From data to decisions? assessing community-based water monitoring in Tuvalu

Abstract

Small island developing states such as Tuvalu face acute water security challenges due to limited freshwater availability, high climate variability, and contamination risks. This study examines the characteristics and outcomes of a community-based water monitoring (CBWM) scheme conducted between 2022 and 2025 across three of Tuvalu’s outer islands: Nanumea, Nui, and Vaitupu. Drawing on a dataset of 536 water monitoring records from groundwater wells and rainwater storage systems, the study assesses freshwater availability, groundwater salinity, and water quality in the three studied islands. Results from the analyzed CBWM dataset show that availability and quality of freshwater in Nanumea are highly dynamic and closely linked to changes in precipitation. Periods of below-average precipitation were associated with increased groundwater salinity and declining water storage levels. Periods with rainfall above average were associated with lower salinity and improved water availability. The results further show that monitoring activity varied across islands and over time. More consistent sampling was observed in Nanumea, which also benefited from sustained engagement between the supporting project and the local community. The data in this study further supports community reports that in some instances water monitoring data has been used for local decision-making processes. As a result, CBWM can generate valuable data that, in turn, can support local water management in remote and climate-vulnerable environments where data is typically scarce. However, its effectiveness and sustainability depend on appropriately designed incentives, continuous institutional support, and the effective use of data in local decision-making processes.

1 Introduction

Small island developing states face severe, interlinked water security challenges that are intensifying under climate change (Mycoo et al., 2022). Water security is of particular concern for Tuvalu since its low-lying limestone islands and atolls provide no permanent source of fresh surface water (CSIRO, Federation University and Climate Comms, 2024; Government of Tuvalu, 2025). Before the 1970s, groundwater in Tuvalu was historically the main water source including for drinking (Antoniou et al., 2023). More recently and where available and salinity levels permit, groundwater in Tuvalu is used as a secondary, non-potable water source and occasionally (particularly during prolonged droughts) as a source of drinking water (SOPAC, 2007). Although more recent groundwater investigations have provided detailed island-level information on groundwater availability on the islands of Nanumea, Nui and Nukufetau, (Antoniou et al., 2023; Antoniou et al., 2019), the availability and quality of groundwater in Tuvalu’s outer islands remains poorly characterized and unevenly documented. As a result, rainwater harvesting is the primary and often the only source of potable water in Tuvalu (Baarsch and Berg, 2015; CSIRO & Deloitte, 2024).

Due to the low elevation of its islands, Tuvalu’s groundwater is vulnerable to saltwater intrusion. The highest natural elevation of the country is only approximately 6–7 m above mean sea level (Wandres et al., 2024). Climate impacts, such as sea level rise, increasing storm surges, and changing precipitation patterns, influence both the availability and quality of the islands’ thin groundwater lens, and contamination from human and animal waste further degrades water quality (Government of Tuvalu, 2025; Fujita et al., 2013).

This combination of climatic, environmental, anthropogenic, and geological factors and stressors creates a highly fragile freshwater system in Tuvalu. Continuous monitoring of water quantity and quality is therefore critical for various reasons. It can help to identify emerging risks such as saline intrusion and microbial contamination and it can track temporal variations in water availability. Once data is available, it can then support evidence-based local decision-making for water allocation, abstraction and management, and inform emergency preparedness and response procedures during emergency conditions such as droughts.

To improve data availability for groundwater management while ensuring sustained monitoring through local ownership, a community-based water monitoring (CBWM) scheme was established under the Managing Coastal Aquifers in Selected Pacific SIDS (MCAP) project in Tuvalu. The project aimed to systematically monitor groundwater and rainwater resources across three of the country’s outer islands (Nanumea, Nui, and Vaitupu) (GEF, 2020). Implemented between 2020 and 2025, the MCAP project established CBWM schemes and supported regular field sampling, community engagement, and capacity-building to generate data on water availability, salinity, and the risk of water contamination. Community members were trained to conduct surveys of wells, rainwater tanks, and communal cisterns, and how to carry out basic water quality testing (SPC, 2024).

