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Article

A Procedure to Estimate Global Natural Recharge in Karst Aquifers

by
Eugenio Sanz Pérez
,
Juan Carlos Mosquera-Feijóo
*,
Joaquín Sanz de Ojeda
and
Ignacio Menéndez-Pidal
ETSI Caminos, Canales y Puertos, Departamento de Ingeniería y Morfología del Terreno, Universidad Politécnica de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Water 2025, 17(12), 1779; https://doi.org/10.3390/w17121779
Submission received: 25 April 2025 / Revised: 27 May 2025 / Accepted: 10 June 2025 / Published: 13 June 2025

Abstract

Natural recharge in karst aquifers is a key component of global water resources, yet its estimation remains challenging due to the complexity of karst hydrogeological processes. The recharge assessment deserves special consideration, especially in the current global climate and sustainability challenges. This study poses a methodology to appraise natural recharge rates in karst aquifers worldwide, drawing on climatic and geological data. In this regard, this study applies a methodology previously developed by two of the authors, in which natural recharge over large areas is considered a fixed fraction of precipitation, which varies according to different lithologies of similar hydrogeological behavior (hydro-lithological units). Given that carbonate rocks are known to have the highest recharge rate relative to precipitation (34.3%), the method builds on existing karst and average precipitation maps to calculate worldwide recharge in karst aquifers. Recharge is appraised at 4,381,063.7 hm3/yr, which represents 34.5% of the global groundwater resources, a percentage that indicates the importance of karst in this regard. Based on maps of recharge values worldwide, this study highlights the importance of carbonate aquifers when compared with assessments of the world’s groundwater resources made by international institutions or other types of aquifers. The method is contrasted with other ways of assessing groundwater resources used in diverse regions of Europe. The impact of different climate change scenarios on the natural recharge of these karst aquifers has also been analyzed. Thus, under a climate change scenario in 2050, it is estimated that natural recharge will be reduced by about 10%.

1. Introduction

Knowledge of the sustainable recharge capacity of aquifers is of great theoretical and practical interest in terms of groundwater potential, especially considering that recharge values are not equivalent to available groundwater resources, given that a large part of the recharge is not exploitable due to technical and economic criteria. Other parts are not available either, as it is mandatory to preserve the base flow of rivers and the water levels of aquifer-dependent wetlands to prevent marine intrusion into coastal aquifers, among other reasons.
Groundwater can significantly contribute to climate change adaptation: its wide availability and generally large reserves, long retention time, and slow response or inertia make it naturally protected from seasonal and interannual variations in precipitation and temperature. Unlike surface reservoirs, aquifers lose negligible amounts of water through evaporation and transpiration. However, groundwater also has its limits of exploitation, and for sustainable groundwater management, overexploitation must be prevented. In this sense, Wada et al. (2010) [1] provide a global overview of groundwater depletion, which they define as extraction in excess of recharge. Other recent studies point in the same direction [2,3].
Recharge is also one of the least understood hydrogeological variables, as it varies in space and time and is difficult to measure directly. Natural recharge at a given location depends mainly on hydrometeorological factors (precipitation, temperature/evapotranspiration) and the nature of the terrain (permeability of the lithology of the aquifers). Still, it also depends on the existence and type of soil, relief, vegetation, land use, etc. [4]. Precipitation is the primary source of recharge in most real situations. Nevertheless, precipitation is a highly spatially and temporally variable phenomenon in the short term and the long term, fluctuating seasonally and interannually. This fact makes the assessment of water balance and recharge highly uncertain [5,6,7,8]. Moeck et al. (2020) studied many published works on recharge estimation in specific aquifers worldwide [9]. They concluded that precipitation rates and the seasonality of temperature and precipitation were the most important variables for predicting recharge. Therefore, multiple correlations between recharge/precipitation and temperature variables have been successfully tested for specific karst aquifers and short periods (weeks, months), with seasonal temperature variations being reflected [10,11,12]. Yet, for annual mean values, the temperature in a given region does not change significantly from one year to another. Conversely, precipitation has a significant interannual variability. Therefore, considering annual average values, there is a good correlation between precipitation and recharge for a given aquifer. In any case, recharge’s high dependence on climate indicates its sensitivity to climate change.
As mentioned above, one of the essential factors determining recharge is lithology, and among all types of ground, karst aquifers have the highest recharge rate relative to precipitation [9,13,14,15]. Carbonate rocks are the geological formations with the highest recharge rate relative to precipitation. Apart from the surface area occupied by karst in the world, this high recharge rate is why these regions have extensive groundwater resources compared to other land types. Karst regions offer a variety of natural resources (such as freshwater and biodiversity), cultural resources, and protected areas [16,17]. According to Goldscheider et al. (2020) [15], 15.2% of the global ice-free continental surface is characterized by the presence of karstifiable carbonate rocks; Europe boasts the highest percentage (21.8%), and the global importance of karst serves to justify future research and international water management strategies. Stevanović (2019) [18] first assessed the worldwide availability of water in karst aquifers, amounting to 3165 km3, with a recharge rate relative to precipitation of 20%. This study also estimated that 9.2% of the world’s population (about 678 million people) are karst water consumers and that 127 km3/yr of water is extracted from karst aquifers, about 13% of the total global groundwater abstraction. Hartmann et al. [19,20] applied the first large-scale simulation model to assess groundwater recharge in karst regions in Europe. The average values for four different climatic environments (humid, mountains, Mediterranean, desert) range from 35% to 40%.
This study focuses on global karst regions. The global distribution of karst was assessed departing from the map and database developed by the WOKAM (World Karst Aquifer Map) project (2012–2017). Based on this, Stevanović (2018) [21] and Goldscheider et al. (2020) [15] indicate that carbonate rock outcrops characterize 15.2% of the Earth’s ice-free land surface. The highest proportion of karst is found in Europe (21.8%), followed by North America (19.6%), Asia (18.6%), Africa (13.5%), Australia and Oceania (6.2%), and South America (4.3%). China has the largest absolute karst area (2.54 million km2) and the highest karst proportion (26.5%) among the ten world’s largest countries.
Regarding topographic distribution, 31.3% of all karst areas are in plains, 28.1% in moderately elevated terrain, and 40.8% in mountainous regions. Approximately 15.7% of the world’s coastlines are composed of carbonate rocks. Regarding climatic zones, the most significant proportion of karst is found in temperate regions, where 19.1% of the land surface consists of carbonate rocks, followed by cold climates (16.8%) and arid zones (14.8%). In contrast, tropical and polar regions have significantly lower proportions of carbonate rocks, with 8.8% and 7.7%, respectively.
The main objective of this work is to provide an approximate assessment of the current natural recharge in karst aquifers worldwide, using the recharge-to-precipitation rate of 34.3% obtained from Sanz and Menéndez Pidal (2013) [13], and to quantify the importance of this type of aquifers’ contribution to the global water balance.
The results provide the world’s first global picture of natural recharge in karst aquifers. They will be of particular value for assessing potential global water resources and modeling the influence of climate–surface–subsurface interactions on global climate change. Some assessments are made based on assumptions of future climate change, but an attempt is also made to roughly infer what karst recharge may have been like in the past during the last ice age.

