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Throughout its history, Papua New Guinea (PNG) has faced recurrent agricultural droughts, imposing considerable strain on both livelihoods and the economy. Particularly severe droughts have been associated with El Niño climate patterns. During these episodes, PNG becomes especially vulnerable to extended periods of aridity and diminished precipitation. Historically, humanitarian assistance for these events has primarily focused on responding to emergencies after an agricultural drought has been declared and communities have already been impacted. Here, we developed a proactive agricultural drought-triggering method for anticipatory action (AA) in PNG to offer a more sustainable and cost-effective approach to address this hazard. Our AA uses weather forecasts and risk data to identify and implement mitigative actions before a disaster occurs. The research details a step-by-step guide from early warning to action implemented by the Food and Agricultural Organization of the United Nations and the Government of Papua New Guinea. This preemptive disaster risk management initiative integrates a combined drought index (CDI) with specific thresholds and tailored anticipatory actions based on crop calendars. Moreover, the developed CDI provides a 3-month lead time for implementing AA to reduce the impact of the agricultural drought. During the El Niño-induced drought event that began in 2023, the CDI was tested and the AA was piloted for the first time. [ABSTRACT FROM AUTHOR]

Advances in impact modeling and numerical weather forecasting have allowed accurate drought monitoring and skilful forecasts that can drive decisions at the regional scale. State-of-the-art drought early-warning systems are currently based on statistical drought indicators, which do not account for dynamic regional vulnerabilities, and hence neglect the socio-economic impact for initiating actions. The transition from conventional physical forecasts of droughts toward impact-based forecasting (IbF) is a recent paradigm shift in early warning services, to ultimately bridge the gap between science and action. The demand to generate predictions of “what the weather will do” underpins the rising interest in drought IbF across all weather-sensitive sectors. Despite the large expected socio-economic benefits, migrating to this new paradigm presents myriad challenges. In this article, we provide a comprehensive overview of drought IbF, outlining the progress made in the field. Additionally, we present a road map highlighting current challenges and limitations in the science and practice of drought IbF and possible ways forward. We identify seven scientific and practical challenges/limitations: the contextual challenge (inadequate accounting for the spatio-sectoral dynamics of vulnerability and exposure), the human-water feedbacks challenge (neglecting how human activities influence the propagation of drought), the typology challenge (oversimplifying drought typology to meteorological), the model challenge (reliance on mainstream machine learning models), and the data challenge (mainly textual) with the linked sectoral and geographical limitations. Our vision is to facilitate the progress of drought IbF and its use in making informed and timely decisions on mitigation measures, thus minimizing the drought impacts globally. This article is categorized under: Science of Water > Water Extremes Science of Water > Methods Science of Water > Water and Environmental Change [ABSTRACT FROM AUTHOR]

Over the past four decades, people around the globe have experienced unprecedented escalations in the frequency, intensity, magnitude, and location of anomalous hydrometeorological (hydromet) hazards attributed in large measure to the direct and indirect effects of global climate-change-related variability and extremes. The WMO, impelled by an unabated warming of the global climate system and its related extremely anomalous hydromet impacts, chose in March 2022 "Early Warning, Early Action" (EWEA) as the theme for its World Meteorology Day. The theme was praised in a press release by UN Secretary-General Antonio Guterres, who called for the development of a new EWEA initiative to ensure that "every person on Earth is protected by early warning systems within five years". By mid-2022, several meetings and workshops had already been held by the WMO to forge the new initiative on its road to the UN Climate Conference of Parties (COP27) in November in Sharm El Sheikh, Egypt. COP27 provided a suitably prominent venue for launching the new USD 3.1 billion, 5-year EWEA initiative; there, Secretary-General Guterres formally tasked the WMO, in partnership with the UNDRR, to lead it. But COP27 proved to be interesting as well as illuminating in other, less publicized ways having to do with EWEA. There, what had been the working title of the new initiative was officially changed to EW4A, "Early Warning for All". Despite the seemingly perfunctory nature of this change, the reality is that it will almost certainly have outsized impacts on the strengths, weaknesses, opportunities, and constraints (SWOC) met specifically in planning and implementing the new initiative's "early action" strategies and tactics. It is particularly important to bear in mind that, as things now stand, various unanticipated challenges having to do with the lack of organizational experience and capacity with regard to "early action" are likely to arise with the WMO-led implementation of the new initiative. Considering the new EW4A acronym as if it was a commercial brand can, like this, be instructive in thinking about how the seemingly perfunctory name change—from EWEA to EW4A—will impact the initiative's implementation of "early action". Doing so can be instructive because, just as the logos of companies like Apple, Nike, or Starbucks eventually became the face of their respective products, so too have branded acronyms like NASA, IOC, WHO, and INTERPOL become the face of their governmental institutions' or global initiatives' respective commissions and commitments. It follows then that if "consumer" interest is to be taken seriously and is (hopefully) long-lasting, then the branding of a new product or initiative must be undertaken with great consideration before a final identifier—be it a logo, a catchphrase, or an acronym—is selected. The question in the case of the new WMO-led initiative, then, is the following: Was this issue seriously taken into consideration before EWEA was so abruptly replaced by EW4A at COP27 in Egypt in November 2022? This pointed question is especially meant to highlight how the continued use of the original EWEA acronym by way of developing regional EWEA centers under the "Early Warning for All" umbrella has the possibility of turning regional potential energy into kinetic energy which will be essential if the theoretical gains of future "early warning" (EW) forecasting science are to be effectively translated into "early action" (EA) strategies and tactics that actually, finally, protect people and property across the entirety of the earth from the impending severe impacts of our changing climate future. Thus does this paper raise valid concerns about the balance between support and funding for EW and EA. [ABSTRACT FROM AUTHOR]

