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Article

An Automated Method to Assess the Suitability of Existing Boreholes for Solar-Based Pumping Systems: An Application to Southern Madagascar

by
Fabio Fussi
1,
Víctor Gómez-Escalonilla
1,
Jean-Jacques Rahobisoa
2,
Hariliva Omena Anahy Ramanantsoa
2 and
Pedro Martinez-Santos
1,*
1
Estratigrafía y Paleontología, Departamento de Geodinámica, Estratigrafía y Paleontología, Universidad Complutense de Madrid, 28040 Madrid, Spain
2
Department of Earth Sciences Antananarivo, Université d’Antananarivo, Antananarivo BP 566, Madagascar
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(3), 1255; https://doi.org/10.3390/su17031255
Submission received: 20 December 2024 / Revised: 24 January 2025 / Accepted: 31 January 2025 / Published: 4 February 2025
(This article belongs to the Special Issue Sustainable Water Management in the Face of Climate Change and Water Scarcity)
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Abstract

:
Groundwater provides a strategic resource in the face of uncertain climate conditions in arid and semi-arid regions. Solar-based groundwater pumping is quickly gaining ground across rural sub-Saharan Africa, promoted by national and international organizations as the new technology of choice for water supply and irrigation. A crucial question in large-scale developments is whether pre-existing boreholes can be fitted with solar pumps. Based on data from southern Madagascar, this paper provides an automated method to deal with this. Our approach relies on a combination of hydrogeological criteria, including well screen depth, drawdown in relation to the static water column, and pumping efficiency. The results show that 60% of the existing boreholes in the study region are potentially suitable for the installation of solar pumps. Out of these, 54% would be able to supply water to large rural communities (>1000 people), whereas the remaining 46% present the potential to provide water to medium communities (500 to 1000 people). There are, however, concerns as to whether the information contained in the dataset is fully representative of current borehole conditions. Furthermore, the potential for installation of solar-based supplies must be placed in the context of the available resources and local capacities in order to ensure future sustainability.

1. Introduction

Hand-pump-based water supply is prevalent across rural sub-Saharan Africa. Recent estimates suggest that there are currently 700,000 hand pumps in the region that supply water to approximately 200 million people [1]. Hand pumps have been prioritized by many governments, international donors and relief organizations because they are robust and cheap to install and maintain. Furthermore, hand pumps grant access to relatively deep groundwater, thus providing a safer alternative than surface water, open wells and unprotected springs. However, hand pumps also present some limitations. While they contribute to reduce the burden of carrying water, they do not eliminate it. Factors such as distance, fetching time, and ownership of a means of transport to haul water constrain per capita water use when hand pumps are the main source [2]. Distance to a water source is not only a predictor of disease risk [3], but is also associated with loss of household productivity, reduced school attendance, and, potentially, physical injury [4,5]. The main source of hand pump criticism, however, pertains to functionality. Hand pumps are not readily repaired when they break down. Reasons include system age, distance from a major town, and the absence of user fees [6], as well as construction quality, lack of funding, incidences of theft, inadequate community-based management approaches, and component durability [7,8]. A report by the Rural Water Supply Network estimated that one-third of all hand pumps in rural sub-Saharan Africa were non-functional at any moment in time a few years ago [9]. More recent estimates suggest that approximately one in four hand pumps in sub-Saharan Africa are non-functional [10]. This amounts to approximately 175,000 inoperative water points.
A single hand pump serves around 300 people [11]. This means that most medium and large rural communities feature more than one. Physical decentralization contributes to reduce fetching times, but the need to keep track of thousands of individual infrastructures hampers the ability of governments to manage groundwater resources sustainably. Thus, authorities and international organizations are gradually moving away from hand pumps in pursuit of the United Nations Sustainable Development Goal ideal of piped supplies in every household [12,13]. Solar-based systems allow higher flow rates, to the point that a single solar pump can replace several hand pumps. Thus, even if solar pumps require greater operational expertise—and are more difficult to maintain—centralized systems can reduce the total number of infrastructures to keep track of, provide more water when demands are highest, minimize the risk of groundwater pollution, and facilitate infrastructure management.
Recent times have witnessed a growing interest in solar-based groundwater supplies, both for domestic supply and irrigation [13,14]. Solar pumping systems are relatively cheap and simple to operate. They are also suited to geographical contexts characterized by the absence of reliable power grids and expensive fuel prices. Last but not least, solar energy has already achieved a significant degree of penetration in sub-Saharan Africa, which could facilitate adoption within the water sector. Madagascar is one of several countries that are currently evaluating the potential of solar groundwater pumping [15]. In this context, profiting from existing boreholes is typically prioritized over drilling new ones. Different efforts have already been conducted across Africa so far, but there is no common methodology to evaluate whether existing boreholes can be fitted with solar-based systems, nor a clear bibliographical reference as to how this issue could be tackled.
This kind of analysis inevitably requires large datasets. The importance of developing groundwater databases for the proper management of this resource is frequently advocated [16]. Data are needed to take action and make decisions, but also need to be presented in a correct and organized way so that it can be used more effectively [17]. In recent decades, the development of large databases has demanded the application of big data techniques and automation procedures with the objective of enhancing the processing of a substantial quantity of information. In this sense, the semi-automation of pumping test analysis is proposed in the ensuing pages. The main aim of this paper is to present an approach to select those boreholes where hydrogeological conditions are suitable for the installation of solar pumps and where it is thus feasible to improve water supply. This method relies on a large database of pumping tests and combines a series of classic hydraulic techniques to estimate whether borehole yield is suitable to sustain a solar pump based on the required yield for medium and large rural communities. We combine three different approaches. The first two, namely the Authossère method and the uppermost screen position, are based on the estimation of expected drawdown, while the third one takes into consideration borehole efficiency. Application is illustrated through a specific case study in the Bekily district, southern Madagascar. The added value of this method in relation to using traditional drawdown tests is two-fold. In the first place, we make use of the wealth of data that exists in regional databases. Even if this information comes with shortcomings of its own, it provides a quick alternative to study borehole yields from a spatial perspective. Furthermore, automation facilitates the analysis. Secondly, by relying on regional datasets it is possible to narrow down the choice of potential locations for solar pumps, thus contributing to underpin large-scale programs such as those that are currently being put in place in the Global South.

