Major Flood Events Research Articles

Spatial and Temporal Dynamics of Chemical and Microbial Contamination in Nonurban Floodwaters.

During major flood events, waterborne contaminants are relatively poorly characterized. This is due to logistical difficulties associated with obtaining water samples in potentially dangerous flood conditions. Herein, we report analyses of water samples from a large, flooded landscape in Victoria, Australia, during a major flood event. We collected 83 samples from seven rivers and 18 river locations as far apart as 520 km. The sampling campaign covered a 26-day window, with 3 samples taken weekly from each site. Floodwater samples were analyzed for 778 contaminants and 544 microbial species were identified using eDNA. Our study shows that 85 contaminants were detected in floodwaters. Fungicides, phthalates, plant macronutrients, metal(loid)s and PPCPs were better explained by land uses, whereas herbicides and insecticides were explained by a mixture of land use and water flow data. Potentially pathogenic orders with the highest detection rates were Enterobacterales (82.4%), Mycobacteriales (70.6%) and Legionellales (58.8%). Contaminants and microbial signatures responded to rainfall, water flow and water level, demonstrating increased and varied human and environmental risks of exposure during the sampling window. Our work underlines the importance of rigorous and timely monitoring and provides an evidence-base for decision making during increasingly frequent and intense climate driven flood events.

An Assessment of Land Use and Land Cover Changes on Urban Flooding: A Case Study in Sri Jayewardenepura Kotte

This study investigates the relationship between Land Use and Land Cover (LULC) changes and urban flooding in the Sri Jayewardenepura Kotte Divisional Secretariat Division (DSD). The research objectives include analysing flooding patterns, mapping LULC changes, and assessing the correlation between these changes and flooding occurrences. Additionally, a temporal rainfall variation analysis was conducted to provide further context. The study employed Geographic Information System (GIS) technology, specifically utilising ArcGIS for LULC classification and Inverse Distance Weighting (IDW) interpolation technique for rainfall data. The analysis reveals a clear association between heightened precipitation and major flood events. In 2010, the flood inundation area was 5.762 km² during the major flood in May, despite a monthly rainfall of over 650mm. However, in 2016, with over 700 mm of rainfall in May, the flood-inundated area was reduced to 4.046 km², highlighting the role of other factors such as wetland recovery. Moreover, it identifies significant LULC changes, emphasising rapid urbanisation and wetland decline. From 2009 to 2018, built-up areas increased from 11.49 km² to 14.18 km², while wetlands decreased from 2.29 km² in 2009 to 1.19 km² in 2015, before recovering slightly to 1.58 km² by 2018. The expansion of built-up areas is found to slightly increase flood risks, while wetland recovery acts as a natural flood buffer. This research underscores the importance of targeted interventions for urban flood resilience, such as flood-resistant infrastructure and wetland management. The findings provide critical insights for evidence-based urban planning and flood management strategies, aiming to create more resilient and sustainable urban environments.

Heavy metal bioaccumulation based on seasonal monsoon impact in benthic macroinvertebrates of Korean streams.

This study investigates the influence of seasonal monsoon flooding on heavy metal contamination and bioaccumulation in benthic macroinvertebrate communities within a stream ecosystem. We analyzed sediment and benthic macroinvertebrate samples for eight heavy metals [zinc (Zn), chromium (Cr), nickel (Ni), lead (Pb), copper (Cu), arsenic (As), cadmium (Cd), and mercury (Hg)] ) before (BF) and after (AF) a major flooding event. Significant spatial and temporal variations in heavy metal concentrations were observed, with generally higher levels detected after the flood. Chironomidae consistently exhibited high bioaccumulation factors (BAFs) for several metals, highlighting their role as bioindicators. Notably, elevated Cu accumulation was observed in multiple species, including Radix auricularia (R. auricularia), Cipangopaludina chinensis malleata (C. c. malleata), and Palaemon spp. Non-metric multidimensional scaling (NMDS) analysis revealed shifting correlations between environmental variables and bioaccumulation patterns before and after flooding. Pre-flood, total nitrogen (TN) showed a strong positive correlation with Hg bioaccumulation, while post-flood, large sand content emerged as a more influential factor for Zn, Cr, Ni, and Pb bioaccumulation. Our findings emphasize the complex interplay between seasonal flooding, environmental factors, and heavy metal dynamics, with potential implications for ecological risk assessment and water quality management.