In the face of climate change, development and humanitarian practitioners increasingly recognize the need to anticipate and manage multiple, concurrent risks. One prominent example of this increasing focus on anticipation is the rapid growth of Forecast-based Financing (FbF), in particular within Red Cross and Red Crescent (RCRC). To evaluate how anticipatory efforts managed multiple compounding risks during the COVID-19 pandemic, we examine how 14 RCRC Societies adapted their Early Action Protocols to COVID-19. Though many National Societies successfully adapted to the onset of the additional hazard of COVID-19, we find that multi-hazard risk management can be improved by: proactively developing guidelines that enable rapid adaptation of existing plans; more flexible funding mechanisms; surge capacity to provide additional human resources; and increasing local capacity and ownership for implementation to ensure supplies, skills, and decision-making authority are available when communication or travel is restricted. These findings align with wider recommendations for improving development, humanitarian, and climate adaptation practice towards local capacity and agency. They also add urgency to broader calls for more flexible disaster financing and more practitioner-oriented investment in climate risk and multi-hazard management. [ABSTRACT FROM AUTHOR]

Sharing simple ideas across a broad community of practitioners helps them to work together more effectively. For this reason, drought early warning systems spend a considerable effort on describing how hazards are detected and defined. Well-articulated definitions of drought provide a shared basis for collaboration, response planning, and impact mitigation. One very useful measure of agricultural drought stress has been the “Water Requirement Satisfaction Index” (WRSI). In this study, we develop a new, simpler metric of water requirement satisfaction, the Phenological Water Balance (PWB). We describe this metric, compare it to WRSI and yield statistics in a food-insecure region (east Africa), and show how it can be easily combined with analog-based rainfall forecasts to produce end-of-season estimates of growing season water deficits. In dry areas, the simpler PWB metric is very similar to the WRSI. In these regions, we show that the coupling between rainfall deficits and increased reference evapotranspiration amplifies the impacts of droughts. In wet areas, on the other hand, our new metric provides useful information about water excess—seasons that are so wet that they may not be conducive to good agricultural outcomes. Finally, we present a PWB-based forecast example, demonstrating how this framework can be easily used to translate assumptions about seasonal rainfall outcomes into predictions of growing season water deficits. Effective humanitarian relief efforts rely on early projections of these deficits to design and deploy appropriate targeted responses. At present, it is difficult to combine gridded satellite-gauge precipitation forecasts with climate forecasts. Our new metric helps overcome this obstacle. Future extensions could use the water requirement framework to contextualize other water supply indicators, like actual evapotranspiration values derived from satellite observations or hydrologic models.

