Magnitude Of Flood Events Research Articles

River floodplains as source or sink for fine sediment and total phosphorus export in an agricultural watershed

AbstractFloodplains constitute a vital and integrated component of the riverine network ensuring the connectivity and continuity of the river with the upland watershed areas. However, the sediment trapping efficiency of floodplains has not been well investigated. The purpose of this experimental study was to evaluate the functionality of floodplains to act as either sources or sinks for fine sediments and sediment‐bound nutrients (e.g., total phosphorus) during floods of various return periods. Thus, we hypothesized that (i) soil texture, in terms of topsoil erodibility and (ii) the magnitude of the incoming flood, in terms of the applied shear stress, are the two key parameters govern river floodplains' ability to store or release fine sediments and total phosphorus, during major flood conditions. Topsoil erodibility experiments were coupled with site‐specific flood inundation maps to estimate the eroded fine sediment mass and the total phosphorus release rates per unit area per unit time of each flood condition considered. Results suggested that the floodplain soils of the upstream reaches act as net sources, the floodplains of the midstream reaches have a dual functionality; during low magnitude flood events (up to 10‐year return periods), they act as net sinks, while during higher flood events, they act as sources; and the floodplains of the downstream reaches largely act as sinks. This study results are applicable for watershed managers to identify floodplain areas vulnerable to erosion and sources of nutrient pollution.

Environmental DNA based biomonitoring for hatchery-raised fish in riverine habitats before and after recordable flood event

It is reported that the magnitudes of flood events in riverine systems have been increasing due to global climate change. Because flood events could displace fish species downstream and/or increase the mortality of fish, it is important to know how the increased floods can affect fish in river networks. In this study, we focused a hatchery-raised amphidromous fish, Ayu Plecoglossus altivelis altivelis in a mainstem-tributary network in Japan and examined the relative fish abundance changes before and after the recordable massive flood using the environmental DNA (eDNA) analysis. We also examined the spatiotemporal patterns of the Ayu eDNA concentrations and the relationships with tributary discharge, width, and depth to examine if the relative abundance changes could be related to tributary size. Our results indicated that Ayu tended to inhabit large, deep tributaries more than small, shallow tributaries even after the flood event. Further, the eDNA concentrations of Ayu have decreased in most study sites after the flood; however, the eDNA concentrations in certain tributaries with lower tributary size have increased during the study period. These results suggest that (1) the habitat conditions could be important for the maintenance of Ayu populations before and after flood events, (2) increase in flood magnitude along climate changes could have impacts on Ayu populations, and (3) not only large tributary, but also small tributaries could be important habitats for the target species to avoid flood disturbances.

Unveiling Torrential Flood Dynamics: A Comprehensive Study of Spatio-Temporal Patterns in the Šumadija Region, Serbia

This paper presents a comprehensive analysis of flood frequency and a spatio-temporal characterization of historical torrential floods in the Šumadija region using water discharge datasets and documented events. A chronology of 344 recorded torrential flood events, spanning from 1929 to 2020, illustrates the region’s vulnerability, with a death toll exceeding 43. The study defines the intra-annual primary and secondary peaks of torrential flood occurrences and explains their spatial distribution. Furthermore, the identification of suitable probability distribution functions underscores the necessity of tailored approaches for effective flood risk management in this diverse geographical environment. The study employed Flood Frequency Analysis (FFA) and goodness-of-fit tests, including the Kolmogorov–Smirnov (K-S) and Cramér–von Mises (CvM) tests, to assess the frequency and magnitude of flood events and evaluate diverse distribution functions. The main results include the identification of suitable probability distribution functions for each river within the region, emphasizing the need for tailored approaches in flood risk management. Additionally, discharge values for various return periods offer crucial insights for informed decision-making in flood risk management and infrastructure planning.