Transferability of machine-learning-based modeling frameworks across flood events for hindcasting maximum river water depths in coastal watersheds

Abstract. Despite applications of machine learning (ML) models for predicting floods, their transferability for out-of-sample data has not been explored. This paper developed an ML-based model for hindcasting maximum river water depths during major events in coastal watersheds and evaluated its transferability across other events (out-of-sample). The model considered the spatial distribution of influential factors that explain the underlying physical processes to hindcast maximum river water depths. Our model evaluations in a six-digit hydrologic unity code (HUC6) watershed in the northeastern USA showed that the model satisfactorily hindcasted maximum water depths at 116 stream gauges during a major flood event, Hurricane Ida (R2 of 0.94). The pre-trained, validated model was successfully transferred to three other major flood events, hurricanes Isaias, Sandy, and Irene (R2>0.70). Our results showed that ML-based models can be transferable for hindcasting maximum river water depths across events when informed by the spatial distribution of pertinent features, their interactions, and underlying physical processes in coastal watersheds.

Extracting Wetlands in Coastal Louisiana from the Operational VIIRS and GOES-R Flood Products

Visible Infrared Imaging Radiometer Suite (VIIRS) and Advanced Baseline Imager (GOES-R ABI) flood products have been widely used by the National Weather Service (NWS) for river flood monitoring, and by the Federal Emergency Management Agency (FEMA) for rescue and relief efforts. Some water bodies, like wetlands, are detected as water but not marked as permanent or normal water, which may result in their misclassification as floodwaters by VIIRS and GOES-R flood products. These water bodies generally do not cause significant property damage or fatalities, but they can complicate the identification of truly hazardous floods. This study utilizes the severe Louisiana flood event caused by Hurricane Ida to demonstrate how to differentiate wetlands from real-hazard flooding. Since Hurricane Ida made landfall in 2021, and there was no major flood event in 2022, VIIRS and ABI flood data from 2021 and 2022 were selected. The difference in annual total flooding days between 2021 and 2022 was calculated and combined with long-time flood frequency to distinguish non-hazard floodwaters due to wetlands identified from real-hazard floods caused by the hurricane. The results were compared with the wetlands from the change detection analysis. The confusion matrix analysis indicated an accuracy of 91.58%, precision of 89.97%, and F1-score of 76.63% for the VIIRS flood products. For the GOES-R ABI flood products, the confusion matrix analysis yielded an accuracy of 86.88%, precision of 97.49%, and F1-score of 75.21%. The accuracy and F1-score values for the GOES-R ABI flood products are slightly lower than those for the VIIRS flood products, possibly due to their lower spatial resolution, but still within a feasible range.

Wasted shores: Using drones to monitor the spatio-temporal evolution of debris accumulation hotspots on South Africa's Umgeni River

Rivers are major contributors of plastic waste to the oceans. Running through the northern part of the 1.3 million-inhabitants City of Durban, South Africa, the Umgeni River is estimated to flush in the order of tens to hundreds of tonnes of plastic waste into the Indian Ocean every year. The riverbanks are lined with plastic and other macro-waste accumulation zones formed due to direct littering and occasional deposition of river debris loads. This study presents the use of Unmanned Aerial Vehicles (UAVs) and hydro-meteorological sensors to (1) identify, quantify and monitor such anthropogenic macro-waste hotspots; and (2) investigate the influence of rainfall, river water level and a major flood event on the spatio-temporal evolution of the hotspots, evidencing the debris' availability to leak into the Indian Ocean. The one-year aerial monitoring (2021−2022) of waste hotspots shows that extreme hydrometeorological events have an immediate but short-term effect on the erosion of debris stocks in riverine systems. We observe that reduction in mean index changes of hotspot surface area after flooding were 2–5 times higher than in non-flood conditions. Despite visual evidence of seasonality in debris erosion between the wet and dry season, only the 'natural' type hotspots showed a significant change. Our findings support reported inconsistencies of macro-debris erosion with hydrological factors. Although the data contributes a baseline for macro-debris erosion in the Umgeni River, future ground truth sampling and finer monitoring scales are important to fully understand debris transfer in river systems. The mapping of waste hotspots and understanding their spatio-temporal transfer dynamics supports policymakers in planning and timing to mitigate environmental pollution.