Alongside remote sensing and modeling, CBWM and other citizen-science approaches are increasingly recognized as effective and scalable responses to growing water security challenges. Such mechanisms can help address critical data gaps by enabling data collection in contexts where conventional monitoring is limited. They also build local awareness and can empower communities to make informed decisions about the management of their water resources (e.g., Woods, 2025; Quinlivan, et al., 2020; UN Water, 2018; Lowry and Fienen, 2013). Evidence suggests that while CBWM holds strong potential to fill data gaps, their effectiveness and sustainability depend on key design factors, including the attributes of participating citizens and supporting institutions as well as the interaction between the two (Capdevila et al., 2020). These findings on success factors of CBWM are particularly relevant for remote islands, which are characterized by limited technical capacity, highly decentralized water systems, and limited existence of, and opportunities for, conventional monitoring systems. As a result, CBWM may represent a promising, and in some instances possibly the only, viable pathway to obtain continuous water data for remote island contexts. In addition, by linking monitoring activities directly to community-level decision-making, CBWM can strengthen local resilience and support more adaptive and responsive water management practices.

This paper presents the outcomes of the CBWM scheme in Tuvalu, drawing on a dataset (2022–2025) of groundwater and rainwater storage monitoring records. It further assesses the extent to which the assessed scheme is aligned with the key CBWM success factors identified in the literature. The paper further addresses the limited empirical evidence of CBWM schemes and general water data available for remote atoll and small island contexts. As such, the study evaluates both water security conditions in remote islands of Tuvalu revealed through the data and the effectiveness of the CBWM approach itself. In doing so, the paper identifies key strengths, limitations, and areas for improvement of CBWM in remote island contexts and derives lessons for the design and implementation of future CBWM schemes in similarly resource-constrained and geographically dispersed settings.

2 Materials and methods

This study assesses a CBWM scheme in Tuvalu, a small island developing state in the central Pacific Ocean made up of six low-lying true coral atolls and three reef islands. The island group is spread between latitudes 5° and 10° south and longitudes 176° and 180°, just west of the International Date Line (SPC, 2026). The CBWM scheme assessed in this study was established in 2022 on three of Tuvalu’s outer islands: Nanumea, Nui, and Vaitupu. These three islands are located at varying distances from Tuvalu’s capital, Funafuti: Nanumea, Tuvalu’s northernmost island, lies approximately 460 km from Funafuti; Nui is located around 200 km to the north of Funafuti; and Vaitupu is approximately 130 km to the northwest of Funafuti. The three islands are spread across a vast ocean area and are accessible only by infrequent inter-island boat transport. Travel times to the islands from Funafuti range from hours to days. Funafuti itself is situated in a remote part of the Pacific Ocean, approximately 1,000 km north of Fiji and over 3,000 km from the closest larger continental landmasses (Australia).

The CBWM scheme was implemented through collaboration between the Pacific Community (SPC), the Government of Tuvalu, and local communities. Community monitoring teams were established on each island, comprising local volunteers and representatives from community institutions. Participants were trained through structured workshops to conduct field surveys of water resources and basic water quality testing. Government stakeholders were involved in coordination and oversight, supporting the integration of monitoring activities into local water management processes. Monitoring was further supported through periodic technical follow-up and project engagement.

Under the CBWM scheme, community members conducted regular field surveys of water resources (groundwater wells, rainwater tanks, and communal cisterns). Monitoring and testing activities were carried out at irregular but repeated intervals between 2022 and 2025, depending on community engagement, training activities, and logistical constraints. Each monitoring record corresponds to a single observation of a water source at a given point in time. The monitoring included three main components, (i) groundwater assessment, including well characteristics, depth to water table and groundwater salinity, (ii) rainwater system assessment, including characteristics of rainwater tanks and cisterns and estimation of available storage, expressed as volume or percentage of total capacity, and (iii) water quality assessment, including bacteriological analysis using E. coli (Escherichia coli) as an indicator of fecal contamination in drinking water.