Assessment of alterations of river flow regimes using hydro-geomorphological parameters

Climate change and anthropogenic activities can alter the streamflow regime by modifying critical elements of the flow regime. The aim of this work is to determine, by means of characteristic indices of rates of change and variability, the stage of alteration of the streamflow regime in a mountain catchment. On the basis of the daily mean streamflow, recorded over the period 1994-2020, a series of hydrological indices (Richards-Baker flashiness index, coefficient of variation, k index) were quantified, by means of which the rates of change and variability of the flow can be assessed. The results obtained show that the temporal and spatial variation of the streamflow is mainly due to natural causes, such as climatic variability and some geomorphological characteristics of the drainage basins. Thus, a clear positive correlation was observed between the Richards-Baker flashiness index and the magnitude of flood events. In the longitudinal profile, an increase in the mean values of Richards-Baker flashiness index was observed, indicating a higher variability of streamflows downstream. The higher Richards-Baker flashiness index values in the lower reaches were reflected in changes in the river channel, particularly after 2004.

Rapid laminated clastic alluviation associated with increased Little Ice Age flooding co-driven by climate variability and historic land-use in the middle Severn catchment, UK

The analysis of exceptionally well-preserved visible clastic laminations in deep alluvial sediments at Kempsey, Worcestershire (UK), allows a new high-resolution analysis of late-Holocene flood-history in the largest UK catchment, as well as local human response. At the sample site over 4.5 m of sandy-silt overbank-alluvium accumulated on the floodplain and optically stimulated luminescence (OSL) dating of the upper 2.25 m demonstrates accretion from the late 14th century CE onwards. Sub-centimetre to centimetre resolution multi-proxy sediment analysis (loss on ignition, magnetic susceptibility, particle size, ITRAX and portable XRF) demonstrate clear variations in depositional history over the last millennium due to channel stability. Between c. 1380 and 1550 CE overbank sedimentation was driven by lower energy flood events, with negligible effect from climatic conditions during the Spörer Minimum (1460–1550 CE). After c. 1550 CE the magnitude of flooding events increased and by c. 1610 CE, the start of the visible sub-centimetre laminations, the accumulation rate regularly exceeded 3 mm year−1, which increased to 4.5 mm year−1 between c. 1690 and 1710 CE, and 3 and 3.5 mm year−1 between c. 1790 and 1840 CE before alluviation was altered by an embankment. The greatest extent of coarse overbank deposition and increased accumulation rate occur concurrently with periods of climatic instability associated with the Maunder (1645–1715 CE) and Dalton (1790–1820 CE) Minima, the periods of largest historical floods and during the intensification of arable cultivation across the middle Severn catchment. This data correlates well with other sites in the catchment suggesting that these are basin-wide forcing-responses. We also present evidence that this catchment-wide hydro-geomorphological history had local effects in shifting the geographical focus of an important settlement away from its historic floodplain edge location – which can be viewed as an adaptation to the flood risk.

Flood hazard potential reveals global floodplain settlement patterns

Flooding is one of the most common natural hazards, causing disastrous impacts worldwide. Stress-testing the global human-Earth system to understand the sensitivity of floodplains and population exposure to a range of plausible conditions is one strategy to identify where future changes to flooding or exposure might be most critical. This study presents a global analysis of the sensitivity of inundated areas and population exposure to varying flood event magnitudes globally for 1.2 million river reaches. Here we show that topography and drainage areas correlate with flood sensitivities as well as with societal behaviour. We find clear settlement patterns in which floodplains most sensitive to frequent, low magnitude events, reveal evenly distributed exposure across hazard zones, suggesting that people have adapted to this risk. In contrast, floodplains most sensitive to extreme magnitude events have a tendency for populations to be most densely settled in these rarely flooded zones, being in significant danger from potentially increasing hazard magnitudes given climate change.

Coastal Science for Resilience and Management at the Cape Hatteras National Seashore, NC, USA

National seashores are cherished public lands with rich environmental, cultural, and historic resources. The Cape Hatteras National Seashore is one such coastal asset that is both bountiful yet vulnerable, with historic lighthouses, critical habitats, and recreational amenities alike facing threats of sea-level rise and continual storm and climate change impacts. Over 3 million visitors to the Seashore in 2021 set an annual visitation record. Historic resources such as the Bodie Island Lighthouse and Ocracoke Lighthouse are among the most visited sites, yet these assets are also among those most vulnerable to flooding, compromised structural integrity, and reduced accessibility. Future challenges to the protection and management of such resources are already being felt in the form of storms, extreme rainfall, and recurrent compound flooding. Such threats are also coincident with increasing visitation and recreational demand. This paper examines the science-based data that are being collected and management efforts underway to inform future planning, intervention, or adaptation to sea-level rise and barrier island evolution. The paper identifies the opportunities for mitigation and adaptation as well as potential environmental tipping points and limits to resilience by assessing the frequency and magnitude of flooding events and shoreline change.