2. Materials and Methods

2.1. Methodology

This study applies a new method for estimating the average natural recharge of large regions based on establishing recharge rates as a function of rainfall for six lithological groups of different permeability (we could also call them hydro-lithological units).
The method was initially tested using a very large sample of springs, allowing researchers to establish specific distribution functions for water supply (or contribution) based on flow rates across different lithological groups in the Iberian Peninsula [22]. This test confirms the validity of the general lognormal function established by Sanz Pérez (1996) [23].
Subsequently, in a large region such as Spain (506,000 km2), statistical inferences were applied to a sample of 875 springs for which the mean flow and the lithology of their feeding area were known. The analysis grouped springs according to regions with different rainfall and showed that mean annual recharge was a fixed fraction of mean rainfall for each lithology and independent of temperature. Recharge rates, as a function of precipitation, were obtained by adjusting the provisional recharge rates obtained to the estimated total recharge in the natural regime in Spain as assessed by the Libro Blanco del Agua (MIMAM, 2000) [24] so that diffuse discharges were also considered.
Thus, the authors determined the recharge rates with respect to average precipitation for six lithological groups with different permeability (hydro-lithological units) [13]: sands, gravels, and alluvial formations in general, 8.3%; conglomerates, 5.6%; sandstones, 7.3%; limestones and dolomites, 34.3%; marls, marlstones, silts, and clays, 3.3%; hard rocks, 1.3%. Among these, the karstic aquifers stand out, with a high average recharge rate of 34.3%.
Spain has a remarkable lithological variability, an abundance of calcareous soils (15%), varied pluviometry, topography, etc. These features then entail a certain representativeness as a sample. Thus, recharge rates relative to precipitation, and especially those of karst, are quasi-universal values that can be used to estimate average recharge or average groundwater resources for large regions anywhere in the world except in singular areas, such as those with permafrost. In this sense, precipitation and lithology data are widely available, so the method is applicable elsewhere to complete water balances. The method applied here in Spain has not yet been extended to the rest of the world because the cartography of the hydro-lithological units available worldwide (e.g., Gleeson et al., 2011) is not exactly the same as the one we used [3,25,26,27]. It would be necessary to translate the geological maps into hydro-lithological maps where the lithostratigraphic formations, and not the chronostratigraphic ones, would be clearly distinguished.
The authors have previously applied this procedure to a river basin in Spain (Cuenca del Duero, 90,000 km2) and four European countries (Spain, Portugal, Ireland, and Italy) to check the goodness of the method. For this purpose, the results have been compared with official statistics (Eurostat, 1998) [28,29,30] obtained by different methods. These countries have a sufficiently large surface area, a varied lithology, high participation of karst aquifers, and very different rainfall (Spain is the driest country in Europe, with an average annual rainfall of 687 mm/yr, and Ireland is the rainiest, with 1150 mm/yr). Therefore, the proposed method has already been adjusted and calibrated and does not require a historical series. The calculation of average recharge builds on knowing the surface distribution of a river basin, region, or country according to these six lithological groups. Once this distribution is known, the analysis can be applied to the average or annual recharge. This method only requires knowing the yearly rainfall in each lithological group. The recharge rates were obtained for Spain but can be considered globally representative, given that Spain has a very diverse geology and lithology. However, these rates could be refined in regions where they could be better adapted. In this way, the method can be applied to any region or country, except in very cold regions or other extreme cases (such as permafrost), since precipitation and lithology data are readily available. Our method allows an approximate assessment of potential groundwater resources worldwide by using readily available data: lithology and mean precipitation.

2.2. Limitations of the Method

This work attempts to assess natural recharge in karst aquifers at a global level. The authors are aware of the difficulties and uncertainties involved in a study that focuses on the Spanish case as a prototype, although it serves to compare different geographical areas and changing situations (climate change and past epochs).
This method is only suitable for large regions where the weights of the various factors involved in aquifer recharge cancel each other out, leaving precipitation and lithology as the determining factors for mean annual recharge. Karst hydrogeology is highly heterogeneous, and recharge is often influenced by diverse factors such as conduit development, land cover, vegetation, and seasonal dynamics, none of which are considered here. Therefore, this method is unsuitable for small geographical areas where these particular local characteristics may be more critical than lithology. The minimum scale at which it is valid is unknown, but it has proven to work for Spanish regions up to 90,000 km2. This method should be used cautiously in smaller areas since local characteristics can influence recharge significantly. The mean annual recharge rates have been derived from statistical analysis of large areas so that they can be applied accurately on a global scale.
The assessments here refer to the karst’s spatial distribution as aquifers exposed to precipitation or outcropping, where predominantly diffuse autogenous recharge is verified. Allogenic recharge from losing rivers that infiltrate the karst and deep confined or semi-confined aquifers below other impermeable geological formations, even if they receive delayed recharge and constitute groundwater resources and reserves, is not included in the calculation. Transfers between aquifers are also neglected. Although this does not substantially change the large numbers obtained, it is indeed a systemic underestimate.
The current approach disregards karst areas covered by glacier ice, as the former mainly affects continental regions. This assumption is a simplification that neglects some exceptional cases, such as the recognition of glaciokarst depressions where recharge occurs at the bottom of the glacier. Areas with permanent or temporarily frozen ground will also not be considered. However, karst development and the behavior of karst aquifers are very different and limited under permafrost conditions [15,31], and recharge is also known to occur in some instances.
Another secondary limitation of the method is the resolution of the data used in the GIS application, which may be limited. For instance, the raster files employed (for rainfall maps, digital elevation models, and similar datasets) have relatively coarse grid sizes. In addition, certain attributes in vector files remain unknown due to the unavailability of data in some regions of the world. The assumed projection system is global, and some inaccuracies may arise in calculating areas