Previous reproductive success and environmental variation influence nest-site fidelity of a subarctic-nesting goose.

Nest-site fidelity is a common strategy in birds and is believed to be adaptive due to familiarity with local conditions. Returning to previously successful nest sites (i.e., the win-stay lose-switch strategy) may be beneficial when habitat quality is spatially variable and temporally predictable; however, changes in environmental conditions may constrain dispersal decisions despite previous reproductive success. We used long-term (2000-2017) capture-mark-reencounter data and hierarchical models to examine fine-scale nest-site fidelity of emperor geese (Anser canagicus) on the Yukon-Kuskokwim Delta in Alaska. Our objectives were to quantify nest-site dispersal distances, determine whether dispersal distance is affected by previous nest fate, spring timing, or major flooding events on the study area, and determine if nest-site fidelity is adaptive in that it leads to higher nest survival. Consistent with the win-stay lose-switch strategy, expected dispersal distance for individuals that failed their nesting attempt in the previous year was greater (207.7 m, 95% HPDI: 151.1-272.7) than expected dispersal distance for individuals that nested successfully in the previous year (125.5 m, 95% HPDI: 107.1-144.9). Expected dispersal distance was slightly greater following years of major flooding events for individuals that nested successfully, although this pattern was not observed for individuals that failed their nesting attempt. We did not find evidence that expected dispersal distance was influenced by spring timing. Importantly, dispersal distance was positively related to daily survival probability of emperor goose nests for individuals that failed their previous nesting attempt, suggesting an adaptive benefit to the win-stay lose-switch strategy. Our results highlight the importance of previous experience and environmental variation for informing dispersal decisions of a long-lived goose species. However, it is unclear if dispersal decisions based on previous experience will continue to be adaptive as variability in environmental conditions increases in northern breeding areas.

Adjoint-based sensitivity analysis and assimilation of multi-source data for the inference of spatio-temporal parameters in a 2D urban flood hydraulic model

This contribution presents a novel approach for the calibration of distributed parameters in a 2D urban flood hydraulic model. It focuses on the challenging issue of inferring distributed friction parameters from multi-source heterogeneous spatio-temporal observations of their hydraulic signatures in the context of an urban flash flood in a complex street network. A variational data assimilation algorithm is used to infer high-dimensional multi-variate parameters (spatialized friction and inflow discharge time series) using multi-source observations. This method relies on a differentiable 2D shallow water hydraulic model which enables to generate high-resolution sensitivity maps of local gradients and Derivative-based Global Sensitivity Measures (DGSM), enabling to guide adequate definition of parameter spatialization for the data assimilation process. Assimilated data include real local limnigraphic measurements and high-water marks collected after a major flood event, as well as modeled flow velocity used in twin experiments setups. This study is the first to leverage high-water marks with a variational method for the calibration of distributed parameters in an urban flood model. The multi-source data is used to infer inflow hydrographs and distributed friction parameters in setups of varying complexity. In the main setup, the complex structure of the street network, along with the sensitivity maps and hydraulics expertise led to define a model configuration with 45 friction patches. A high-dimensional parameter vector composed of these friction values and an upstream inflow is inferred simultaneously by assimilating real limnigraphic data and high-water marks. This leads to an increase in model fit to observations and satisfying parameter estimates.

Comprehensive climatic variability analysis and its significance on flood occurrences in the Middle Ganga Plain, India

Climate variability significantly affects rainfall, air temperature, relative humidity, and solar radiation. In subtropical regions like India, intense monsoon rainfall primarily causes floods. This study aims to analyze the climatic factors contributing to flood occurrence in the Middle Ganga Plain (MGP) by examining meteorological parameters through various analyses, including monthly and yearly trends, spatial variability, exceedance probability, historical highest intensity rainfall, and wind trajectory analysis. By establishing a strong link between climatic variables and flood events, this research provides valuable insights into the impact of climate variability on flood patterns in the MGP. Results indicate that monsoon rainfall peaks from July to October, correlating with major flood events. During these months, high relative humidity increases the likelihood of rainfall. Spatial analysis shows higher rainfall in the northern Middle Ganga Plain (MGP), which aligns with observed flood patterns. Trend detection tests reveal increasing annual rainfall and rising average temperatures. Geostatistical analysis identifies the western and eastern MGP as areas prone to extreme rainfall. Exceedance probability analysis confirms the occurrence of substantial monsoon rainfall events. Wind trajectory analysis uncovers seasonal shifts that lead to low-pressure systems and heavy monsoon rainfall. The study establishes a strong link between climatic variables and flood events in the MGP region.