Hydrologic evaluation of the global precipitation measurement mission over the U.S.: Flood peak discharge and duration

In recent years, a great amount of research has been done towards evaluating precipitation data generated by satellites, but less has focused on how these estimates and their uncertainties manifest further into the water cycle. In this study, ten years of satellite-based and ground-based radar data are used as forcings for a distributed hydrologic model across the Continental United States. They are compared using a methodology designed to assess the flood signals and characteristics generated by the model. By focusing on how well the model reproduces flood characteristics rather than fits traditional bulk statistics, this research provides robust insights into satellite precipitation deficiencies. It is found that satellite data has greater success at resolving lower magnitude flood events while tending to generate floods of longer durations. Additionally, flood managers should note that satellites tend to generate floods that characteristically both begin earlier and end later than the ground radar reference. Subsequent research is recommended into other satellite data products in order to better understand these discrepancies and mitigate or plan for them in the future. Plain Language SummaryIn recent years, satellites have been increasingly used to provide valuable insights on rainfall across the globe, especially in locations where radars are unable to be installed on the ground. By nature, however, the rainfall data provided by satellites has uncertainties. Large amounts of research has gone into the difference in accuracy between satellite radar and ground references, but less has focused on how these differences impact flood simulations, respectively. In this study it was found that the rainfall data from satellites tends to predict floods that are more severe (have higher magnitudes), last longer (have longer durations), and have different timings (start earlier and end later) than the reference. It is also found that satellites struggle with predictions involving extreme rainfall values. Further research is suggested to better understand these issues, as well as compare against other forms of satellite rainfall data.

Climate related changes to flood regimes show an increasing rainfall influence

Climate change can result in changes to floods and flood regimes, but the relationship between floods and climate change is complex and poorly understood. The flood regime influences the nature, severity, and timing of flood events for any watershed. Flood regimes should be viewed as a continuum with completely nival (snowmelt-driven) watersheds at one end of the continuum and purely pluvial (rainfall-driven) watersheds at the other. Flood regimes are important for the operation of flood defenses and to better understand how changes in the flood regime can affect the magnitude of flood events. Data from 46 long term streamflow gauging stations from reference hydrologic networks (RHNs) in Canada (23) and the US (23), are examined to detect changes that have occurred, or are continuing to occur, in flood regimes from watersheds responding only to climate variations and changes. Peaks over Threshold (POT) flood events are used to investigate changes in the timing of flood events. Seasonality measures, using circular statistics, illustrate changes in the nature of the flood regime based on changes in the timing and regularity of flood threshold exceedences. A nival fraction is determined for each watershed and for each year based on a clustering of the flood events into two groups, representing nival and pluvial events. Changes to the flood regime over time, and based on annual temperature, are determined from logistic regression of the number of nival and pluvial events for each year. While strongly nival watersheds show no changes, roughly 15% of the stations exhibit significant changes that represent shifts towards the pluvial end of the flood regime continuum, which has implications for design flood estimation and the operation of flood control infrastructure.

Surprising suspended sediment dynamics of an alpine basin affected by a large infrequent disturbance