2. Materials and Methods

2.1. Study Region

This research focuses on the Bekily district, Androy region, southern Madagascar (Figure 1). Bekily spans a surface of approximately 5575 km2 in the Toliara province. The study area is limited to the east and north by the Anosy region (Betroka district), to the west by the Atsimo Andrefana region (Ampanihy district), to the southwest by the Beloha district and to the southeast by the Antanimora and Ambovombe districts.
Bekily presents a semi-arid to arid climate with two distinct seasons. The rainy hot season runs from November to March, while the dry season takes place between April and October. Annual temperatures vary between 19 °C and 28 °C, with an average of 24 °C [18]. Between July and August, temperatures are lower [19], while extreme heat may increase up to 40 °C during the summer season, leading to significant droughts. Aridity progresses from the north and northeast to south and southwest, and its influence is observed on vegetation changes, landscapes and soil types [20]. Aridity is usually intensified by persistent high temperatures and strong, persistent, dry winds, particularly on the southern coastal fringe of the area. Between 70% and over 90% of the annual rainfall occurs between December and February. Even in the wet season, rainfall is limited and irregular. Mean annual rainfall varies considerably between 600 and 795 mm/yr, while potential evapotranspiration is about 1000 mm/yr [21].
There is a clear topographic north–south gradient, from approximately 650 to 350 m.a.s.l. Mountains, hills and irregular plains dominate in the northern and central parts of the region, and gradually evolve into flats in the sourthernmost area [22]. Geological information can be obtained from various sources, including satellite images and geological data. The Precambrian crystalline basement in the southern Madagascar is sub-divided into four domains, namely Ikalamavony, Anosyan, Androyan, and Vohibory [23,24,25]. The Androyan domain presents a peneplain-like landscape where Bekily is located. This consists of mafic and felsic orthogneiss with intercalated low-Al paragneiss and marble [26]. Mafic orthogneisses are interpreted as metamorphosed island-arc basalt and andesite with ages between 850 and 700 Ma [27]. These rocks are also accompanied of gneiss, leptynite, pyroxenite, quartzite, amphibolite, migmatite and clastic deposits [27,28,29]. Due to tectonic constraints, intrusion of igneous rocks such as granite and anorthosite are in combination with fractured metamorphic rocks, especially within gneissic formations [30,31,32]. Precambrian metamorphic rocks bounded by shear zones in the East and west are formed at high metamorphic grade and show sub-vertical foliation oriented approximately N–S [33,34,35].
Groundwater systems in the area are relatively complex and their hydrogeological behavior is still subject to uncertainties. The altered and fractured metamorphic rocks with alluvial deposits along the main river courses constitute the main aquifers in this area [36] Weathered rocks also hold moderate amounts of groundwater, their thickness oscillating widely, between 2 and 45 m. These two types of aquifers are often interconnected [37] The average permeability is typically low and heterogeneous, ranging from 10−6 m·s−1 to 10−4 m·s−1 [37,38,39]. Aquifers are generally shallow and unconfined, but instances of semi-confined systems are found in some areas [37,39]. Groundwater flow patterns reveal a north–south gradient in the order of 7% [39]. The main recharge is located in the northern part, wherefrom groundwater flow diverges radially towards the south [39,40]. Groundwater recharge also decreases from east to west owing to climatic factors. Streams and rivers also contribute to groundwater recharge during the rainy season. Thus, groundwater baseflow to surface water bodies is considered insignificant.
Borehole cross sections show that the water table depth varies considerably. In general, the water table is shallow in the alluvial deposits, although it reaches up to 15 to 30 m in the higher altitude areas [41]. Groundwater quality is variable. Electrical conductivity ranges between 100 and 4000 µS/cm but it reaches up to 30,000 µS/cm in some areas, especially in the southern part of the study regions (Bekily and its surrounding areas) [37,42].
The Bekily area is known for significant water scarcity and groundwater salinity problems [37,42]. Fractured bedrock aquifers and boreholes are the main source of water supply. Mean yields are in the order of 1.5 L·s−1. In the alluvial deposits and valley bottoms of the south, maximum yields in the order of 3 L·s−1 are observed [37,41]. Groundwater is traditionally used for domestic purposes. More recently, recurrent droughts, coupled with the threat of starvation and climatic variability, have led people to pump groundwater for small irrigation developments.