This study’s underlying dataset consists of CBWM survey records collected using the KoboToolbox. During the implementation of the CBWM, the survey was revised in May 2023. At that time, a separate category for cisterns was introduced to the survey, which had previously been included under communal rainwater tanks. KoboToolbox automatically stored the two survey versions in parallel. As such, the dataset was restructured, and the results from the two surveys were merged to enable comparison of data over time and across asset types.

The initial dataset comprised 575 monitoring records. Records from the other islands were removed: Funafuti (28), Niulakita (1), Niutao (4), and Nanumaga (4). This resulted in a final dataset of 536 monitoring records across the three study islands of Nanumea, Nui, and Vaitupu (Table 1).

Sampling periods varied across islands, with the longest continuous record available for Nanumea, spanning from 21 June 2022 to 16 May 2025. Differences in sampling frequency reflect varying levels of engagement, accessibility, and project support across islands. The monitoring focused on two main types of water resources surveys: (i) groundwater resources assessment (well surveying) and (ii) rainwater harvesting system assessments (rainwater tanks and cisterns). In addition, monitoring also included water quality sampling. A total of 238 water quality samples were collected, with the majority from Nanumea (105), followed by Vaitupu (70) and Nui (63). Most water quality samples were taken from communal cisterns, with a smaller number from rainwater tanks and groundwater wells (Table 2).

Data analysis focused on identifying temporal and spatial variations in water availability, groundwater salinity, and water quality. Groundwater salinity was analyzed using electrical conductivity measurements, and only samples with clearly reported units were included to ensure consistency. Rainwater availability was analyzed using storage levels expressed as a percentage of total capacity. Water quality analysis was based on E. coli concentrations (Most Probable Number per 100 ml), which were used as an indicator of fecal contamination risk.

3 Results

3.1 Microbiological water quality

Across all three islands, the results indicate microbiological contamination of drinking water sources, while only a lower proportion of samples fall within safe categories. Escherichia coli concentrations were interpreted using the Aquagenx CBT MPN Table where MPN of E. coli per 100 mL is estimated from the combination of positive (blue color) and negative (no blue color) compartments in the test kit. The CBT MPN Table is based on World Health Organization’s Guidelines for Drinking Water Quality (4th Edition), and values close to 0 MP N/100 ml indicate low contamination risk, values between 1.0 and 9.6 represent intermediate risk, values of 13.6, 17.1, 32.6 and 48.3 represent high risk, and values above 100 are considered unsafe (Aquagenx, 2013). According to the monitoring data, microbiological contamination of drinking water sources is widespread in all three islands and across multiple asset types (Figure 1). Nui stands out with notably higher average values. Only 16% of all water quality samples in Nui were of low/risk safe (Figure 1B).

FIGURE 1

Communal cisterns, which represent the primary source of drinking water, show average contamination levels that are considered as high risk/probably unsafe across all three islands. Although based on a small sample size, water quality results from wells consistently indicate high levels of fecal contamination (Table 2). All water quality samples from wells were collected between May 2022 and May 2023, during the initial phase of the monitoring campaign. Based on these early findings of high contamination and widespread fecal contamination in wells, the monitoring teams decided to shift the focus of subsequent monitoring efforts away from groundwater wells towards cisterns.

3.2 Groundwater salinity

Groundwater salinity was analyzed using electrical conductivity measurements (µS/cm) collected during the CBWM from wells on Nanumea. To ensure consistency and comparability of the results, only samples with clearly reported measurement units were included in the dataset. Due to limited sample sizes for Nui and Vaitupu, the analysis was restricted to Nanumea.

According to the data, groundwater salinity in Nanumea varies across locations and over time. The median electrical conductivity of the observed wells in Nanumea is approximately 2,388.5 μS/cm. However, several outliers exceed 20,000 μS/cm (Figure 2).