2.3. Data Sources and the Application of Geographic Information Systems (GISs)

Regarding data source and lithology distribution in particular, this study built on the 1:400,000 Map from Riba Arderiu (1969) for Spain [32] and the CEC-Eurostat GISCO/1995 Map Series for Portugal, Ireland, and Italy, which group the multiple lithologies differentiated in the six categories considered above [33]. Figure 1 illustrates the lithological distribution involved in the study. Current global precipitation data, along with another map for the period 1941–2060, were taken from WorldClim [34] to analyze the future scenario of the variation in global mean precipitation due to climate change. The results yield a 1–3% decrease from the original values. Likewise, the map information concerning karst aquifers was taken from WHYMAP (BGR, IAH, KIT & UNESCO, 2017) [34], that of the distribution of glaciated areas from Natural Earth [35], and that of current permafrost from the FAO-UNESCO Soil Map of the World [36].
The procedure used to gather all the information related to the karst terrain surface and the associated precipitation in a single layer requires the use of the Intersection tool, which superimposes the vector layer of the karst from the WHYMAP on the raster maps of current and future precipitation from the Natural Earth website [35]. The high latitude and high mountain glacial and permafrost layers were subtracted later with the aid of a GIS tool.

3. Examples of Application of the Proposed Method for the Assessment of Total Annual Mean Natural Recharge

3.1. Application to the Assessment of Natural Recharge in the Duero River Basin (Spain)

The Duero River basin is located in the northwest of Spain and covers an area of almost 90,000 km2. It receives an average rainfall of 621.3 mm/yr. It is a large sedimentary basin containing detrital and marly deposits, surrounded by predominantly carbonate mountain ranges (Figure 1).
Carbonate rocks belong mainly to the Paleozoic limestones of the Cantabrian Mountains to the north (e.g., “Calizas de Montaña”—“Mountain Carbonates”—of the Carboniferous of Picos de Europa). To the east, the Jurassic and Upper Cretaceous limestones and dolomites of the Iberian Cordillera predominate. To the south is the Upper Cretaceous limestone rim bordering the Sistema Central. There are also horizontal Miocene limestones forming plateaus (‘Calizas del Páramo’) in the central areas of the basin.
The Duero basin (object of this study) was divided into 11 areas defined by isohyets at intervals of 100 L/m2, ranging from 350 L/m2 to 1450 L/m2. The class marks of each area or interval were rounded with precipitations of 400 L/m2 and 500 L/m2, i.e., in multiples of 100. The lithological groups’ occupied areas were calculated for each of these 11 areas.
These data were derived from the 1:400,000-scale lithological map [32], in which each 5 × 5 km2 grid cell indicates both the area occupied by each lithological group and the corresponding average rainfall. Table 1 shows the distribution results for the entire Duero basin.
For the sake of brevity, in Table 1 and the following ones, which correspond to the assessment in several European countries, we have selected a few lithologies out of the nine shown in Figure 1. Thus, the rest have been gathered in a group called “others”, which collects the results of the remaining rock types: quartzite, slate, plutonic, gypsum, and volcanic rocks. However, the recharge rates corresponding to each of these lithologies have been included in the recharge estimation calculations.
Thus, a total contribution of 3311.5 hm3/yr has been obtained, very similar to that obtained by Estrela et al. (1999) [38], from a distributed mathematical model applied to the whole of Spain, which gave an average annual natural recharge value of 3000 hm3/yr for the Duero basin. We used the hydrological model SIMPA (Simulation of Precipitation Input, developed by CEDEX, Centro de Estudios y Experimentación de Obras Públicas, Spain) for these calculations. This distributed conceptual model simulates average monthly flows in a natural regime at any point in a basin’s hydrographic network. It reproduces the essential processes of water transport that occur during the diverse phases of the hydrological cycle. The approach applies the principle of continuity, establishing distribution and transfer laws between storages in each cell of the discretized territory. The temporal resolution was set to one month, and the spatial resolution to a cell size of 1 km2. The model assumes that recharge to the aquifer coincides with infiltration within each cell and that there are no transfers between aquifers or losses from allogenic rivers. Although the latter is a limitation of the method, it does not detract from its value in national-scale assessments.

3.2. Application to the Calculation of Natural Recharge in Several European Countries

To demonstrate the versatility of this method, the approach has been applied to four Western European countries: Spain, Portugal, Ireland, and Italy, which have sufficiently large surface areas and assorted lithologies and rainfall. In addition, Spain is the most arid country in Europe, and Ireland is the wettest (Figure 2). It is also assumed that natural recharge has been assessed with sufficient accuracy by other very different methods. Table 2 summarizes the area, the average rainfall period 1901/1902–1995/1996 [39], the average recharge calculated in previous work, and the recharge calculated in the current study.
As for Portugal, recharge calculations were based on separating the base flow from selected rivers. Using the average recharge values obtained for various basins, regression lines were fitted to mean precipitation data and subsequently extrapolated to the remaining basins [41,42,43].
In Ireland, water balance calculations were based on actual evapotranspiration using the Penman formula. Where possible, the resulting recharge estimates were compared with values derived from base flow separations in river hydrographs.
In Italy, water balance studies were conducted in well-documented basins, assessing basin outflows (river base flow, direct discharge to the sea, and extractions) using both mathematical and analog models. Recharge values obtained from these studies were subsequently extrapolated to other aquifers.
The 1:400,000 Map from Riba Arderiu (1969) [32] was used for the lithological data for Spain. The CEC-Eurostat GISCO/1995 Maps were used for Portugal, Ireland, and Italy, where the numerous lithologies differentiated are grouped into the six groups considered above. Table 2 shows the lithological distribution. To calculate the recharge, the P i coefficients of Table 3 and the average precipitation of each country were used.
The lack of precision associated with using mean precipitation introduces some errors, but the large spatial scale of the analysis partly compensates for this. Except for Italy, the results obtained (Table 3 and Table 4) are reasonably reliable. In the former case, two factors can explain the estimated mean recharge value: First, limestone outcrops are mainly located in areas with the highest precipitation, which means that above-average precipitation should have been used in the calculations. Second, Italy has a significant amount of volcanic rock, for which the recharge rate relative to precipitation remains uncertain, but is assumed to be relatively high.

