The study involved 773 participants in a nationwide online survey, with a subsample of 191 completing a follow-up survey one month later for test-retest analysis. Investigators examined the factor structure through exploratory and confirmatory factor analyses, randomly dividing the main sample into two subsamples for cross-validation. They also assessed measurement invariance across sex and age groups, internal consistency, test-retest reliability, and convergent and discriminant validity. The abstract describes this as a psychometric validation study, not an intervention trial, so the reported results concern measurement properties rather than the effects of a disaster-preparedness program.

Exploratory and confirmatory analyses supported a three-factor structure covering knowledge and management of the external situational environment, management of one’s emotional and psychological response, and management of one’s social environment. The confirmatory factor model showed adequate fit, with a comparative fit index of 0.942 and a root mean square error of approximation of 0.062. The total PPDTS-J23 score had high internal consistency, with alpha equal to 0.956. Alpha values for the three subscales were 0.919, 0.936 and 0.827, while measurement invariance was supported across sex and age groups. Convergent validity was supported, but discriminant validity was only partially supported.

Test-retest reliability was acceptable for the total score, with an intraclass correlation coefficient of 0.780 at the one-month follow-up. The coefficient for the social-environment subscale was lower, at 0.657, below the criterion adopted by the researchers. These findings indicate that the PPDTS-J23 can serve as a reliable measure of psychological preparedness for hydro-meteorological hazards in Japan, while the partially supported discriminant validity and lower reliability for one subscale bound the conclusions. The abstract states that the scale may be used to evaluate disaster-education program outcomes, characterize groups’ preparedness profiles, inform community-based disaster-risk reduction and support mental-health planning. Because the available report is the abstract of an accepted article that remains subject to further edits, it does not provide the full methods or results needed to assess those proposed applications directly.

Subject of Research: Psychometric validation of a Japanese scale for psychological preparedness against hydro-meteorological hazards

Article Title: Development and validation of the Japanese version of the psychological preparedness for disaster threat scale

Article References: Kubo, T., Takamoto, M., Suzuki, M., Takenouchi, K., & Sadamitsu, C. (2026). Development and validation of the Japanese version of the psychological preparedness for disaster threat scale. BMC Psychology. https://doi.org/10.1186/s40359-026-05639-3

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05639-3

Keywords: psychological preparedness, disaster risk, Japan, psychometric validation, survey research, typhoons, flooding, severe storms, measurement invariance, disaster education, Development, validation

The Miljašić jaruga is one of the most important watercourses in Zadar County, in the Dalmatian hinterland of the eastern Adriatic. The stream runs approximately 16 kilometers from an altitude of about 88 meters above sea level down to the sea roughly 900 meters northeast of the old town of Nin, draining a topographic catchment of approximately 191 square kilometers. Its lowermost 1.5 kilometers form a genuine estuary, directly influenced by the sea. Like most Croatian coastal streams, it flows through classic Dinaric karst terrain, a landscape of Eocene limestone, marl, and flysch where surface and underground waters interact rapidly. The hydrological regime is strongly seasonal: for most of the year, catchment waters flow out to sea, but in the dry summer months the bed is largely without outflow. It is precisely this pattern, a long dry period followed by extreme precipitation, that generates the sudden water-level surges and flash floods characteristic of karst regions.

The 2017 event was textbook flash flooding. Rain gauges and meteorological stations across the catchment recorded three-day totals exceeding 300 millimeters at Zadar and Zadar Airport, with the maximum daily value of 284 millimeters falling on September 11 at Zadar, the second-highest daily record in the station’s history after the 357 millimeters of September 10, 1986. Curiously, the rain gauge at Nin itself recorded almost negligible amounts on those days, showing how localized such storms can be. The rainfall activated violent torrential runoff across the entire 191-square-kilometer basin. At the Poljaki station on the upper stream, water levels began rising at 6 a.m. and climbed 357 centimeters within seven hours, peaking at 367 centimeters at noon. Downstream at Boljkovac, the peak of 353 centimeters arrived at 3 p.m., a typical flash-flood hydrograph shape with steep rise gradients of up to 121 millimeters per hour.

The discharge estimates are extraordinary for a stream whose average annual flow at Boljkovac is just 1 cubic meter per second. The extrapolated discharge curve of the Boljkovac station put the 2017 flood maximum at an estimated 112 cubic meters per second, with a total flood volume of approximately 10.6 million cubic meters. Upstream at Poljaki, the maximum was 91 cubic meters per second and the volume about 7.7 million cubic meters, while the Bokanjačko blato drainage tunnel, which diverts water from an indirect 59-square-kilometer sub-catchment into the stream through a 2-kilometer hydrotechnical tunnel, contributed 1.8 million cubic meters with a peak of 22.6 cubic meters per second. The time lag between the rainfall peak at 8 a.m. and the discharge peaks was four hours at Poljaki and seven hours at Boljkovac. The researchers caution that flows for such extreme levels are based on extrapolated rating curves and may carry relatively large errors, so the official maxima should be treated as estimates. Even so, they capture the order of magnitude of rare hydrological phenomena in this karst catchment.

The flood’s consequences were severe. Floodwater overtopped the embankment built along the stream bed on the eastern side of the Nin salt pan, damaging it along nearly its entire 700-meter length and completely destroying a 50-meter section. Water spilled laterally over the embankment, across the salt pan basin, and along the abandoned old river bed toward the town center. All the salt works pools were flooded and contaminated by torrential water, inflicting the greatest economic damage. Two historically valuable bridges in Nin were significantly damaged, their partial collapse aggravated by reduced flow capacity from sea-level rise since they were built. Roads, beaches, and numerous residential and commercial buildings were also hit. The salt exploitation at Nin dates back more than 1,500 years, and the modern salt works established in the mid-twentieth century cover 55 hectares, producing excellent-quality salt from seawater, sun, and wind in a chain of shallow pools.

To understand how rare the 2017 flood actually was, the team turned to flood frequency analysis at the Boljkovac hydrological station, comparing hydrological series of 26 and 27 years using three theoretical distributions: normal, log-normal, and Gamma. They deliberately analyzed water levels rather than discharges, because annual maximum discharges are obtained by extrapolating the rating curve, whereas water levels are continuously recorded by limnigraph and are therefore more reliable input data. The agreement between empirical and theoretical distributions was tested with the Kolmogorov–Smirnov test, and all three distributions proved statistically acceptable, with the Gamma distribution showing the best fit. But the calculated design levels diverged sharply. The 2017 flood level of 353 centimeters came out with a return period greater than 500 years under the normal distribution, roughly 500 years under the Gamma distribution, and slightly less than 200 years under the log-normal distribution.

The variability grew worse at longer return periods and, strikingly, hinged on a single data point. Comparing the 27-year series, which includes the 2017 flood, with the 26-year series that excludes it, the estimated 100-year water levels differed by 39 to 60 centimeters depending on the distribution. Translated into discharges through the Boljkovac rating curve, the 100-year high-water flow ranged from 79 cubic meters per second under the normal distribution to 101 cubic meters per second under the log-normal distribution, a difference of roughly 20 percent. Excluding the 2017 event dropped the 100-year flows to between 60 and 85 cubic meters per second, a decrease of 16 to 29 percent, even though the two input series differed by only one term. Adopting the Gamma distribution as the most relevant, the team settled on characteristic flows of 67, 81, and 92 cubic meters per second for return periods of 20, 50, and 100 years, and characteristic levels of 252, 284, and 308 centimeters for the same periods.

For engineering practice, these numbers matter enormously, because they directly determine how flood defense structures are sized, including the height of embankments protecting populations along rivers and estuaries. After the 2017 flood, all damage to the existing embankment was repaired and a new clay embankment was constructed on the destroyed section, with a projected crown width of 2.5 meters and an adopted crown height of 3.0 meters above sea level, calculated to accommodate a 100-year high-water event. Yet all three distributions indicate that the 2017 flood had a return period significantly longer than 100 years. The authors note that reconstruction or construction of new flood defense facilities in rural or smaller urban areas is commonly designed for return periods of up to 100 years, and that experience from Dalmatian catchments and the current issue of climate change suggest extreme events are occurring more frequently and with greater intensity than before.

Geographically, the study also underscores why Croatian estuaries are so vulnerable to fluvial flooding. In the Adriatic, fluvial flooding dominates owing to strong orographic influence: mountain massifs higher than 1,000 meters, running northwest-southeast along the Dinaric coast, sit in the immediate vicinity of the sea and squeeze intense short-term precipitation out of passing weather systems. Meanwhile, the sea’s influence as the downstream boundary is comparatively weak, because tidal amplitudes rarely exceed 40 centimeters in the southern Adriatic and reach about 1 meter in the north. Rivers therefore exert the dominant influence on Croatian estuaries, and combinations of high sea levels and intense basin precipitation can still produce fluvio-tidal floods that raise estuary water levels further. Rising sea levels and intensifying extreme climatic conditions are expected to increase inundation hazards in estuaries, and the authors argue that future research should consider multivariate flood frequency analysis for estimating coastal-estuarine flooding risks, rather than the classic univariate approach applied here because the 2017 flood was caused exclusively by inflow from the basin.

