\text{MIN }}\left( {Fmac_{p} ;flo\_out_{r} } \right)$$

where, ${EVHP}_{ror hps}$ are the annual benefits (in the currency chosen by the user) produced in each run-off-river (ror) hydropower station (hps), G is the acceleration of gravity. Ft_d is the turbined flow on day d. This is determined by the maximum flow allowed per contract at each derivation point p (Fmac_p), the environmental flow on month m in the derivation point p (Fmef_mp), and the daily average flow rate at the river section of point p or reservoir r (which is based on SWAT+ output flo_out). All the previous variables and parameters are expressed in m³/s. HF is the gross head from each p (in meters). HL is the head loss coefficient. Rt, Rg and Rs are the turbines, generators, and transformers coefficients. ${OpDay}_{hpsd}$ is a dichotomous variable (0, 1) that indicates if a hydropower station produces energy on day d, depending on Ft_d is being greater than Ftm_hps, which is the technical minimum flow rate in each hps. EP is the electricity marginal price in currency unit divided by KWh.

Note that in the equations for the reservoir-based stations, the environmental flows are not explicitly mentioned. This omission does not imply that environmental flows are not considered in the modelling process. Rather, it is because SWAT+ utilizes decision tables to accurately simulate the intricate decision-making processes that dictate how water is released from reservoirs [2]. These decision tables are constructed using expert knowledge of reservoir-specific releases. Therefore, the consideration of environmental flows must be configured within the decision tables of each reservoir and is not directly managed within the S + HydPower tool.

Application of the S + HydPower tool for the case of the run-of-river SHP of the CRBD

S + HydPower has been designed to be a versatile tool that allows for modifying its code to adapt the tool to the characteristics and objectives of each case study. In this study, we adapted the S + HydPower tool to evaluate the impact of implementing environmental flows (Fmef) on the hydropower production of multiple small run-of-river hydropower plants (< 10 MW) in the subbasins of the CRBD. Therefore, although land use, climate change, or other SWAT+ simulable scenarios could have been developed and tested, we decided to test the modelling approach involving changes in the hydropower system’s functioning, thus demonstrating the versatility and utility of the S + HydPower tool.

To build up the model S + HydPower for the CRBD we required data on all the water derivation points, the corresponding environmental flows, and the linked SHP, which were provided by the Catalan Water Agency (CWA), although some of the variables, such as Ftm_hps, could not be obtained as they were considered private and had to be extrapolated from others. We were provided with data from 226 hydropower stations. Two were discarded for having and installed power above 10 MW, three more for depending on the water stored in reservoirs, that is, they cannot be considered run-of-river SHP, and twelve other run-of-river SHP could not be considered for having the derivation points in small streams not modelled in the SWAT+ CRBD model. Therefore, the S + HydPower in CRBD considers 209 run-of-river SHP. The corresponding derivation points of these SHP sum 215. The numbers are not the same because it may be the case that a SHP receives water from more than one derivation point, or that a single point and diversion channel supplies more than one power plant. The environmental flow values at monthly level are provided for each derivation point (Table S1 in the supplementary materials). These specificities are considered during the modelling process. For the acceleration of gravity G we used the value of 9.81 in m/s², and for the head loss coefficient HL 0.925, both based on [20]. For the turbines, generators, and transformers coefficients (Rt, Rg and Rs), we applied the value 0.928 for each, based on CWA expert judgment.

SWAT+ modelling of CRBD (the SWAT+ CRBD model)

SWAT is a widely utilized modelling tool for assessing the influence of watershed management scenarios on the water balance of extensive basins [36]. To simulate hydrological processes within the CRBD, we employed SWAT+, an enhanced version of SWAT that offers improved spatial representation of watershed processes [6].

