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The hydrogeochemical characteristics of springs in the granites of the Spanish Central System (SCS), a mountain range affected by cortical tectonic structures, are described, along with an investigation of the spring water origin. In springs with variable flow and where they are associated with minor alterations and fractures, water type is Ca-(Na)-HCO3 with low total dissolved solids (TDS; 54–200 ppm) and a neutral or slightly acid pH. In springs that have continuous flow and association with relevant fractures, water type is Na-HCO3, with higher pH and TDS (240–563 ppm). There are five springs with water type Na-(Ca)-Cl and high TDS (780–9,205 ppm) near the SCS’s southern tectonic borders. Within 5,000 years of apparent residence time, Ca-(Na)-HCO3 water progresses to Na-HCO3 type, slightly increasing HCO3 content, losing Ca due to calcite precipitation and ionic exchange, and gaining S due to sulphate reduction. No changes are observed after 20,000 years of apparent age. The influence of internal CO2 is compatible with Na-HCO3 water type characteristics, facilitated by fracturing. Most of the springs yield cold water; thus, a flow depth up to 500 m can be deduced. Only the Messejana-Plasencia fault region shows Na-HCO3-type thermal springs. Chloride type water is a result of the influence of the Tertiary basins’ water moving towards the southern border of the SCS. The reverse fault in such contact, together with the subvertical structures affected by it, are responsible for the springs emerging in the granite. The northern border of the SCS shows the opposite behaviour.

Groundwater is crucial for domestic supplies in the Sahel, where the strategic importance of aquifers will increase in the coming years due to climate change. Groundwater potential mapping is a valuable tool to underpin water management in the region and, hence, to improve drinking water access. This paper presents a machine learning method to map groundwater potential. This is illustrated through its application in two administrative regions of Mali. A set of explanatory variables for the presence of groundwater is developed first. Scaling methods (standardization, normalization, maximum absolute value and max–min scaling) are used to avoid the pitfalls associated with reclassification. Noisy, collinear and counterproductive variables are identified and excluded from the input dataset. A total of 20 machine learning classifiers are then trained and tested on a large borehole database (n=3345) in order to find meaningful correlations between the presence or absence of groundwater and the explanatory variables. Maximum absolute value and standardization proved the most efficient scaling techniques, while tree-based algorithms (accuracy >0.85) consistently outperformed other classifiers. The borehole flow rate data were then used to calibrate the results beyond standard machine learning metrics, thereby adding robustness to the predictions. The southern part of the study area presents the better groundwater prospect, which is consistent with the geological and climatic setting. Outcomes lead to three major conclusions: (1) picking the best performers out of a large number of machine learning classifiers is recommended as a good methodological practice, (2) standard machine learning metrics should be complemented with additional hydrogeological indicators whenever possible and (3) variable scaling contributes to minimize expert bias.

Groundwater resources are crucial to safe drinking supplies in sub-Saharan Africa, and will be increasingly relied upon in a context of climate change. The need to better understand groundwater calls for innovative approaches to make the best out of the existing information. A methodology to map groundwater potential based on an ensemble of machine learning classifiers is presented. A large borehole database (n = 1848) was integrated into a Geographic Information Systems (GIS) environment and used to train, validate and test 12 machine learning algorithms. Each classifier predicts a binary target (positive or negative borehole) based on the minimum flow rate required for communal domestic supplies. Classification is based on a number of explanatory variables, including landforms, lineaments, soil, vegetation, geology and slope, among others. Correlations between the target and explanatory variables were then generalized to develop groundwater potential maps. Most algorithms attained success rates between 80% and 96% in terms of test score, which suggests that the outcomes provide an accurate picture of field conditions. Statistical learners were observed to perform better than most other algorithms, excepting random forests and support vector machines. Furthermore, it is concluded that the ensemble approach provides added value by incorporating a measure of uncertainty to the results. This technique may be used to rapidly map groundwater potential for rural supply or humanitarian emergencies in areas where there is sufficient historical data but where comprehensive field work is unfeasible.

Groundwater resources can be expected to be increasingly relied upon in the near future, as a consequence of rapid population growth and global environmental change. Cost-effective and efficient techniques for groundwater exploration are gaining recognition as tools to underpin hydrogeological surveys in mid- and low-income regions. This paper provides a state of the art on groundwater potential mapping, an explorative technique based on remote sensing and geographical databases that has experienced major developments in recent years. A systematic review of over 200 directly relevant papers is presented. Twenty variables were found to be frequently involved in groundwater potential investigations, of which eight are almost always present: geology, lineaments, landforms, soil, land use/land cover, rainfall, drainage density, and slope. The more innovative approaches draw from satellite images to develop indicators related to vegetation, evapotranspiration, soil moisture and thermal anomalies, among others. Data integration is carried out either through expert judgement or through machine-learning techniques, the latter being less common. Three main conclusions were reached: (1) for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute; (2) the potential of remote-sensing techniques in groundwater exploration is enormous, particularly when the power of machine learning is harnessed by involving human judgement; (3) quality assurance remains the main challenge ahead, as exemplified by the fact that a majority of the existing studies in the literature lack adequate validation.

Wetlands are vulnerable to groundwater extraction, which has proven detrimental to aquatic ecosystems around the planet. As wetlands rank among the world’s most endangered ecosystems, versatile strategies are required to protect them. This paper provides a modelling-based method to delineate protection buffers in wetlands subject to groundwater extraction. The technique is sufficiently flexible to cater to a wide variety of conditions, and simple enough to underpin management decisions on a daily basis. A numerical model is used to obtain a map of the critical rate of groundwater abstraction, based on the distance between wetlands and suitable discharge thresholds. The outcomes determine the allowed pumping rate at any point under steady and transient-state conditions. A new iteration is developed every time a new pumping allowance is made. This procedure is demonstrated by means of hypothetical scenarios, as well as by a case study application in the Valle del Cauca region, Colombia.