The team’s recommendations reach beyond the embankment. They propose catchment-wide water management, including the construction of retention basins and barriers to calm flows and prevent sedimentation, and note that a retention basin called Rašinovac is planned for the Miljašić jaruga, approximately 3.2 kilometers upstream from the river mouth. High-quality catchment management, they stress, requires engagement across several professions, from spatial planning and climatology to hydrology. The broader lesson is methodological: the procedure for determining relevant hydrological quantities is complex and ambiguous, and continuous validation with the widest possible analysis of all available climatic, hydrological, geological, and land-use parameters is required to quantify runoff processes as precisely as possible. Hydrological bases used for designing hydrotechnical systems should be updated and validated as frequently as possible, especially under obvious climatic variation. For the residents of Nin, whose town sits on the alluvium of a stream that can rise three and a half meters in a single afternoon, that statistical humility is not an academic nicety but the difference between a defense system that holds and one that fails when the next historic storm arrives.

Subject of Research: Flash flood hydrology and flood frequency analysis of the Miljašić jaruga estuary in Nin, Croatia

Article Title: Estuary fluvial flooding: the example of the watercourse Miljašić jaruga in the town of Nin (Croatia)

Article References: Ljubenkov, I., Oskoruš, D., Rubinić, J., Peša, I., & Papić, J. (2024). Estuary fluvial flooding: the example of the watercourse Miljašić jaruga in the town of Nin (Croatia). Estuarine Management and Technologies, 1(1), 19-37. https://doi.org/10.3897/emt.1.120413

Image Credits: AI Generated

DOI: 10.3897/emt.1.120413

Keywords: flash flood, estuary flooding, karst hydrology, Croatia, flood frequency analysis, climate change, Zadar, Nin salt works, Estuary, fluvial, flooding, example

Scientists led by Carla de Souza Farias of Brazil’s National Institute for Amazonian Research set out to answer a deceptively simple question: does the mere presence of a city in the central Amazon induce more extreme precipitation? Previous work on Manaus had examined single storm events, leaving open whether the urban effect was a one-off curiosity or a robust, repeatable pattern. To settle the matter, the team assembled a decade of observations from 2010 to 2020 and identified 45 extreme precipitation events that appeared in two independent datasets: the IMERG satellite rainfall product and the ERA5 atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts.

The screening was deliberately strict. Of the roughly 177 extreme events flagged by IMERG and 176 by ERA5, only 45 were coincident in both products. This filtering matters because satellite grids and reanalyses often disagree on the exact timing and location of localized convective storms in the Amazon, and the researchers wanted simulations initialized with physically consistent conditions. Extreme days were defined as those exceeding the 97.5th percentile of daily rainfall, and the events clustered in the rainy season from November to May, with February and June showing the highest monthly counts.

For each of the 45 events, the team ran paired simulations with the Weather Research and Forecasting model, or WRF, coupled to the Single Layer Urban Canopy Model. In the urban experiment, Manaus was represented with three district classes: industrial and commercial zones, low-intensity residential areas, and high-intensity residential neighborhoods, with parameters tuned using local street widths, roof dimensions, and census-based population density. In the control experiment, the entire urban footprint was replaced with forest. Ninety simulations in total, each 60 hours long, allowed the researchers to compare the same storms over the same 427 square kilometers with and without the city.

The verdict was striking. In 65 percent of the events, total accumulated rainfall was higher with the city present, and in the urban center the average increase reached 16.8 percent. Hourly rainfall intensity told an even sharper story: about 79.2 percent of hourly values in the urban run exceeded those of the forested control, and the maximum hourly precipitation intensity rose by up to 50 percent. The urban scenario also produced longer-lived storms, with the 90th percentile of event duration reaching 19 hours compared with 16.6 hours without the city, suggesting that urban forcing helps sustain convection once it begins.

The mechanism unfolds in three linked steps. First, the city heats up. Asphalt, concrete, and other high-thermal-inertia materials raised the simulated surface temperature by as much as 2.9 degrees Celsius at midday relative to the forested scenario, with air temperature at two meters rising by about 0.6 to 0.7 degrees Celsius. This warming acts as a thermal trigger: the anomalous surface heating peaks around noon, and the largest precipitation intensification follows in the afternoon between 14:00 and 17:00 local time, exactly the window in which the urban heat island of Manaus has been observed to peak in field measurements.

Second, the heated boundary layer drives the atmosphere upward. The researchers found a statistically significant positive correlation between the precipitation difference and vertical wind speed at the 800 hectopascal level, in the middle troposphere, with a correlation coefficient of 0.39 and a p-value of 0.008. Stronger updrafts over the city lift warm, unstable air toward the level where deep convective clouds form. Third, and perhaps most surprising given the setting, the city imports its own moisture. Although near-surface humidity was actually lower over the urban area than over the forest, because trees pump water into the air through evapotranspiration, specific humidity at 800 hectopascals showed a significant positive correlation with the precipitation increase. The interpretation is that urban heating and the rough, friction-generating canopy converge moist air laterally from the surrounding forest and rivers, drawing it into the urban core where it fuels towering convective cells.

The spatial fingerprint of this process is unmistakable. When the domain was divided into nine geographic sectors, the central quadrant coinciding with the urban area recorded the highest accumulated rainfall, 1,136.1 millimeters across the 45 events, and captured the maximum in 11 cases, or 24.4 percent of the total. The southwest sector followed with 1,101.3 millimeters and nine events, consistent with the prevailing northeast-to-southwest flow that advects storms initiated over the city downwind. In the forested control run, by contrast, the precipitation maxima shifted to the peripheral southeast and east sectors, and the central sector dropped to 972.6 millimeters with only five winning cases. In effect, the city traps and concentrates rainfall that would otherwise be distributed over forest and rivers.

The findings place Manaus within a growing global picture. A 2024 analysis of more than 1,000 cities found that over 60 percent of urban areas act as so-called urban wet islands, where precipitation exceeds that of surrounding rural areas, a phenomenon that has roughly doubled in magnitude over the past two decades. Yet the Amazonian case is distinctive because of its setting: the city sits between the Negro and Solimões rivers, embedded in an atmosphere so humid that near-surface specific humidity exceeds 18 grams per kilogram even during extremes. That abundance of moisture means the urban heat island does not dry out storms, as it can in arid cities such as Phoenix, but instead supercharges them, converting a modest thermal anomaly into a deep convective engine fed by the surrounding rainforest.

The practical implications are sobering. Manaus already suffers recurring flash floods and landslides, aggravated by rapid and often unplanned growth on highly impermeable ground. If urbanization reliably intensifies the heaviest rainfall by double-digit percentages, then the city’s own expansion is compounding its flood risk at precisely the moment climate change is loading the atmosphere with more water vapor. The authors note that their controlled experiments deliberately excluded anthropogenic heat emissions and urban aerosols, both of which could add further complexity, and they call for multi-layer canopy models and coupled chemistry simulations in future work. For now, the message for Amazonian cities is clear: as the forest gives way to pavement, the storms above it grow heavier, and the water that falls has nowhere to go but the streets.

Subject of Research: Urbanization effects on extreme precipitation in the central Amazon city of Manaus

Article Title: Does the urban presence of a city in the central Amazon induce more extreme precipitation?

Article References: de Souza Farias, C., Candido, L. A., de Melo Monte, M. J., Buscioli Capistrano, V., Andreoli, R. V., Holanda Hall, D., de Jesus Machado, J., & Quaresmas Dias-Júnior, C. (2026). Does the urban presence of a city in the central Amazon induce more extreme precipitation?. Theoretical and Applied Climatology, 157(11), Article 722. https://doi.org/10.1007/s00704-026-06646-5

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06646-5

Keywords: Manaus, Amazon, extreme precipitation, urban heat island, WRF model, convection, urbanization, flooding, tropical meteorology, moisture convergence, land-use change, climate modeling

The research, conducted by Francisco Proença Garcia, Lucie Calléja and Raquel Duque at the Instituto de Estudos Políticos of the Universidade Católica Portuguesa, examines how regional organisations can act as peacebuilders in climate-related conflicts, using the African Union as its central case. The authors frame climate change not as a direct trigger of war but as a threat multiplier, a term borrowed from security analysis that describes how environmental stress interacts with poverty, inequality and weak institutions to raise the risk of instability. Their findings arrive at a moment when the climate-security debate is intensifying across Africa, a continent that spans the latitudes of the Tropics of Cancer and Capricorn and faces heatwaves, droughts, floods and storms with increasing frequency and severity.