Our land use data was primarily derived from the CORINE Land Cover 2018 dataset. The SWAT+ CRBD model was divided into five sub-models, although for this study we will only use four: Fluvià, Ter, Tordera, and Llobregat. Their calibration was conducted using daily streamflow data spanning from January 1, 2001, to December 31, 2022, collected from 45 different gauging stations. The variability in data series length and spatiotemporal distribution across gauging stations posed challenges in establishing fixed calibration and validation periods that could encompass all spatiotemporal variations. To address this challenge, we allocated 70% of the data for calibration and the remaining 30% for validation for each station, employing a single validation window that could randomly fall within any part of the series.

We carried out a sensitivity analysis involving 30 SWAT+ parameters, utilizing the Fourier Amplitude Sensitivity Test (FAST) method. For each sub-model, we identified between 6 and 13 sensitive parameters using the Kling-Gupta Efficiency (KGE) with a sensitivity threshold exceeding 1‰ of the total variance. Subsequently, we generated 2000 parameter combinations for each sub-model and their corresponding sensitive parameter set using Latin hypercube sampling. The model’s performance was assessed with the objective functions Kling-Gupta efficiency (KGE) and the percent bias (PBIAS). We consider values of KGE > 0.5 and − 25% < PBIAS < 25% as satisfactory [32].

The global daily KGE values for the calibration and validation periods were 0.54 and 0.53, with corresponding PBIAS values of − 13.7% and − 12.8%, respectively. Similarly, the global monthly KGE values were 0.72 and 0.78 for the calibration and validation periods, accompanied by PBIAS values of − 14% and − 12.8%, respectively.

For more comprehensive information on the SWAT+ CRBD model input data, configuration, sensitivity analysis, calibration, validation, and results, please refer to Annexe 1 (supplementary material).

Climate change impact modelling

We simulated the impact of climate change on the future production of run-of-river hydropower plants of the CRBD. We based this analysis on scenarios framed in the Shared Socioeconomic Pathways (SSPs), which are often used in climate change research to explore plausible future socio-economic conditions and their implications for greenhouse gas emissions and climate change impacts. Concretely, we used three different scenarios: SSP126, SSP370, and SSP585.

The scenario SSP126 represents a future world where sustainability is a key priority. It assumes rapid technological development, low population growth, and strong international cooperation to mitigate climate change. In this scenario, efforts to reduce greenhouse gas emissions are successful, leading to a low emission pathway. On the other hand, SSP370 represents a future where socio-economic trends continue along their current trajectories without significant changes. It assumes moderate population growth, uneven development, and fragmented efforts to address climate change. Greenhouse gas emissions continue to rise throughout the twenty-first century, leading to a moderate level of climate change. Finally, SSP585 depicts a future where economic and population growth is high, and reliance on fossil fuels remains dominant. It assumes limited efforts to mitigate climate change, resulting in high greenhouse gas emissions and severe climate impacts by the end of the century.

The related data was obtained from the repository of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. Specifically, we used ISIMIP3b, a segment of the third simulation round. The focus lies on quantifying climate-related risks under varying levels of global warming and socio-economic change [26]. The dataset in question covers CMIP6-based and bias-adjusted atmospheric climate input data for all three groups of ISIMIP3b simulations. It includes data from 5 CMIP6 global climate models (GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL). For this study, we have used the daily simulated weather data from the MRI-ESM2-0 global climate model [45], as it has been used in previous studies to assess the hydrological impact [43] and hydropower production impact [47] of climate change.

Statistical analyses to compare scenarios and the relationship with climate change

Hydropower production results from S + HydPower, measured in monthly MWh, were collected during the simulation period from 2001 to 2020 for each SHP facility. To summarize, we calculated the average production across all SHPs, resulting in a time series dataset with 240 observations (20 years × 12 months). We generated plots to compare the general and yearly distributions of the monthly average MWh under two scenarios: business-as-usual (BAS) and environmental flows (EF). To assess potential differences in hydropower production between these scenarios, we conducted the Wilcoxon signed-rank test. This non-parametric test was chosen due to the non-normal distribution of the data and the paired nature of the observations. The impact of climate change on hydropower production was explored descriptively and considering the implementation of ES compared to BAS, in different projection periods (2025–2049, 2050–2074, and 2075–2100) and scenarios (SSP126, SSP370, and SSP585).