3.3. Assessment of World Average Natural Recharge in Karst Aquifers

Figure 3 shows the map of karst outcrops totaling 20,259,600 km2, representing 15.17% of the Earth’s surface. The mean annual precipitation isohyets and areas covered by glaciers and permafrost are superimposed on this layer. The spatial information has been harmonized by back-projection to WGS 84. Likewise, raster files have been resampled to a standard resolution of ~1 km2 (30 arc-seconds), which ensures geometric consistency between the layers used (WorldClim v2, WHYMAP, Natural Earth, FAO-UNESCO). Then, 2350 km2 of karst surface (11.6% out of the total) is located in regions topped by permafrost and glaciers, having either low or null recharge rates. Consequently, these are disregarded in the assessment, leaving a net karst area of 18,509,000 km2 (13.8% of the Earth’s surface). According to data provided by WorldClim on monthly precipitation averages recorded during the period 1980–2010, the estimated recharge worldwide is 4,381,063.7 hm3/yr. Table 5 shows its distribution per continent, with Asia contributing the most and having the highest recharge rate per unit area of karst surface (434 mm/m2).

3.4. Recharge at the 2050 Horizon Taking into Account Climate Change

This analysis considers a future scenario in 2050, where average annual precipitation over karstic surfaces drops by 2% from the current 732.8 mm/yr to 718.1 mm/yr (source: WorldClim) [34]. However, this scenario’s spatial distribution of precipitation does not mirror the current pattern proportionally. The hypothesis assumes that rising temperatures eliminate all seasonal permafrost, allowing frozen karstic terrains to function as new aquifers. As a result, total recharge declines to 3,918,530.9 hm3/yr (Table 6). This assumption implies a decrease in recharge of approximately 10.55%. It should be noted that the reduction in precipitation to 2% is an average and that, according to predictions, this reduction is more significant in areas with high rainfall.
Finally, although it is a mere testing exercise of very relative value, an estimate has been made of the recharge in the karst during the Last Maximum Glacial (LMG), assuming that the distribution of precipitation and recharge rate is the same as at present, which may be highly debatable. Thus, according to the distribution of glaciated and permafrost areas in the LMG [47], the total recharge was 3,800,000 hm3/year, which is a 12% reduction, mainly in Europe, Asia, and North America.

4. Discussion

The intrinsic characteristics of karst aquifers—such as their heterogeneity, degree of karstification, and variable recharge rates—and the limited data available for many poorly studied systems make it extremely difficult to carry out global recharge and water resources assessments. This results in a high level of uncertainty. Assessing both the degree of uncertainty and the statistical error is challenging because, although the natural recharge assessment method has been tested in other Spanish and European basins, insufficient data is available to calibrate it in areas outside Europe. Furthermore, there are no recharge assessment data on karst at a global level, nor on specific aquifers or general recharge at the country level. Using a universal recharge rate relative to precipitation might seem like an oversimplification that overlooks the complexity of karst systems. We suggest that future work should incorporate more detailed karst typologies where such data are available. However, nothing can truly be understood without measurement, which requires representing reality through a limited set of measurable attributes and quantifiable and operational variables. In this context, the recharge rate relative to precipitation used in this study (34.31%) appears reasonable and falls within the range reported in numerous karst hydrogeology studies. For instance, it closely aligns with the average values identified by Hartmann et al. (2015) for European karst regions (35–40%) [19].
This way, total recharge across exposed karst areas worldwide reaches 4,381,063.7 hm3/year, corresponding to 236 mm/yr per square meter of karst terrain. This estimate exceeds the initial assessment of Stevanović (2019) [18], who reported 3165 km3.
Nine evaluations compiled by Margat and Van der Gun (2013) [48] have been considered to estimate global groundwater resources. These range between 12,000 and 15,000 km3/yr, although the most frequent figures fall between 12,000 and 13,000 km3/yr—such as Yoshikawa et al. (2011), reporting 11,968 km3/yr [49], and Döll and Fiedler (2008), who reported 12,700 km3/yr [50].
Using the latter as a reference, the recharge estimated in this study represents 34.5% of global groundwater resources, highlighting the significance of karst-related water reserves and their potential availability for supply purposes. Analysis shows that 50% of total natural recharge in the world’s karst regions occurs within the precipitation range of 600 to 1600 mm/yr (Figure 4). In contrast, areas with extremely low precipitation (0–400 mm/yr) contribute only 5.57% to global recharge. Likewise, regions receiving over 3500 mm/yr account for just 5% of the total.
These figures indicate that extreme climate zones—where deviations from typical recharge behaviors and rates could occur—have a limited influence on the global balance. Notably, the 34.3% recharge rate used in this study was derived from a region that falls within the 600–1600 mm/yr range, which lends further credibility to its applicability.
According to climate change projections for 2050, Table 6 shows that global natural recharge decreases to 3,918,530.9 hm3/yr, representing a 10.55% reduction compared to current levels. Some of the losses caused by increased temperature and evaporation have been partially offset by the exposure of ice from newly thawed karst terrains.
However, the behavior of these areas remains uncertain. It is unclear whether they possess inherited karstification or will function effectively as aquifers. As Ford and Williams (2007) note, karstic lithologies may require several tens of thousands of years to evolve into fully functional aquifers [51].

5. Conclusions

Despite the uncertainty in estimating the global average natural recharge of aquifers, this study attempts to provide a reasonable approximation in the case of karst systems. The approach is based on a method that uses the recharge–precipitation ratio derived for lithological groups with similar hydrogeological behavior, initially established in Spain.
This method is useful for large-scale assessments, where the numerous factors influencing recharge ultimately reduce to two key variables: lithology and precipitation. The researchers validated the method at smaller scales in a Spanish river basin and at broader scales across several European countries by comparing the results with those obtained through other methodologies.
Researchers have calculated a natural recharge-to-precipitation ratio of 34.31% for karst aquifers, proposed here as a globally representative average value, though it can be later regionally adjusted. Upon using this ratio, the method was applied to a global assessment of natural recharge, excluding areas currently covered by glaciers and permafrost.
As a result, total recharge in exposed karst outcrops worldwide reaches 4,381,063.7 hm3/year. Although karst terrains cover only 15.17% of the Earth’s surface, they account for 34.5% of global groundwater resources—a figure that underscores the significance of karst systems in global water availability. Climate change projections for 2050 suggest a 10.55% reduction in recharge compared to present-day values.