FIGURE 2

A temporal analysis of groundwater salinity was conducted to examine how salinity levels changed over time in specific locations, using electrical conductivity measurements from three selected wells located in different parts of Nanumea: a well located in the north-west (Well 1), a well located in the south (Well 2), and a well located in the north-east near the airfield currently under construction (Well 3). These wells were selected as they were continuously monitored from August 2023 to February 2025. The three selected wells also represent adequate spatial variation across the island.

Over the analyzed period, there was substantial temporal variation in groundwater salinity across the three monitored wells. In August and September 2023, salinity levels were high in the south (Well 2) and north-west (Well 1). The wells reached values over 20,000 μS/cm (Figure 3). High salinity coincides with below-average precipitation in the preceding months (Figure 4), which could mean that reduced rainfall was associated with lower freshwater recharge and increased salinity levels. According to the Tuvalu Meteorological Service (TMS), both the period from April to June 2023 and July to September 2023 observed below-average precipitation relative to their historical median (TMS, 2026).

FIGURE 3

FIGURE 4

Located near the airport, Well 3 showed lower salinity levels than the other two wells (although values in 2023 remained elevated relative to its own later measurements). These findings are particularly relevant as Well 3 remains in active household use, primarily for non-potable purposes. This well is also closely located to the area of a groundwater infiltration gallery for groundwater abstraction, currently under construction.

Salinity levels declined in all three wells from September 2023 onwards, reaching much lower values by mid-2024. This reduction in salinity aligns with a period of above-average precipitation. Several quarters of this period rank among the wettest conditions in historical observation records (TMS, 2026). This indicates sustained and increased rainfall could have contributed to aquifer recharge and reduced groundwater salinity levels in the monitored wells over the observed period.

Compared to the other two wells, the north-east well (Well 3) had lower salinity levels over the entire monitoring period. Salinity levels increased again towards the end of the observation period, which was aligned to a return to below-average precipitation conditions (Figure 4). However, salinity levels were significantly lower than the initial values observed in mid-2023. Overall, results show that variations in precipitation patterns over the observed period appear to be associated with changes in salinity levels. Furthermore, groundwater salinity on Nanumea seemed to significantly differ among (relatively close) locations and over time. During and after periods of low precipitation, groundwater sources appear highly vulnerable to a rapid increase in salinity levels. At the same time, wet conditions with a lot of rainfall seemed to contribute to the recovery of the freshwater lens relatively quickly, over a couple of months.

3.3 Water resource monitoring

Data from the monitoring campaign also allows to analyze the temporal variation in stored rainwater levels, expressed as a percentage of total capacity in community cisterns and rainwater tanks. Due to limited sampling activity in Nui and Vaitupu, also this analysis was restricted to Nanumea. During the first half of the observation period, the data shows relatively high storage levels in Nanumea. Most cisterns were at or near full capacity between February and July 2024 (Figure 5). This aligns with the above-average precipitation observed during the same period (Figure 4).

FIGURE 5

From August 2024, storage levels began to decline across most cisterns, probably due to reduced recharge relative to water use. The decline became more pronounced towards the end of 2024. Several cisterns reached critically low levels in December 2024, in some cases dropping to around 30%–40% of capacity. This decline in storage levels corresponds with a period of below-average precipitation in the last quarter of 2024 (Figure 4). Only 49.6 mm of rainfall was recorded in November 2024, significantly lower than the historical median for rainfall in November (148.3 mm) over the period 1943–2023 (TMS, 2026).

With a return to wetter conditions and an increase in precipitation, cistern storage levels also increase in January 2025 (although the increase is uneven across cisterns). Some cisterns, such as Cistern 1, return to full capacity by February 2025, while others remain below their earlier levels (Figure 5).