The conceptual foundation of the study reflects a hard-won consensus in the climate-conflict literature. Scholars increasingly agree that climatic shocks rarely generate violence in a linear fashion. Instead, they interact with exposure, sensitivity and adaptive capacity, shaping social and political outcomes through pathways that are deeply context-specific. Quantitative research has yet to identify a robust, generalisable relationship between climate variability and armed conflict; climate-related stress is more likely to manifest as communal violence, protests or displacement than as full-scale war. The authors also cite a caution that is often overlooked: poorly designed responses to climate change, including securitised approaches to migration or mitigation projects that compete with local land use, can themselves become sources of conflict. This is why the study insists on conflict-sensitive climate governance that prioritises cooperation and prevention.

What makes regional organisations uniquely important in this landscape, the authors argue, is their position between the global and the local. Compared with global actors, bodies like the African Union offer greater contextual sensitivity and political ownership over risks such as droughts, floods and resource competition, whose impacts routinely cross borders. Since the mid-1990s, regional organisations have expanded from traditional diplomacy into preventive diplomacy, mediation, peace operations and post-conflict reconstruction. The African Union, formed in 2002 under the banner of African solutions to African problems, has built an ambitious peace and security architecture, including the Peace and Security Council and the Continental Early Warning System. Yet scholars caution against overestimating its operational capacity: dependence on external funding, sovereignty concerns and uneven political will among member states have long constrained outcomes.

To investigate how the AU translates climate-security awareness into practice, the team focused on the Africa Multi-Hazard Early Warning and Early Action System, known as AMHEWAS. Established in 2022 by the African Union Commission, AMHEWAS is designed to strengthen continental capacity for early warning across droughts, floods, extreme rainfall and other hydro-meteorological hazards. Its stated objectives include enhancing access to multi-hazard warning information at continental, regional and national levels, reducing disaster impacts through anticipatory action, supporting resilience in line with the Sendai Framework for Disaster Risk Reduction 2015-2030 and Agenda 2063, and improving interoperability across member states and Regional Economic Communities. Implementation is supported by the Italian Government in partnership with the United Nations Office for Disaster Risk Reduction and the CIMA Research Foundation.

Methodologically, the study is a qualitative case study combining document analysis of AU policy documents, peace and security frameworks and official AMHEWAS reports with a structured questionnaire administered online between January and May 2026 to AU policymakers, technical experts, representatives of Regional Economic Communities and climate-security specialists. Respondents were identified through purposive and snowball sampling, and four responses were received, reflecting the access constraints inherent in research on active institutional programmes. The sample included two respondents affiliated with the AMHEWAS programme, a former senior official of a Regional Economic Community, and an academic expert in peace and security with policy engagement in AU governance. Responses were analysed through thematic coding organised around five categories: early warning, early action, institutional coordination, knowledge production and information sharing, and political constraints. The authors are candid that the results are exploratory rather than fully generalisable, but the consistency of insights across documents and interviews strengthens their reliability.

The technical architecture that emerged from this analysis is striking. AMHEWAS operates through a subsidiarity-based governance model in which the African Union provides strategic orientation and norm harmonisation, Regional Economic Communities serve as technical and operational interfaces, and member states retain primary responsibility for implementation on the ground. A Steering Committee provides strategic oversight while a Technical Working Group of experts from member states, UN agencies, civil society and academia refines methodologies. The system’s operational backbone includes a Continental Situation Room in Addis Ababa, a Multi-Hazard Early Warning Advisory Centre in Niamey, regional situation rooms in Nairobi under IGAD and Abuja under ECOWAS, and the first national situation room in Dodoma, Tanzania. These facilities run around the clock on standardised operating procedures, aggregating risk data and issuing continental watches and advisories.

At the heart of AMHEWAS’s ambition is a shift from hazard-based to impact-based forecasting, a paradigm that links meteorological hazards directly to their anticipated social, economic and infrastructural consequences. The approach operates across three analytical levels: hazard forecasts based on thresholds such as extreme rainfall predictions; impact-based warnings that qualitatively assess expected disruptions to populations and infrastructure; and impact forecasts that quantify affected people, damaged roads and inundated cropland. Operational tools include Flood-PROOFS East Africa, an impact-based river flood forecasting system for the Greater Horn of Africa that combines hydrological modelling with flood mapping and risk analysis, and the African Drought Watch, which provides monthly continental assessments. These systems draw on data from the Copernicus Emergency Management Service and the European Commission’s Joint Research Centre, including five-day discharge forecasts from the Global Flood Awareness System, and collectively reach an estimated 1.5 billion people.

Yet the study’s most compelling findings concern the gap between sophisticated forecasting and effective response. Respondents converged on four structural constraints: heterogeneous national capacities in human resources, technical infrastructure and hazard monitoring equipment across 55 member states; institutional fragmentation, with environment, agriculture and civil protection agencies operating in silos with poorly interoperable data systems; financial sustainability, with early warning systems dependent on external funding that respondents described as frequently motivated by disasters, reactive rather than anticipatory; and limited political ownership by member states, which reduces the operational impact of alerts and constrains investment. On the cultural front, one respondent noted that many administrations are accustomed to communicating danger in generic terms rather than expected impacts, and that changing this logic requires training, analytical depth and clear protocols.

The relationship between AMHEWAS and the Continental Early Warning System emerged as one of the most analytically significant dimensions of the research. CEWS, a pillar of the African Peace and Security Architecture, maintains a mandate of conflict anticipation directly supporting the Peace and Security Council, while AMHEWAS addresses natural and hydro-meteorological hazards. One respondent described the complementarity in institutional terms: CEWS ensures the political-security reading and direct linkage to the Peace and Security Council’s decision-making mechanisms, while AMHEWAS adds a multi-risk analysis that allows anticipatory identification of factors of instability before they materialise into crises. Collaboration between the two systems has existed since AMHEWAS’s inception, with knowledge exchanges and training in 2021 enriching the design of multi-hazard advisories. But respondents also flagged that CEWS has suffered from institutional restructuring that effectively downgraded the system, and that persistent limitations in coordination, data sharing and activation mechanisms continue to constrain integration. Looking ahead, one respondent identified the Extraordinary Conference of Luanda, scheduled for August 2026, as a decisive political moment to drive structural decisions on the coherence, complementarity and operationalisation of early warning systems on the continent.

Ultimately, the study argues that the existence of sophisticated forecasting tools does not automatically generate preventive responses. What determines operational effectiveness is the credibility of alerts, the clarity of communication, the existence of predefined institutional protocols linking alert levels to concrete measures, and the availability of anticipatory financing. Respondents emphasised that trust in the quality of data, resulting from the integration of information on hazards, exposure and vulnerability, is a sine qua non condition for mobilising resources and activating responses. They also highlighted the role of traditional and local knowledge, noting that collaboration with traditional and local authorities enhances early action by ensuring warnings are contextually meaningful. Training has been delivered to representatives from 37 AU member states across five Regional Economic Communities, with national situation rooms planned or in process in Tanzania, Namibia and Ethiopia. The authors conclude that the African Union adds value by coordinating, setting standards and integrating knowledge across levels of governance, but that the challenges facing AMHEWAS are not only technical but fundamentally political and institutional. As climate-related events rise in frequency and impact across the continent, the credibility of anticipatory systems will be measured not by the sophistication of the alerts they produce but by the collective capacity to act preventively, coherently and consequentially before crises materialise.

Subject of Research: The role of the African Union and its AMHEWAS early-warning system in preventing climate-related conflicts through regional peacebuilding governance.

Article Title: The role of regional organisations as peacebuilders in climate-related conflicts: the case of the African Union

Article References: Proença Garcia, F., Calléja, L., & Duque, R. (2026). The role of regional organisations as peacebuilders in climate-related conflicts: the case of the African Union. Frontiers in Political Science, 8, Article 1894679. https://doi.org/10.3389/fpos.2026.1894679

Image Credits: AI Generated

DOI: 10.3389/fpos.2026.1894679

Keywords: African Union, climate security, AMHEWAS, early warning systems, peacebuilding, climate-related conflicts, regional organisations, anticipatory governance, drought, flooding, Sendai Framework, impact-based forecasting

The core idea is deceptively simple. When climate extremes hit rain-fed farming systems, livelihoods collapse. At the individual level, people experience what researchers call ecological grief, climate anxiety and solastalgia—the distress of watching a valued landscape degrade around you. But when losses repeat across a community, and across generations, something bigger emerges: collective trauma, a shared psychological wound that reshapes social norms, institutional trust, cultural memory and patterns of collective action. Drawing on social-ecological systems theory and Conservation of Resources theory, the authors argue that this collective trauma is not merely a by-product of climate change. It is an active driver of environmental change, and one that conventional adaptation frameworks have almost entirely ignored.