Sources of nutrients fuelling post-flood phytoplankton biomass in a subtropical bay

Extreme rainfall from an ex-tropical cyclone caused a major flood event in the Logan River system in southeast Queensland, Australia. This resulted in a significant flood plume, containing nutrients and sediment, being discharged into the adjacent estuary/Bay system. The spatial extent of higher phytoplankton biomass (Chl a) matched the distribution of higher nutrient and sediment concentrations post-flood, suggesting nutrients fuelled phytoplankton production. Particulate nitrogen (PN) constituted over 50 % of total nitrogen in floodwaters, with lower proportions of dissolved inorganic nitrogen (DIN) and phosphate (PO4-P). Phytoplankton utilised DIN rapidly but may have maintained growth due to the release of ammonia from suspended sediments and microbial mineralisation of particulate organic nitrogen. Ammonia release from intertidal sediments contributed minimally (0.85 %) to daily phytoplankton nitrogen demands. Our study highlights the need to understand the fate of particulate nitrogen in coastal systems and its role in stimulating phytoplankton growth.

115 years of sediment deposition in a reservoir in Central Europe: Effects of the industrial history and environmental protection on heavy metals and microplastic

AbstractHumans have considerably influenced accumulation rates and sediment composition in lake deposits. Due to near‐continuous accumulation, lakes and reservoirs are an excellent archive of these anthropogenic influences. The Urft Reservoir in the Eifel Mountains, western Germany, provides a unique record of the human influence on the landscape for the past 115 years. In 2020 and 2021, 24 cores and 23 surface samples were obtained from the bottom of the, by that time drained, reservoir. Grain size, heavy metals, weathering signatures and microplastic were analysed. For the chronology, caesium‐137 and microplastic were used. Using the first occurrence of microplastic as well as different plastic types for dating was not successful. However, a distinct layer with a high number of microplastic particles could be traced back to a fire in 1991 and was used as an additional stratigraphic marker in the age‐depth model. A period of relatively high accumulation rates in the reservoir occurred in the mid‐1950s and was related to enhanced construction works in the local valleys. Analysis of heavy metal content in the reservoir sediments shows a strong connection to historical changes in ore industry in the valley of the Urft. Stricter environmental protection laws and the decline of the metal processing industry resulted in a reduced input of lead, copper and zinc in the reservoir until the mid‐1980s. Since then, heavy metal content has remained relatively constant. A major flooding event in July 2021 did not lead to the remobilisation of older contaminated deposits as indicated by low heavy metal content in flood deposits. Accordingly, also the microplastic content is not increasing following the extreme event. Due to the degree of weathering of the flood deposits, it is argued that mainly hillslope material was transported into the Urft and subsequently into the Urft Reservoir during this event.

Mixed response of trace element concentrations in fluvial sediments to a flash flood in a former mining area

BackgroundFloods, especially flash floods, are the major transporting agent for fluvial sediments, whose pollution is a global concern. As floods result in the dispersion of and exposure to these sediments, a profound understanding of sedimentary dynamics during flood events and the related pollutant dispersion is of relevance. However, the characteristics of extreme flood events concerning pollutant dynamics are insufficiently known so far.ResultsIn a Central European catchment impacted by intense industrial activities and former mining, over the course of five years, we surveyed six high-discharge events, five of them approx. bankfull discharge and one major flash flood event, supplemented by sampling of bank sediments. Fluvial sediments were analyzed for elemental composition by X-Ray fluorescence and for grain size distribution of the fine faction by laser diffraction. By applying a local enrichment factor, trace metal(loid) signatures in these sample sets were compared. Furthermore, Positive Matrix Factorization was used to investigate the trace metal(loid)s’ sources.The sediments deposited by minor flooding had continual trace metal(loid) signatures. However, for the extreme event, significant divergencies arose and persisted for the following years: The enrichment of anthropogenically influenced elements increased, with a slowly decreasing trend in the subsequent two years. Naturally dominated metal(oid)s decrease in enrichment without indicating a return to original levels. In contrast, other elements were insensitive to the extreme event. Positive Matrix Factorization identified anthropogenic influences in elements originating from copper and lead processing and mining activities. Furthermore, bed sediments and a natural background factor were found to dominate the non-anthropogenically influenced metal(loid)s.ConclusionsIn between extreme events, winnowing processes slowly alter the elemental composition of bed sediments. The depletion of such sediments due to the flash flood proves catchment-wide flushing, which induces a natural resetting of the geochemical signals. This ability to renew is an integral part of resilience in fluvial systems. This mechanism is disturbed by industrial activities in floodplains. The exceptional flooding reaches infrastructure that is assumed to be safe and, therefore, unprotected. These additional sources can shift flood sediments’ trace metal(loid) signature, which has a long-lasting impact on the catchment sediments. However, the modifications depend on the flooding extent, possible emitters, and protection measures.