Groundwater is crucial for domestic supplies in the Sahel, where the strategic importance of aquifers can only be expected to increase in the coming years due to climate change. Groundwater potential mapping is gaining recognition as a valuable tool to underpin water management practices in the region, and hence, to improve water access. This paper presents a machine learning method to map groundwater potential and illustrates it through an application to two regions of Mali. A set of explanatory variables for the presence of groundwater is developed first. Several scaling methods (standardization, normalization, maximum absolute value and min-max scaling) are used to avoid the pitfalls associated with the reclassification of explanatory variables. A number of supervised learning classifiers is then trained and tested on a large borehole database (n = 3,345) in order to find meaningful correlations between the presence or absence of groundwater and the explanatory variables. This process identifies noisy, collinear and counterproductive variables and excludes them from the input dataset. Tree-based algorithms, including the AdaBoost, Gradient Boosting, Random Forest, Decision Tree and Extra Trees classifiers were found to outperform other algorithms on a consistent basis (accuracy > 0.85), whereas maximum absolute value and standardization proved the most efficient methods to scale explanatory variables. Borehole flow rate data is used to calibrate the results beyond standard machine learning metrics, thus adding robustness to the predictions. The southern part of the study area was identified as the better groundwater prospect, which is consistent with the geological and climatic setting. From a methodological standpoint, the outcomes lead to three major conclusions: (1) because there is no aprioristic way to know which algorithm will work better on a given dataset, we advocate the use of a large number of machine learning classifiers, out of which the best are subsequently picked for ensembling; (2) standard machine learning metrics may be of limited value when appraising map outcomes, and should be complemented with hydrogeological indicators whenever possible; and (3) the scaling of the variables helps to minimize bias arising from expert judgement and maintains robust predictive capabilities.

Granting safe water access worldwide is a major objective of the Sustainable Development Goals. Water access is a manifold concept that encompasses collection time, distance from the household, water quality, affordability, and reliability of water sources, among other factors. GIS-based methods can be particularly useful in improving water access estimates, particularly in rural areas of developing countries. Based on an extensive water point database (n = 770), this paper explores the main challenges involved in mapping water access in two rural communes of Burkina Faso. Water access is estimated in terms of coverage per surface area. Coverage is filtered into four distinct categories of improved water sources, namely existing infrastructures, operational infrastructures, permanent infrastructures, and permanent infrastructures that provide safe water. The outcomes suggest that the study area is better endowed with water access than rural Burkina Faso and the remainder of the African continent, although there are important questions regarding groundwater quality. The outcomes highlight the conceptual differences between coverage and access, as well as some of the practical difficulties involved in estimating water access beyond standard ratios. The shortcomings include the absence of continuous monitoring of infrastructure functionality and water quality, as well as water affordability, among others. Enhancing national borehole databases with items aligned with the United Nations’ definition of water access is recommended.

Identifying groundwater-dependent ecosystems is the first step towards their protection. This paper presents a machine learning approach that maps groundwater-dependent ecosystems by extrapolating from the characteristics of a small sample of known wetland and non-wetland areas to find other areas with similar geological, hydrological and biotic markers. Explanatory variables for wetland occurrence include topographic elevation, lithology, vegetation vigor, and slope-related variables, among others. Supervised classification algorithms are trained based on the ground truth sample, and their outcomes are checked against an official inventory of groundwater-dependent ecosystems for calibration. This method is illustrated through its application to a UNESCO Biosphere Reserve in central Spain. Support vector machines, tree-based classifiers, logistic regression and k-neighbors classification predicted the presence of groundwater-dependent ecosystems adequately (>96% test and AUC scores). The ensemble mean of the best five classifiers rendered a 90% success rate when computed per surface area. This method can optimize fieldwork during the characterization stage of groundwater-dependent ecosystems, thus contributing to integrate wetland protection in land use planning.

Groundwater stored in aquifers experiences a wide variety of natural, induced and/or anthropogenic disturbances. Among them, groundwater extraction is the main disturbance that affects most of the aquifers in the world. Aquifer’s resilience, understood as the potential of the aquifer to sustain disturbances on the long term and to guarantee essential qualities and functions, provides a key tool when assessing sustainable groundwater management alternatives. The aim of this work is to illustrate an aquifer resilience framework that can support groundwater sustainable management. A theoretical framework is based on the identification of the key variables that parameterize the quantitative and qualitative responses of the groundwater flow system to pumping. An example from the literature based in Denmark is provided as an illustration of the proposed framework. The results show that long-term high quality data are essential to make a step further in aquifers dynamic responses. The quantitative understanding of the aquifer’s behavior before, during and after groundwater extraction provides a valuable source of information in order to identify thresholds of change (tipping points, transitions or regime shifts) which could permit pro-active groundwater management decisions. Moreover, a deeper understanding on the aquifer’s dynamics provides useful information in order to avert threats that may put the sustainability of the system at risk.

20 p. - Supplementary material related to this article can be found, in the online version, at doi: https://doi.org/10.1016/j.ejrh.2021.100781., [EN] Study region Old Las Salinas spring in Medina del Campo, Duero river basin, central Spain. Study focus Medina del Campo groundwater body (MCGWB) is a multilayer semiconfined aquifer subject to intensive pumping since the 1970’s, where the current existence of spas where there used to be traditional baths could confirm the existence of deep groundwater flow paths. The old spring of Las Salinas (OSLS) is a saline anomaly in an aquifer with predominance of CaCO3H waters whose occurrence has not yet been formally explained. Long-term geological, geophysical, hydrogeological and hydrochemical records were integrated and complemented with field work to clarify its existence. New hydrological insights for the region Outcomes led to the conclusion that the hydrochemistry of the Olmedo and Palacio de las Salinas salt baths is associated with the existence of a major threshold in the impervious basement of the aquifer, which intercepted deep regional groundwater flow and caused upwelling to the surface under unperturbed conditions. These results allow for the development of a conceptual flow model at the regional scale that explains the changes in natural water chemistry that have been identified in recent decades., This research has received funding from the European Union H2020 Programme under Grant Agreement No. 730497 for the research project NAIAD-NAture Insurance value: Assessment and Demonstration.