2.2. Data Sources

This research relies mostly on UNICEF Madagascar’s groundwater database. Information within this database was obtained directly from borehole construction and pump tests carried out either by this organization or by external agencies (Bushproof, Médecins Sans Frontières, Action contre la Faim, and others). The database contains more than 3000 entries (wells and boreholes), not all of which include pump test information.
We present a specific analysis for the region of Bekily, where there are 255 boreholes. Out of these, 135 include information for at least one step of the pumping test (Figure 1 and Table 1). About 50% of the water points present one or two steps, while a minimum of three steps is typically recommended for interpretation [43]. While sub-optimal, tests featuring only two steps can provide useful information in contexts such as the one at hand. For instance, in terms of the maximum flow rate for the test, approximately half of the available points exceeded 2 m3/h. This limits the analysis to some extent, but still allows for an assessment of the potential yield of the borehole and therefore its suitability for the installation of a solar pump.

2.3. Suitability Assessment Method

To the authors’ knowledge, there is no such thing as a widely accepted methodology to select water points for the installation of solar pumps, neither in Madagascar nor at the international scale. Inroads were made in the context of the MIONJO project, a joint effort by various organizations that aims to improve access to basic services in Madagascar. This initiative gathered the opinion of local hydrogeologists. Taking this as a starting point, our work evaluates the suitability of a water point for a solar pump on the basis of two criteria, namely hydrological suitability and social suitability. The first aspect, which is the main focus of this paper, considers the hydraulic properties of the borehole and water quality. The second element, social suitability, is based on the distribution of the local population and their relative proximity to other pumps that provide an improved service and yield when compared to hand pumps.
Additionally, it is important to note that the project activities are carried out in a region characterized by small or medium rural settlements. Therefore, this assessment is designed to meet the specific needs of this type of community. In this sense, water demands are computed assuming a daily pumping time of eight hours and an average water needs of 30 L/person/day. Thus, to be suitable for small and medium villages (up to 500 people), a solar pump needs to yield about 2 m3/h. In the case of medium to large villages (1000 people), yield should exceed 4 m3/h.
The first two methods of analysis (Authossère and screen position) are based on the estimation of expected drawdown and the comparison with a maximum acceptable value (Figure 2), while the third method (borehole efficiency) takes into consideration the efficiency of the water flow into the borehole with the required pumping rate.
The Authossère method does not require screen position as an input [44]. The main criterion is the height of the water column inside the borehole when the dynamic drops to its minimum, and the acceptable drawdown is 2/3 of the static water column. This is based on the assumption that the screens are located mostly at the bottom of the borehole, which is considered reasonable in the vast majority of cases (it does not usually make sense to keep on drilling if the deeper aquifers traversed by the borehole are not to be exploited). In other words, if the screens are mainly located in the lower part of the borehole, depressing the initial water column by one-third should imply that there is always water inflow through most of the screens.
The acceptable drawdown using the screen position method is three meters above the top of the first screen. This means that all screens should remain operational throughout the entire pumping process. The three-meter value is an estimate of the space required to install the pump above the top screen in order to prevent problems associated with the dynamic level dropping too low in relation to the pump.
Finally, the efficiency method relies on pumping efficiency as per Jacob’s formula [45]. We plot the step pump test in a chart S/Q vs. Q (where S is the drawdown, in meters, and Q is the yield, in cubic meters per hour) and make a linear interpolation of the data. Parameters B and C are obtained from the fitted line before efficiency is calculated (Figure 3).