A geospatial perspective of flood risk hotspots, transport networks and emergency response services in Accra, Ghana

ABSTRACT This paper adds to existing knowledge about flood management in Accra and contributes insights into emergency responses to major flood events in a geospatial context. The study identifies and analyses the specific routes from the facilities of emergency responders to designated flood-prone areas within four sites in the peripheral areas of the Greater Accra Metropolitan Area. Flood hotspots were ascertained from several sources including local knowledge and bluespot maps derived from a 10 m resolution elevation model. GIS-based network analysis was used to determine the fastest routes from emergency responder facilities to flood hotspots, based on OpenStreetMap data. Interviews revealed that the computed routes are unsuitable for emergency services due to narrow passages and prevailing conditions during the floods. It is necessary to incorporate the individual responder’s knowledge gained through familiarization with the local terrain to identify the optimal routes. The study further analysed the accessibility of emergency response services using indicative service area maps that present an account of time-distance from various emergency responders’ bases. Finally, the study recommends the need for better planning of the expanding areas of the Greater Accra Metropolitan Area, in terms of accessibility for emergency responders.

A Study on the Rainfall-Storage Volume-Target Water Level Curve for Flood Control on the Small Size Dam: Case study for Goesan Dam

Dams in South Korea serve various functions, including water supply, hydropower, and transportation; in particular, they are responsible for a significant portion of flood control. This study aims to propose a methodology that field engineers can easily utilize to assess the hydrological conditions of small dams that require simultaneous discharge during flood inflow due to limited storage capacity. Therefore, the relationship between rainfall, storage volume, and target water level was established for dams. This relationship is represented as a curve and is based on the storage volume during the rising phases of floods. Historical data of the Goesan Dam, located in the Dalcheon Basin of the Han River, including inflow, discharge, and rainfall were collected at 10-minute intervals. Analysis was conducted on four major flood events occurring since 2018. The proposed methodology was applied to derive the rainfall-storage volume-target water level curve for the Goesan Dam. Subsequently, the appropriate flood response water level for the Gosan Dam was calculated, and its applicability was examined.

A 7000-year record of extreme flood events reconstructed from a threshold lake in southern Norway

Recent decades have witnessed a shift in the seasonality and frequency of river floods in Norway, primarily attributed to contemporary global warming. Such changes necessitate a more comprehensive understanding of climate-flood dynamics across river systems. A significant challenge in flood risk assessment is that instrumental data records cover only the last few decades and do not capture low-frequency, high-magnitude extremes. Another challenge is the non-stationarity of the leading atmospheric pattern over Scandinavia, the North Atlantic Oscillation (NAO), which requires a spatial understanding of extreme events through time. To address this issue, we use lacustrine sediments from southernmost Norway, aiming to extend flood records beyond the scope of instrumental and historical data by exploring a threshold lake that accumulates flood deposits only when river discharge exceeds a critical level. A multi-proxy approach, which includes X-ray fluorescence (XRF), computed tomography (CT), and magnetic susceptibility (MS), was applied to fingerprint the sediments. We detected thin layers of minerogenic sediments, which we interpreted as slackwater deposits accumulated in a lake environment during extreme flood events. These fine-grained minerogenic bands were quantified using XRF and CT data to reconstruct the frequency of major floods over the past ∼7000 years. The minimum water discharge necessary for transporting sediments into the lake was assessed with the HEC-RAS hydraulic simulation software. Our record shows a high frequency of extreme floods from 7000 to 5000 cal yr BP before a significant decrease from 5000 to 2300 cal yr BP. The frequency has been high since 2300 cal yr BP, with a peak frequency after 1600 CE, coinciding with the Little Ice Age. There is a strong co-variability between a positive NAO index, winter precipitation, and major flood events over the past 120 years. A comparison between our flood record and other palaeorecords suggests that this relationship also holds on multi-millennial time scales.

