Multi-Hazard Climate Vulnerability Assessment of 18 PROKLIM Pilot Villages in Gorontalo Province, Indonesia

Climate change represents a critical challenge for sustainable development, as its impacts extend beyond long-term environmental shifts and increasingly manifest as recurrent hazards that disrupt livelihoods, infrastructure, public health, and ecosystem services. The Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) highlights that both human and ecological systems are already experiencing intensified climate-related risks, with the most severe effects often borne by populations with limited adaptive capacity [1]. In tropical developing regions, these risks are compounded by the interaction of climatic stressors with rapid land-use change, uneven infrastructure, poverty, and high reliance on climate-sensitive sectors. Southeast Asia exemplifies a region where monsoon variability, rising temperatures, extreme rainfall, sea-level rise, and hydrometeorological disasters intersect with densely populated rural and coastal settlements, underscoring the necessity of local-scale vulnerability assessments for effective adaptation planning [2, 3].

In Indonesia, climate change is manifested through shifts in rainfall patterns, rising temperatures, increased seasonal uncertainty, drought, floods, landslides, extreme winds, coastal inundation, and degradation of environmental support systems. These hazards have direct implications for agriculture, water resources, settlements, infrastructure, health, and coastal livelihoods. Rural and peri-urban communities are often exposed to multiple risks because their livelihoods depend on land, water, ecosystem stability, and basic infrastructure that may be sensitive to climate variability. Studies in Southeast Asia show that flood risk, water insecurity, salinization, and heat stress are not merely physical phenomena; they become development risks when they reduce agricultural productivity, disrupt household income, damage roads and drainage systems, affect water quality, and increase the burden of climate-sensitive diseases [4-6]. Therefore, climate vulnerability must be understood as a place-based condition produced by the interaction between hazards, exposed populations and assets, sectoral sensitivity, and the capacity of communities and institutions to respond.

Despite increased policy focus on climate adaptation, many local contexts continue to lack integrated, standardized vulnerability information at the village scale. While national and provincial assessments help identify broad patterns of climate risk, they often obscure critical differences among villages in topography, livelihood structures, infrastructure, demographic composition, water access, and disaster history. This limitation is significant because adaptation measures are implemented at specific locations where risks are shaped by local biophysical and socio-economic factors. Research on flood and climate risk in Southeast Asia indicates that vulnerability assessments often prioritize hazard and exposure, with insufficient attention to social, institutional, and livelihood-related determinants of vulnerability [6]. Consequently, adaptation priorities may not effectively target the communities and sectors most in need of intervention.

A further challenge is the fragmentation of climate-risk information across sectoral datasets, administrative reports, disaster records, spatial maps, and community observations. This fragmentation impedes decision-makers' ability to compare vulnerability levels across locations and to design adaptation strategies that are both technically robust and socially relevant. For communities exposed to floods, droughts, landslides, extreme winds, and coastal hazards, fragmented data often result in generic interventions that fail to address specific risk pathways. For instance, villages with similar exposure to rainfall extremes may differ significantly in vulnerability due to variations in drainage capacity, access to clean water, demographic composition, reliance on agriculture, infrastructure quality, and the presence of local preparedness institutions. Therefore, an integrated approach that combines biophysical, socio-economic, infrastructural, and institutional indicators within a coherent framework is necessary to support evidence-based prioritization.

The vulnerability framework developed in climate change research provides a conceptual basis for addressing this problem. The IPCC tradition defines vulnerability as a function of exposure, sensitivity, and adaptive capacity, where exposure refers to the presence of people, livelihoods, ecosystems, infrastructure, or assets in places that could be adversely affected; sensitivity refers to the degree to which these systems are affected by climate stimuli; and adaptive capacity refers to the ability to adjust, cope, recover, or transform in response to risks [1] This framework has been widely applied in local and household-level studies because it allows researchers to move beyond hazard description and examine why some communities suffer greater impacts than others. Livelihood vulnerability studies also demonstrate that food, water, health, livelihood strategies, land access, and disaster frequency can be translated into composite indicators that reveal spatial and social differences in climate vulnerability [7, 8].