2.4. Pumping Test Analysis Automatization

There are several commercially available software packages able of analyzing step drawdown tests. Take for instance StepMaster [46] and AQTESOLV [47]. These usually require organizing the data in a specific manner. When working with large databases such as the ones at hand, this can be extremely time-consuming. Furthermore, this research uses two independent databases organized in completely different ways, which would have made the task even more complex. Developing a Python script to automate the analysis was thus deemed the most appropriate course of action.
Figure 4 presents a schematic overview of the Python script. An Excel file for each of the test points is created first. This includes basic data for each of the boreholes, including village and region, coordinates, test date, electrical conductivity (μS/cm), database ID, static level depth, total depth and grid position.
The second part consists of generating a table of flow rate (Q) for each step (m3/h), stabilized descent (S) at the end of each step (m), and finally, the S/Q ratio. For tests with at least two steps, two plots are generated. The first one presents flow rate (m3/h) versus drawdown (m). The scatter plot is fitted with a polynomial function that allows for the calculation of expected drawdown for each of the two target flow rates (2 and 4 m3/h). The second one is a scatter plot with S/Q and Q. A linear function is fitted based on Jacob’s approximation to obtain parameters B and C. This in turn allows for the calculation of borehole efficiency for different pumping rates.
Finally, the code generates an Excel file with the basic data of each of the boreholes, the maximum flow rate of the test, the number of steps of the test, the flow rates that would give efficiencies of 60% and 80%, the maximum flow rate according to the Authossère method, the drawdown generated with a flow rate of 2 and 4 m3/h, and the hydrogeological suitability.

2.5. Suitability Classification

Suitability is established first for each of the three methods (Table 2). This provides relevant information not only as to whether a given borehole is suitable for a solar pump, but also as to the exploitable yield with respect to the two reference values of 2 and 4 m3/h and the size of the village that can be supplied. Furthermore, as the Authossère and screen position methods rely on the static water level as a classification input, the fluctuations of this parameter across the dry and wet seasons are incorporated into the analysis.
We observe that, in general, the Authossère method tends to label more boreholes as “suitable” than the other two. This leads to disagreements that were resolved based on a more in-depth analysis. For instance, if the screen position method gives a lower suitability than the Authossère method, then the presence and position of deeper screen sections can be examined in more detail. Boreholes logs and video inspection (when available) were used in this process. If a deeper screen was present and could be expected to provide most of the yield, then it was deemed possible to install the pump at a deeper level, below the first screen, and leave less than three meters of water above the first screen. In this case, the outcome of the Authossère method was favored over that of the screen position method.
If the efficiency method indicates a lower suitability, then it is possible to estimate whether intensive borehole development and/or rehabilitation is likely to enhance water flow (considering the borehole age, discontinuous operation, and observed borehole status via video logging) and augment pumping efficiency.

3. Results

The proposed method to estimate the suitability for solar pumps has been applied to a set of 255 boreholes in the district of Bekily, southeastern Madagascar. The results identified 82 boreholes with suitable conditions for the installation of a solar pump (Table 3), while a total of 151 data points were found to be unsuitable. Out of these, 32 had some pumping test data, while the other 119 were dry. In addition, 46 of the 82 wells with suitable conditions presented a medium potential, i.e., a yield of 2 m3/h capable of supplying 500 people, and 36 were capable of yields in excess of 4 m3/h.
It should be noted, however, that the databases comprise heterogeneous information. For instance, hydraulic conditions may differ considerably from one borehole to another. This can be attributed to different construction standards, as well as to borehole age. Besides, there was no common procedure for the step drawdown tests. This can be readily observed in the results. Thus, Table 3 shows that boreholes classified as suitable have, on average, a higher maximum test flow rate (in the order of 3 m3/h) and at least two steps, whereas water points classified as unsuitable have an average maximum test flow rate of less than 1 m3/h and between one and two steps (Figure 5).
The present study has a marked applied component. It addressed a number of different situations, which necessitated various modifications to the base method to provide a sufficiently comprehensive interpretation. Below we present a series of representative cases. These are primarily derived from the absence of high flow rates in many of the available pumping tests.
The first case consists of a group of boreholes (16) with pumping tests showing that, at 2 and 4 m3/h, they are suitable for a solar pump under all three estimation methods and that they can produce more than 4 m3/h (Figure 6). In this case, the borehole is considered fully suitable for a solar pump with a yield of 4 m3/h, but it is recommended to perform a pumping test with a higher yield and to take into account the creation of a water distribution network for larger communities or for medium irrigation developments.
The second case comprises a series of boreholes that appear to be potentially suitable for solar pumps. All methods suggest that these boreholes may yield flow rates in excess of 4 m3/h (Figure 7). However, these estimates are not fully reliable because the maximum yield in the drawdown tests was too low (less than 3 m3/h). Consequently, while the borehole is considered suitable for solar pumps in small communities, its operation in larger communities should be confirmed with an additional pumping test.
The third case study represents a series of boreholes that appear to yield at least 2 m3/h (Figure 8). However, the available data do not offer a definitive basis for this conclusion, as the maximum yield achieved during the step down test was equal to or less than 1.6 m3/h. Consequently, it is advised again that a pumping test is conducted prior to labelling the borehole as suitable.
Limitations in input data largely explain why a spatial analysis of borehole yields and suitability is inconclusive. Figure 9 shows the spatial distribution of boreholes and their suitability for the installation of solar pumps, while Figure 10 presents the maximum operating flow rate as per Authossère’s method. There is no clear relationship between lithology and borehole suitability. Out of the 32 unsuitable wells, 27 are in gneiss, leptynite, pyroxenite, marble, charnockite and graphitic leptynite, the two main lithologies in the study area. However, lithological criteria alone do not provide a strong correlation with potential well yield, as 72 of the 82 wells suitable for solar pump installation were in the same materials. It would be necessary to carry out a more detailed analysis on other variables such as aquifer thickness, hydrogeological parameters of the materials or recharge rates in order to relate these yields to spatially distributed variables.