Flooding, season and habitat interact to drive changes in vertebrate scavenging and carcass persistence rates

Scavenging dynamics are influenced by many abiotic and biotic factors, but there is little knowledge of how scavengers respond to extreme weather events. As carrion is a major driver of the organisation and structure of food webs within ecological communities, understanding the response of scavengers to extreme weather events is critical in a world that is increasingly subject to climate change. In this study, vertebrate scavenging and carcass persistence rates were quantified in the Simpson Desert of central Australia; a system that experiences major fluctuations and extremes in weather conditions. Specifically, a total of 80 adult red kangaroo (Osphranter rufus) carcasses were placed on the landscape and monitored using remote sensor cameras. This included 40 carcasses monitored before and then 40 carcasses monitored after a major flooding event. The carcasses were monitored equally before and after the flood across different seasons (warm and cool) and in dune and interdune habitats. Overall, a total of 8124 scavenging events for 97,976 visitation minutes were recorded for 11 vertebrate species within 30 days of carcass placement pre- and post-flood. Vertebrate scavenging increased post-flood in the warm season, especially by corvids which quadrupled their scavenging events during this time. There was little difference in carcass persistence between habitats, but carcasses persisted 5.3-fold longer post-flood in warm seasons despite increased vertebrate scavenging. The results demonstrate that a flood event can influence scavenging dynamics and suggest a need to further understand how seasons, habitats and extreme weather events can drive changes in carrion-based food webs.

Urban planning for flood resilience under technical and financial constraints: The role of planners and competence development in building a flood-resilient city in Matola, Mozambique

Today, urban flood resilience constitutes an academic and political discourse as well as a ‘proposed state’ to be achieved within urban management, planning, and development. Matola, a major Mozambican coastal city, has witnessed many floods, mainly caused by rainfall, the most devastating of which happened in 2000. This study analyses the actions the urban planners took during that major flood event, what flood mitigation and adaptation strategies and measures for increased flood resilience they have developed since that flood event, and the contribution of urban planning to building flood resilience under financial and technical constraints. The study is based on interviews with 32 urban planners from Matola and observations in the field. In addition to financial limitations, the main challenge in promoting flood resilience in Matola is the deficient and insufficient coordination in mitigation and adaptation actions among urban planners, political elites, and members of low-income urban communities, who use floodplain areas for purposes that contradict resilience-building actions. During the 2000 floods, mitigation actions were carried out by rescuing people and goods and placing them in accommodation centres. After the 2000 floods, gradual adaptation strategies and measures were carried out, such as hiring and training staff, designing a new urban plan, gradual resettlement, opening drainage channels, and allocating water pumping systems in some areas to promote flood resilience. The study concludes that urban planning contributed significantly to the building and promotion of flood resilience in Matola: the strategies and measures taken so far have contributed significantly to reducing the exposure and vulnerability to flooding of the population, their assets, and urban infrastructure, as well as improving the ecosystem in lowlands and coastal protection wetlands. The study brings a contribution from retrospective and prospective resilience thinking to the debate on building and promoting resilience in urban socio-ecological systems, showing the role of urban planners, and planning and management activity since the 2000 floods, and perspectives on the future. The study demonstrates that the development of competences or technical skills to plan and manage strategies and measures to promote resilience is a key factor in promoting socio-ecological resilience.

The 2023 report of the MJA-Lancet Countdown on health and climate change: sustainability needed in Australia's health care sector.