In many environments, climate change causes an increase in the frequency and magnitude of Large Infrequent Disturbances (LIDs). LIDs make fragile areas, as mountain basins, even more vulnerable, along with local communities that could be severely affected by extreme events. Among all LIDs, windthrows are one of the most relevant and yet rather unpredictable disturbances affecting the Alpine region. Windthrows can affect the forest cover and morphological settings at the basin scale, changing the supply of sediments to river networks and affecting the sediment cascading processes. This work aims at (i) identifying the contribution of Suspended Sediment Load (SSL) from a windthrow-managed-affected area induced in an Alpine basin by a recent LID (Vaia rainstorm, 2018), (ii) assessing the annual, seasonal and monthly variation in the SSL, and (iii) analysing the changes in SSL fluxes and dynamics in the 2nd and 3rd year after the LID in comparison to those detected after a similar high magnitude event occurred in 1994. To do so, two multiparameter sondes measuring the water level and the turbidity were installed upstream and downstream the windthrow-affected area. Discharge measurements and water samples were collected to obtain the rating curves and calibrate the turbidity meters in order to derive suspended sediment loads (SSL). The results show that the windthrow-affected area was significantly contributing suspended sediment during events occurring two years after Vaia (2020) but less intensively in those occurred three years after the event itself (2021). Both the events average intensity rainfalls and the total precipitation appear to be the best predictors of both the peak of suspended sediment concentration (SSCp), the total suspended sediment (SSL) and the suspended sediment percentage variation among the two cross-sections. The seasonal and monthly analysis revealed to be in line with those detected prior the disturbance. The analyzed LID affected the transport efficiency for near-bankfull events but not the annual sediment yield as it was found after the previous high magnitude flood event recorded in 1994. Unexpectedly, the mean rate of SSL (42 t km -2 yr−1) is indeed comparable with what monitored during the decade before Vaia (2004–2014) (40 t km -2 yr−1). Such surprising results may be explained by the fact that the Rio Cordon basin have had an alluvial response rather than colluvial during the Vaia rainstorm event and that the basin’s resilience may be in a different stage as compared to the one of 1994, when the catchment featured different cascading processes that completely overturn the suspended sediment dynamics and fluxes for about a decade.

The Performance of Natural Flood Management at the Large Catchment-Scale: A Case Study in the Warwickshire Stour Valley

The limited understanding of Natural Flood Management (NFM) performance, especially at large hydrological scales, is considered a critical barrier for the further funding and implementation of these nature-based solutions to the increasing international problem of flooding. The publications of the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report and Environment Agency’s National Flood and Coastal Erosion Risk Management Strategy (NFCERMS) for England have shown that extreme weather, including increased likelihood of high magnitude flood events, will occur and will require more novel management methods. This study focused on the ability of co-designed NFM measures to ameliorate downstream fluvial flooding by attenuating catchment response through a highly spatially distributed network of attenuating and roughening measures. Performance was characterised by the ability of NFM to attenuate flood peaks at different spatial scales across a large (187 km2) dendritic catchment, including the lowering of flood peaks and delaying the time-to-peak. Using a coupled modelling methodology and applying it to the upper Stour Valley, Warwickshire-Avon, UK, a rural response to the application of a set of NFM interventions was developed using the hydrodynamic model Flood Modeller Pro and XPSWMM ©. The method demonstrated a means of incorporating local knowledge in a realistic set of NFM schemes, tested to multiple flood risk scenarios (including climate change). Under frequent, smaller design storm events (e.g., Index Flood (QMED) and 3.3% AEP), flood peaks were lowered across all hydrological scales tested (5.8 km2 to 187 km2). As the design flood event severity increases, impact from upstream NFM attenuation on downstream peak response diminished significantly, especially at the largest hydrological scales. However, even at the largest hydrological scale, delays in time-to-peak were noted, increasing the ability of downstream communities to respond and enact flood preparation activities, thus increasing resilience to potential flooding events. While the benefits were limited to large flood events, the modelling indicated that NFM has the potential to reduce downstream flood risk. However, greater integration of observed data to improve model confidence and reduce uncertainty in modelled events is needed, especially the uncertainty associated with using single peaked design storm events from the Flood Estimation Handbook (FEH). This paper proposes a future Before–After Control–Impact (BACI) monitoring programme that could be integrated with models and applied across non-tidally influenced catchments seeking to empirically test the hydrological performance of in-situ NFM.