4. Discussion

4.1. Quality of the Available Information

Based on the results above, installing solar pumps in pre-existing boreholes would result in improved water access for many local communities. This shows the potential of data analysis of groundwater database for those regions with urgent needs of improving the access to safe water. Unfortunately, however, large databases tend to be a mixed bag in terms of quality. In the case at hand, a large part of the available information is not considered fully reliable. An important reason for this is that pumping tests were carried out with the goal of assessing the capacity to provide water for hand pumps, which is typically lower than for solar pumps. Pumping data are also limited to lower yields because local drilling companies often lack the equipment (pumps, generators) to carry out higher performance tests. Thus, 43% of the pump tests in the original databases are limited to 1.7 m3/h, that is, less than the minimum 2 m3/h threshold (with the assumption that a reliable interpretation cannot be extended for more than 20% of the maximum yield of a given test). Furthermore, 32% present a maximum yield below 1 m3/h. These tests were all discarded, as using them would have undermined the reliability of the outcomes. Finally, a significant part of the information is outdated. This potentially renders misleading results, as some of the pumping tests were carried out over a decade ago. Be as it may, field inspection, together with the existing data, suggests that yields may often exceed 4 m3/h. Asserting this with updated tests is crucial if alternative and more ambitious water supply solutions are to be devised for southern Madagascar.
The above necessarily hampers the interpretation of results. It also raises question marks as to the consistency of the available information. However, it also provides an opportunity to evaluate the current state of hydrogeological knowledge in the Bekily region, as well as to identify needs for future research. Last but not least, dealing with this information delivers a series of valuable lessons as to how the quality of a groundwater database can be enhanced. In particular, we found there is a dire need to improve the structure and consistency of the available information. A large part of the work carried out within this research could have been avoided if there had been a centralized, well-maintained information hub, and if the original data had been dealt with and stored in standard manner from the outset. Consistent, well-organized databases are not important for research purposes, though they also facilitate collaboration among actors such as governments, non-profit organizations, and research institutions.