In poverty-stricken regions of Sub-Saharan Africa, groundwater for supply is often obtained by means of hand pumps, which means that low-yield boreholes are acceptable. However, boreholes are often sited without sufficient hydrogeological information due to budget constraints, which leads to high failure rates. Cost-effective techniques for borehole siting need to be developed in order to maximize the success rate. In regions underlain by granite, weathered formations are usually targeted for drilling, as these are generally presented as a better cost-benefit ratio than the fractured basement. Within this context, this research focuses on a granite region of Angola. A comparison of two mapping techniques for borehole siting-groundwater prospect is presented. A classic hydrogeomorphological map was developed first based on aerial photographs, field mapping and a geophysical survey. This map represents a considerable time investment and was developed by qualified technicians. The second map (RS/GIS) is considerably simpler and more cost-effective. It was developed by the integration in a GIS platform of six maps of equal importance-slope, drainage density, vegetation vigor, presence of clay in the soil, lineaments and rock outcrops-prepared from Landsat 8 imagery and a Digital Elevation Model (DEM). Similar results were obtained in both cases. By means of a supervised classification of Landsat images, RS/GIS analysis allows for the identification of granitic outcrops, house clusters and sandy alluvial valleys. This in turn allows for the delineation of low-interest or contamination-prone areas, thus contributing additional qualitative information. The position of a well that is going to be powered by a handpump is chosen also upon social and local matters as the distance to the stakeholders, information that are not difficult to integrate in the GIS. Although the second map needs some field inputs (i.e. surveys to determine the thickness of the weathered pack), results show that RS/GIS analyses such as this one provide a valuable and cost-effective alternative for siting low-yield boreholes in remote regions.

Aquifers provide a reliable freshwater source in arid and semiarid regions, where droughts are common and irrigated crops present significant water requirements, so intensive pumping is generally needed. Over-extraction leads to dropping water tables, which in turn threatens the survival of groundwater-dependent ecosystems and water supplies. This calls for strategies to channel hydrological, environmental, agricultural, political and social change. Based on the experience of the Mancha Occidental aquifer, Spain, this paper explores some of the complexities of managing groundwater, dealing with the long-term changes that intensive groundwater use has generated in the region. The Mancha experience shows how environmental conservation may drive social and economic change at the regional scale for periods spanning several decades. What makes this case study unique, however, is the combination of social and environmental conflicts, most of which stem from the prevalence of illegal water use, and their detrimental effect on Ramsar wetlands. The situation exposed a paradox, namely that subsidies for farmers to cut down on water use were actually detrimental to the welfare of groundwater-dependent ecosystems. The unexpected (and timely) occurrence of extreme rainfall events in recent times, after 40 years of ineffective management measures and sustained environmental degradation, enabled the aquifer and its associated wetlands to recover spectacularly to a near-pristine condition. As groundwater-dependent wetlands are highly sensitive ecosystems, it is concluded that it is up to society to decide how much environmental damage can be tolerated in exchange for the social and economic benefits of groundwater-based development.

This paper deals with the design of optimal spatial sampling of water quality variables in remote regions, where logistics are complicated and the optimization of monitoring networks may be critical to maximize the effectiveness of human and material resources. A methodology that combines the probability of exceeding some particular thresholds with a measurement of the information provided by each pair of experimental points has been introduced. This network optimization concept, where the basic unit of information is not a single spatial location but a pair of spatial locations, is used to emphasize the locations with the greatest information, which are those at the border of the phenomenon (for example contamination or a quality variable exceeding a given threshold), that is, where the variable at one of the locations in the pair is above the threshold value and the other is below the threshold. The methodology is illustrated with a case of optimizing the monitoring network by optimal selection of the subset that best describes the information provided by an exhaustive survey done at a given moment in time but which cannot be repeated systematically due to time or economic constrains.

Water supply must take into consideration a variety of factors, including consumer habits, options and needs. Little is known about water demands in rural areas of developing regions. Based on data from southern Mali, this paper banks on the hypothesis that water consumption in rural villages can be predicted by combining measurable variables with spatial analyses. A ten-day field campaign was carried out at the end of the dry season 2016. All improved water sources were checked for functionality, flow rate and water quality. Outcomes were coupled with those from over one-hundred household interviews and incorporated into a geographic database. Buffered network analyses were used to quantify the main spatial determinants for water use. Simple and multiple regression models were then developed to establish the main predictors for per capita and household water consumption. Multiple regression reveals that models based on the number of household members, travel time and total travel distance provide robust forecasts for water consumption (R 2 > 0.93). Conversely, potentially relevant parameters such as affordability or water quality were not statistically significant. This could be attributed to the presence of free water sources and to the absence of quality-monitoring, respectively. Outcomes also suggest that having access to basic means of transportation, such as pushcarts, doubles water consumption at the household level. In terms of access to improved water sources, coverage was found to be lower in practice than on paper. These outcomes contribute to the growing body of literature that challenges the widely accepted assumption that 90% of the world population has access to safe drinking supplies.

Halving the number of people without sustainable access to safe drinking water was a core target of the Millennium Development Goals. This led to an unprecedented effort in the water sector, improving the livelihoods of millions of people. While the goal has officially been accomplished, unsuitable benchmarks have led to overstatement of the results. Indicators overemphasize improved water sources, disregarding the fact that many continue to be contaminated, unreliable or unaffordable. The alleged success needs to be reframed to avoid confusion, prevent investments from being reallocated away from the water sector and obtain more accurate estimates of water access.