The mechanism works like this. Communities that have lost crops, animals and livelihoods several times over prioritize immediate survival over long-term sustainability. They cultivate fragile marginal lands, clear forests for charcoal, overgraze rangelands and abstract water unsustainably. These coping strategies buy a season of relief, but they accelerate soil erosion, reduce rainwater infiltration, increase sedimentation and diminish the landscape’s capacity to regulate floods. Degraded ecosystems buffer climate extremes less effectively, so the next drought or flood hits harder, deepening losses and compounding the trauma. The loop closes, and each rotation leaves both the land and the people more vulnerable than before.

Kenya’s Rift Valley provides the ideal laboratory for this idea. The region spans extraordinary diversity, from the semi-arid rangelands of Baringo, Laikipia and Narok to the high-potential maize belts of Nakuru, Uasin Gishu and Trans-Nzoia, and it contains the Mau Forest Complex, one of East Africa’s most important water towers. A census-based analysis presented in the paper shows more than 12.7 million people living across fifteen counties with densities ranging from roughly 13 persons per square kilometre in Turkana to nearly 400 in Kericho and Trans-Nzoia. That heterogeneity matters, because climate risk is spatially uneven: semi-arid counties face chronic drought and water scarcity, high-rainfall counties face delayed rainfall onset and intense erosive precipitation, and intermediate counties such as Nakuru and Elgeyo-Marakwet face compound hazards including deadly landslides, as occurred in West Pokot and Elgeyo-Marakwet in 2019.

Historical records show that climate-related disasters in the region have become markedly more frequent since the early 1990s, and, critically, that recovery windows between shocks have shortened. The 1991–92 and 1999–2001 droughts devastated pastoral and mixed farming systems in Baringo, Laikipia and Narok, triggering distress livestock sales, migration and expansion into marginal land. The 2008–09 drought coincided with a global food-price crisis, and the 2011 Horn of Africa drought extended the damage regionally. Then the severe 2020–23 drought arrived before many communities had rebuilt their productive assets from the previous catastrophe. The result, the authors argue, is chronic rather than temporary vulnerability: communities are no longer responding to isolated disasters but living in a permanent state of uncertainty that extends across generations.

Land tenure adds another layer of complexity to this picture. The paper reviews census and county data showing that in Nakuru more than 95 percent of land is private freehold or leasehold, while in Baringo roughly 45 percent is private and 55 percent communal, with group ranches subdivided and unregistered community lands persisting elsewhere. Secure tenure encourages farmers to invest in terracing, agroforestry, water harvesting and soil restoration, because they can expect to capture the benefits of long-term investments. Fragmentation and insecure rights discourage them. But the authors are careful to avoid a simple private-versus-communal verdict: in pastoral areas, communal tenure supports the mobility and collective grazing management on which dryland livelihoods depend. What matters, they write, is the security, legitimacy and quality of tenure governance, not the tenure category itself.

Crucially, the framework does not treat trauma as destiny. The authors draw on scholarship on post-traumatic growth to argue that repeated adversity can also generate learning, strengthened social relationships and renewed collective agency. Communities battered by droughts and floods have built water-harvesting infrastructure, developed local early-warning systems, restored degraded landscapes and established mutual-support networks. Which path a community takes—destructive coping or collective transformation—depends on enabling conditions: social cohesion, institutional and policy support, access to resources, and opportunities for meaningful participation. Climate shocks may generate trauma, but trauma can also catalyse resilience when communities are given the resources and institutional space to convert adversity into adaptation.

The practical payoff is a new model of trauma-informed climate governance, which treats adaptation as a psychosocial process rather than a purely technical one. The authors map climate stressors to their trauma responses, ecological consequences and governance implications: recurrent drought produces chronic food insecurity and overgrazing, calling for climate-smart agriculture; flooding produces displacement and riverbank erosion, calling for watershed restoration; livestock mortality drives charcoal production, calling for alternative livelihoods; and repeated shocks produce collective trauma itself, calling for a fundamentally different governance approach. That approach rests on several pillars. Climate-smart agriculture—drought-tolerant varieties, conservation tillage, mulching, crop diversification and efficient water harvesting—reduces exposure, but only works when farmers have confidence in the future. Participatory ecosystem restoration, through community-led reforestation and watershed committees, functions simultaneously as ecological recovery and psychosocial healing. Indigenous and local ecological knowledge informs adaptation while reaffirming cultural continuity in disrupted landscapes. Climate risk financing, including index-based insurance and adaptive social protection, eases the financial desperation that pushes households toward destructive coping. And livelihood-specific psychosocial recovery—community dialogue, peer support, customary conflict resolution and culturally appropriate healing—should be recognized as a legitimate component of adaptation policy, because rebuilding trust is a precondition for collective stewardship.

The policy implications are concrete. Kenya already has a strong institutional architecture, including the Climate Change Act of 2016, the National Climate Change Action Plan for 2023–2027, the National Adaptation Plan running to 2030 and the National Drought Management Authority. But these instruments currently emphasize physical adaptation and disaster risk reduction over psychosocial well-being. The authors argue that explicitly incorporating collective trauma and appropriate metrics into these frameworks—at national, county, community and regional scales, including through the Intergovernmental Authority on Development’s drought management strategies—would make them substantially more effective. They also call for a research agenda: standardized, gender-sensitive indicators for measuring collective trauma in climate vulnerability assessments; interdisciplinary work bridging ecology, psychology, sociology and public health; longitudinal studies of cumulative impacts; and comparative tests of whether trauma-informed governance genuinely produces more durable conservation outcomes than conventional approaches.

What elevates this work beyond a regional case study is its claim about how climate vulnerability works everywhere. Similar cycles of drought, flooding, displacement and degradation are documented across the Sahel, the Horn of Africa, Madagascar, Australia and Indigenous and rural communities in North America. The burdens are unevenly distributed too, with women disproportionately affected given their responsibilities for water and wood collection and childcare. If the authors are right, then conservation science stands at a crossroads: protecting species and restoring ecosystems cannot succeed in isolation from the communities that inhabit those landscapes. Ecosystem health and human well-being, they conclude, are inseparable components of resilient socio-ecological systems—and restoring landscapes and healing communities are mutually dependent processes. Psychosocial recovery, on this view, is not a soft add-on to hard adaptation spending. It is the missing mechanism that determines whether people become partners in conservation or, worn down by loss, its reluctant opponents.

Subject of Research: The role of collective trauma in climate-driven socio-ecological feedback loops and adaptation governance in Kenya's Rift Valley

Article Title: Cyclic droughts, flooding and collective trauma: an environmental feedback loop to inform governance and socio-ecological resilience in Kenya’s rift valley

Article References: Obwoyere, G. O., & Jones, S. (2026). Cyclic droughts, flooding and collective trauma: an environmental feedback loop to inform governance and socio-ecological resilience in Kenya’s rift valley. Frontiers in Conservation Science, 7, Article 1866800. https://doi.org/10.3389/fcosc.2026.1866800

Image Credits: AI Generated

DOI: 10.3389/fcosc.2026.1866800

Keywords: collective trauma, climate adaptation, Kenya Rift Valley, socio-ecological resilience, ecological grief, drought, flooding, land degradation, trauma-informed governance, indigenous ecological knowledge, ecosystem restoration, climate-smart agriculture

The conceptual heart of the study lies in distinguishing two related but distinct phenomena. Compound risks emerge when multiple climatic drivers, hazards, or vulnerabilities interact to produce impacts greater than any factor alone would suggest, whether simultaneously, as when heat and drought strike together, or sequentially, as when prolonged drought is followed by intense rainfall on desiccated, impermeable ground. Cascading risks describe something different: the propagation of an initial shock through interconnected systems, so that a meteorological event becomes a crisis of electricity, water, telecommunications, housing, mobility, and public health. A heatwave strains the electricity grid at precisely the moment demand for cooling peaks; a power outage then disables water pumping, refrigeration, traffic control, and hospital systems. The authors emphasize that these terms are not synonyms, and that conflating them obscures the specific pathways through which urban crises unfold.

Underpinning the analysis is the idea that cities are not passive recipients of hazards but dense socio-technical systems in which physical infrastructure, economic activity, ecological conditions, social vulnerability, and institutional decision-making are deeply intertwined. Electricity, water supply, drainage, transport, telecommunications, food distribution, and emergency response are so interdependent that a disruption in one domain can propagate across the others, transforming a localized event into a systemic urban crisis. Crucially, the authors note, infrastructure is not merely technical. It is shaped by political choices, investment patterns, maintenance gaps, institutional fragmentation, and unequal territorial development, which means that resilience is as much a governance, finance, and equity challenge as an engineering one.