Author Contributions

Conceptualization, E.S.P. and I.M.-P.; methodology, E.S.P.; software, E.S.P. and J.C.M.-F.; validation, J.C.M.-F. and J.S.d.O.; formal analysis, E.S.P., J.C.M.-F. and J.S.d.O.; investigation, I.M.-P., J.C.M.-F. and J.S.d.O.; resources, E.S.P., I.M.-P. and J.C.M.-F.; data curation, E.S.P., J.S.d.O. and I.M.-P.; writing—original draft preparation, E.S.P. and I.M.-P.; writing—review and editing, J.C.M.-F.; visualization, E.S.P., J.C.M.-F. and I.M.-P.; supervision, J.C.M.-F. and I.M.-P.; project administration, E.S.P.; funding acquisition, E.S.P. All authors have read and agreed to the published version of the manuscript.

Funding

This work has received a small grant from the Research Group of Geology Applied to Civil Engineering of the Universidad Politécnica de Madrid (VAGI24ESP).

Data Availability Statement

The data presented in this study are available from the authors upon request.

Acknowledgments

The authors would like to express their gratitude to the three undisclosed reviewers whose comments and suggestions have helped us to enhance the quality of this paper. We also thank Ignacio Laja for his help in the application of GIS tools.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
MIMAMMinisterio de Medio Ambiente (Ministry of Environment of Spain)
WHYMAPWorldwide Hydrogeological Mapping and Assessment Programme
ESDAC European Soil Data Centre
YAPYearly Average Precipitation