Groundwater is key to economic growth in the Mediterranean region. This is particularly true of areas such as southern Spain, where aquifers underpin social development by supplying water to a booming tourist industry. Intensive groundwater use raises sustainability concerns, as pumping often exceeds the long-term recharge rate. Climate change and population growth are likely to exacerbate the water supply challenge in the coming years, due to the expected decrease in rainfall and to increasing competition among users. This paper examines some of the main aquifers in the Costa del Sol region, one of Spain's leading tourist destinations, where intensive groundwater extraction has led to water table drawdowns and the desiccation of all major springs. A numerical model was developed and calibrated for the purpose of evaluating the likely evolution of the system in the future. Downscaled scenarios from global circulation models were coupled with population growth forecasts to establish a range of plausible water management scenarios. Given the relatively small size of the aquifers and the limited recharge rate, the current pumping patterns appear unsustainable. Results suggest that drawdowns in excess of 150 m could take place within the next decade, thus compromising domestic supplies.

Numerical modeling provides well-established tools for advancing in water management. In this study, a simplified version of the semi-distributed VarKarst approach has been developed to reduce modeling routine and, therefore, the time of calculation needed for jointly simulating spring discharge and piezometric head variations in the same karst system located in southern Spain. Simulated spring outflows were compared with spring flow data derived from a previous application of the original VarKarst. Scatter correlation of spring flows yields Kling-Gupta efficiency (KGE) and a Pearson’s coefficient (R2) of 0.90 and 0.89, respectively. The modified approach includes new equations that consider the distance between sea level and the basement of the aquifer, from which the piezometric-level variations were calculated. The KGE, R2, and the root-mean-squared error results obtained of groundwater level were 0.79, 0.85, and 3.07 m, respectively. We conclude that the simplified VarKarst numerical code can provide realistic hydrodynamic results in the karst system, as original VarKarst, concerning both discharge and groundwater level dynamics. This capacity of simulation could help to reduce uncertainty in model routines.

In a context of rapid change, mapping aquatic ecosystems is crucial for their protection, particularly in regions of the world where a comprehensive inventory of water bodies is yet to be developed. This paper presents a machine learning methodology for predictive aquatic ecosystem mapping. Two state-of-the-art classifiers were used, namely support vector machines (SVM) and random forests (RFC). These were implemented in a GIS environment and trained on a sample of 350 points of a western Colombian catchment, where the presence or absence or water was known beforehand. Sixty percent of the dataset was used to train the algorithms and the remainder was used to calibrate predictive accuracy. Both classifiers rendered a realistic picture of the catchment’s water bodies. RFC obtained a mean test score in excess of 0.93 and an area under the receiver operating characteristic curve of 0.95. SVM scored 0.89 and 0.89, respectively, after optimization. Performance was better overall in flat regions. SVM identified correctly over 87% of the surface area of lentic and 82% of lotic water bodies, while RFC scored over 80% in both cases. In mountain regions precision dropped to 69% and 62% for SVM and 65% and 76% for RFC. This leads to three conclusions: (a) the method provides satisfactory results at the regional scale and is versatile enough to export to other settings; (b) local-scale detail cannot be captured in the absence of an accurate high-resolution digital elevation model, particularly in mountain areas; (c) complementing standard machine learning metrics with ad hoc indicators is likely needed in cases where the input dataset consists solely of unambiguous examples.

Water access remains a challenge in rural areas of low-income countries. Manual drilling technologies have the potential to enhance water access by providing a low cost drinking water alternative for communities in low and middle income countries. This paper provides an overview of the main successes and challenges experienced by manual boreholes in the last two decades. A review of the existing methods is provided, discussing their advantages and disadvantages and comparing their potential against alternatives such as excavated wells and mechanized boreholes. Manual boreholes are found to be a competitive solution in relatively soft rocks, such as unconsolidated sediments and weathered materials, as well as and in hydrogeological settings characterized by moderately shallow water tables. Ensuring professional workmanship, the development of regulatory frameworks, protection against groundwater pollution and standards for quality assurance rank among the main challenges for the future.

Las Tablas de Daimiel National Park is one of Spain's most representative groundwater‐ dependent ecosystems. Under natural conditions, water inflows combined brackish surface water from River Gigüela with freshwater inputs from River Guadiana and the underlying aquifer. Since the mid‐1970s, aquifer overexploitation caused the desiccation of the wetlands and neighbouring springs. The National Park remained in precarious hydrological conditions for three decades, with the only exception of rapid floods due to extreme rainfall events and sporadic water transfers from other basins. In the late 2000s, a decrease in groundwater abstraction and an extraordinarily wet period reversed the trend. The aquifer experienced an unexpected recovery of groundwater levels (over 20 m in some areas), thus restoring groundwater discharge to springs and wetlands. The complex historical evolution of the water balance in this site has resulted in substantial changes in surface and groundwater quality. This becomes evident when comparing the pre‐1980 groundwater quality and the hydrochemical status in the wetland in two different periods, under “dry” and “wet” conditions. Although the system is close to full recovery from the groundwater‐level viewpoint, bouncing back in the major hydrochemical constituents has not yet been obtained. These still appear to evolve in response to the previous overexploitation state. Moreover, in some sectors, there are groundwater‐dependent ecosystems that remain different to those found in preoverexploitation times. The experience of Las Tablas de Damiel provides an observatory of long‐term changes in wetland water quality, demonstrating that the effects of aquifer overexploitation on aquatic ecosystems are more than a mere alteration of the water balance and that groundwater quality is the key to aquifer and aquatic ecosystem sustainability., Centro de Estudios y Experimentación de Obras Públicas, España, Instituto Geológico y Minero de España, España, Facultad de Ciencias Geológicas, Universidad Complutense de Madrid, España, UNESCO/UNITWIN Chair “Appropriate Technologies for Human Development", Universidad Complutense de Madrid, España

