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.

Spatially compounding drought events affect multiple locations simultaneously, severely affecting food, water, energy, human health, and infrastructure sectors. Despite the cascading impacts and challenges compound droughts impose on society, we still lack an in‐depth understanding of spatially connected drought occurrences. Given the complexity and costs of droughts in Brazil, identifying regions prone to co‐experiencing droughts is critical for developing effective adaptation measures. Here, we develop a novel framework to assess the spatial co‐occurrence of hydrological drought events, which can be adapted for global applications to evaluate spatially compounding drought. This framework involves extracting drought data from individual catchments and calculating the co‐occurrence of droughts across all catchments. We apply this method to investigate the spatial connectedness of droughts in 511 Brazilian catchments over 39 years (1983–2022). Additionally, we classify catchments based on drought duration, intensity, deficit, number of events, and spatial connectedness to identify regions with similar drought behavior. Our findings reveal significant variability in drought characteristics and connectedness across Brazil, with the Central‐Northeast and Northwest Amazon regions being most affected by multiple and widespread droughts. We identify five distinct regions in Brazil that exhibit common drought behaviors, sharing attributes such as aridity, catchment area, and precipitation seasonality. These regions hold the potential to guide future adaptation plans for managing hydrological compound extremes at both the catchment and regional scales, including the development of risk pool networks. Our results underscore the importance of considering the interactions of spatially compounding hydrological droughts in risk assessments and adaptation strategies.

The climate-related variables, river discharge, and water temperature, are the main factors controlling the quality of the bank filtrate by affecting infiltration rates, travel times, and redox conditions. The impact of temperature and discharge on manganese release from a riverbed were assessed by water quality data from a monitoring transect at a riverbank filtration site in Dresden-Tolkewitz. Column experiments with riverbed material were used to assess the Mn release for four temperature and three discharge conditions, represented by varying infiltration rates. The observed Mn release was modeled as kinetic reactions via Monod-type rate formulations in PHREEQC. The temperature had a bigger impact than the infiltration rates on the Mn release. Infiltration rates of 20 °C to trigger the Mn release. With increasing temperatures, the infiltration rates became less important. The modeled consumption rates of dissolved oxygen are in agreement with results from other bank filtration sites and are potentially suited for the further application of the given conditions. The determined Mn reduction rate constants were appropriate to simulate Mn release from the riverbed sediments but seemed not to be suited for simulations in which Mn reduction is likely to occur within the aquifer. Sequential extractions revealed a decrease of easily reducible Mn up to 25%, which was found to reflect the natural stratification within the riverbed, rather than a depletion of the Mn reservoir.