References

  1. Wada, Y.; van Beek, L.P.H.; van Kempen, C.M.; Reckman, J.W.; Vasak, S.; Bierkens, M.F. Global depletion of groundwater resources. Geophys. Res. Lett. 2010, 37, L20402. [Google Scholar] [CrossRef]
  2. Scanlon, B.R.; Fakhreddine, S.; Rateb, A.; de Graaf, I.; Famiglietti, J.; Gleeson, T.; Zheng, C. Global water resources and the role of groundwater in a resilient water future. Nat. Rev. Earth Environ. 2023, 4, 87–101. [Google Scholar] [CrossRef]
  3. Jasechko, S.; Seybold, H.; Perrone, D.; Fan, Y.; Shamsudduha, M.; Taylor, R.G.; Kirchner, J.W. Rapid groundwater decline and some cases of recovery in aquifers globally. Nature 2024, 625, 715–721. [Google Scholar] [PubMed]
  4. Custodio, E. Recarga Natural A Los Acuíferos, Metodología y Soporte de La Isotopía Del Agua: Aplicación a La Planificación Hidrológica y Conocimiento de Las Aguas Subterráneas en España: Informe RAEMIA; Iniciativa Digital Politécnica Oficina de Publicacions Acadèmiques Digitals de la UPC: Barcelona, Spain, 2019; Available online: https://www.mdx.cat/handle/2117/182282 (accessed on 10 April 2025)ISBN 978-84-9880-814-8.
  5. Milly, P.C.D.; Eagleson, P.S. Effects of spatial variability on annual average water balance. Water Resour. Res. 1987, 23, 2135–2143. [Google Scholar] [CrossRef]
  6. Pulido-Velazquez, D.; Collados-Lara, A.J.; Alcalá, F.J. Assessing impacts of future potential climate change scenarios on aquifer recharge in continental Spain. J. Hydrol. 2018, 567, 803–819. [Google Scholar] [CrossRef]
  7. Pardo-Igúzquiza, E.; Collados-Lara, A.J.; Pulido-Velazquez, D. Potential future impact of climate change on recharge in the Sierra de las Nieves (southern Spain) high-relief karst aquifer using regional climate models and statistical corrections. Environ. Earth Sci. 2019, 78, 1–12. [Google Scholar] [CrossRef]
  8. Jourde, H.; Wang, X. Advances, challenges and perspective in modelling the functioning of karst systems: A review. Environ. Earth Sci. 2023, 82, 396. [Google Scholar] [CrossRef]
  9. Moeck, C.; Grech-Cumbo, N.; Podgorski, J.; Bretzler, A.; Gurdak, J.J.; Berg, M.; Schirmer, M. A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships. Sci. Total Environ. 2020, 717, 137042. [Google Scholar] [CrossRef]
  10. Sanz Pérez, E. Estimation of basin wide recharge rates using spring flow, precipitation, and temperature data. Ground Water 1997, 35, 1058–1065. [Google Scholar] [CrossRef]
  11. Manga, M. Using springs to study groundwater flow and active geologic processes. Annu. Rev. Earth Planet. Sci. 2001, 29, 201–228. [Google Scholar] [CrossRef]
  12. Gerard, B.R. Effects of Environmental Parameters and Precipitation Dynamics on Infiltration and Recharge into the Trinity Aquifer of Central Texas. Master’s Thesis, Texas State University, San Marcos, TX, USA, 2012. Available online: https://digital.library.txstate.edu/bitstream/10877/4405/1/GERARD-THESIS.pdf (accessed on 10 April 2025).
  13. Sanz-Pérez, E.; Menéndez-Pidal, I. Cálculo de la recarga natural en grandes áreas, en función de la litología y la precipitación. Tecnol. Y Cienc. Del agua 2013, 4, 195–202. [Google Scholar]
  14. Allocca, V.; Manna, F.; De Vita, P. Estimating annual groundwater recharge coefficient for karst aquifers of the southern Apennines (Italy). Hydrol. Earth Syst. Sci. 2014, 18, 803–817. [Google Scholar] [CrossRef]
  15. Goldscheider, N.; Chen, Z.; Auler, A.S.; Bakalowicz, M.; Broda, S.; Drew, D.; Veni, G. Global distribution of carbonate rocks and karst water resources. Hydrogeol. J. 2020, 28, 1661–1677. [Google Scholar] [CrossRef]
  16. Gunn, J. Karst groundwater in UNESCO protected areas: A global overview. Hydrogeol. J. 2021, 29, 297–314. [Google Scholar] [CrossRef]
  17. de Sena, Í.S.; de Azevedo Ruchkys, Ú.; Travassos, L.E.P. Geotourism Potential in Karst Geosystems: An example from the Lund Warming Ramsar Site, Minas Gerais, Brazil. Catena 2022, 208, 105717. [Google Scholar] [CrossRef]
  18. Stevanović, Z. Karst waters in potable water supply: A global scale overview. Environ. Earth Sci. 2019, 78, 662. [Google Scholar] [CrossRef]
  19. Hartmann, A.; Gleeson, T.; Rosolem, R.; Pianosi, F.; Wada, Y.; Wagener, T. A large-scale simulation model to assess karstic groundwater recharge over Europe and the Mediterranean. Geosci. Model Dev. 2015, 8, 1729–1746. [Google Scholar] [CrossRef]
  20. Hartmann, A.; Liu, Y.; Olarinoye, T.; Berthelin, R.; Marx, V. Integrating field work and large-scale modeling to improve assessment of karst water resources. Hydrogeol. J. 2021, 29, 315–329. [Google Scholar] [CrossRef]
  21. Stevanović, Z. Global Distribution and Use of Water from Karst Aquifers; The Geological Society, Special Publications: London, UK, 2018; Volume 466, pp. 217–236. [Google Scholar] [CrossRef]
  22. Sanz Pérez, E. Distribution Functions of Spring Discharge According to Their Lithologies and the Influence of Lower Limit to Flows in Spain. Ground Water 2001, 2, 203–209. [Google Scholar] [CrossRef] [PubMed]
  23. Sanz Perez, E. Springs in Spain: Classification according to their flows and lithologies and their hydraulic contributions. Ground Water 1996, 34, 1033–1041. [Google Scholar] [CrossRef]
  24. Ministerio de Medio Ambiente (MIMAM). Secretaria de Estado de Aguas y Costas. Libro Blanco Del Agua en España [The White Book of Water in Spain]; Dirección General de Obras Hidráulicas y Calidad de las Aguas: Madrid, Spain, 2000. [Google Scholar]
  25. Gleeson, T.; Smith, L.; Moosdorf, N.; Hartmann, J.; Dürr, H.H.; Manning, A.H.; van Beek, L.P.H.; Jellinek, A.M. Mapping permeability over the surface of the Earth. Geophys. Res. Lett. 2011, 38, L02401. [Google Scholar] [CrossRef]
  26. Gleeson, T.; Wada, Y.; Bierkens, M.F.; Van Beek, L.P. Water balance of global aquifers revealed by groundwater footprint. Nature 2012, 488, 197–200. [Google Scholar] [CrossRef] [PubMed]
  27. Kuang, X.; Liu, J.; Scanlon, B.R.; Jiao, J.J.; Jasechko, S.; Lancia, M.; Biskaborn, B.K.; Wada, Y.; Li, H.; Zeng, Z.; et al. The changing nature of groundwater in the global water cycle. Science 2024, 383, eadf0630. [Google Scholar] [CrossRef]
  28. Eurostat. Water in Europe, Part 1. Renewable Water Resource; Office for Official Publications or the European Communities: Luxembourg, 1998; Available online: https://www.eea.europa.eu/publications/binaryeenviasses01pdf/at_download/file (accessed on 9 June 2025).
  29. Tóth, G.; Montanarella, L.; Stolbovoy, V.; Máté, F.; Bódis, K.; Jones, A.; Van Liedekerke, M. Soils of the European Union. Italy: EUR, 23439; Institute for Environment and Sustainability Land Management and Natural Hazards Unit. Action SOIL: Ispra, Italy, 2008; Available online: https://esdac.jrc.ec.europa.eu/ESDB_Archive/eusoils_docs/other/EUR23439.pdf (accessed on 9 June 2025).