Groundwater represents an essential resource in sub-Saharan Africa, where several hundred million people rely on aquifers for domestic supply. This paper presents a method to map groundwater potential in the Republic of Mali based on a spatially-distributed database of 26,040 boreholes. The database includes exhaustive information on key parameters such as borehole location, success rate of borehole production, depth, yield, static groundwater level or water quality. Representative variables were classified and interpreted jointly to develop a groundwater potential index for each of the 703 communes in Mali. This provides a methodological novelty because groundwater potential studies typically rely on indirect indicators such as lineaments, slope, soil moisture and landforms. Also, such large borehole databases have seldom been used to estimate groundwater potential. The highest indexes were obtained for the areas in and around the River Niger’s Inner Delta, including southern Tombouctou and the central parts of the Ségou and Mopti Regions. The lower Precambrian formations, which include the country’s thoroughly populated southern plateau, had moderate scores. The lowest groundwater potential was found in the northern part of the Kayes and Koulikoro Regions, as well as in the entire region of Kidal. By providing results at the commune scale, these outcomes show that groundwater potential across the country’s geological and hydrogeological units can be highly variable, and that local and regional-scale information may be useful for groundwater management purposes. These results are policy-relevant in a context of rapid change and population growth, where groundwater resources can be expected to be increasingly relied upon in the coming years.

© 2017 Elsevier GmbH On-site sanitation is generally advocated as a means to eradicate the health hazards associated with open defecation. While this has provided a welcome upgrade to the livelihoods of millions of people in low-income countries, improved sanitation facilities are increasingly becoming a threat to domestic groundwater-based supplies. Within this context, a survey of pit latrines, domestic wells and improved water sources was carried out in a large rural village of southern Mali. All households were surveyed for water, sanitation and hygiene habits. Domestic wells and improved water sources were georeferenced and sampled for water quality (pH, electric conductivity, temperature, turbidity, total dissolved solids, thermotolerant coliforms, chloride and nitrate) and groundwater level, while all latrines were inspected and georeferenced. A GIS database was then used to evaluate the proportion of water points within the influence area of latrines, as well as to underpin multiple regression models to establish the determinants for fecal contamination in drinking supplies. Moreover, an appraisal of domestic water treatment practices was carried out. This revealed that nearly two-thirds of the population uses bleach to purify drinking supplies, but also that domestic-scale treatment as currently implemented by the population is far from effective. It is thus concluded that existing habits could be enhanced as a means to make water supplies safer. Furthermore, population, well and latrine density were all identified as statistically significant predictors for fecal pollution at different spatial scales. These findings are policy-relevant in the context of groundwater-dependent human settlements, since many countries in the developing world currently pursue the objective of eliminating open defecation.

Water and wireless coverage were evaluated in a rural commune of southern Mali. All improved water sources in the area were checked for operability, accessibility, and water quality, while wireless coverage was tested by means of smartphones, phone calls, and instant messaging applications. Theoretical water coverage exceeded 82% of the total village surface area, thus beating the national and sub-Saharan African averages, but dropped to just 39% when considering only serviceable and contamination-free sources. In contrast, wireless coverage exceeded 90%. These outcomes highlight a triple paradox: (1) water from theoretically safe (i.e., improved) water sources is often unsafe to drink; (2) wireless access is better than water access even though water is essential for human survival and telecommunications are not; and (3) excellent Internet coverage does not help a large number of people, who lack the skills, devices, or need to access it. While telecommunications seem to be making inroads towards universal access faster than the water sector, a survey of water committees uncovered a hidden nexus between both resources, revealing that increased wireless access is actually contributing to underpin water coverage in a variety of ways.

Groundwater resources are essential to underpin the daily life of communities in remote regions. Hydrogeological studies in these areas are complex, largely due to the absence of long water table records and to the difficulties involved in accessing some relevant locations. This hampers attempts to manage local resources. Devising cost-effective methods to explore these aquifers is important to understand how they work and to come up with adequate protection strategies. This paper deals with the joint application of Geographic Information Systems (GIS) tools and numerical groundwater models to explore groundwater resources in desert areas. The method is illustrated through its application to Erg Chebbi, a water table aquifer located in southern Morocco, which supplies drinking and irrigation water for local communities while also underpinning agriculture and tourism. The geometry of the aquifer was established based on existing cartography, GIS and a field survey. This led to the development of a steady-state numerical model. Modeling results suggest that the aquifer has been depleted by almost 30% due to groundwater extractions in less than 50 years. The average drawdown was found to be in the order of three meters. This corresponds to a total depletion in the order of 20–60 Mm 3 .

Engineering heritage refers to a broad variety of items of social, economic, aesthetic or historic relevance, including roads, dams, buildings and supply networks. Due to their utilitarian nature, their heritage value is often overlooked. This occurs even with those infrastructures that have played an essential role in underpinning the daily existence of entire civilizations. Underground water-supply networks provide an excellent example. Although there are exceptions, water networks tend to be functional in design, rather than monumental. Moreover, they present intricate linear layouts that often span several kilometres. This means they are costly to maintain once their operational life is over, and that they are prone to abandonment and destruction. Devising a priori protection strategies is important to preserve these valuable cultural assets. The following pages present a method to map linear structures based on archive records and sparse material remains. The method is illustrated through its application to the Amaniel qanat, a water-supply gallery built in Madrid, Spain, in the early 17th Century. An appraisal of the known remains was carried out first, leading to an inventory of galleries, shafts, shaft caps and deposits. This was followed by a thorough survey of over one thousand handwritten manuscripts, including physical descriptions of the aqueduct, budget accounts or water metering campaigns, among other documents. Known remains and written evidence were matched against original and auxiliary maps to reconstruct the itinerary of the aqueduct. This led to the identification of sectors where it is still possible to find remains in good condition. Thus, a priori mapping is advocated a valuable technique to locate and preserve these remains, as well as to devise non-invasive surveys and establish heritage protection zones.