4.2. From Hand Pumps to Solar Pumps

Another important point from a practical perspective is the shift from hand pumps to solar pumps. The capacity of solar pumps can be modified to align with the specific yield requirements of a given community, taking into account variables such as population density and the intended use of the pump. It is therefore evident that a universal standard cannot be applied, as the relevance of solar pumps is reliant on the distribution pattern of the population. The transition from hand pumps to solar pumps with an elevated tank and taps (or distribution network) allows for a different use of water and presents the potential for future household connections. This undoubtedly signifies an enhancement in the standard of service provided to the population.
With the advent of more affordable and durable equipment, the transition from manual to solar-powered water pumps has become prominent in Africa. However, extended use of solar pumping may also result in an increase in water consumption, and with it, in the threat of aquifer depletion. Aquifer depletion is by no means an unknown hazard, as it has triggered both sustainability concerns and instances of social conflict in arid and semi-arid regions worldwide [48,49,50]. In this context, it must be kept in mind that a large part of Africa’s rural populations inhabits geological environments where hydrogeological conditions—not sunlight—constitute the limiting factor to solar pumping [51]. It is therefore crucial to conduct an aquifer-level analysis, which goes beyond the interpretation of individual pump tests, in order to assess the sustainability of promoting solar pumps over hand pumps. In the case at hand, hydrograph separation for the 1950–2004 interval, coupled with isotopic data, suggests that recharge rate is in the order of 13–19% of rainfall [38]. No research has yet been carried out on the percentage of recharge consumed by the population but no major changes are observed so far in groundwater levels. Well logs suggest that aquifer thickness typically oscillates between 30 and 45 m.
Another point in relation to this is the effect of pumping cones. In the case at hand, the maximum expected yield to feed a solar pump is modest (4 m3/h are roughly equivalent to 1 l/s). Furthermore, pumping only takes place during a few hours each day, so pumping cones are not expected to grow beyond a few hundred meters. A spatial analysis reveals that only 13 water points in the database are located within 500 m from another, whereas over 70% of the water points are at least one kilometer away from the closest borehole (Figure 11). In other words, interference between boreholes is perceived as a minor issue. It is, however, acknowledged that mutual influence can be important in the limited number of cases in which two boreholes are too close. While the available dataset does not allow for the computation of influence radii, this issue should be easily spotted during the field stage and additional field tests should be performed to prevent unwanted outcomes. Similar considerations apply to water quality. Pumping tests carried out directly by the authors in the study area suggest that changes in water quality are relatively small. This assessment is, however, based on a limited number of field experiences. In this sense, it is important to realize that the outcomes of this research are an initial screening, rather than a replacement for fieldwork. As a general rule, the final decision as to whether or not to replace a hand pump with a solar pump should be based on additional fieldwork.
Finally, introducing solar pumps to a new geographical domain requires the establishment of local capacity for their maintenance and the availability of spare parts. Subsequently, all relevant stakeholders, potentially including the private sector, must assume responsibility for providing the necessary technical and logistical support to maintain the system’s operational status. This can be seen as a major challenge, given the difficulties experienced by a theoretically simple technology—the hand pump—both presently and in the past [9].

4.3. Automated Tools and Database Interpretation

Reference [52] shows the importance of groundwater databases as a means to achieve objectives related to general groundwater status and trends. This pertains to everything related to improving management, supporting hydrogeological science, and protecting groundwater systems and the environment. An advantage in using methods such as the one proposed in these pages is that solid groundwater databases are far from rare in the African context. For example, the German Development Cooperation has supported the Niger Basin Authority through ‘Support to Groundwater Management in the Niger Basin (AGES)’ a joint technical cooperation project between the Niger Basin Authority (NBA) and the German Federal Institute for Geosciences and Natural Resources (BGR) funded by the Federal Ministry for Economic Cooperation and Development (BMZ) [53]. Activities under this project include “collecting and evaluating groundwater data and maps in the Niger Basin to develop a groundwater database as well as a basis for preparing a hydrogeological map of the Niger Basin”. In the Nile river, the Nile Basin Initiative Secretariat has designed and developed the online Groundwater Database and Knowledge Management System (GWDB) for selected transboundary aquifers in the Nile Basin. The GWDB stores raw groundwater data and information/maps on groundwater sources of interest and knowledge generated by several national groundwater projects [54].
In some cases, however, there may be large databases which, notwithstanding high development costs, have not yet been explored or used for the purposes for which they were designed. Take for instance the pumping test information that is available for more than 3000 points distributed throughout southern Madagascar. Despite this wealth of information, the authors are unaware of attempts to make use of these data to underpin groundwater management other than this research.
It is true that large databases can be problematic to use, even with the help of spreadsheets and geographic information systems. To avoid these limitations, [55] proposed a tool to semi-automatic interpretation of borehole logs to determine the hydraulic and textural characteristics of shallow aquifers in Senegal. These authors also demonstrated the importance of setting up a groundwater database with well-organized stratigraphic information in Guinea Bissau [56,57]. In this context, we advocate semi-automated procedures such as the one that has been presented above as (1) a means to speed up the use of all available information as a decision-making tool, and (2) contribute to identify potential problems associated with outdated information and make suitable proposals as to how and why to update it.
Setting up large databases, keeping the information updated and developing tools for groundwater data analysis requires effort and resources. If these databases are used for practical purposes, and if this is done with the collaboration of scientific staff and managers who understand the advantage of a data-driven approach, then local and national administrations will be willing to provide these human, logistic and financial resources to enhance decision-making processes.