To build the evidence base, the researchers conducted a targeted comparative scoping review combined with qualitative policy-document analysis, covering literature published primarily between January 2020 and June 2026. Searches in Scopus, Web of Science, and Google Scholar, supplemented by policy repositories and conducted in both English and Spanish, yielded a final corpus of 81 sources: 54 academic publications and 27 policy, governmental, or institutional documents. Each source was coded across eight dimensions, including hazard profile, compound interaction, cascading pathway, social amplification, governance challenge, funding challenge, and policy response. The urban cases spanned New Orleans and Los Angeles in the United States; Toronto, Vancouver, Halifax, Calgary, and Edmonton in Canada; and Mexico City, Monterrey, Acapulco, and Veracruz–Boca del Río in Mexico, selected to capture contrasting combinations of coastal storms, heat, drought, flooding, sea-level rise, and institutional capacity.

The United States cases reveal the tension between strong subnational innovation and unstable federal climate policy. New Orleans illustrates how a coastal hazard becomes a systemic urban crisis: Hurricane Katrina combined storm surge and flooding with levee failure, electricity and communications disruption, constrained emergency access, housing loss, prolonged displacement, and racialized recovery outcomes. The city now possesses a relatively mature hazard-mitigation architecture linking its Hazard Mitigation Office, Office of Sustainability, NOLA Ready, and the Sewerage and Water Board, yet institutional coordination and equitable implementation remain continuing challenges. Los Angeles, meanwhile, faces interacting heat, drought, wildfire and smoke, flooding, and electricity stress, and benefits from California’s adaptation strategy and novel financing mechanisms such as climate-resilience districts under Senate Bill 852. But responsibility for heat, wildfire, water, drainage, energy, and housing remains divided among agencies, and the availability of state and federal funds varies across programs and political cycles.

Canada presents a different profile: a relatively advanced national adaptation framework paired with a persistent urban implementation gap. The National Adaptation Strategy establishes shared goals for disaster resilience, health, nature, infrastructure, and the economy, while provinces retain major responsibilities for municipalities, land use, and emergency management. Canada’s National Issues Report concludes that local governments are moving from planning toward implementation, but that action is not keeping pace with present and projected risks. Toronto’s climate-risk assessment connects heat, flooding, wildfire smoke, infrastructure, and vulnerable populations; Vancouver’s adaptation strategy integrates sea-level rise and coastal exposure; Halifax, Calgary, and Edmonton each maintain formal strategies. The recurring deficit, the review finds, is not the absence of plans but the incomplete integration of municipal instruments with infrastructure ownership, provincial authority, long-term finance, Indigenous governance, and operational performance indicators.

Mexico’s cases expose how cascading risks intensify under uneven urbanization, water insecurity, infrastructure deficits, informality, and fragmented metropolitan governance. In the Mexico City Metropolitan Area, drought and flooding are interconnected rather than opposing risks: low reservoir levels in the Cutzamala system, groundwater depletion, subsidence, leakage, and unequal household access can convert climatic drought into a wider service and governance crisis, while intense rainfall overwhelms drainage and mobility systems. Monterrey’s 2022 water crisis combined prolonged drought, reservoir depletion, infrastructure deficiencies, and unequal access. Acapulco offers perhaps the most dramatic illustration: Hurricane Otis in 2023, a rapidly intensifying cyclone, damaged housing, hotels, roads, electricity, water, telecommunications, and livelihoods, turning a single storm into an urban economic and social crisis. The Veracruz–Boca del Río conurbation demonstrates horizontal fragmentation, where the ecological and infrastructure system is metropolitan but planning authority and budgets remain divided between two municipalities and the state.

From the cross-case comparison, the authors distill three types of governance deficit. A vertical deficit occurs when national or state commitments are not matched by predictable municipal finance, authority, or implementation support, a pattern visible in Canadian municipal dependence on federal programs, U.S. dependence on shifting federal funding, and Mexican municipal dependence on state institutions. A horizontal deficit arises when sectoral agencies or adjacent municipalities manage interconnected systems separately, as in Los Angeles infrastructure governance, Mexico City’s metropolitan water system, and Veracruz–Boca del Río. An operational deficit emerges when plans or risk atlases identify hazards but remain weakly connected to budgets, maintenance, enforcement, monitoring, or social protection, with Acapulco cited as a clear example. A study of twenty North American city governments cited in the review similarly found that resilience governance frequently remains divided across agencies and sectors even when climate risks are cross-sectoral.

The review also highlights a subtler danger: strategies intended to enhance resilience to one event may inadvertently reduce resilience to another concurrent hazard. Prospective analysis, infrastructure stress testing, and scenario planning can help identify and minimize such unintended consequences, particularly as research projects increases in the frequency and duration of compound dry-hot extremes across major U.S. cities under the combined effects of climate change and urban development. Community-centered approaches and the co-design of problem-solving processes can strengthen adaptation programs, while interagency coordination and transdisciplinary research are needed to address effects that move across sectors and reduce siloed management. The authors caution that their findings should be interpreted as an analytically structured synthesis rather than a statistical ranking of urban performance, given the targeted nature of the review and the uneven evidence base across countries.

The ultimate message is a call to move from isolated adaptation measures toward integrated risk governance. Cities are exposed not only to individual hazards but to hazards that interact with one another and with the infrastructure, social, and governance systems that sustain urban life. A heatwave can become an energy and public-health crisis; a drought can become a water, economic, and governance crisis; a hurricane can become a housing, telecommunications, transport, energy, and social-protection crisis. Without prospective scenario planning, infrastructure stress testing, stable resilience financing, intersectoral metropolitan coordination, and equity-centered infrastructure planning, the authors warn, cities may remain trapped in reactive cycles of emergency response and reconstruction rather than achieving sustained risk reduction. The future of urban resilience, the review suggests, will depend on whether cities can govern the relationships among infrastructure, inequality, finance, and climate uncertainty in coordinated and equitable ways.

Subject of Research: Compound and cascading climate risks in urban infrastructure governance and resilience in North American cities

Article Title: Compound and cascading climate risks in urban infrastructure governance and resilience across North America

Article References: Lucatello, S., & Henríquez, B. P. (2026). Compound and cascading climate risks in urban infrastructure governance and resilience across North America. Discover Cities, 3(1), Article 201. https://doi.org/10.1007/s44327-026-00374-1

Image Credits: AI Generated

DOI: 10.1007/s44327-026-00374-1

Keywords: compound climate risk, cascading failures, urban resilience, critical infrastructure, climate adaptation, governance, North America, flooding, extreme heat, drought, hurricanes, social vulnerability

The review, published in PLOS Water by a team led by J. L. Wallace of the University of Leeds, together with colleagues from the University of Oxford, the University of Bristol, the University of Technology Sydney, the World Health Organization, UNICEF, and other institutions, set out to answer a deceptively simple question: what is the evidence that specific technical, operational, and governance attributes or adaptation actions keep sanitation systems functioning during and after climate hazards? The answer, after screening nearly four thousand articles, was just seventeen studies that met the review’s inclusion criteria. From those seventeen studies, the team distilled twenty-seven distinct attributes or adaptation actions with potential to enhance resilience. None of them, the authors note, is currently considered in any existing global monitoring process.

The scale of the screening effort makes the small yield all the more striking. The researchers searched five major databases, including Web of Science, Medline, Scopus, CAB Abstracts and Global Health, in July 2024, following PRISMA guidelines for systematic reviews. Almost 4,000 returns were reduced to 3,461 unique articles for title screening, with two independent reviewers assessing titles, abstracts and full texts and a third resolving disagreements. Fifty-seven articles were selected for full-text review, and after exclusions, including eight that were inaccessible, only seventeen survived. Hand-searching reference lists added thirteen candidates, but grey literature searches and expert consultations produced nothing eligible. The dominant reason for exclusion was a lack of grounding in empirical or reported data: many papers proposed indicators of resilient sanitation without ever testing them against real-world cases.

The seventeen surviving studies split into two revealing clusters. Six came from the engineering literature, focused overwhelmingly on sewered systems in high-income countries, quantitative in style, and framed around the classic engineering resilience triad of robustness, redundancy and reparability. Eleven came from the international development literature, centred on non-sewered sanitation in lower-income settings, more qualitative in method, and notable for capturing something entirely absent from the engineering cluster: the experience of the user. Geographically, the picture is lopsided. One third of the studies were based in high-income countries, all addressing sewers or treatment facilities. Eight studies came from low-income countries, and five of those were conducted in Bangladesh alone, a country acutely exposed to flooding. The authors attribute this concentration partly to research bias toward simpler, more accessible interventions rather than complex, system-level solutions.