Mexico City relies on groundwater for most of its domestic supply. Over the years, intensive pumping has led to significant drawdowns and, subsequently, to severe land subsidence. Tensile cracks have also developed or reactivated as a result. All such processes cause damage to urban infrastructure, increasing the risk of spills and favoring contaminant propagation into the aquifer. The effects of ground deformation are frequently ignored in groundwater vulnerability studies, but can be relevant in subsiding cities. This report presents an extension to the DRASTIC methodology, named DRASTIC-Sg, which focuses on evaluating groundwater vulnerability in urban aquifers affected by differential subsidence. A subsidence parameter is developed to represent the ground deformation gradient (Sg), and then used to depict areas where damage risk to urban infrastructure is higher due to fracture propagation. Space-geodetic SqueeSAR data and global positioning system (GPS) validation were used to evaluate subsidence rates and gradients, integrating hydrogeological and geomechanical variables into a GIS environment. Results show that classic DRASTIC approaches may underestimate groundwater vulnerability in settings such as the one at hand. Hence, it is concluded that the Sg parameter is a welcome contribution to develop reliable vulnerability assessments in subsiding basins.

Fecal contamination poses a threat to groundwater supplies in low income regions. This is often due to the coexistence of pit latrines with domestic wells in densely populated areas. In this context, developing alternative methodologies to map fecal pollution in shallow wells is needed. A thorough survey of over 240 domestic wells and 570 pit latrines was conducted in a rural town of southern Mali. Water samples were collected from all wells and tested for temperature, pH, electric conductivity, total dissolved solids, turbidity and thermotolerant coliforms. The outcomes of the field survey were incorporated into a GIS database. Thirteen machine leaning classifiers, including different statistical algorithms, instance-based learners and tree-based models, were used to determine the spatial distribution of fecal pollution as per five explanatory variables (latrine density, distance to the closest latrine, borehole yield, water table depth and population density). The best performing classifiers, selected on test scores, were then used to develop predictive maps. Random forest and logistic regression rendered prediction scores for fecal pollution in excess of 0.90. Multilayer perceptrons, support vector machines and quadratic discriminant analyses also proved adept at forecasting fecal pollution. Ensemble mapping shows that 30–50 m buffers around domestic wells may be sufficient to prevent contamination of domestic supplies in most instances. This demonstrates that machine learning may provide a versatile methodological alternative to traditional Darcian approaches. On the other hand, the practical difficulties involved in maintaining wellhead protection areas suggests the need to implement piped water supplies.

Artesian springs are localized aquifer outlets that originate when pressurized ground water is allowed to rise to the surface. Computing artesian discharge directly is often subject to practical difficulties such as restricted accessibility, abundant vegetation or slow flow rates. These circumstances call for indirect approaches to quantify flow. This paper presents a method to estimate ground water discharge through an upwelling spring by means of a three-layer steady-state groundwater flow model. Model inputs include on-site measurements of vertical sediment permeability, sediment temperatures and hydraulic gradients. About 70 spring bed piezometers were used to carry out permeability tests within the spring sediments, as well as to quantify the hydraulic head at different depths below the discharge point. Sediment temperatures were measured at different depths and correlated to permeabilities in order to demonstrate the potential of temperature as a substitute for cumbersome slug tests. Results show that the spatial distribution of discharge through the spring bottom is highly heterogeneous, as sediment permeability varies by several orders of magnitude within centimetres. Sensitivity analyses imply that geostatistical interpolation is irrelevant to the results if field datasets come from a sufficiently high resolution of piezometric records. Copyright © 2013 John Wiley & Sons, Ltd.

The European Union (EU) Water Framework Directive (WFD) requires EU countries to achieve good status of all their waters by 2015. This should be achieved through the implementation of river basin management plans (RBMPs), which in turn are based on water resources baseline data. While it is too soon to assess the WFD effectiveness, the planning process has contributed to identify possible pitfalls of the WFD design and has provided an opportunity to enhance the knowledge of European water resources. Groundwater plays a strategic role in Spain’s economy and also in the maintenance of its aquatic ecosystems, making that country an excellent testing ground for getting an insight into the definition of baseline groundwater under the WFD mandate. This paper presents the results of compiling the information produced for the RBMPs to attain an overall picture at a national scale. In doing so, it examines some of the methodological and technical choices involved in the definition of a baseline for groundwater, assessing their practical consequences on groundwater management. This paper argues that having baseline figures for the RBMPs required compromises or shortcuts to be taken. Undoubtedly, the process leading to the first WFD Plans has been an extremely enriching learning process, but it leaves questions unanswered. The periodic (6 year) RBMP revision should become an opportunity to revisit and better tune the baseline conditions established during this first planning cycle.

Carbonate aquifers represent an important source of freshwater, both for urban and agricultural uses. This is particularly true in semiarid regions, where intensive pumping has often led to aquifer overexploitation. One example is the Mijas mountain carbonate diffuse flow system (80 km2), located to the SW of the city of Malaga, Spain. From a geolo-gical standpoint, this area consists of Triassic dolomitic and calcareous rocks, which overlay Palaeozoic metapelites. The geological structure is formed by ESE-WNW folds and the me-tapelites anticlinal cores have divided the study area into four aquifer systems. The recharge of Mijas mountain aquifers comes from direct infiltration of rainfall, while pumping is the main discharge. To improve the knowledge of geological and hydrodynamic parameters, and therefore to improve water resources management, a hydrogeological model has been developed with Processing Modflow 8.0.42. Piezometric level and spring flows have been modelled, under steady and transient-flow conditions for a 35-year period. Five future scenarios were simulated for different rainfall and pumping conditions. Outcomes confirm that the water level evolution is determined by the quantity and distribution of rainfall during the hydrological year, with the same pumping rate. The results also suggest that current trends are likely to raise sustainability issues in the future. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

"Abstract Nitrate pollution is a worldwide problem in groundwater, as it may limit water supply and increase health risk when high concen - trations are present. The North Maresme coastal alluvial groundwater-dependent agrosystem, one of the most heavily nitrate polluted aquifers in Spain, is located 70 km northeast from Barcelona. Field monitoring campaigns performed in this aquifer yielded nitrate concentrations up to ten times the permitted limit for drinking water suggested by the World Health Organization (50 mg/l), with a maximum concentration of 567 mg/l and a mean of 137.5 mg/l. Nitrate contamination was quantified by means of a mass balance, taking into account the main hydrogeological and anthropogenic processes that control the behavior of this ion in the aquifer, such as recharge, groundwater extraction, irrigation and fertilizer application to crops. Nitrate balance is an integrative approach for assessing nitrate loading based on linking different sources of nitrates to a groundwater balance. This methodology considers nitrate as a conser - vative ion because the geological-geochemical medium behaves under oxidant conditions. Results show that the studied aquifer system receives, yields and retains approximately 935, 844 and 91 tons of NO 3 - /year, respectively. This methodology can be applied to other nitrate-contaminated aquifers with similar conditions to improve management of fertilizers practices in areas of intensive agriculture."