Results

S + HydPower QGIS plug-in

S + HydPower has been developed as a QGIS plug-in using Python programming language (Fig. 3). Its use is open to public, and it can be downloaded and installed within the “Plugins” section of the QGIS software, under the name “S + HydPower”. It was made available in September 2023, and within seven months, it has been downloaded by 580 users.

Fig. 3

Screenshots of the plugin and its use. A Download the plugin from the downloads section from GIS, B execute the plugin from the QGIS menu, C plugin interface, with all the required inputs, D resulting layer

Impact of environmental flows implementation on hydropower generation of SHP

The results obtained from the integration of the S + HydPower modelling tool with the SWAT+ CRBD model indicate that the application of environmental flows compared to the business-as-usual (BAS) situation, can lead to a notable adverse effect on run-of-river SHP production. Figure 4 illustrates the distribution of monthly average hydropower productions, facilitating a comparison between both scenarios and effectively demonstrating this negative impact.

Fig. 4

Box plots comparing the distribution of the monthly average hydropower productions for both the business-as-usual (right) and the environmental flow (left) scenario

For the environmental flow scenario, the average hydropower production is quantified at 92.66 MWh (standard deviation = 58.71 MWh). This represents an approximate decrease in production of 27% compared to the BAS scenario, with an average of 127.11 MWh (standard deviation = 57.28). Notably, the results of the Wilcoxon signed rank test (V = 0, p-value < 0.01) underscore a highly significant distinction between the two scenarios, thereby validating the substantial disparity in hydropower productions between both scenarios.

Climate change impact on hydropower production

Table 2 summarizes the projected impacts of climate change on hydropower production under two management scenarios: environmental flow (EF) and business-as-usual (BAS). The results are further differentiated by Shared Socioeconomic Pathways (SSP): SSP126, SSP370, and SSP585. Finally, the results are also differentiated regarding the time periods (2025–2049, 2050–2074, and 2075–2100).

Table 2 Climate change impact analyses comparing environmental flow (EF) and business-as-usual (BAS) scenarios

As expected, under all SSP scenarios and time periods, monthly average hydropower production (MWh) values under the EF scenario are below those under the BAS scenario. These averages reach their minimum at the end of the simulation period of the climate projections (2075–2100) and under the most pessimistic scenario (SSP585), with values of 25.02 MWh for EF and 47.89 MWh for BAS. In the near-term (2025–2049), it is SSP370 that obtains the lower average for both EF (52.01 MWh) and BAS (80.72 MWh) scenarios.

The data consistently shows a downward trend: hydropower production is projected to decrease under all SSPs and timeframes compared to the current baseline. However, this decrease is less severe under the BAS scenario than under the EF scenario. For example, under SSP126 in the near-term (2025–2049), hydropower production is expected to decline by − 33.56% under EF, but only by − 31.87% under BAS. The most substantial impact of implementing the EF scenario compared to BAS would be observed under the severe climate change scenario SSP585 in the long term (2075–2100), with a potential 50% reduction in production.

Assuming SSP370 represents a middle ground, the results suggest that effective measures to mitigate climate change effects would benefit hydropower production in the medium (2050–2074) and long term (2075–2100), regardless of implementing environmental flows. Specifically, this could prevent a production loss of around 13–15%. Conversely, following a less responsible path (SSP585) could lead to an approximate 51% loss in production by the end of the century if environmental flows are implemented.