5. Conclusions

Based on the outcomes of this work, fitting pre-existing boreholes with solar pumps could improve water access for nearly 60,000 people in disadvantaged communities of southern Madagascar. This might potentially enhance their living conditions while also saving the costs of drilling hundreds of new boreholes in the region. More specifically, there are 82 boreholes that would allow for the installation of a solar pump based on flow rate. About 57% of these are able to yield 2 m3/h, enough to supply a medium village each (500 people), while the others present yields in excess of 4 m3/h.
Sustainability factors should, however, be assessed with care: first, in terms of the available groundwater resources in an area subject to frequent droughts; and second, in terms of the capacity of stakeholders and local institutions to adopt and maintain a new technology.
These results attest to the importance of developing and maintaining groundwater databases, as well as to their potential usefulness in sustaining practical decisions. In recent years, there seems to be a growing interest in setting up groundwater databases across the African continent. While this has been supported by international organizations and national governments, as well as by research institutes and private sector actors, there is still a lack of coordination between all parts. This results in huge amounts of information that is neither properly organized nor accessible for decision makers. Giving value to this information and integrating new data would create powerful tools to deal with the ever-growing challenges of groundwater management, particularly in arid and semi-arid regions. In this context, it is important to make sure that data are not only collected, but also organized and updated; that tools and procedures to enhance interpretation are developed accordingly; and that the technical and institutional capacity to carry out data analysis and make data-driven decisions are strengthened. All these aspects need to be developed together, with medium- to long-term visions. If the strategy is not extended over time, then the results achieved will not be as effective.
Finally, the proposed method must not be seen as a means to make final decisions without giving due consideration to other potentially important factors. Rather, it must be interpreted as an alternative to narrow down the choice of potential locations for the installation of solar pumps based on the wealth of information that exists in regional databases. As it often happens in the field of hydrogeology, expert judgement will be required to decide whether to replace a hand pump with a solar pump, or whether additional tests are required prior to adopting a given course of action.

Author Contributions

Conceptualization, F.F., J.-J.R., V.G.-E., H.O.A.R. and P.M.-S.; methodology, F.F., J.-J.R. and V.G.-E.; software, V.G.-E.; writing—original draft preparation, F.F., J.-J.R., V.G.-E. and P.M.-S.; project administration, P.M.-S. and F.F.; funding acquisition, P.M.-S. and F.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Spain’s Ministry for Science and Innovation (project DEME-ML-2, grant number PID2021-124018OB-I00).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Restrictions apply to the availability of these data. Data were obtained from Bushproof and UNICEF Madagascar.