Abstract In this article, we provide an impact evaluation of an intervention in Peru regarding preparedness for El Niño impacts in Picsi District of Chiclayo Province in Peru’s northwestern coastal Lambayeque region. This effort involved the provision of special kits that reduce the potential damage to homes as a consequence of rainfall and floods associated with an El Niño-Southern Oscillation event. Information was collected in 2016 when this Forecast-based Financing early action was activated by an El Niño forecast, and after a coastal El Niño actually struck in 2017. This dual database permits us to estimate the impact of the intervention on the damage level of homes by comparing those homes supported by the program with those homes not receiving pilot-program support. This comparison is achieved by using propensity score matching techniques, which identify the most comparable homes to the ones that were supported by the intervention. The main findings of the study suggest a positive impact of the program in terms of its effectiveness in mitigating the damage caused by the 2017 El Niño. These results suggest a drop in the scale of house damage (less damage) by around 63% for a home that received the modular kit treatment. When considering other specifications of the model, the decrease in the scale of house damage improves up to approximately 66%.

The last decade has seen a major innovation within disaster risk management through the emergence of standardized forecast-based action and financing protocols. Given sufficient lead time and forecast skill, a portion of relief funds may be shifted from disaster recovery to disaster preparedness, reducing losses in lives and property. While short-term early warnings systems are commonplace, forecasts at the monthly or seasonal scale are relatively underused, despite their potential value. Incorporating both, numerous relief organizations have developed operational early action protocols for natural hazards. These plans may have well-defined forecasts, trigger criteria, and identification of early actions ranging from weeks to months prior to a predicted disaster, but many have not been explicitly optimized to maximize financial or utilitarian returns. This study investigates the effect of different forecast methodologies, performance metrics, and levels of risk aversion on optimal decision-making through a sensitivity analysis of an early action protocol, using a case study in coastal Peru. Results suggest that the relative benefit of actions at different lead times plays the largest role in determining optimal decisions, with forecast methodology and risk aversion playing a lesser role. The optimization framework is designed to be applicable even in the absence of post-disaster monitoring and evaluation, supporting the proliferation of adaptive early action protocols more broadly. Plain language summary: Forecast-based early actions for disasters are increasingly common, and some relief organizations have adopted standardized early action protocols to identify and respond to disasters. Because they are often new and untested, these protocols may not be optimized to provide the maximum return on investment. This paper presents a way to test different types of decisions in an early action protocol, including forecast type, willingness to take action, and ways in which to calculate benefits. We find that early preparation—that is, seasons or months in advance—is valuable, and that the value of preparation at different times before the disaster is more important than the accuracy of the forecasts or our willingness to take risks.

A growing body of literature has identified methane mitigation as a key component of limiting the rate and extent of global warming. However, little is known about how methane mitigation can benefit other critical aspects of the climate system. This study explores the value of early methane mitigation in addition to carbon dioxide mitigation in helping avert an approaching and concerning climate event: the near-complete loss of Arctic summer sea ice. While drastic cuts in carbon dioxide emissions will ultimately control the fate of Arctic summer sea ice, we show that simultaneous early deployment of feasible methane mitigation measures is essential to avoiding the loss of Arctic summer sea ice this century. In fact, the benefit of combined methane and carbon dioxide mitigation on reducing the likelihood of a seasonally ice-free Arctic can be greater than the simple sum of benefits from two independent greenhouse gas policies. The extent to which methane mitigation can help preserve Arctic summer sea ice depends on the implementation timeline. The benefit of methane mitigation is maximized when all technically feasible measures are implemented within this decade, and it decreases with each decade of delay in implementation due to its influence on end-of-century temperature. A key insight is that methane mitigation substantially lowers the risk of losing Arctic summer sea ice across varying levels of concomitant carbon dioxide mitigation. This analysis provides further evidence of the value of early methane mitigation and the need to consider its benefits beyond reduced global temperature and improved air quality.

In this article, we provide an impact evaluation of an intervention in Peru regarding preparedness for El Niño impacts in Picsi District of Chiclayo Province in Peru's northwestern coastal Lambayeque region. This effort involved the provision of special kits that reduce the potential damage to homes as a consequence of rainfall and floods associated with an El Niño-Southern Oscillation event. Information was collected in 2016 when this Forecast-based Financing early action was activated by an El Niño forecast, and after a coastal El Niño actually struck in 2017. This dual database permits us to estimate the impact of the intervention on the damage level of homes by comparing those homes supported by the program with those homes not receiving pilot-program support. This comparison is achieved by using propensity score matching techniques, which identify the most comparable homes to the ones that were supported by the intervention. The main findings of the study suggest a positive impact of the program in terms of its effectiveness in mitigating the damage caused by the 2017 El Niño. These results suggest a drop in the scale of house damage (less damage) by around 63% for a home that received the modular kit treatment. When considering other specifications of the model, the decrease in the scale of house damage improves up to approximately 66%. [ABSTRACT FROM AUTHOR]

