Floods and rivers: a circular causality perspective

Upscaling drought resilience by coupling soil data and UAV-multispectral imageries

Monitoring crop responses to drought is crucial for understanding the progressive impact of drought on food production and identifying management practices that can enhance agricultural resilience. This study combined drone-based multispectral data (MDd) with laboratory determination over multiple pilot farms to identify the main soil physical and chemical parameters correlated with a crop health index (SVI- Standardized Vegetation Index), which compares the Normalized Difference Vegetation Index (NDVI) at the observed time to historical (NDVI at similar dates in previous years) values. Significant relationships were found between MDd and selected soil properties for different crops. Differences found at the plot scale were primarily related to texture, organic carbon and total nitrogen content, resulting in heterogeneous responses to droughts. The performance of the proposed indicators was further validated for the same crops by extending the findings across similar climatic regions in Europe, using satellite-based multispectral data (MDs) and field-based soil data from LUCAS (Land Use/Cover Area frame statistical Survey Soil) for 2018, as well as MDs and digital soil data from SoilGrids 2.0 for 2022. Varying drought magnitudes were also considered. The method effectively identified drought-prone areas and distinguished crop health across varying drought intensities, making it a valuable tool for drought monitoring and agricultural planning.

Monitoring flood risk evolution: A systematic review

Land-use change, climate change, human interventions, and socio-economic developments influence the evolution of the risk components hazard, exposure, and vulnerability, and consequently of flood risk. Adaptive flood risk management is a way to cope with evolving risks, but it requires measuring the evolution of risks. To develop principles of flood risk monitoring, we systematically reviewed scientific literature on flood risk evolution analyses. The reviewed publications indicate a wide spread in increase or decrease of flood risk evolution over decades. Furthermore, the publications show a high diversity in factors and methods for flood risk evolution analysis and indicate the main challenges for developing flood risk monitoring. Flood risk monitoring needs the systematic detection of flood risk evolution by periodically (re)evaluate the factors that influence the risk components-hazard, exposure and vulnerability-modeling those risk components and combining them to quantify flood risk.

Factors Affecting Survival of Common Sandpiper (Actitis hypoleucos) Nests along the Semi-Natural Vistula River in Poland

Predation is an important factor limiting bird populations and is usually the main factor influencing nest survival. In riverine habitats, flooding poses an additional significant challenge. Our study aimed to elucidate the influence of nest location and incubation timing on the survival of common sandpiper nests in a large, semi-natural, lowland river. The survey was carried out in central Poland on the Vistula River, in 2014-2015, 2021, and 2023, along two river sections 2 km and 10 km in length. The nest survival rate was 27%, which is twice as low as that reported on small upland rivers, with flooding being an additional factor causing losses on the Vistula River. Our research showed that mammalian and avian predation accounted for 51% of losses and flooding for 49% of losses. The negative impact of floods on nest survival decreased as the breeding season progressed between May and July, while the chances of being depredated increased during the same period. Nests placed under shrubs were less likely predated than nests located in grass. Moreover, locating the nest in proximity to water increased nesting survival and in fact, more nests found in our study were situated close to the water's edge.

Local and Environmental Reservoirs of Salmonella enterica After Hurricane Florence Flooding

In many regions of the world, including the United States, human and animal fecal genetic markers have been found in flood waters. In this study, we use high-resolution whole genomic sequencing to examine the origin and distribution of Salmonella enterica after the 2018 Hurricane Florence flooding. We specifically asked whether S. enterica isolated from water samples collected near swine farms in North Carolina shortly after Hurricane Florence had evidence of swine origin. To investigate this, we isolated and fully sequenced 18 independent S. enterica strains from 10 locations (five flooded and five unflooded). We found that all strains have extremely similar chromosomes with only five single nucleotide polymorphisms (SNPs) and possessed two plasmids assigned bioinformatically to the incompatibility groups IncFIB and IncFII. The chromosomal core genome and the IncFIB plasmid are most closely related to environmental Salmonella strains isolated previously from the southeastern US. In contrast, the IncFII plasmid was found in environmental S. enterica strains whose genomes were more divergent, suggesting the IncFII plasmid is more promiscuous than the IncFIB type. We identified 65 antibiotic resistance genes (ARGs) in each of our 18 S. enterica isolates. All ARGs were located on the Salmonella chromosome, similar to other previously characterized environmental isolates. All isolates with different SNPs were resistant to a panel of commonly used antibiotics. These results highlight the importance of environmental sources of antibiotic-resistant S. enterica after extreme flood events.

Global assessment of storm disaster-prone areas

Background

Advances in climate change research contribute to improved forecasts of hydrological extremes with potentially severe impacts on human societies and natural landscapes. Rainfall erosivity density (RED), i.e. rainfall erosivity (MJ mm hm^-2 h^-1 yr^-1) per rainfall unit (mm), is a measure of rainstorm aggressiveness and a proxy indicator of damaging hydrological events.

Methods and findings

Here, using downscaled RED data from 3,625 raingauges worldwide and log-normal ordinary kriging with probability mapping, we identify damaging hydrological hazard-prone areas that exceed warning and alert thresholds (1.5 and 3.0 MJ hm^-2 h^-1, respectively). Applying exceedance probabilities in a geographical information system shows that, under current climate conditions, hazard-prone areas exceeding a 50% probability cover ~31% and ~19% of the world’s land at warning and alert states, respectively.

Conclusion

RED is identified as a key driver behind the spatial growth of environmental disruption worldwide (with tropical Latin America, South Africa, India and the Indian Archipelago most affected).

Disentangling the ecosystem service 'flood regulation': Mechanisms and relevant ecosystem condition characteristics

Riverine floods cause increasingly severe damages to human settlements and infrastructure. Ecosystems have a natural capacity to decrease both severity and frequency of floods. Natural flood regulation processes along freshwaters can be attributed to two different mechanisms: flood prevention that takes place in the whole catchment and flood mitigation once the water has accumulated in the stream. These flood regulating mechanisms are not consistently recognized in major ecosystem service (ES) classifications. For a balanced landscape management, it is important to assess the ES flood regulation so that it can account for the different processes at the relevant sites. We reviewed literature, classified them according to these mechanisms, and analysed the influencing ecosystem characteristics. For prevention, vegetation biomass and forest extent were predominant, while for mitigation, the available space for water was decisive. We add some aspects on assessing flood regulation as ES, and suggest also to include flood hazard into calculations.

Multiscale Hydrogeomorphometric Analysis for Fluvial Risk Management. Application in the Carrión River, Spain

The sustainable management of fluvial systems requires reliable knowledge of the mechanisms that control the basins and their drainages, which in turn must be prioritized for the application of measures for flood-risk reduction. Thus, given the need to develop methodological frameworks capable of integrating remote sensing technologies at different scales, as well as traditional metrics and anthropic variables, in this study, a multiscale method is proposed for the characterization and prioritization of river stretches for fluvial risk management. This methodology involves the study of drivers at the watershed level, and a detailed morphometric and hydrogeomorphological analysis of the main channel for fluvial landscape classification, segmentation, and aggregation into units, considering also anthropic variables. Therefore, it includes the use of LiDAR data and exploration GIS tools, whose results are corroborated through fieldwork, where ephemeral and topographic evidence of fluvial dynamics are collected. The procedure is validated in the Carrión river basin, Palencia, Spain, where a high degree of maturity and geomorphological development are determined. Hence, the main channel can be classified into eight geomorphic units and divided into homogeneous segments, which, according to categorical elements such as urban interventions, are prioritized, obtaining, as a result, six stretches of main interest for river risk management.