  30. JOINT RESEARCH CENTRE; European Soil Data Centre (ESDAC). European Soil Database. Available online: https://esdac.jrc.ec.europa.eu/content/european-soil-database-v20-vector-and-attribute-data (accessed on 9 June 2025).
  31. Ford, D. Effects of glaciations and permafrost upon the development of karst in Canada. Earth Surf. Process Landf. 1987, 12, 507–521. [Google Scholar] [CrossRef]
  32. Riba Arderiu, O. Mapa litológico de España E. 1:400.000; Instituto Nacional de Edafología y Servicio Geológico de Obras Públicas (IGME): Madrid-Zaragoza, Spain, 1969. [Google Scholar]
  33. European Soil Data Centre. CEC—Eurostat/GISCO (1995): European Soil Database, Version 2.0, Scale 1:1,000,000 CEC-DGXI/CORINE and JRC-IRSA at ISPRA; European Soil Data Centre: Ispra, Italy, 1995. [Google Scholar]
  34. WorldClim. Global Climate and Weather Data. Available online: https://worldclim.org/data/index.html (accessed on 21 November 2024).
  35. Natural Earth, Glaciated Areas. Available online: https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-glaciated-areas/ (accessed on 21 November 2024).
  36. FAO Soils Portal, FAO/UNESCO Soil Map of the World. Available online: https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/faounesco-soil-map-of-the-world/en/ (accessed on 21 November 2024).
  37. Sanz de Ojeda, A.; Alhama, I.; Sanz, E. Aquifer sensitivity to earthquakes: The 1755 Lisbon earthquake. J. Geophys. Res. Solid Earth 2019, 124, 8844–8866. [Google Scholar] [CrossRef]
  38. Estrela, T.; Cabezas, F.; Estrada, F. La evaluación de los recursos hídricos en el Libro Blanco del Agua en España. Rev. De Ing. Del Agua 1999, 6, 125–138. [Google Scholar] [CrossRef]
  39. New, M.; Hulme, M.; Jones, P. Representing twentieth-century space–time climate variability. Part II: Development of 1901–96 monthly grids of terrestrial surface climate. J. Clim. 2000, 13, 2217–2238. [Google Scholar] [CrossRef]
  40. Ministerio del Medio Ambiente (MIMAM). Las Aguas Continentales en la Unión Europea; CEDEX-Centro de Estudios y Experimentación de Obras Públicas: Madrid, Spain, 2004; ISBN 8483202689. [Google Scholar]
  41. Lobo Ferreira, J.P.; Oliveira, M.; Ciabatti, P. Desenvolvimento de Um Inventario Das Aguas Subterráneas de Portugal; LNEC, Dep. Hidráulica: Lisboa, Portugal, 1995; Volume I, Available online: https://repositorio.lnec.pt/handle/123456789/5212 (accessed on 9 May 2025).
  42. Oliveira, M.; Moinante, J.; Lobo Ferreira, J.P. Determinaçao da Recarga Deaguas Subterrâneas a Partir Da Analise de Hidrogramas de Escoamento, Seminario Sobre Aguas Subterraneas; APRH—Assoc. Portg. Rec. Hid.: Lisboa, Portugal, 1997; Available online: https://repositorio.lnec.pt/handle/123456789/5264 (accessed on 9 May 2025).
  43. Carmona, A. Water frameworks and water resources in Portugal. A contribution to the workshop. In Overview on Inland Water in the Mediterranean EU Countries; CEDEX: Madrid, Spain, 1999; Available online: https://hispagua.cedex.es/sites/default/files/aguas_continentales_union_europea.pdf (accessed on 9 May 2025).
  44. European Environment Agency (EEA). EEA Annual Report 2001. 2002. Available online: https://www.eea.europa.eu/en/analysis/publications/corporate_document_2001_1 (accessed on 15 November 2024).
  45. Water Research Institute (IRSA). Italy: N.R.C. Long-Range Study on Water Supply and Demand in Europe, Level A: Studies at Country Level—Italy; Water Research Institute: Rome, Italy, 1997. [Google Scholar]
  46. BGR; UNESCO. Worldwide Hydrogeological Mapping and Assessment Programme (WHYMAP). World Karst Aquifer Map. Available online: https://www.whymap.org/whymap/EN/Maps_Data/Wokam/wokam_node_en.html (accessed on 21 November 2024).
  47. Lindgren, A. Biomes of the Last Glacial Maximum Permafrost Region; Dataset Version 1; Bolin Centre Database: Stockholm, Sweden, 2018. [Google Scholar] [CrossRef]
  48. Margat, J.; Van der Gun, J. Groundwater Around the World: A Geographic Synopsis; CRC Press: London, UK, 2013. [Google Scholar]
  49. Yoshikawa, S.; Yamada, H.; Hanasaki, N.; Kanae, S. Evaluation for sustainable agriculture water use from River, Reservoirs and Groundwater in the 20th century. In Proceedings of the AGU Fall Meeting Abstracts, San Francisco, CA, USA, 5–9 December 2011; Volume 2011, p. GC13A-0968. [Google Scholar]
  50. Döll, P.; Fiedler, K. Global-scale modeling of groundwater recharge. Hydrol. Earth Syst. Sci. 2008, 12, 863–885. [Google Scholar] [CrossRef]
  51. Ford, D.; Williams, P.D. Karst Hydrogeology and Geomorphology; John Wiley & Sons: New York, NY, USA, 2007. [Google Scholar]
Figure 1. Left: Yearly average precipitation (YAP) in peninsular Spain. The contour of the Duero Basin is highlighted in black. Values range from nearly zero to 2600 mm. Right: Lithological map in the Duero basin (Spain) showing the following types: (1) alluvial sediments; (2) conglomerates; (3) sandstones (differentiated only for Spain; included in type 7 for Portugal); (4) calcareous rocks (limestones and dolomites); (5) silts, clays, sands, marls, and calcareous loams that correspond, in general, to the great Tertiary Continental Basins of the great Spanish rivers, with the exception of the limestones of the Paramo; (6) quartzites (differentiated only for Spain; included in 7 for Portugal); (7) slates (differentiated only for Spain; for Portugal, this color represents all metamorphic rocks, including most sandstones); (8) plutonic rocks; (9) other rocks (gypsum and volcanic rocks) (Source: Riba Arderiu, 1969 [32] and Sanz de Ojeda et al., 2019 [37]).
Figure 1. Left: Yearly average precipitation (YAP) in peninsular Spain. The contour of the Duero Basin is highlighted in black. Values range from nearly zero to 2600 mm. Right: Lithological map in the Duero basin (Spain) showing the following types: (1) alluvial sediments; (2) conglomerates; (3) sandstones (differentiated only for Spain; included in type 7 for Portugal); (4) calcareous rocks (limestones and dolomites); (5) silts, clays, sands, marls, and calcareous loams that correspond, in general, to the great Tertiary Continental Basins of the great Spanish rivers, with the exception of the limestones of the Paramo; (6) quartzites (differentiated only for Spain; included in 7 for Portugal); (7) slates (differentiated only for Spain; for Portugal, this color represents all metamorphic rocks, including most sandstones); (8) plutonic rocks; (9) other rocks (gypsum and volcanic rocks) (Source: Riba Arderiu, 1969 [32] and Sanz de Ojeda et al., 2019 [37]).
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Figure 2. Mean annual precipitation in Europe (mm) during the period 1940/1941–1995/1996. (Map source: MIMAM, 2004 [40]).
Figure 2. Mean annual precipitation in Europe (mm) during the period 1940/1941–1995/1996. (Map source: MIMAM, 2004 [40]).