Discussion

Considerations of the followed approach

One of the most significant limitations of this study is our inability to access production data from the small hydropower plants (SHP). This lack of data prevented us from effectively carrying out the optimization and validation process of the S + HydPower parameters. Unfortunately, this production data was considered private, and we were unable to obtain permission to access it. In fact, from the previously reviewed literature for this study, only Skoulikaris and Kasimis [38] based the calibration and validation of the hydropower production modelling approach on real production data, although from only one station. To address this gap, a crucial research direction involves emphasizing the significance of calibrating hydropower production models based on authentic production data rather than relying solely on hydrological simulated results.

Similarly, certain critical plant parameters, including technical minimum flow rates (Ftm), were unavailable to researchers due to privacy-related reasons, and extrapolated values from other variables were used. Addressing data access challenges remains a significant concern in the field of hydropower research, particularly when balancing the need for transparency and privacy. Researchers should establish collaborations with hydropower operators or regulatory bodies to gain access to the actual production and system parameters information. Researchers can underscore the critical role of real-world data in refining and enhancing the accuracy of hydropower production models.

Impact of the implementation of environmental flows in the CRBD SHP system

The results of the study confirm that the implementation of environmental flows would lead to a significant decrease in the production of SHP in the CRBD, concretely of about − 27%. This finding aligns with previous studies, such as Boodoo et al. [7]. In their case study in a river basin in Colombia, considering three SHP, they found that the application of different environmental flow methods would result in a reduction in production ranging from − 16.9% to − 76.4%. Similarly, Kuriqi et al. [24], in their case study in the Ebro River Basin (Spain), tested the impact of production in a single SHP by implementing different environmental flow methods. Although in their study BAS productions are not reported, the differences between the most and the least conservative environmental flow methods are close to − 65% of the production.

Translated into terms of aquatic ecosystem protection, these results underscore the presence of significant trade-offs associated with the implementation of environmental flows [5]. Nonetheless, one of the primary strengths of this study is its regional-level calculations, enabling us to contextualize the potential consequences of this reduction in the broader context of electrical energy demand. Under the BAS scenario, the annual run-of-river production of SHP in the CRBD totals 337.1 GWh. This represents a mere 0.91% of the annual electricity demand, which stands at 37,006.8 GWh. When environmental flows are incorporated, annual production decreases to 245.7 GWh, representing approximately 0.66% of the electric demand. This 0.25% reduction, in relation to the 32% renewable energy target that member states are striving to achieve by 2030 (EU 2023), indicates a relatively small impact on the overall renewable energy landscape. Therefore, policymakers and stakeholders can view this reduction as a worthwhile trade-off for the long-term ecological health and protection of aquatic biodiversity [19].

Climate change impact on the CRBD SHP system

Another of the objectives of applying S + HydPower on the run-of-river SHP of the CRBD was to evaluate the potential impact of climate change hydropower production on this system. This was achieved by simulating the performance of run-of-river hydropower plants under different climate change scenarios, using data from the ISIMIP3b framework and the MRI-ESM2-0 global climate model, within the context of the SSP126, SSP370, SSP585 scenarios. According to the results, it can be concluded that the effects of climate change could severely influence the performance of an SHP system CRBD [12, 17, 37, 38], as it has been the case of the run-of-river SHPs in the Catalan River Basin District (CRBD). This can be attributed to the potential reduction in the precipitation that might affect the northeastern part of the Iberian Peninsula [9], and consequently, to the decrease in the average flows available for power generation and also to the reduction in production time, i.e., the portion of time during which there is enough water available for generating power [28].

Skoulikaris and Kasimis [38], whose case study is also located in the Mediterranean region, in this case in the Northwest of Greece, found for the worst-case scenario (RCP8.5) a production reduction in their run-of-river SHP of -25.79% in their long-term simulation period (2071–2100). Using the SWAT model, Yalcin [44] estimated that a planned reservoir-based hydropower plant that would be constructed in the Euphrates-Tigris River would have a decrease of over 21% at the end of this century and under another climate change BAS scenario (SSP5). Therefore, the results obtained in our study align with findings from climate change simulation approaches applied in other Mediterranean regions, in that the realization of the most pessimistic climate change scenarios would entail a significant decrease in production. Under the most pessimistic climate change scenario (SSP585) and without implementing environmental flows, the average reduction in our case can reach 62.32%.