Previous studies further suggest that local climate adaptation becomes more actionable when vulnerability assessment is combined with participatory methods and spatial analysis. Mixed-method designs allow researchers to integrate quantitative indicators, community perceptions, key informant knowledge, and field observations, while geographic information systems (GIS) can visualize the spatial distribution of hazards and vulnerable assets. Such approaches are especially relevant in archipelagic and tropical settings, where risk is spatially uneven and shaped by micro-scale environmental conditions. In Indonesia, village-level vulnerability mapping has been institutionalized through tools such as the vulnerability index Data Information System, which uses exposure, sensitivity, and adaptive capacity indicators to support the identification of priority locations and adaptation actions. Community-based programs such as Program Kampung Iklim also indicate the importance of linking climate assessment with locally implemented adaptation practices, including water management, sanitation improvement, livelihood diversification, disaster preparedness, and ecosystem-based protection.

The literature closely related to this study provides important guidance but also reveals a gap. Studies on Southeast Asian climate vulnerability have examined flood risk, coastal resilience, mangrove-based adaptation, climate-smart agriculture, water insecurity, and livelihood diversification [9-12]. However, many assessments remain focused on a single sector, a particular hazard, or a broader administrative scale. There is still a need for integrated village-scale assessments that compare multiple locations using a consistent framework and document sectoral impacts across agriculture, water resources, public health, settlements, infrastructure, and coastal areas. This gap is especially relevant for Gorontalo Province, where pilot villages represent diverse urban, lowland, upland, agricultural, and coastal systems, yet climate vulnerability information remains insufficiently consolidated for prioritizing adaptation interventions.

This study addresses the identified gap by evaluating climate vulnerability and qualitative climate-risk pathways across 18 pilot villages and urban wards in Gorontalo Province within the Result-Based Payment (RBP) Reducing Emissions from Deforestation and forest Degradation (REDD+) Green Climate Fund Output 2 framework. The analysis focuses exclusively on climate-related hazards and does not assess greenhouse gas emission sources. The objectives are to: (i) identify the dominant climate-related hazards experienced by the pilot locations; (ii) develop a transparent and reproducible village-level vulnerability index using exposure, sensitivity, and adaptive-capacity indicators; (iii) interpret how hazards interact with livelihood, infrastructure, water, health, settlement, and coastal conditions; and (iv) provide an evidence-based baseline for prioritizing Climate Village Program (PROKLIM) adaptation actions. The novelty of the study lies in its integrated, site-based, and spatially explicit assessment across diverse urban, lowland, upland, agricultural, and coastal village typologies in Gorontalo.

Table 3. Classification of climate vulnerability levels based on exposure, sensitivity, and adaptive capacity indicators

3.4 Sectoral impacts of climate change

Agriculture emerged as one of the most climate-sensitive sectors in the study area. The main agricultural impacts included reduced productivity, increased crop failures, disrupted planting calendars, and uncertainty about water availability. Villages with agricultural land were more vulnerable when farming systems depended on seasonal rainfall, irrigation reliability was limited, or land degradation reduced soil resilience. Drought and extreme temperatures increased crop stress, while heavy rainfall and flooding damaged fields, delayed cultivation, and increased the likelihood of harvest loss. These results align with the climate-smart agriculture literature, which shows that rainfall variability, heat stress, and extreme events directly affect smallholder production through altered growing seasons, pest and disease pressure, water stress, and reduced yields [2, 9, 22].

The findings also indicate that agricultural vulnerability is not only biophysical but also socio-economic. Farmers with limited resources, weak access to inputs, low livelihood diversification, or limited access to climate information are less able to adjust planting schedules or invest in adaptive practices. Consequently, adaptation in the agricultural sector should include improved water management, crop diversification, climate information services, soil and land conservation, and support for climate-resilient livelihood strategies. Such measures are consistent with previous studies that emphasize climate-smart agriculture and livelihood diversification as key responses to reduce sensitivity in tropical rural communities [21, 22].

Water-resource impacts were evident in both dry and wet climate conditions. During dry periods, several villages experienced increased pressure on household and agricultural water supply, especially where communities relied on limited or unevenly distributed water sources. During high-rainfall periods, water quality and sanitation risks increased, particularly in settlements with weak drainage or incomplete sanitation infrastructure. This dual pressure reflects the broader climate-water security problem identified in Southeast Asia, where rainfall variability, urbanization, and uneven infrastructure jointly affect water availability, water quality, and household resilience [5, 11].