What the evidence does show is instructive. In low-income settings, the dominant strategy is what the review calls infrastructure stacking: households diversifying their sanitation options so that when floods or droughts knock out one option, another remains. During droughts, when water for flushing runs short, households fall back on multiple water sources for manual flushing or switch to non-flush and low-flush latrines. During storms that cut water supplies or flatten superstructures, resilience has come from stronger construction, temporary facilities, and stored water for flushing. Against flooding, the evidence centres on robustness of the latrine pit and its superstructure: higher cement content for structural integrity, trenches and earthen walls to redirect surface water, elevated bases and siting on higher ground, and informal quality assurance during construction. Crucially, almost all of these were autonomous household responses, not planned interventions by utilities or governments.

For sewered systems, the technical findings are more granular. Pipe material matters: sewers made of brittle vitrified clay fracture more readily under increased dynamic pressure than those of polyvinyl chloride or reinforced concrete, and concrete and clay pipes suffer higher blockage rates during droughts, partly because older pipes lack rubber gaskets that resist root intrusion and infiltration. Smaller-diameter sewers, being shallower and requiring less debris to clog, block more often, particularly in drought conditions. Iron manhole covers corrode on contact with saline stormwater. On the operational side, maintenance and timely pipe replacement reduce blockages, and one study demonstrated that drag-reducing polymers can raise sewer flow velocities by 60 to 70 percent by cutting friction losses. At treatment works, flood defences, expanded capacity, backup processes such as emergency chlorination, and early warning systems that trigger preparatory actions all appear in the evidence, while comparative studies under arid conditions found activated sludge treatment outperforming aerated lagoons for pollutant removal, with constructed wetlands similarly effective but less stable across seasons.

Yet the gaps dwarf the findings. Sixteen of the seventeen studies examined a single element of the sanitation service chain; only one took a genuinely system-wide perspective. Nine articles addressed latrines and containment, four addressed sewers, and three addressed treatment works. Not a single study captured resilience-building for the road-based conveyance of faecal sludge, wastewater, or supernatant, the trucks and informal workers that empty pits across much of the urban developing world. No studies provided evidence on pits and tanks as containment technologies, despite known vulnerabilities of septic tanks to flooding and backflow. Sea level rise, a slow-onset hazard that directly threatens the coastal locations where treatment works are typically built, was entirely unrepresented. Twenty of the twenty-seven identified attributes and actions address rapid-onset events such as storms, heavy rainfall and flooding, a bias the authors attribute to the simple fact that immediate disasters are easier to study within the time and resource constraints of research projects than gradual, less visible changes.

The review also raises an uncomfortable conceptual question: how much of what passes for climate resilience is simply good sanitation practice? Mapping the identified attributes against the Sanitation and Water for All definition of climate-resilient WASH services, which describes services that anticipate, respond to, cope with, recover from, adapt to, or transform based on climate-related events, the authors found that most evidence clusters around responding and coping, or falls into the category of good sanitation outright. Robust materials in flood-prone areas, for example, are good engineering practice regardless of climate change. Adaptation actions focused on system recovery and long-term transformation are notably absent from the evidence base, even though sector initiatives such as Systems Strengthening and Citywide Inclusive Sanitation are actively trying to reinforce the institutional fabric around infrastructure. The engineering notion of restoring a system to its functional state is itself contested, the authors note, because the pre-disaster state was one in which the system already failed.

Underlying all of this is a structural imbalance in who acts. In low- and middle-income settings, resilience is delegated to users, who bear responsibility for building and maintaining latrines without always having access to the knowledge, skills, and materials needed to do so durably, a situation that can produce maladaptation rather than resilience. Evidence on operational or enabling-environment strategies implemented by service providers or governments is minimal, and the review found a significant lack of studies connecting policy, institutional, regulatory, or financial actions by national or subnational governments with sanitation outcomes. Because government actions operate upstream, enabling users and providers downstream, their effects are indirect and hard to trace, which may explain why they vanish from the literature. The authors argue that effective resilience cannot be achieved through technical measures alone; it requires governance structures that create the conditions for adaptive strategies, cross-institutional collaboration, data sharing, and an end to the silos in which sanitation strategies operate in isolation from water, transport, and disaster planning.

The implications reach the highest levels of global policy. The review was conducted as part of a multi-year initiative by the WHO/UNICEF Joint Monitoring Programme and GLAAS to develop indicators for monitoring climate-resilient WASH within the Sustainable Development Goal framework, where no region is on track for universal sanitation access by 2030. The twenty-seven identified attributes offer a conceptual foundation and practical entry points for measurable indicators, but with only four of seventeen studies providing empirical measurements, the authors warn that indicators built from this evidence risk measuring successes while underrepresenting failure, trade-offs, and maladaptation. Their prescription is threefold: evaluate adaptation measures against observable service outcomes rather than assuming they work; shift from component-level studies to whole-system research that traces how disruption propagates across the sanitation chain, including the resilience of the workers who empty pits; and expand adaptation beyond infrastructure toward the governance, financing, and institutional conditions that determine whether systems merely survive climate hazards or genuinely transform. Until that evidence exists, the world is building sanitation for a changing climate largely on faith.

Subject of Research: Climate resilience of sanitation systems: a global systematic review of adaptation evidence

Article Title: Where is the evidence? A global systematic review of sanitation system resilience to climate hazards

Article References: Wallace, J. L., Wright, M. K., Camargo-Valero, M. A., Charles, K. J., Engebretson, B., Gordon, B., Gore, F., Howard, G., Johnston, R., Kohlitz, J., Mills, F., Moon, K., Nijhawan, A., Slaymaker, T., Takane, M., Willetts, J., & Evans, B. E. (2026). Where is the evidence? A global systematic review of sanitation system resilience to climate hazards. PLOS Water, 5(10), e0000474. https://doi.org/10.1371/journal.pwat.0000474

Image Credits: AI Generated

DOI: 10.1371/journal.pwat.0000474

Keywords: sanitation, climate resilience, systematic review, WASH, flooding, drought, faecal sludge management, sewers, pit latrines, SDG 6, JMP, adaptation

The research, led by Md. Mamun Miah and colleagues including Kabir Hossain, Hafiz T. A. Khan, and H. M. Shahadat Ali, focused on two of Bangladesh’s most flood-prone districts, Noakhali and Feni. Both lie in the country’s coastal delta region, where monsoon rains, tidal surges, and river overflow regularly inundate villages and overwhelm sanitation infrastructure. The team conducted a cross-sectional survey, going door to door to interview 501 respondents selected through simple random sampling. The face-to-face interviews captured a detailed picture of each household: who lived there, what they earned, where their drinking water came from, how they treated it, how often and how severely floods reached them, and whether medical help and community preparedness programs were within reach.

The headline finding was stark. In these flood-affected areas, 63.7 percent of surveyed households—319 of the 501—reported at least one member suffering from a waterborne disease. That figure underscores why the researchers argue that conventional, reactive approaches to post-flood health crises are insufficient. If nearly two out of three households are affected, interventions based on guesswork or broad geographic targeting risk wasting scarce resources on families at comparatively lower risk while missing those most vulnerable. A predictive model, the authors reasoned, could sharpen the focus.

Before any algorithm could be trained, the raw survey data required careful preparation. The researchers ran a sequence of feature selection techniques to distill dozens of potential variables into a compact, informative set. They began with correlation analysis to detect redundant variables, then assessed multicollinearity using the variance inflation factor, a standard diagnostic that flags predictors which overlap too heavily with one another. Mutual information analysis followed, measuring how much each variable contributed non-linear information about disease outcomes. Finally, the team applied Recursive Feature Elimination with Cross-Validation, or RFECV, an iterative method that repeatedly trains a model, drops the least useful feature, and tests whether predictive performance holds up across data splits. The process retained ten predictors: age, gender, monthly household income, household size, flood frequency, flood severity, source of drinking water, availability of medical assistance, water purification method, and community preparedness for preventing waterborne diseases.

With the feature set fixed, the researchers benchmarked five widely used machine learning algorithms: Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, and Extreme Gradient Boosting, better known as XGBoost. Each model was optimized through randomized hyperparameter tuning, a search strategy that samples combinations of algorithm settings rather than exhaustively testing every possibility, paired with five-fold cross-validation to ensure the tuning generalized beyond a single data split. The models were then evaluated on an independent test set they had never seen during training, using a battery of metrics including accuracy, precision, recall, specificity, F1-score, and the area under the receiver operating characteristic curve, or ROC-AUC, which captures how well a model separates affected from unaffected households across all decision thresholds.