Our study investigated the potential interactions between climate change and the effects of implementing environmental flows on hydropower production. The results indicate that the most significant impact on hydropower production would occur over the long term, particularly under the most severe climate change scenario (SSP585), resulting in a substantial decline of up to 73% compared to the baseline (BAS). Thus, our findings suggest that the decline in hydropower production due to climate change is exacerbated by the implementation of environmental flows. While no other studies, to our knowledge, have analysed these combined scenarios of conservation and climate, it is reasonable to hypothesize that both factors contribute to a reduction in the flow available for turbine operation [42]. On the other hand, the drop in production over time under the implementation of environmental flows seems to be stable over time if severe measures are adopted to mitigate climate change, as is the case with SSP126, remaining at around 38%.

In light of the envisioned application scenario of environmental flows, which represents a plausible future management strategy, particularly under SSP370, reflecting potential outcomes if current emission trends persist [29], and focusing on the near-term period (2025–2049), our analysis reveals a projected reduction in monthly average hydropower production to 52.01 MWh. This reduction prompts a consideration of its impact on the overall electricity demand for the CRBD (assuming a constant demand trajectory until the end of the twenty-first century). Relative to the present, such a decrease could result in a decline in the percentage supplied by hydropower to as low as 0.37% (compared to the current 0.66%). This suggests a significant potential diminishment in the contribution of run-of-river SHP to the CRBD's overall electricity supply in the forthcoming years. This declining trend underscores the susceptibility of hydropower to the impacts of climate change, raising pertinent inquiries regarding its reliability and enduring sustainability as a renewable energy source [41].

Conclusion

This study describes the development and application of a novel and useful tool called S + HydPower. It assesses the impact of climate change and watershed management scenarios that can be modelled using SWAT+ on hydropower production, whether for a single plant or a regional system. In addition, S + HydPower can also be used to evaluate the effects of hydropower management regarding the functioning and characteristics of the plants, such as the case of the implementation of environmental flows. S + HydPower not only enables the evaluation of climate change and watershed management effects on hydropower production but also assesses the impact of different hydropower system scenarios, including the implementation of environmental flows. In this research, we adapted S + HydPower to investigate the potential consequences of environmental flows and climate change on the run-of-river small hydropower (SHP) plants in the Catalan Rivers Basin District (CRBD). Our findings reveal that the implementation of environmental flows would result in a substantial − 27% reduction in SHP production. However, it is essential to contextualize this reduction within the broader renewable energy landscape of the CRBD. This reduction would represent only 0.25% of the current energy demand in the region, particularly considering the 32% renewable energy target set for 2030 by member states. This trade-off becomes more than acceptable when we consider the urgent need to protect the aquatic ecosystems in the region and the potential ecosystem services that such restoration actions could provide. Furthermore, our study highlights the potential severity of climate change’s impact on the SHP system in the CRBD. With anticipated decreases in stream flows in the northeastern part of the Iberian Peninsula due to climate change, SHP production could experience a significant reduction, ranging between 38 and 78% depending on the SSP scenario. The combined effects of environmental flows and climate change could lead to a considerable decline in the contribution of run-of-river SHP to the overall electricity supply in the CRBD.

These results underscore the weakness of SHP over the effects of climate change and the advance in the implementation of aquatic ecosystems conservation measures in water scarce regions. This emphasizes the importance of considering alternative and sustainable energy sources to ensure the long-term reliability and resilience of the region’s energy supply. While the challenges are evident, the study provides valuable insights for informed decision-making in the transition to a more sustainable energy future in the CRBD and similar regions.