Acknowledgments

The authors would like to thank UNICEF Madagascar and Bushproof for making available their borehole databases, and all the institutions and staff involved in the Mionjo project (www.mionjo.mg). (Accessed on 25 December 2024).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location of the study area. (a) Madagascar in the context of African countries; (b) Bekily region in Madagascar; (c) boreholes with available pump test information in the Bekily region. Communes are administrative entities akin to municipalities.
Figure 1. Location of the study area. (a) Madagascar in the context of African countries; (b) Bekily region in Madagascar; (c) boreholes with available pump test information in the Bekily region. Communes are administrative entities akin to municipalities.
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Figure 2. Conceptual model of the Authossère and screen position methods based on the estimation of expected drawdown.
Figure 2. Conceptual model of the Authossère and screen position methods based on the estimation of expected drawdown.
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Figure 3. Calculating borehole efficiency for different flow rates based on Jacob’s approach.
Figure 3. Calculating borehole efficiency for different flow rates based on Jacob’s approach.
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Figure 4. Schematic overview of the automated classification procedure.
Figure 4. Schematic overview of the automated classification procedure.
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Figure 5. (a) Spatial distribution of maximum step test yield. (b) Spatial distribution of drawdown tests per number of steps.
Figure 5. (a) Spatial distribution of maximum step test yield. (b) Spatial distribution of drawdown tests per number of steps.
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Figure 6. Pump test results of boreholes that can produce more than 4 m3/h but the maximum yield cannot be estimated. Village Beraketa Centre.
Figure 6. Pump test results of boreholes that can produce more than 4 m3/h but the maximum yield cannot be estimated. Village Beraketa Centre.
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Figure 7. Pump test results of boreholes that can potentially produce 4 m3/h or more, but the available pump test has maximum yield too low for the interpretation in that yield range. Village Antsohamamy.
Figure 7. Pump test results of boreholes that can potentially produce 4 m3/h or more, but the available pump test has maximum yield too low for the interpretation in that yield range. Village Antsohamamy.
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Figure 8. Pump test results of boreholes that can potentially be suitable for solar pumps, but the limited maximum yield used in the step drawdown test is not adequate for a reliable interpretation. Village Ankilimiary bas (commune Ankanarabo Nord).
Figure 8. Pump test results of boreholes that can potentially be suitable for solar pumps, but the limited maximum yield used in the step drawdown test is not adequate for a reliable interpretation. Village Ankilimiary bas (commune Ankanarabo Nord).
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Figure 9. Spatial distribution of boreholes and their suitability for the installation of solar pumps. This information is overlaid with the distribution of geological materials and the drainage network.
Figure 9. Spatial distribution of boreholes and their suitability for the installation of solar pumps. This information is overlaid with the distribution of geological materials and the drainage network.
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Figure 10. Maximum operating flow rate as per the Authossère method.
Figure 10. Maximum operating flow rate as per the Authossère method.
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Figure 11. Minimum distance between each borehole and the closest borehole.
Figure 11. Minimum distance between each borehole and the closest borehole.
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Table 1. Descriptive analysis of the source, number of steps, and maximum test flow rate for the data analyzed in this work.
Table 1. Descriptive analysis of the source, number of steps, and maximum test flow rate for the data analyzed in this work.
SourceNumber of Points
UNICEF24
Bushproof111
Number of stepsNumber of points
1 step43
2 steps32
3 steps57
4 steps3
Max flow rateNumber of points
<1 m3/h42
Between 1 and 2 m3/h25
Between 2 and 4 m3/h50
>4 m3/h18
Table 2. Classification of suitability according to the Authossère method, well screen position, and borehole efficiency. Hmin = height of water column during dry season; Hmax = height of water column during wet season; DLd = dynamic level during dry season; DLw = dynamic level during wet season; FS = depth of first screen.
Table 2. Classification of suitability according to the Authossère method, well screen position, and borehole efficiency. Hmin = height of water column during dry season; Hmax = height of water column during wet season; DLd = dynamic level during dry season; DLw = dynamic level during wet season; FS = depth of first screen.
SuitabilityEfficiency MethodComparison Dynamic Level and Depth of Screen
(Screen Method)		Comparison Drawdown and Height of Static Water Column
(Authossère Method)
Suitable, with high potentialEfficiency at 4 m3/h > 60%DLd at 4 m3/h—FS > 3 mDrawdown at 4 m3/h < 2/3 Hmin
Drawdown at 2 m3/h < 2/3 Hmin
Suitable, with low potentialEfficiency at 4 m3/h < 60%
Efficiency at 2 m3/h > 60%		DLd at 4 m3/h—FS < 3 m
DLd at 2 m3/h—FS > 3 m		Drawdown at 4 m3/h > 2/3 Hmin
Drawdown at 2 m3/h < 2/3 Hmin
Partially suitable (only in wet season)Efficiency at 2 m3/h between 40 and 60%DLd at 2 m3/h—FS < 3 m
DLw at 2 m3/h—FS > 3 m		Drawdown at 2 m3/h >2/3 Hmin
Drawdown at 2 m3/h < 2/3 Hmax
UnsuitableEfficiency at 2 m3/h < 40%DLw at 2 m3/h—FS < 3 mDrawdown at 2 m3/h > 2/3 Hmax
Table 3. Number of points that were found to be suitable, not suitable, and need to be checked regarding the suitability of a solar pump to operate. The average values of the maximum test flow rate and the number of steps are also shown.
Table 3. Number of points that were found to be suitable, not suitable, and need to be checked regarding the suitability of a solar pump to operate. The average values of the maximum test flow rate and the number of steps are also shown.
Suitability for the Installation of Solar PumpsNumber of PointsAverage Max Flow Rate of the Test (m3/h)Average Number of Steps
Suitable823.072.72
Not suitable320.851.22
To be checked211.451.33
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Fussi, F.; Gómez-Escalonilla, V.; Rahobisoa, J.-J.; Ramanantsoa, H.O.A.; Martinez-Santos, P. An Automated Method to Assess the Suitability of Existing Boreholes for Solar-Based Pumping Systems: An Application to Southern Madagascar. Sustainability 2025, 17, 1255. https://doi.org/10.3390/su17031255

AMA Style

Fussi F, Gómez-Escalonilla V, Rahobisoa J-J, Ramanantsoa HOA, Martinez-Santos P. An Automated Method to Assess the Suitability of Existing Boreholes for Solar-Based Pumping Systems: An Application to Southern Madagascar. Sustainability. 2025; 17(3):1255. https://doi.org/10.3390/su17031255

Chicago/Turabian Style

Fussi, Fabio, Víctor Gómez-Escalonilla, Jean-Jacques Rahobisoa, Hariliva Omena Anahy Ramanantsoa, and Pedro Martinez-Santos. 2025. "An Automated Method to Assess the Suitability of Existing Boreholes for Solar-Based Pumping Systems: An Application to Southern Madagascar" Sustainability 17, no. 3: 1255. https://doi.org/10.3390/su17031255

APA Style

Fussi, F., Gómez-Escalonilla, V., Rahobisoa, J.-J., Ramanantsoa, H. O. A., & Martinez-Santos, P. (2025). An Automated Method to Assess the Suitability of Existing Boreholes for Solar-Based Pumping Systems: An Application to Southern Madagascar. Sustainability, 17(3), 1255. https://doi.org/10.3390/su17031255

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