This paper addresses the application of bioproducts produced by plants (locust bean, guar, and mesquite seed gums) to enhance remediation processes of different nature: soil washing and biodegradation methodologies. These natural gums were tested at laboratory scale to remove total petroleum hydrocarbons-diesel fraction (TPH-diesel) from oil-contaminated volcanic soils sampled from a polluted site in an agricultural area of western Mexico. TPH-diesel removal by natural gums was compared to common synthetic surfactants. There is a strong evidence of contamination caused by the presence of TPH-diesel at a concentration of 32,100 mg/kg, which is above the legal limit of 1,200 mg/kg for agricultural soils in Mexico. Regarding the surfactant soil washing experiments, ionic surfactants showed removal rates above the control test of about 78.51 % (Maranil LAB), 71.27 % (Texapon 40), 60.13 % (SDS), and 48.19 % (Surfacpol G). In contrast, some nonionic surfactants showed removal rates below soil-washing background rate (40 %). On the other hand, natural gums showed interesting and promising results. Guar gum and locust bean gum showed efficiencies of 54.38 % and 53.46 %, respectively. Biodegradation experiments confirmed the effectiveness of natural gums as biodegradation enhancers in diesel-contaminated soils. Specifically, guar gum showed an excellent performance. An 82 % TPH-diesel removal rate was achieved for a very low gum concentration (2 ppm). In this particular context, reported surfactant concentrations to assist biodegradation are, in general, higher. This work demonstrated the applicability of natural gums as soil remediation enhancers in diesel-contaminated systems. Particularly, guar gum might represent a cost-effective alternative for biodegradation enhancement processes.

Mediterranean aquifers are frequently subject to the joint effect of intensive exploitation and low recharge values. Besides, groundwater is the only available water resource in many Mediterranean regions. Groundwater recharge studies are therefore necessary to underpin water management practices. This manuscript presents a methodology to estimate groundwater recharge in a small limestone aquifer of southeastern Spain. The HYDROBAL model is used to calculate daily soil water balances on the basis of hydrological and soil data as well as on vegetation cover. Deep drainage model outputs are converted into water table variations using a lumped model add-on. The adjustment between observed and calculated water table levels is in the order of r2 = 0.87. This correlation coefficient suggests that HYDROBAL is a useful tool to estimate groundwater recharge in the region. In addition, differences in groundwater recharge rates are observed for dry, average and wet years. Estimated recharge rates range between 0% and 18% of the mean annual rainfall, which corresponds to a net recharge of 0 to 59 mm year−1. Recharge rates increase proportionally with precipitation (r2 = 0.90). Copyright © 2012 John Wiley & Sons, Ltd.

Light non-aqueous phase liquids (LNAPL) represent one of the most serious problems in aquifers contaminated with petroleum hydrocarbons liquids. To design an appropriate remediation strategy it is essential to understand the behavior of the plume. The aim of this paper is threefold: (1) to characterize the fluid distribution of an LNAPL plume detected in a volcanic low-conductivity aquifer (∼0.4 m/day from slug tests interpretation), (2) to simulate the recovery processes of the free-product contamination and (3) to evaluate the primary recovery efficiency of the following alternatives: skimming, dual-phase extraction, Bioslurping and multi-phase extraction wells. The API/Charbeneau analytical model was used to investigate the recovery feasibility based on the geological properties and hydrogeological conditions with a multi-phase (water, air, LNAPL) transport approach in the vadose zone. The modeling performed in this research, in terms of LNAPL distribution in the subsurface, show that oil saturation is 7% in the air–oil interface, with a maximum value of 70% in the capillary fringe. Equilibrium between water and LNAPL phases is reached at a depth of 1.80 m from the air–oil interface. On the other hand, the LNAPL recovery model results suggest a remarkable enhancement of the free-product recovery when simultaneous extra-phase extraction was simulated from wells, in addition to the LNAPL lens. Recovery efficiencies were 27%, 65%, 66% and 67% for skimming, dual-phase extraction, Bioslurping and multi-phase extraction, respectively. During a 3-year simulation, skimmer wells and multi-phase extraction showed the lowest and highest LNAPL recovery rates, with expected values from 207 to 163 and 2305 to 707 l-LNAPL/day, respectively. At a field level we are proposing a well distribution arrangement that alternates pairs of dual-phase well-Bioslurping well. This not only improves the recovery of the free-product plume, but also pumps the dissolve plume and enhances in situ biodegradation in the vadose zone. Thus, aquifer and soil remediation can be achieved at a shorter time. Rough calculations suggest that LNAPL can be recovered at an approximate cost of $6–$10/l.

Measuring groundwater extractions is central to adequate groundwater management in agricultural basins. Groundwater pumping records are often subject to considerable uncertainties, particularly in the case of arid and semiarid settings where irrigation is the most important water use. In most cases this is due to the difficulties involved in locating and monitoring all wells. We describe the estimation of groundwater pumping by coupling the water table fluctuation method with the groundwater balance equation. This is demonstrated through its application to the Mancha Occidental aquifer, Spain, an area subject to intensive pumping for irrigation since the early 1970s. A sensitivity analysis is conducted to evaluate the effect of relevant hydrogeological parameters, namely specific yield, as well as the most appropriate theoretical semivariogram, to calculate yearly storage variations within the system. Results are validated in the light of official pumping estimates.