Forecast‐based drought early warning/early action has been hampered by both inadequate decision‐making frameworks and a lack of appropriate funding mechanisms. Rural communities in Nicaragua and Ethiopia that have participated in resilience‐building interventions of varying durations demonstrate the value of community‐based actions informed by early warning, forecasts and drought management advice, both before and during the agricultural season. While drought affected all crops negatively, participants were better able to mitigate impacts, were more organised in accessing relief and recovered more effectively. These results are consistent with other research on the cost/benefit of anticipatory actions, use of climate services and appropriate drought management advice. They also confirm the importance of embedding short‐term early action in long‐term resilience‐building. Despite this, formal systems, national and local, remain essentially unimplemented. Systems being developed at global level now need to be operationalised and translated into effective local drought management standard operating procedures for the most vulnerable. [ABSTRACT FROM AUTHOR]

Over the past 40 years, drought has affected more people in the world than any other natural hazard, affecting large segments of the population and destroying the natural resource base, livestock and livelihoods. Recent projections show that drought events are expected to increase in frequency and intensity due to climate change. According to studies conducted by the Food and Agriculture Organization of the United Nations (FAO), 83% of all damages and losses caused globally by drought between 2006 and 2016 have been absorbed by agriculture, putting a large part of the world’s population at risk of food insecurity. This study shows the advantage of scaling-up FAO’s agricultural drought monitoring and early warning system (ASIS) and building the bridge with the anticipatory action, drought financial mechanisms, social protection and other initiatives for preventing the deterioration of food security and strengthening resilience. The results of the methodology that is based on and supported by the digital innovation, machine learning, matured knowledge and experiences accumulated over the past 10 years are illustrated with practical examples from different countries, ecological environments and crops. A fused time series of Advanced Very-High-Resolution Radiometer (AVHRR) data from Meteorological Operational satellite (METOP) and National Oceanic and Atmospheric Administration (NOAA) was used to produce a consistent time series of a vegetation health index (VHI) at 1 km spatial resolution from 1984 to present. VHI is multiplied by the crop coefficient (kc) to provide more responsiveness to the VHI anomaly that occurs during sensitive phenological phases to water stress such as a flowering and grain filling. The weighted VHI (wVHI) is integrated from the start of the season (SOS) up to the end of season (EOS). Once the temporal analysis of wVHI is completed, the spatial average is calculated using the values of pixels within a specific crop mask and administrative unit. The system proposed different vegetation indices to assess the impact of drought in agriculture; including an agricultural drought forecast that provide more time to the decision makers for implementing anticipatory actions to mitigate the drought in agriculture. Next generation agricultural stress index system (ASIS) offers full capabilities to support: parametric crop insurance, social protection schemes, early action, national drought management plans and to guide public investments.

Methane mitigation is essential for addressing climate change, but the value of rapidly implementing available mitigation measures is not well understood. In this paper, we analyze the climate benefits of fast action to reduce methane emissions as compared to slower and delayed mitigation timelines. We find that the scale up and deployment of greatly underutilized but available mitigation measures will have significant near-term temperature benefits beyond that from slow or delayed action. Overall, strategies exist to cut global methane emissions from human activities in half within the next ten years and half of these strategies currently incur no net cost. Pursuing all mitigation measures now could slow the global-mean rate of near-term decadal warming by around 30%, avoid a quarter of a degree centigrade of additional global-mean warming by midcentury, and set ourselves on a path to avoid more than half a degree centigrade by end of century. On the other hand, slow implementation of these measures may result in an additional tenth of a degree of global-mean warming by midcentury and 5% faster warming rate (relative to fast action), and waiting to pursue these measures until midcentury may result in an additional two tenths of a degree centigrade by midcentury and 15% faster warming rate (relative to fast action). Slow or delayed methane action is viewed by many as reasonable given that current and on-the-horizon climate policies heavily emphasize actions that benefit the climate in the long-term, such as decarbonization and reaching net-zero emissions, whereas methane emitted over the next couple of decades will play a limited role in long-term warming. However, given that fast methane action can considerably limit climate damages in the near-term, it is urgent to scale up efforts and take advantage of this achievable and affordable opportunity as we simultaneously reduce carbon dioxide emissions.