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021 and 2022. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the sixth report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. Our results highlight the health and economic costs of inaction on health and climate change. A series of major flood events across the four eastern states of Australia in 2022 was the main contributor to insured losses from climate-related catastrophes of $7.168 billion - the highest amount on record. The floods also directly caused 23 deaths and resulted in the displacement of tens of thousands of people. High red meat and processed meat consumption and insufficient consumption of fruit and vegetables accounted for about half of the 87 166 diet-related deaths in Australia in 2021. Correction of this imbalance would both save lives and reduce the heavy carbon footprint associated with meat production. We find signs of progress on health and climate change. Importantly, the Australian Government released Australia's first National Health and Climate Strategy, and the Government of Western Australia is preparing a Health Sector Adaptation Plan. We also find increasing action on, and engagement with, health and climate change at a community level, with the number of electric vehicle sales almost doubling in 2022 compared with 2021, and with a 65% increase in coverage of health and climate change in the media in 2022 compared with 2021. Overall, the urgency of substantial enhancements in Australia's mitigation and adaptation responses to the enormous health and climate change challenge cannot be overstated. Australia's energy system, and its health care sector, currently emit an unreasonable and unjust proportion of greenhouse gases into the atmosphere. As the Lancet Countdown enters its second and most critical phase in the leadup to 2030, the depth and breadth of our assessment of health and climate change will be augmented to increasingly examine Australia in its regional context, and to better measure and track key issues in Australia such as mental health and Aboriginal and Torres Strait Islander health and wellbeing.

Daily Simulation of the Rainfall–Runoff Relationship in the Sirba River Basin in West Africa: Insights from the HEC-HMS Model

This study focuses on the Sirba River Basin (SRB), a transboundary West African catchment of 38,950 km2 shared by Burkina Faso and Niger, which contributes to flooding downstream in Niamey (Niger). The study uses the HEC-HMS hydrological model to explore the dynamics of the daily rainfall–runoff relationship over the period 2006–2020. The model is calibrated using observed rainfall at 13 meteorological stations within the river basin and observed discharges at the Garbey Kourou hydrometric station outlet. Two types of simulation are compared: (i) a continuous simulation (CS) over the period 2006–2020 and (ii) an event-based simulation (ES) using selected major flood events in 2010, 2012, 2013, 2015 and 2020. The results showed satisfactory model performance under both modeling schemes (R2 = 0.84–0.87 for CS and R2 = 0.94–0.98 for ES), with a superior performance of ES over CS. Also, significant differences in the distribution of calibrated model parameters for the percent impervious and the attenuation flood wave factor were observed. A sensitivity analysis revealed that the curve number, initial abstraction, lag time and routing time factors were influential on the model outputs. The study therefore underscores the model’s robustness and contributes crucial insights for flood control management and infrastructure planning in the SRB.

Nitrogen loading resulting from major floods and sediment resuspension to a large coastal embayment

Major floods pose a severe threat to coastal receiving environments, negatively impacting environmental health and ecosystem services through direct smothering with sediment and nutrient loading. This study examined the short and long-term impacts of the February 2022 major flood event on mud extent and sediment nitrogen flux in Moreton Bay (the Bay), a large, sub-tropical embayment in Southeast Queensland, Australia. Short-term impacts were assessed three days after the flood peak by sampling surface water at 47 sites in the direction of the predominant circulation pattern. Longer-term impacts were assessed by undertaking an intensive sediment survey of 223 sites and a nutrient flux experiment using sediment core incubations to simulate calm and resuspension conditions for the four key sediment classes. Short-term impacts revealed elevated turbidity levels extended across the Bay but were highest at the Brisbane River mouth, ammonium concentrations varied inversely with surface turbidity, whereas nitrate concentrates closely tracked surface turbidity. The sediment survey confirmed fine sediment deposition across 98 % of the Bay. Porewater within the upper 10 cm contained a standing pool of 280 t of ammonium, with concentrations more than three orders of magnitude higher than overlying surface waters. The nutrient flux experiment revealed an order of magnitude higher sediment ammonium flux rate in the sandy mud sediment class compared to the other sediment classes; and for simulated resuspension conditions compared to calm conditions for sand, muddy sand, and mud sediment classes. Scaling across the whole Bay, we estimated a mean annual sediment flux of 17,700 t/year ammonium, with a range of 13,500 to 21,900 t/year. Delivery of fine sediments by major floods over the last 50 years now impact >98 % of the benthic zone and provide a major loading pathway of available nitrogen to surface waters of Moreton Bay; representing a significant threat to ecosystem health.