Globally, the direct cost of natural disasters stands in the hundreds of billions of USD per year, at a time when water resources are under increasing stress and variability. Much of this burden rests on low- and middle-income countries that, despite their relative lack of wealth, exhibit considerable vulnerability such that losses measurably impact GDP. Within these countries, a growing middle class retains much of its wealth in property that may be increasingly exposed, while the few assets the poor may possess are often highly exposed. Vulnerability to extreme events is thus heterogeneous at both the global and subnational level. Moreover, the distribution and predictability of extreme events is also heterogeneous. Disaster managers and relief organizations are increasingly consulting operational climate information services as a way to mitigate the risks of extreme events, but approp...

Geographically isolated places are often sites of exported environmental risks, intense resource extraction,exploitation and marginalization, and social policy neglect. These conditions create unique challengesrelated to vulnerability and adaptation that have direct disaster management implications. Our researchinvestigates the relationship between geographic isolation and flood-related social vulnerability across Peru’secological regions. Ecoregions have different relationships with colonialism and capitalism that shapevulnerability, and we hypothesize that the relationship between vulnerability and geographic isolation variesacross ecoregions. Using mapping techniques and spatial regression analysis, we find that relationshipsbetween vulnerability and geographic isolation vary regionally, with differences that suggest alignment withregional contexts of extraction. We find notable dif...

Disaster planning has historically allocated minimal effort and finances toward advanced preparedness; however, evidence supports reduced vulnerability to flood events, saving lives and money, through appropriate early actions. Among other requirements, effective early action systems necessitate the availability of high-quality forecasts to inform decision making. In this study, we evaluate the ability of statistical and physically based season-ahead prediction models to appropriately trigger flood early preparedness actions based on a 75 % or greater probability of surpassing the 80th percentile of historical seasonal streamflow for the flood-prone Marañón River and Piura River in Peru. The statistical prediction model, developed in this work, leverages the asymmetric relationship between seasonal streamflow and the ENSO phenomenon. Additionally, a multi-model (least-squares combina...

Weather forecasts, climate change projections, and epidemiological predictions all represent domains that are using forecast data to take early action for risk management. However, the methods and applications of the modeling efforts in each of these three fields have been developed and applied with little cross-fertilization. This perspective identifies best practices in each domain that can be adopted by the others, which can be used to inform each field separately as well as to facilitate a more effective combined use for the management of compound and evolving risks. In light of increased attention to predictive modeling during theCOVID-19 pandemic,we identify three major areas that all three of these modeling fields should prioritize for future investmentand improvement: (1) decision support, (2) conveying uncertainty, and (3) capturingvulnerability.

In June 2018, the Peruvian provinces of Arequipa and Puno in the southern Andean region were affected by heavy snowfall, which caused severe damage to people and livelihoods in several communities. Using the Forecast-based Financing approach, the Peruvian Red Cross implemented its pre-defined early action protocol before this event, after receiving an extreme snowfall warning (Level 4) from the Peruvian meteorological service. Here, we provide a case study of the approach and event itself, documenting the decision-making thresholds as well as the actions taken. This warning activated the thresholds established in the protocol, and Peruvian Red Cross prioritized 10 communities for pre-disaster support based on the forecasted severity of the event in combination with vulnerability and exposure information. The activation took place 2 days before the extreme snowfall in the communities, and...

Social vulnerability is a key component of the risk equation alongside the context of the hazard and exposure. Increasingly, social vulnerability indices are used to better understand and predict the consequences of disasters, and support the development of improved disaster management policies. Humanitarian organisations particularly strive to capture social vulnerability in their decision processes relative to prioritisation of actions before disasters occur. This research sup- ports the Ecuadorian Red Cross in generating a flood-specific social vulnerability index to inform flash flood early action at the Parroquia level in Ecuador. This paper compares the results from the two most common approaches used to create composite indices, one using the weighting of variables from disaster experts’ judgments (referred to as Expert method) and the other using PCA analysis, with one or more ...

In June 2018, the Peruvian provinces of Arequipa and Puno in the southern Andean region were affected by heavy snowfall, which caused severe damage to people and livelihoods in several communities. Using the Forecast-based Financing approach, the Peruvian Red Cross implemented its pre-defined early action protocol before this event, after receiving an extreme snowfall warning (Level 4) from the Peruvian meteorological service. Here, we provide a case study of the approach and event itself, documenting the decision-making thresholds as well as the actions taken. This warning activated the thresholds established in the protocol, and Peruvian Red Cross prioritized 10 communities for pre-disaster support based on the forecasted severity of the event in combination with vulnerability and exposure information. The activation took place 2 days before the extreme snowfall in the communities, and...

Empirical evidence shows that acting on early warnings can help humanitarian organizations reduce losses, damages and suffering while reducing costs. Available forecasts of extreme events can provide the information required to automatically trigger preparedness measures, while ‘value of information’ approaches can, in principle, guide the selection of forecast thresholds that make early action preferable to inaction. We acknowledge here that, for real-world humanitarian situations, the value of information approach accurately estimates the value of forecasts only if key factors relevant for the humanitarian sector are taken into account. First, the negative consequences of acting in vain are significant and must be factored in. Secondly, the “most valuable” forecast thresholds depend on criteria beyond expenses reduction, and this choice must be explicitly considered in funding ...

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 o...

Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Niño–Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tro...

The analysis of historical disaster events is a critical step towards understanding current risk levels and changes in disaster risk over time. Disaster databases are potentially useful tools for exploring trends, however, criteria for inclusion of events and for associated descriptive characteristics is not standardized. For example, some databases include only primary disaster types, such as ‘flood’, while others include subtypes, such as ‘coastal flood’ and ‘flash flood’. Here we outline a method to identify candidate events for assignment of a specific disaster subtype—namely, ‘flash floods’—from the corresponding primary disaster type—namely, ‘flood’. Geophysical data, including variables derived from remote sensing, are integrated to develop an enhanced flash flood confidence index, consisting of both a flash flood confidence index based on text mining of ...