The Random Forest classifier emerged as the strongest performer, delivering the most balanced results on the test set. It achieved an accuracy of 61.4 percent, precision of 71.9 percent, recall of 64.1 percent, specificity of 56.8 percent, an F1-score of 67.8 percent, and a ROC-AUC of 0.643. Those numbers tell a nuanced story. The precision figure is particularly notable: when the model flags a household as high risk, it is right roughly seven times out of ten, which matters greatly in resource-constrained settings where misdirected aid carries real costs. The ROC-AUC of 0.643 indicates performance modestly better than random guessing—useful, but not infallible. The researchers were transparent about this, and they also tested more elaborate approaches, including stacking and weighted soft voting ensembles that combine multiple models. Neither outperformed the single Random Forest, a reminder that in applied machine learning, complexity does not automatically buy accuracy, especially with moderate-sized survey datasets.

What elevates the study beyond a standard prediction exercise is its commitment to explainability. Black-box models are notoriously difficult for health officials to act on, so the team turned to SHAP—SHapley Additive exPlanations—a technique rooted in cooperative game theory that assigns each feature a contribution value for every individual prediction. The SHAP analysis identified flood severity, community preparedness, water purification practices, and socio-economic factors as the most influential drivers of predicted risk. In practical terms, households facing the deepest or most prolonged flooding, lacking effective water treatment, and situated in communities without organized prevention efforts were consistently ranked as most vulnerable, with income and household size shaping the risk profile as well.

These findings carry immediate implications for how flood response is organized in Bangladesh and beyond. Rather than distributing water purification tablets or deploying medical teams uniformly across an affected district, health authorities could use a trained model to triage, prioritizing households whose characteristics match the high-risk profile identified by SHAP. The same logic supports early warning strategies: because flood frequency and severity are among the top predictors, seasonal forecasts and river gauge data could feed into risk models before floodwaters arrive, allowing pre-positioning of supplies in the most exposed communities. The emphasis on community preparedness as a key predictor also suggests that investments in local education, sanitation planning, and coordinated response networks yield measurable reductions in disease risk that algorithms can detect.

The authors are careful to frame the framework as promising but not yet deployment-ready. External validation—testing the model on data from other flood-affected regions—is required before it can be trusted at scale, and the moderate ROC-AUC signals that unmeasured variables, from pathogen concentrations in specific water sources to individual hygiene behaviors, likely influence outcomes. Still, the study demonstrates a replicable pipeline: rigorous survey design, statistically grounded feature selection, hyperparameter-optimized modeling, and transparent interpretation. All analyses were conducted in Python, and the methods are documented in enough detail to be adapted by other research teams working in low- and middle-income countries where waterborne disease remains a leading burden.

As climate change intensifies monsoon variability and sea-level rise pushes saline floodwater deeper into the Bengal delta, the stakes of this kind of predictive public health work will only grow. Bangladesh has long been on the front line of climate adaptation, and studies like this one point toward a future where the response to a flood begins not when the first patients arrive at a clinic, but when a model, trained on the experiences of hundreds of households, flags which doors relief workers should knock on first. The 319 affected families in Noakhali and Feni are, in that sense, more than statistics; they are the training signal for a smarter, faster defense against the diseases that follow the water.

Subject of Research: Machine learning prediction of household-level waterborne disease risk in flood-affected districts of Bangladesh

Article Title: Predicting households risks of waterborne diseases in flood-affected areas using machine learning: A study of Noakhali and Feni, Bangladesh

Article References: Miah, M. M., Hossain, K., Khan, H. T. A., & Ali, H. M. S. (2026). Predicting households risks of waterborne diseases in flood-affected areas using machine learning: A study of Noakhali and Feni, Bangladesh. PLOS Water, 5(8), e0000542. https://doi.org/10.1371/journal.pwat.0000542

Image Credits: AI Generated

DOI: 10.1371/journal.pwat.0000542

Keywords: waterborne diseases, machine learning, Bangladesh, flooding, Random Forest, SHAP, public health, feature selection, XGBoost, early warning, Noakhali, Feni

Diarrheal disease remains one of the leading causes of illness and death among children under five worldwide. Although the global burden has declined substantially over recent decades, thanks to improved sanitation, oral rehydration therapy and vaccination against rotavirus, that progress is unevenly distributed. Low-income urban settlements, where piped water may be intermittent, sanitation infrastructure strained and housing precarious, remain hotspots of risk. Climate change threatens to stall or even reverse decades of gains in these communities, because the meteorological conditions associated with a warming world, including heavy rainfall events, elevated ambient temperatures and flooding, are precisely the conditions that disrupt water safety and accelerate pathogen transmission. Quantifying those relationships is therefore a critical step toward anticipating the health burden that climate change will impose on vulnerable populations.

The research, conducted by an international team led by investigators from the PAASIM Study Authorship Consortium, including Rebecca S. Kann, Sydney Hubbard, Jedidiah Snyder, Karen Levy and Matthew C. Freeman, focused on Beira, a low-lying port city that is widely regarded as one of the most climate-vulnerable urban areas in Africa. Cyclones and flooding have repeatedly battered the region in recent years, and its dense, rapidly growing neighborhoods combine high water tables with aging or absent drainage systems. Against this backdrop, the team followed mother-child dyads from the third trimester of pregnancy through the infant’s first birthday, collecting data when the infants were three, six, nine and twelve months old. This longitudinal design allowed the researchers to observe how the same households fared as seasons turned and weather shifted.

At each contact, the study team recorded whether the infant had experienced diarrhea and collected samples of water stored in the household for drinking, along with information about the source from which that water had been drawn. The stored water samples were analyzed for contamination with fecal indicator bacteria, a standard proxy for the presence of pathogens that cause diarrheal illness. Weather data, including ambient temperature, heavy rainfall events and flooding, were linked to each household observation, and each visit was classified as occurring in either the rainy or the dry season. The researchers then applied modified Poisson regression mixed effects models, a statistical framework well suited to repeated measures and binary health outcomes, to estimate the strength of the associations between weather variables and the two outcomes of interest: stored water contamination and infant diarrhea.

The results reveal a pronounced seasonal signature in household water safety. During the rainy season, the prevalence of contamination in stored household water was 49 percent higher than during the dry season, with an adjusted prevalence ratio of 1.49 and a 95 percent confidence interval spanning 1.34 to 1.67. This finding is consistent with the mechanistic expectation that heavy rains wash fecal material from latrines, open drains and soil into shallow wells, piped networks and other water sources, overwhelming any treatment barriers that exist. In a city like Beira, where flooding is frequent during the wet months, rain does not merely fall on the city; it mobilizes the microbial contents of its streets and sanitation systems into the water that families collect and store.

Temperature told a different and equally instructive story. Higher ambient temperatures were associated with a higher prevalence of stored water contamination, but only during the dry season, with an adjusted prevalence ratio of 1.14 and a 95 percent confidence interval of 1.03 to 1.27. The seasonal asymmetry makes biological sense. During dry months, when water may sit longer in storage containers and ambient heat accelerates bacterial regrowth, warmth can amplify contamination within the household itself. During the rainy season, by contrast, the dominant driver of contamination appears to be the influx of pathogens from the environment, which may swamp the more modest effect of temperature on bacterial multiplication in storage vessels. The distinction matters for intervention design: protecting stored water from recontamination may yield the greatest benefits in hot, dry periods, while safeguarding sources from flood-driven infiltration is paramount when the rains arrive.

The study also quantified the link between the quality of water at its source and the quality of water in the home. When the source water was contaminated, the prevalence of contamination in stored household water rose by 32 percent during the rainy season, with an adjusted prevalence ratio of 1.32 and a confidence interval of 1.11 to 1.56, and by 56 percent during the dry season, with a ratio of 1.56 and a confidence interval of 1.22 to 2.00. That the association was stronger in the dry season suggests that when environmental dilution and flushing are minimal, the quality of the source dominates the quality of what families ultimately drink. It also underscores a sobering reality documented in many settings: water that leaves a tap or well clean can become contaminated inside the home through dirty containers, hands and utensils, so source protection alone is insufficient.

Crucially, the weather patterns that degraded water quality also translated into illness. Infants were 18 percent more likely to experience diarrhea during the rainy season than during the dry season, with an adjusted prevalence ratio of 1.18 and a confidence interval of 1.01 to 1.38. Higher temperatures again exerted a dry-season-specific effect, raising the prevalence of infant diarrhea by 19 percent for each increment of elevated heat, with a ratio of 1.19 and a confidence interval of 1.05 to 1.35. The parallel structure of the water-quality and illness findings, with rainy season and dry-season heat each leaving its mark on both outcomes, strengthens the plausibility of a causal chain running from meteorology through water contamination to child health, although the authors are careful to note that the study characterizes associations rather than proving mechanisms.