Comparing the data on water storage levels with water quality measurements can reveal whether the local community considered the monitoring data when taking water management decisions. In December 2024, Cistern 5 still contained approximately 80% of its storage capacity. At the same time, the storage capacity of the other five analyzed cisterns ranged between 30% and 59% (Figure 5).

In October 2024, Cistern 5 also showed the highest risk of potential E. coli contamination among the group of analyzed cisterns (Table 3). This may indicate a result of data-informed management of water resources by the local community, where adjusting the use of available cisterns was based on water quality information obtained through the CBWM. During a community consultation in 2024, it was reported that water quality results were reviewed before deciding which communal cisterns should remain in use: “We assess water quantity and quality in community in cisterns, testing for E. coli contamination. Cisterns with high contamination are temporarily out of use” (Community Representative of Nanumea, SPC, 2024).

3.4 Sampling activity

Over the monitoring period, sampling activity in Nanumea varied (Figure 6). Following the initial rollout and training phase of the CBWM in June 2022, sampling activity declined between August 2022 and June 2023. This means that regular monitoring paused after the initial campaign phase. Activity increased again in August and September 2023, due to targeted training and sampling efforts which were associated with the construction of a groundwater infiltration gallery. From early 2024 onwards, sampling activity became more consistent, with regular monitoring of approximately 20 assets. Sampling in Nanumea was most frequent and regular during the final quarter of 2024. The same quarter was also a period of lower-than-average precipitation (Figure 4). Put differently, community monitoring efforts increased during drier weather, when less water was available.

FIGURE 6

Sampling in Nui (March 2023 – November 2024) and Vaitupu (May 2022 – October 2024) was conducted less frequently compared to Nanumea. Only seven sampling campaigns were carried out over the entire period in both islands, and often several months lay between sampling events. This suggests that monitoring activities in Nui and Vaitupu were mainly undertaken during training activities or visits by project staff, rather than being carried out autonomously by community members. This also indicates that CBWM did not fully establish itself in these two islands.

4 Discussion

4.1 Key findings

The results of this study show that the implementation and performance of the CBWM scheme in Tuvalu varied considerably across islands and over time. While initial training enabled communities to carry out monitoring activities, the decline in sampling activity observed in all three islands indicates that such efforts are difficult to maintain without continued interaction, reinforcement, and perceived relevance. Sampling activity appears to have been responsive to both institutional support and community needs. This is most evident in Nanumea, where sustained engagement and continued support (e.g., the construction of an infiltration gallery) resulted in more regular monitoring compared to Nui and Vaitupu. In addition, sampling intensity in Nanumea increased during periods of reduced rainfall and increased drought risk. This indicates that perceived risks to water scarcity mobilized monitoring efforts by the community. This further suggests that CBWM may be more effective and sustainable when appropriate support structures and local engagement are in place.

The data in this study further supports community reports from Nanumea that CBWM data is integrated into local decision-making processes (SPC, 2024). A cistern on Nanumea with higher contamination levels showed lower abstraction compared to other cisterns with relatively lower contamination levels. Such cases highlight the practical value of CBWM in contexts where water supply is limited but, at the same time, at risk of contamination.

The data also show a link between rainfall patterns, groundwater salinity, and rainwater storage. This backs the argument for the importance of continuous water monitoring. Periods of below-average precipitation were associated with elevated groundwater salinity and declining storage levels. Above-average rainfall was associated with lower groundwater salinity and recovering water storage levels. These dynamics unfolded relatively quickly in both directions, over a couple of months. The results underline the sensitivity of atoll freshwater systems to short-term climatic variability and demonstrate the value of combining environmental data with community-based observations to support timely decision-making.

The findings from this study confirm previous findings in the literature (e.g., Capdevila et al., 2020), suggesting that the effectiveness of CBWM in Tuvalu is closely linked to three interrelated factors: (i) sustained community engagement, (ii) the presence of supporting structures such as training and coordination, and (iii) the practical use of data in local decision-making. Where these elements aligned, monitoring was more consistent (e.g., in Nanumea in the second half of the CBWM). Where these factors were weaker or absent, monitoring activity declined or failed to establish itself. This indicates that CBWM systems are not self-sustaining under any condition, but may require continuous external support and integration into local governance processes.