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Figure 3. Map of karst outcrops (1), distribution of areas covered by glaciers (2), permanent permafrost (3), temporary permafrost (4), and current mean annual precipitation (mm) (5) (source: WHYMAP, 2017 [46], Natural Earth, Soil Map of the World by FAO-UNESCO) [36]).
Figure 3. Map of karst outcrops (1), distribution of areas covered by glaciers (2), permanent permafrost (3), temporary permafrost (4), and current mean annual precipitation (mm) (5) (source: WHYMAP, 2017 [46], Natural Earth, Soil Map of the World by FAO-UNESCO) [36]).
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Figure 4. Distribution of natural recharge (in hm3/yr) with respect to precipitation (in mm) in karst areas of the world.
Figure 4. Distribution of natural recharge (in hm3/yr) with respect to precipitation (in mm) in karst areas of the world.
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Table 1. Calculation of hydraulic contributions to the Duero catchment (Spain).
Table 1. Calculation of hydraulic contributions to the Duero catchment (Spain).
Precipitation (L/m2)Lithological Areas (km2)
IntervalsClass MarksAlluvialsConglomeratesSandstonesLimestonesMarlsOthersTotal
350–44940063111126801122732785216,818
450–5495005296180319335807184350021,556
550–6496002403220923713872992316912,397
650–74970010201431223893107233367975
750–84980079352319016426963528291
850–94990010351047165329109418575527
950–1049100014126215218051328584106
1050–11491100--19106-9801105
1150–12491200-------
1250–13491300--1656 481553
1350–1449140010--88-534632
All 17,0098401127579052,045123,91978,960
% 21.510.61.61025.930.4100
Spain % 16.16.33.91524.833.9100
Precipitation 532.02631.08722.35583.93527.17768.81621.3
Hydraulic contribution (hm3) 751296.967.21583.2355.8257.43311.5
Table 2. Calculation of average annual recharge for four European countries (Spain, Portugal, Ireland, and Italy) according to their lithology. Data source: MIMAM (2004) [40]. P m accounts for the average yearly precipitation.
Table 2. Calculation of average annual recharge for four European countries (Spain, Portugal, Ireland, and Italy) according to their lithology. Data source: MIMAM (2004) [40]. P m accounts for the average yearly precipitation.
CountryLithology Area   ( k m 2 ) P m ( L / m 2 ) P i Recharge
h m 3 / y r
PeninsularAlluvials80,1046870.0834567.6
SpainConglomerates31,1416870.0561198.1
Sandstones19,2136870.073963.6
Limestones74,5826870.34317,574.6
Marts123,4646870.0332799.1
Others168,9736870.0141625.2
Total497,477687-28,728.2
PortugalAlluvials12,4858820.083913.9
Conglomerates08820.0560
Sandstones13,5168820.073870.24
Limestones55008820.3431663.8
Marls16788820.03348.83
Others56,7208820.014700.37
Total89,898882-4197.14
IrelandAlluvials338411500.083323
Conglomerates011500.0560
Sandstones11,75811500.073987.1
Limestones24,44611500.3439642.7
Marls011500.0330
Others29,98911500.014482.8
Total69,5771150-11,435.6
ItalyAlluvials80,7229820.0836579.3
Conglomerates09820.0560
Sandstones31,8129820.0732280.4
Limestones71,9119820.34324,421.5
Marls59,2129820.0331918.8
Others41,2049820.014566.48
Volcanics17,6949820.2 *3539
Total302,557982-39,305.5
Note: * Estimate.
Table 3. Natural recharge rate to precipitation ( P i ) according to lithological groups in Spain (source: Sanz and Menéndez-Pidal, 2013 [13]).
Table 3. Natural recharge rate to precipitation ( P i ) according to lithological groups in Spain (source: Sanz and Menéndez-Pidal, 2013 [13]).
Recharge of
Peninsular Spain
Lithologies P i ( % ) km2%
Alluvials, sands, gravels8.29456215.9
Conglomerates5.6312044.2
Sandstones7.299623.4
Limestones, dolomites34.3117,58061.4
Marls, silts, clays3.3228169.8
Others1.3215325.3
Total 28,656100
Table 4. Comparison of estimated mean recharge in earlier published works, and in the present study for Spain, Portugal, Ireland, and Italy during the period 1940–1941 to 1995–1996.
Table 4. Comparison of estimated mean recharge in earlier published works, and in the present study for Spain, Portugal, Ireland, and Italy during the period 1940–1941 to 1995–1996.
Mean Recharge (hm3/yr)
Area (km2)Average Precipitation (mm/yr)Previous Works *Estimates of This Work
Spain (Peninsular)497,47768728,908 128,728.2
Portugal89,8988824000 24197.14
Ireland69,577115010,800 311,435.6
Italy302,55798243,000 439,305.5
Notes: * Sources: 1: Estrela et al. (1999) [38]; 2: MIMAM (2000) [24]; Carmona (1999) [43]; 3: EEA (2001) [44]; WRI (2001); MIMAM (2004) [40]; 4: IRSA (1997) [45].
Table 5. Breakdown of variables for calculating total natural recharge by continent.
Table 5. Breakdown of variables for calculating total natural recharge by continent.
ContinentTotal Karst (km2)Glaciers and Permafrost in Karst (km2)Net
Karst
(km2)
Net Karst
Percentage
(%)
Average Yearly Precipitation
(mm/yr)
Recharge Rate
(%)
Natural Recharge
(hm3)
Natural
Recharge
(mm)
Africa4,053,40004,053,40013.5496.7134.31690,785.3170,421
Asia8,340,000818,0007,522,00018.6694.1734.311,791,512.7238,170
Oceania501,300600500,7006.21266.7834.31217,620.4434,632
Europe2,166,00067,0002,099,00021.8671.8734.31483,858.5230,519
North America 4,431,000742,0003,689,00019.6726.1434.31919,072.4249,139
South America767,900123,000644,9004.31257.3834.31278,214.4431,407
Global20,259,6001,750,60018,509,000 4,381,063.7
Table 6. Estimation of the decrease in total and continent-specific natural recharge according to climate change predictions in 2050.
Table 6. Estimation of the decrease in total and continent-specific natural recharge according to climate change predictions in 2050.
ContinentEstimated Precipitation in 2050 (mm/Yr)Recharge Rate (%)Estimated Natural Recharge in 2050 (hm3)
Africa407.5434.31566,779.72
Asia595.8334.311,537,717.14
Oceania820.3834.31140,932.48
Europe830.7734.31598,292.92
North America 559.5034.31708,161.32
South America1657.0534.31366,647.32
Global 3,918,530.9
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Sanz Pérez, E.; Mosquera-Feijóo, J.C.; Sanz de Ojeda, J.; Menéndez-Pidal, I. A Procedure to Estimate Global Natural Recharge in Karst Aquifers. Water 2025, 17, 1779. https://doi.org/10.3390/w17121779

AMA Style

Sanz Pérez E, Mosquera-Feijóo JC, Sanz de Ojeda J, Menéndez-Pidal I. A Procedure to Estimate Global Natural Recharge in Karst Aquifers. Water. 2025; 17(12):1779. https://doi.org/10.3390/w17121779

Chicago/Turabian Style

Sanz Pérez, Eugenio, Juan Carlos Mosquera-Feijóo, Joaquín Sanz de Ojeda, and Ignacio Menéndez-Pidal. 2025. "A Procedure to Estimate Global Natural Recharge in Karst Aquifers" Water 17, no. 12: 1779. https://doi.org/10.3390/w17121779

APA Style

Sanz Pérez, E., Mosquera-Feijóo, J. C., Sanz de Ojeda, J., & Menéndez-Pidal, I. (2025). A Procedure to Estimate Global Natural Recharge in Karst Aquifers. Water, 17(12), 1779. https://doi.org/10.3390/w17121779

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