For public health planners, the implications are concrete. The findings argue for interventions that are timed and targeted to the seasons: household water treatment and safe storage promotion may be most urgent as the rains approach, while attention to source water protection and thermal risks to stored water becomes critical during hot, dry months. They also argue for integrating climate information into water, sanitation and hygiene programming in climate-vulnerable cities, rather than treating weather as background noise. As global temperatures rise and extreme rainfall events become more frequent, the seasonal and weather-dependent variation documented in Beira is likely to intensify, and the communities least responsible for climate change will continue to bear a disproportionate share of its health consequences.

The study, published on September 22, 2026, in PLOS Water under the title describing the impact of weather and season on stored water contamination and infant diarrhea in climate-vulnerable, urban Mozambique, adds an important piece to the growing evidence base linking climate and child health. Its longitudinal design, repeated measurement of both exposure and outcome, and explicit modeling of seasonal interactions set a methodological standard for future work in other climate-exposed cities. For the mothers and infants of Beira, the message is stark but actionable: the risks their children face are not random, but follow the rhythm of the seasons and the mercury of the thermometer, and that rhythm can be anticipated, planned for and, with sustained investment in water safety, blunted.

Subject of Research: The impact of weather and season on stored drinking water contamination and infant diarrhea in climate-vulnerable urban Mozambique

Article Title: Impact of weather and season on stored water contamination and infant diarrhea in climate-vulnerable, urban Mozambique

Article References: Kann, R. S., Hubbard, S., Snyder, J., McGunegill, S., Muneme, B., Manuel, J. L., Waller, L. A., Nalá, R., Levy, K., Freeman, M. C., & the PAASIM Study Authorship Consortium (2026). Impact of weather and season on stored water contamination and infant diarrhea in climate-vulnerable, urban Mozambique. PLOS Water, 5(9), e0000599. https://doi.org/10.1371/journal.pwat.0000599

Image Credits: AI Generated

DOI: 10.1371/journal.pwat.0000599

Keywords: infant diarrhea, water contamination, Mozambique, climate change, rainy season, ambient temperature, flooding, stored water quality, PLOS Water, public health, Beira, epidemiology

The authors’ central framing is deceptively simple: sanitation functionality during floods is not a secondary concern to be addressed after the emergency passes, but a core component of how cities should prepare for epidemics. Climate change is intensifying rainfall extremes and urban flooding across many regions, and the public health consequences are sharpest where sanitation and drainage infrastructure is weakest. In an informal settlement, a single heavy storm can overwhelm onsite sanitation and fecal sludge management systems that were already operating at or beyond capacity. Pit latrines fill with floodwater, overflow, or collapse outright, and the fecal material they contained disperses into the household environment. What follows is a dramatic increase in fecal exposure, the pathway through which enteric pathogens, including Vibrio cholerae, find new hosts.

The technical logic of this exposure pathway is worth unpacking, because it explains why cholera risk can spike so rapidly after a flood. Cholera transmission is exquisitely sensitive to the dose of ingested bacteria, and flooding effectively multiplies the number of routes by which fecal contamination reaches human mouths. When latrines overflow, contamination spreads into soil and standing water; when households rely on intermittent piped supply or unsafe sources such as shallow wells and untreated surface water, the contaminated environment translates directly into contaminated drinking water. Waterborne transmission can then be amplified by person-to-person spread within crowded households, where space for isolation and hygiene is limited. The result is a setting in which a sanitation failure that lasts days can seed a transmission chain that persists for months, particularly in settlements where drainage is poor and floodwater lingers.

Lusaka, Zambia, serves as the essay’s illustrative case, and it is a revealing one. Like many rapidly growing cities in sub-Saharan Africa, Lusaka contains large informal settlements where most residents rely on onsite sanitation, pit latrines and septic tanks that must be emptied and their contents safely managed, rather than sewerage. When heavy rains strike, these containment systems are vulnerable in predictable ways: pits flood and overflow, latrine structures collapse in saturated ground, and fecal sludge that cannot be collected and treated because roads are impassable and treatment capacity is limited simply accumulates in the environment. Lusaka has experienced prolonged cholera epidemics in precisely these fragile water and sanitation conditions, and the essay draws lessons from those outbreaks about what it takes to interrupt transmission and, crucially, what it takes to prevent it from returning.

One of the most important lessons is that emergency response tools work, but only up to a point. During cholera epidemics, health authorities can deploy oral cholera vaccine campaigns, establish oral rehydration treatment points, distribute chlorine tablets for household water treatment, and intensify hygiene promotion. These measures can suppress transmission and save lives, and the experience of prolonged epidemics in fragile settings shows that they are indispensable. Yet the essay is emphatic that emergency response is not a substitute for durable services. Transmission can be pushed down temporarily while the underlying conditions, unsafe water, unreliable sanitation, and inadequate fecal sludge management, remain intact. When the emergency machinery stands down, the same vulnerabilities are waiting for the next heavy rain, and the cycle can repeat with each new flood season.

That repetition is captured in the essay’s discussion of feedback loops that sustain exposure and delay recovery. Flood-driven sanitation failure is not a one-off event that the environment simply absorbs. Inundated latrines contaminate the soil and shallow groundwater that households draw on, meaning that exposure continues long after floodwater recedes. Damaged sanitation facilities are often slow to repair in settlements where households have limited resources and responsibility for shared toilets is unclear, so people may resort to open defecation or unsafe shared facilities for extended periods. Intermittent water supply compounds the problem, because storing water in containers creates new opportunities for contamination, and rationing limits the water available for handwashing and cleaning. Each of these loops can keep fecal exposure elevated for weeks or months, sustaining the conditions under which cholera and other enteric diseases flourish and making recovery slower and more expensive than prevention would have been.

Building on recent calls for climate-resilient sanitation, the essay lays out a set of priorities that translate the concept into practice. The first is flood-resilient containment and fecal sludge services: designing latrines and septic systems that can withstand inundation, elevating or sealing containment where flooding is recurrent, and ensuring that sludge collection and treatment can continue or rapidly resume after a flood. The second concerns shared sanitation facilities, which are common in informal settlements and often fail not because of engineering but because of governance. The authors highlight the need for clear responsibility, along with cleaning and maintenance systems, so that shared toilets remain functional and hygienic rather than becoming points of concentrated exposure. These may sound like mundane management details, but in dense settlements a single poorly maintained shared block serving dozens of households can become an amplifier of transmission during a flood.

The remaining priorities extend from infrastructure to institutions and information. Routine maintenance and supply-chain reliability matter because sanitation systems fail quietly when spare parts, emptying services, and treatment chemicals are unavailable, and floods stress those supply chains at exactly the moment demand peaks. Community-engaged early warning and response is equally critical: residents of informal settlements are the first to know when latrines are flooding or water sources are turning turbid, and systems that channel that knowledge into rapid action, whether pre-emptive sludge emptying, water treatment distribution, or health surveillance, can intervene before contamination becomes an epidemic. Finally, the essay calls for monitoring systems that link service and environmental indicators to health outcomes, so that data on latrine functionality, water quality, and flood extent can feed directly into public health decision-making rather than sitting in separate silos managed by different agencies.

The broader significance of this argument lies in how it reframes the relationship between climate adaptation and infectious disease control. Much of the policy conversation about climate and health focuses on heat, vector-borne disease, and extreme weather mortality, while sanitation is often treated as a development sector with its own separate funding streams and institutions. The essay’s framing collapses that separation: in LMIC cities, a flood-resilient latrine is epidemic preparedness, and a reliable fecal sludge treatment plant is a cholera vaccine of sorts, working continuously and invisibly before any outbreak begins. As rainfall extremes intensify and informal settlements continue to grow, the authors’ message is that the durability of public health in these cities will be decided not only in clinics and laboratories but in the pits, pipes, and shared toilets that determine whether a storm remains a nuisance or becomes the first chapter of an epidemic.

Subject of Research: Flood-driven sanitation failure and cholera risk in urban informal settlements of low- and middle-income countries

Article Title: Flooding-driven sanitation failure and enteric disease risk in urban informal settlements: Cholera as an illustrative case for climate-resilient sanitation in low- and middle-income countries

Article References: Tusabe, F., Lebu, S., & Manga, M. (2026). Flooding-driven sanitation failure and enteric disease risk in urban informal settlements: Cholera as an illustrative case for climate-resilient sanitation in low- and middle-income countries. PLOS Climate, 5(9), e0001082. https://doi.org/10.1371/journal.pclm.0001082

Image Credits: AI Generated

DOI: 10.1371/journal.pclm.0001082

Keywords: cholera, sanitation, flooding, informal settlements, climate resilience, urban health, fecal sludge management, water quality, Lusaka, Zambia, enteric disease, epidemic preparedness