A Comprehensive Assessment of Floodwater Depth Estimation Models in Semiarid Regions

AbstractSimple models continue to be important for continental‐scale floodwater depth mapping due to the prohibitively expensive cost of calibrating and applying hydrodynamic models. This paper investigates the accuracy of three simple models for floodwater depth estimation from remote sensing derived water extent and/or Digital Elevation Models (DEMs) in semiarid regions. The three models are Height Above Nearest Drainage (HAND; Nobre et al., 2011, https://doi.org/10.1016/j.jhydrol.2011.03.051), Teng Vaze Dutta (TVD; Teng et al., 2013, http://hdl.handle.net/102.100.100/97033?index=1), and Floodwater Depth Estimation Tool (FwDET; Cohen, Brakenridge, et al., 2018, https://doi.org/10.1111/1752-1688.12609). The model accuracy and nature of errors are established using industry's best practice hydrodynamic models as benchmarks in three regions in eastern Australia. The overall results show that FwDET tends to underestimate (by 0.32 m at 50th percentile) while HAND and TVD overestimate floodwater depth for almost all floods (by 0.97 and 0.98 m, respectively). We quantify how switching DEM from 5 m LiDAR to national or global data sets DEM‐H (Gallant et al., 2011, https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/72759), MERIT (Yamazaki et al., 2019, https://doi.org/10.1029/2019WR024873), or FABDEM (Hawker et al., 2022, https://doi.org/10.1088/1748-9326/ac4d4f) can affect different models differently; and we evaluate model performance against reach geomorphology and magnitude of flood events. The findings emphasize the importance of choosing a model that is fit for the intended application. By describing the applicability, advantages, and limitations of these models, this paper assists practitioners to choose the most appropriate model based on characteristics of their study area, type of problems they try to solve, and data availability.

Multi‐Level Monte Carlo Models for Flood Inundation Uncertainty Quantification

AbstractFlood events are the most commonly occurring natural disaster, with over 5 million properties at risk in the UK alone. Changes in the global climate are expected to increase the frequency and magnitude of flood events. Flood hazard assessments, using climate projections as input, guide policy decisions and engineering projects to reduce the impact of large return period events. Probabilistic flood modeling is required to take into account uncertainties in climate model projections. However, the dichotomous relationship between probabilistic modeling, computational cost and model resolution limits the applicability of such techniques. This paper examines improvements to traditional Monte Carlo methods using Latin hypercube sampling (LHS) and Multi‐level Monte Carlo (MLMC) to quantify the uncertainty in flood extent resulting from input hydrograph uncertainty. The results demonstrate that MLMC is a more efficient modeling strategy than current methods (i.e., traditional Monte Carlo) with high resolution outputs produced in less time than previously possible. The novel application of MLMC technique to three Scottish case studies, demonstrating a variety of river characteristics, domain sizes and computational costs, using a high resolution 5 m grid resulted in a 99.2% reduction in computational cost compared to traditional Monte Carlo methods and up to 2.3 times speedup over Latin Hypercube Sampling.

Best practices in post-flood surveys: The study case of Pioverna torrent

Floods cause fatalities and considerable economic damage to infrastructures and settlements, besides impacting fluvial-geomorphic landforms. The increase in the frequency and magnitude of flood events has contributed to inevitably gaining public concern over the flood risk and awareness of the necessity to improve forecasting and monitoring streamflows. In this context, an efficient and systematic procedure of post-event surveys that documents the impacts of a flood event over the territory is often missing. Flood areas delimitation, erosion-sediment variation, and riparian vegetation change are often neglected. The present study shows the field- and desk-based post-flood surveys conducted after an extreme event occurred on June 12th, 2019, along the Pioverna torrent in Valsassina (North Italy). The post-flood surveys consist in collecting meteorological data and time-series satellite images to detect the land cover change (identifying areas covered by water, sediments, and vegetation), and in planning, a few weeks later, an unmanned aerial vehicle (UAV)-based survey to observe the riverbed and streambank change and the modifications in vegetation patterns through high-resolution derived-topographic data. The results show accurate maps of a ground classification from satellite-based elaboration and high-resolution digital elevation models from UAV-based surveys that can support restoration activities and the design of effective countermeasures. This practical application is appropriate and suitable as a river management strategy regarding timing, resources, and economic costs. Thus, standardising the procedure could be essential for creating a historical database, useful to improve specific guidelines and postemergency management strategies.

Hazard identification and risk assessment of the organic, inorganic and microbial contaminants in the surface water after the high magnitude of flood event.