Diabetes is epidemic worldwide and places a huge burden on healthcare systems. The majority of the cost of type 2 diabetes (T2D) is related to hospitalization and the management of complications, and these also have a negative impact on the individual's quality of life. The Berlin Declaration is a global call for early action for the identification of high risk individuals, prevention of T2D and the prevention of complications in those with T2D, through prevention, early detection, early control and early access to the right multidisciplinary interventions. This should empower people to take action to prevent T2D and its complications. [ABSTRACT FROM AUTHOR]

Diabetes is a major global epidemic and places a huge burden on healthcare systems worldwide. The complications of type 2 diabetes (T2D) and related hospitalizations are major contributors to this burden, and there is strong evidence that the risk for these can be reduced by early action to identify and prevent progression of people at high risk of T2D and ensure tight glycemic control in those with established disease. In response to this, the Berlin Declaration was developed by four working groups of experts and ratified by healthcare professionals from 38 countries. Its aim is to act as a global call to action for early intervention in diabetes, in addition to providing short-, medium- and long-term targets that should be relevant to all nations. The Berlin Declaration focuses on four aspects of early action, and proposes actionable policies relating to each aspect: early detection, prevention, early control and early access to the right interventions. In addition, a number of treatment targets are proposed to provide goals for these policies. To ensure that the suggested policies are enacted in the most effective manner, the support of specialist care professionals is considered essential. [ABSTRACT FROM AUTHOR]

Climate shocks contribute to a significant share of the humanitarian burden, and are a key factor in increasing poverty and food insecurity. Social protection is increasingly recognised as an instrument to help build resilience to climate risks through long-term, large-scale national systems. However, most experiences to date have focused on social protection's role for chronic needs, or at best, shock-response, rather than on anticipation and prevention. This article argues that social protection can support more effective resilience building at scale by integrating early action and preparedness. We propose a concrete solution, namely linking a Forecast-based Financing mechanism to a social protection system to enable anticipatory actions based on forecast triggers and guaranteed funding ahead of a shock. Such a system may enhance scalability, timeliness, predictability and adequacy of social protection benefits. Key considerations for success of this emerging approach include sound analysis of forecast, risks, cost and benefits, and ring-fenced funding. [ABSTRACT FROM AUTHOR]

Armed conflict increases people's vulnerability to climate extremes. Since many of these climate extremes are predictable beforehand, Early Warning Early Action (EWEA) can help protect people's lives, livelihoods, and wellbeing. While such EWEA systems exist in several countries, there is limited scientific knowledge about EWEA in conflict-affected countries where communities experience the compounding effects of both disaster and conflict risks. By doing a retrospective analysis of the most severe disaster events and historical forecast information, this paper examines whether global forecast models predicted historical floods in conflict-affected regions and whether forecast information was communicated for droughts . It analyses the historical forecast availability and communication for the most severe disaster events in 20 countries affected by protracted conflict over the last 20 years. These 72 disaster events were reported to affect approximately 150 million individuals and more than 150,000 were reported dead. The results show that heavy rainfall was predicted in advance for 48 out of 50 flood events, with lead times of more than three days and probabilities between 10 and 90%. In addition, in 16 out of 20 major drought events a low rainfall forecast was communicated in advance of the disaster declaration. We conclude that forecasts exist and could be used to provide early warnings in conflict-affected areas. Further research is needed as to what extent forecast warnings did lead to early action to protect populations affected by conflict. [ABSTRACT FROM AUTHOR]

This article examines the state of the art of early warning in Africa. It looks at the definitions of early warning, considers the historical evolution of conflict early warning systems, and takes a critical look at the debate about the link or the gap between early warning and early action. To this end, it tries to answer some important questions, particularly in relation to the purpose of early warning systems (EWSs) and their limitations so as to ensure that EWSs and early warning analysts are taken for what they are, and not criticised for what they are not or cannot do. In essence, it underscores the fact that the field of conflict early warning is not a fortune-telling business; an industry aimed at predicting socio-political events. The field and its different actors and mechanisms typically serve various purposes and rely on networks and open sources as well as cooperation. At times, some actions are indeed taken and potential conflicts prevented, but these actions do not come to the attention of outside observers precisely because nothing happened. It acknowledges, however, that the field can still learn from past experiences and improve on its delivery, at the level of both analysis and the ensuing action. [ABSTRACT FROM PUBLISHER]