The findings suggest that water security is a cross-cutting determinant of adaptive capacity. Villages with more stable access to clean water were better positioned to cope with climate stress, while villages with limited or seasonally variable water access were more vulnerable to drought and health-related impacts. Adaptation priorities should therefore include water-source protection, improved distribution systems, rainwater harvesting, sanitation improvement, and community-based water governance. These interventions would not only address immediate water needs but also strengthen long-term resilience to rainfall variability and extreme climate events.

Climate-related health impacts were associated with flooding, heat exposure, water insecurity, and sanitation risks. Flooding and inundation can increase exposure to waterborne and vector-borne diseases, particularly where drainage is poor or sanitation facilities are inadequate. Extreme temperatures can increase heat stress and dehydration risk, especially for elderly populations, children, outdoor workers, and households with limited access to clean water. The assessment identified children and elderly people as socially and biologically vulnerable groups, reinforcing the need to integrate demographic sensitivity into local climate-risk analysis.

These results are consistent with the broader climate-health literature, which recognizes that climate change affects health through direct exposure to heat and disasters as well as indirect pathways involving water quality, sanitation, nutrition, and disease ecology [1]. In Gorontalo, public health adaptation should therefore be linked to water management, sanitation, early warning, health service readiness, and community education. Climate-health risks cannot be separated from settlement conditions and basic service provision, as health impacts are amplified when environmental hazards interact with inadequate infrastructure.

Settlements and infrastructure were affected primarily through flooding, inundation, landslides, strong winds, and coastal processes. The most common impacts included disrupted access roads, damaged drainage systems, vulnerable housing, and reduced access to public services during extreme events. In upland areas, slope instability and land degradation increased the potential for erosion and landslide-related damage. In coastal areas, inundation, abrasion, and degradation of coastal protection systems increased the exposure of households, roads, and livelihoods. These findings are consistent with studies showing that climate hazards in tropical regions affect settlements by damaging physical assets, disrupting mobility, and weakening protective ecosystems such as mangroves and coastal vegetation [10-12].

The results highlight the importance of spatially targeted adaptation. Lowland and urban settlements require improvements in drainage and flood management, as well as resilient road planning. Upland villages require slope stabilization, vegetation restoration, erosion control, and risk-sensitive land management. Coastal villages require ecosystem-based adaptation, shoreline protection, and integration of coastal risk into village development planning. Overall, the sectoral results demonstrate that climate impacts in the 18 pilot locations are interconnected across agriculture, water, health, settlements, infrastructure, and coastal systems. This interconnection reinforces the need for integrated adaptation planning rather than sectoral interventions designed in isolation. Sectoral pathways through which climate hazards affect agriculture, water resources, public health, settlements, infrastructure, and coastal areas are shown in Figure 2.

Figure 2. Sectoral pathways through which climate hazards affect agriculture, water resources, public health, settlements, infrastructure, and coastal areas

This study demonstrates that climate vulnerability across the 18 PROKLIM pilot villages and urban wards in Gorontalo Province is shaped by the interaction between recurrent hydrometeorological hazards, socio-economic sensitivity, and uneven adaptive capacity. The vulnerability index ranged from 0.460 to 0.691, with 14 villages classified as medium vulnerability and 4 villages classified as high vulnerability. The hazard-priority rubric identified 10 high, 6 moderate, and 2 low priority locations. Floods and inundation, drought, extreme temperature, landslides, land degradation, strong winds, and coastal impacts were the dominant hazards affecting the study area.

The study confirms that village-scale climate vulnerability cannot be explained by hazard exposure alone. Socio-economic conditions, infrastructure quality, institutional support, and access to adaptive resources strongly influenced whether hazards translated into serious impacts. The reproducible formula V = (E + S + LAC)/3 clarified the role of exposure, sensitivity, and LAC, while sensitivity analysis showed that the medium-to-high vulnerability pattern remained robust under alternative weighting assumptions. Adaptive capacity emerged as the most important practical entry point for reducing climate-related impacts through improved water access, drainage, sanitation, resilient infrastructure, livelihood diversification, local institutions, and preparedness.

The study contributes to village-scale climate vulnerability assessment in tropical regions by translating climate-risk concepts into operational local indicators for community-based adaptation planning. The findings provide an evidence-based baseline for strengthening PROKLIM implementation and supporting regional climate-resilience planning in Gorontalo Province. Future studies should incorporate longitudinal monitoring, household-level inequality analysis, and climate projections to better capture dynamic vulnerability patterns and evaluate the long-term effectiveness of adaptation interventions.