Summary Recharge is a key component of the hydrological balance in groundwater systems. Particularly in arid and semiarid settings recharge often takes place during isolated rainfall episodes. As a result pumping might cause groundwater levels to fall continuously for long periods of time, even if yearly abstractions remain below the average replenishment rate. Recharge is naturally difficult to quantify, as it depends on a complex variety of factors. Indirect techniques based on mathematical models have long since been advocated as valuable means to estimate recharge. This paper presents a methodology to estimate groundwater recharge in quick-response semiarid karst aquifers. Lumped and distributed models are used to evaluate the fraction of rainfall that ultimately results in aquifer recharge, as well as the correlation between the magnitude of rainfall events and infiltration rates. Modelling results are then compared with direct observations of the recharge processes and discussed to evaluate the implications of time scales. This study is demonstrated through a case-specific application to the Ventos aquifer, an intensively exploited carbonate system located in one of the driest areas of peninsular Spain. Overall, both approaches perform similarly, although the lumped model exhibits a better agreement with field records. Results reflect the nonlinear nature of the rainfall/recharge ratio. The fraction of rainfall that ultimately recharges the aquifer seems to increase exponentially with the magnitude of the event.

The European Union Water Framework Directive establishes the obligation to all Member States to develop and implement catchment-scale management plans. These aim at reaching a good status of all water bodies in Member States by 2015 or, at the latest, by 2027. Numerical models provide a suitable approach to evaluate the possibilities of achieving this goal by enabling users to deal with complex hydrological interrelations in a dynamic manner. This paper presents a modelling-based approach to examine the past and future effects of groundwater-based urban supply in Metropolitan Madrid, Spain. Monthly scale model calibration is based on 32 years of water table observations. Care is taken to address the effect of intensive pumping on groundwater levels and streamflows, as well as the role of groundwater resources in meeting urban demands during dry spells. The paper concludes by reflecting on the implications and probabilities of meeting the aforementioned deadlines, as well as on the sustainability of past and future pumping trends. Policy considerations aside, modelling results suggest that groundwater extractions could be augmented considerably without causing a significant decrease in streamflows.

Evaluating aquifer–river interactions is naturally complex, particularly within urban settings. This is largely due to the difficulties involved in quantifying most elements of the water balance. The ability of numerical models to deal with several dynamic variables simultaneously makes them valuable tools to address this kind of problem. An applied, modeling-based approach to investigate the spatial and temporal variations of aquifer–river connectivity within a shallow urban aquifer is presented. Model development is based on comprehensive field campaigns in Langreo, Spain. Two calibration runs (for summer and winter conditions) were carried out in order to evaluate the spatial distribution of recharge rates. The model suggests that baseflows are largely negligible in comparison with total streamflows. This is mostly attributed to the abrupt nature of the catchment, which prevents the existence of sufficiently large alluvial systems to a great extent. Modelling results also show that aquifer–river connectivity at the study site is constrained by urban pumping as well as by seasonal fluctuations.

Las Tablas de Daimiel National Park is a series of wetlands which naturally originated from groundwater discharges from the Mancha Occidental aquifer, Spain. Despite the relatively large size of this aquifer, 30 years of intensive groundwater pumping have significantly depleted the water table. As a result, wetlands only remain functional due to artificial inflows. Infiltration loss is therefore a key parameter to evaluate how much water is needed to maintain ecosystem functionality. Although yearly infiltration estimates existed prior to this work, these did not take into account key parameters such as the temporal evolution of the flooded area. This paper presents a more concrete estimate of the average infiltration losses. Infiltration is calculated as the closure term of daily water balances during a period of time where all other elements were known to an acceptable accuracy. A validation mechanism is provided to check the potential utility of the calculated infiltration in wetland management practices. Copyright © 2008 John Wiley & Sons, Ltd.

The Mezquital Valley (MV) hosts the largest unmanaged aquifer recharge scheme in the world. The metropolitan area of Mexico City discharges ~60 m3/s of raw wastewater into the valley, a substantial share of which infiltrates into the regional aquifer. In this work, we aim to develop a comprehensive approach, adapted from oil and gas reservoir modeling frameworks, to assess water supply sources located downgradient from unmanaged aquifer recharge zones. The methodology is demonstrated through its application to the Mezquital Valley region. Geological, geoelectrical, petrophysical and hydraulic information is combined into a 3D subsurface model and used to evaluate downgradient supply sources. Although hydrogeochemical variables are yet to be assessed, outcomes suggest that the newly-found groundwater sources may provide a long-term solution for water supply. Piezometric analyses based on 25-year records suggest that the MV is close to steady-state conditions. Thus, unmanaged recharge seems to have been regulating the groundwater balance for the last decades. The transition from unmanaged to managed recharge is expected to provide benefits to the MV inhabitants. It will also be likely to generate new uncertainties in relation to aquifer dynamics and downgradient systems.

Over the last decades, groundwater irrigation has become commonplace in many arid and semiarid regions worldwide, including Spain. This is largely a consequence of the advances in drilling and pumping technologies, and of the development of Hydrogeology. Compared with traditional surface water irrigation systems, groundwater irrigation offers more reliable supplies, lesser vulnerability to droughts, and ready accessibility for individual users. Economic forces influence the groundwater irrigation sector and its development. In Spain's Mediterranean regions, abstraction costs often amount to a very small fraction of the value of crops. In the inner areas, groundwater irrigation supports a more stable flow of farm income than rainfed agriculture. The social (jobs/m3) and economic (€/m3) value of groundwater irrigation generally exceeds that of surface water irrigation systems. However, poor groundwater management and legal controversies are currently at the base of Spain's social disputes over water. A thorough and transparent assessment of the relative socio-economic value of groundwater in relation to surface water irrigation might contribute to mitigate or avoid potential future conflicts. Enforcement of the European Union's Water Framework Directive may deliver better groundwater governance and a more sustainable use.