Current “business as usual” projections suggest greenhouse gas emissions from industrialized nations will grow substantially over the next decade. However, if it comes into force, the Kyoto Protocol will require industrialized nations to reduce emissions to an average of 5% below 1990 levels in the 2008–2012 period. Taking early action to close this gap has a number of advantages. It reduces the risks of passing thresholds that trigger climate change “surprises.” Early action also increases future generations' ability to choose greater levels of climate protection, and it leads to faster reductions of other pollutants. From an economic sense, early action is important because it allows shifts to less carbon-intensive technologies during the course of normal capital stock turnover. Moreover, many options for emission reduction have negative costs, and thus are economically worthwhile, because of paybacks in energy costs, healthcare costs, and other benefits. Finally, early emission reductions enhance the probability of successful ratification and lower the risk of noncompliance with the protocol. We discuss policy approaches for the period prior to 2008. Disadvantages of the current proposals for Credit for Early Action are the possibility of adverse selection due to problematic baseline calculation methods as well as the distributionary impacts of allocating a part of the emissions budget already before 2008. One simple policy without drawbacks is the so-called baseline protection, which removes the disincentive to early action due to the expectation that businesses may, in the future, receive emission rights in proportion to past emissions. It is particularly important to adopt policies that shift investment in long-lived capital stock towards less carbon-intensive technologies and to encourage innovation and technology development that will reduce future compliance costs. [ABSTRACT FROM AUTHOR]

Over the past 40 years, drought has affected more people in the world than any other natural hazard, affecting large segments of the population and destroying the natural resource base, livestock and livelihoods. Recent projections show that drought events are expected to increase in frequency and intensity due to climate change. According to studies conducted by the Food and Agriculture Organization of the United Nations (FAO), 83% of all damages and losses caused globally by drought between 2006 and 2016 have been absorbed by agriculture, putting a large part of the world's population at risk of food insecurity. This study shows the advantage of scaling-up FAO's agricultural drought monitoring and early warning system (ASIS) and building the bridge with the anticipatory action, drought financial mechanisms, social protection and other initiatives for preventing the deterioration of food security and strengthening resilience. The results of the methodology that is based on and supported by the digital innovation, machine learning, matured knowledge and experiences accumulated over the past 10 years are illustrated with practical examples from different countries, ecological environments and crops. A fused time series of Advanced Very-High-Resolution Radiometer (AVHRR) data from Meteorological Operational satellite (METOP) and National Oceanic and Atmospheric Administration (NOAA) was used to produce a consistent time series of a vegetation health index (VHI) at 1 km spatial resolution from 1984 to present. VHI is multiplied by the crop coefficient (kc) to provide more responsiveness to the VHI anomaly that occurs during sensitive phenological phases to water stress such as a flowering and grain filling. The weighted VHI (wVHI) is integrated from the start of the season (SOS) up to the end of season (EOS). Once the temporal analysis of wVHI is completed, the spatial average is calculated using the values of pixels within a specific crop mask and administrative unit. The system proposed different vegetation indices to assess the impact of drought in agriculture; including an agricultural drought forecast that provide more time to the decision makers for implementing anticipatory actions to mitigate the drought in agriculture. Next generation agricultural stress index system (ASIS) offers full capabilities to support: parametric crop insurance, social protection schemes, early action, national drought management plans and to guide public investments. [ABSTRACT FROM AUTHOR]

People possess a creative set of strategies based on their local knowledge (LK) that allow them to stay in flood-prone areas. Stakeholders involved with local level flood risk management (FRM) often overlook and underutilise this LK. There is thus an increasing need for its identification, documentation and assessment. Based on qualitative research, this paper critically explores the notion of LK in Malawi. Data was collected through 15 focus group discussions, 36 interviews and field observation, and analysed using thematic analysis. Findings indicate that local communities have a complex knowledge system that cuts across different stages of the FRM cycle and forms a component of community resilience. LK is not homogenous within a community, and is highly dependent on the social and political contexts. Access to LK is not equally available to everyone, conditioned by the access to resources and underlying causes of vulnerability that are outside communities' influence. There are also limits to LK; it is impacted by exogenous processes (e.g., environmental degradation, climate change) that are changing the nature of flooding at local levels, rendering LK, which is based on historical observations, less relevant. It is dynamic and informally triangulated with scientific knowledge brought about by development partners. This paper offers valuable insights for FRM stakeholders as to how to consider LK in their approaches. [ABSTRACT FROM AUTHOR]