Search

Ensuring food security against climate risks has been a growing challenge recently. Weather index insurance has been pointed out as a tool for increasing the financial resilience of food production. However, the multi-hazard insurance design needs to be better understood. This paper aims to review weather index insurance design for food security resilience, including the methodology for calculating natural hazards' indices, vulnerability assessment, and risk pricing. We searched for relevant research papers in the Scopus database using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) protocol. Initially, 364 peer-reviewed papers from 1 January 2010 to 19 February 2022 were screened for bibliometric analysis. Then, the 26 most relevant papers from the last 5 years were systematically analyzed. Our results demonstrate that despite a significant research effort on index insurance, most papers focused on food production. However, research considering other aspects of food security, such as transportation, storage, and distribution, is lacking. Most research focuses on droughts. Other hazards, such as extreme temperature variation, excessive rainfall, and wildfires, were poorly covered. Most studies considered only single-hazard risk, and the multi-hazard risk studies assumed independence between hazards, neglecting the synergy hypothesis between hazards. Lastly, we proposed a conceptual framework that illustrates design paths for a generalized weather index insurance design and evaluation. Solutions for addressing multi-hazard problems are considered. An illustrative example demonstrates the importance of testing the multi-hazard risk hypothesis for weather-based index insurance design for soybean production in Brazil.

As the global economy expands, increasing losses of natural capital translate into substantially higher costs and inefficiencies in achieving future water security. Risk transfer is one risk management tools used to protect regions particularly vulnerable to the effects of extreme events that affect water availability. Index insurance has been investigated as a potential solution for dealing with drought events that lead to water scarcity in the water supply sector. Nonetheless, water scarcity can result not only from drought but also from the degradation of quality. Floods also have an impact on water supply, resulting in economic losses for the supply sector. Water supply services are under threat from a variety of hazards intensified by extremes of climate variability and climate change and socioeconomic factors. This work aims to discuss index insurance adaptation to cover financial losses incurred by water utility companies as a result of a variety of extreme hydrological events and uncertainty drivers, bringing opportunities to improve index insurance application to the sector. Given the complex vulnerability to different hazards related to the quantity and quality of raw water, in addition to the drivers of uncertainty affecting water availability, improved risk transfer model application is still required to incorporate such multiple risks and uncertainties. Many gaps and limitations in the design and implementation of water infrastructure insurance remain, including improved characterization of the relationship between droughts, floods, and pollution extremes and their implications in financial losses for supply; and the development of damage quantification methodologies, among other issues.

In Latin American and Caribbean (LAC) countries, Disaster Risk Reduction (DRR) options have accelerated “education for preparedness” initiatives for 100 million people living at >90,000 water-risk prone areas. Before and during COVID pandemic, innovative T-shaped (“breadth-and-depth”) labs of open science have promoted education towards the Agenda 2030. Here we depict actions delivered by the Water-Adaptive Design & Innovation lab (@TheWADILab) to provide citizen science with inclusiveness (CC+), as a learning accelerator of human-water coevolution under change (i.e. ‘Panta Rhei Open Science for Future Earth’, PROSFE). We summarize CC+PROSFE examples of practical learning with a blend of options at the DRR Center for Education and Research on Disasters (CEPED, www.ceped.eesc.usp.br) through: open access to data and tools, new mechanisms, hybrid curation platforms, competency-skill curricula, and blended education. First, examples have been applied during >1,200 hours of lectures of hydrology to >600 students, ranging from “puzzling 3D transboundary aquifer” for undergraduate students (Fig 1) to competency learning (skills, fundamentals, attitudes) of blended education for professionals (Fig 2). Second, CC+PROSFE aims to: (1) mobilize international cooperation to improve knowledge and innovation to address water security challenges at “Panta Rhei Schools", i.e. welcoming visiting scientists to the School of Advanced Studies in Water & Society Under Change (SASW≻ http://www1.eesc.usp.br/ppgshs/internacionalizacao), (2) strengthen science-policy interface to reach water security at local-to-global levels through the new UNESCO Chair in Urban Waters and the new WMO-Americas Regional Climate Centre hosted by Prohimet (https://www.prohimet.org/), (3) pave new pathways for water security knowledge to empower and activate citizenry at the local level using the Socio-Hydrological Observatory for Water Security (SHOWS), cycles of #OneDropOfScience #OneDoseOfResilience and Academia-Community’s Waters for Our World! Project (https://prg.usp.br/academia-comunidade-wow-waters-for-our-world/), and (4) develop institutional and human capacities for water security, sustainability and inspiration through water literacy and communication in the joint initiative of UNESCO-IHP-LAC & Pechakucha (https://www.pechakucha.com/events/agua-todavia-unesco-x-pechakucha).

Water is a critical resource for food production. Climate change has shown that shifts in precipitation regimes and increases in atmospheric temperature threaten food production worldwide. Therefore, it plays an essential role as a driver in the water-environment-food nexus. Strategies to cope with impacts of climate risk require understanding the relationship between hydro-meteorological extremes and crop yield shortfalls to guide decision-making. The purpose of this paper is to propose a fully data-driven model for predicting the impacts of hydrological extremes on food production for decision-making at the municipal level. We use the Support Vector Machine (SVM) model considering a variety of kernels for predicting crop yields using reanalysis data of water storage (WS) from 0 to 28 cm of soil during the soybean growing season. We used ERA5 WS data for Paraná state in Brazil and official annual soybean crop yields (SBY) at the municipal level. We tuned a SVM radial basis function kernel with sigma and cost parameters for municipalities with significant production of soybean. The SVM model predicted crop yields accurately with R² ranging from 0.12 to 0.85. The use of soil moisture data increased model accuracy from 30 to 95% and reduced error from 5 to 58% in relation to using only SBY, except for one location. These results indicate that the model is better able to depict SBY during drier conditions, reducing prediction accuracy in years with average or above average yields. The model we proposed is useful for estimating crop losses due to water shortage at the municipal level. Our results suggest that using WS data from ERA5 as an additional input to past SBY adds relevant information for several applications such as risk transfer, irrigation planning and farm-level management with data that are made available for most countries. Our model has potential for climate impact studies coupled with projections from Global Circulation Models forced by Shared Socioeconomic Pathways (SPP).