4.2 Implications for the design and implementation of CBWM schemes in islands

The results also allow us to draw implications for the design and implementation of CBWM schemes in similar contexts. First, if continuous engagement is expected, appropriate incentive structures may be needed to sustain community participation over time. Such incentives could include linking participation in monitoring with targeted project support or in-kind benefits (e.g., materials, equipment, or priority access to water-related services). This was the case for Nanumea, which benefited from continued engagement and water infrastructure support and also was the most active case to establish the CBWM. Participation in monitoring can be rewarded with timely and targeted support that addresses gaps identified through the CBWM. Second, the integration of remote or automated monitoring technologies could complement community-based efforts by providing more continuous data and reducing the burden on local participants. Third, ongoing technical support and assistance with data interpretation seem to be critical as they help ensure that monitoring results are understood by the local community and, subsequently, effectively translated into action. Finally, the establishment of dedicated monitoring infrastructure, such as boreholes in areas where groundwater is abstracted, could improve the accuracy and reliability of groundwater assessments.

4.3 Limitations

This study provides insights into the implementation and outcomes of a CBWM scheme in Tuvalu. However, several limitations of this study should be acknowledged. First, the number of monitoring records varies between the three islands, and Nanumea has more monitoring records than Nui and Vaitupu, reflecting differences in engagement and monitoring continuity. However, this also limits the comparability of results across islands and may bias the analysis toward the more active case.

Second, temporal coverage of the analyzed water data varies between water sources and parameters. While groundwater salinity and precipitation data in Nanumea allowed for a more detailed temporal analysis, water quality measurements took place more sporadically and were concentrated in specific assets (primarily communal cisterns). As a result, the assessment of contamination patterns is indicative rather than comprehensive.

Third, while the study identifies relationships between rainfall variability, salinity, and water availability, it does not use hydrological modeling or further experiments to establish causal relationships. However, this is also not the primary objective of the study. Rather, the study aims to demonstrate the type and value of data that can be generated through community-based monitoring and how it can be useful for local water management. It should be noted, however, that the link between precipitation patterns and groundwater salinity in atolls found in this study is consistent with established findings in the literature (e.g., Werner et al., 2017; Bailey et al., 2010).

4.4 Conclusion

This study analyzes the data and the characteristics of a CBWM scheme in Tuvalu. The results show that CBWM can provide critical insights into water availability, salinity, and contamination. This, in turn, can help address key information gaps in data-scarce settings and support more informed and adaptive water management at the community level in vulnerable atoll environments.

Monitoring activity in the assessed CBWM was not uniform but rather linked to both community engagement and environmental conditions. Where engagement between the supporting institutions and communities was continuous, monitoring was more regular and responsive to periods of increased water stress, including drought risk. In contrast, limited engagement and follow-up support resulted in reduced monitoring activity. This highlights the importance of continuous support, interaction between communities and supporting institutions to maintain monitoring systems over time.

This study also shows that CBWM data can inform local water governance and management. The case of Nanumea, where a cistern with higher E. coli contamination risk showed lower abstraction levels, illustrates how data generated through CBWM can inform water management decisions and help reduce exposure to contaminated water sources. In turn, this demonstrates that CBWM can move beyond mere data collection and actively contribute to strengthened local water governance and resilience.

At the same time, the findings underline that CBWM is not necessarily a self-sustaining solution in all contexts. As we show in this study, its effectiveness depends on a range of factors including appropriately designed incentives, continuous institutional support, and the ability to understand and use data effectively in local decision-making processes. Future efforts should therefore focus on strengthening feedback mechanisms between data collection and management actions, designing appropriate incentives for monitoring, complementing community-based monitoring with technological solutions, and ensuring that adequate resources are available to both monitor and respond to identified water risks.

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