The present work has been oriented to the qualitative and quantitative assessments of the aftermath effects of 2014 flood tragedy on the organic, inorganic and microbial contaminants in the floodwater, with a particular emphasis on their relative health risks and microbial infectious hazards to the flood-affected population, using average daily dose, hazard quotient, hazard index (HI), cancer risk (CR) and quantitative microbial risk assessment. Statistical comparison of the organic and inorganic contents was performed using the paired t-tests, while the predominant socio-demographic profiles and health attributes of the respondents to flood-induced health risks (HI) were verified by the chi-square test and binary logistic regression analysis. Among all, Fe, Cu, Pb, Ni, Zn, Cr, Cd, chlorpyrifos, diazinon, polycyclic aromatic hydrocarbons, estriol, 17α-ethinylestradiol, estrone, β-estradiol and bisphenol A were detected at the study area after flooding. The microbiological quality of the floodwater samples has been tracked positive for Escherichia coli, Salmonella typhimurium and Shigella flexneri, with the mean concentrations of 6500, 50 and 180CFU/100mL, respectively. Exposure and health risk assessments revealed that the overall HI value for organic and inorganic contaminants in the water samples was 1.19, exceeding the USEPA maximum limit of 1, after the flood incidence. The largest CR contributors were Ni, Cr and Cd, while the infection risks (Pinf,single) associated with the exposure of E. coli, Salmonella spp. and Shigella spp. were identified to be 3.1×10-2, 1.2×10-4 and 3.2×10-5 for incidental scenario; and 8.3×10-1, 3.9×10-1 and 1.9×10-1 for intentional scenario, respectively. The findings of these integrated tools are critically important to provide a more reliable quantitative assessment of human health hazards and microbial risks for different environmental settings, to safeguard water resource, and preservation of public health and the overall river ecosystem.

Palaeoflood hydrology of the fluvial continental records of western India: A synthesis

Palaeoflood hydrology has emerged as an important tool to infer quantitative and qualitative aspects of ungauged floods based on their physical evidence. Palaeoflood studies in India have largely been undertaken in the rivers of Peninsular India, western India, Ganga plains and the Himalayas to determine the magnitude and age of extreme floods and their connection to variations in the monsoon intensity. Usually, the alluvial domains are unfavourable for the occurrence and preservation of flood deposits and related discharge estimation. However, the alluvial rivers of western India owing to their semi–confined banks comprising late Pleistocene sediments provide an opportunity for investigating both, the high magnitude flood events as well as average flow conditions. In this synthesis we concisely review the recent palaeohydrological studies in western India in terms of flood magnitude, occurrence of extreme events and its relation to the southwest monsoon variability over various time scales. Based on palaeo–fluvial reconstructions, the sedimentation pattern during late Pleistocene appears to be related to changes in channel gradient and the water surface width rather than to discharge variability. On the other hand, the aggradation in channels during early Holocene was largely controlled by the huge sediment influx and the incision that followed was in response to the increase in the discharge and competence of the river flow. The slackwater records from the bedrock channels have revealed that the large magnitude flood events occurred during wet climate phases during the last two millennia. A clustering of high magnitude events at climatic transitions and arid periods during mid–late Holocene has been surmised. Further the flood associated deposits delimited within Quaternary fluvial landforms and channel morphology are vital as these allow quantification of past flood discharges, velocities and stage levels and thus improve the future flood predictions.

Reliability Assessment of Machine Learning Models in Hydrological Predictions Through Metamorphic Testing

AbstractThe reliability of the machine learning model prediction for a given input can be assessed by comparing it against the actual output. However, in hydrological studies, machine learning models are often adopted to predict future or unknown events, where the actual outputs are unavailable. The prediction accuracy of a model, which measures its average performance across an observed data set, may not be relevant for a specific input. This study presents a method based on metamorphic testing (MT), adopted from software engineering, to assess the prediction reliability where the actual outputs are unknown. In this method, the predictions for a group of related inputs are considered consistent only if the input and output follow certain relations that are deduced from the properties of the system being modeled. For instance, the predicted runoff volume should increase in a rainfall‐runoff model as the rainfall magnitude of an input increases. In this study, the MT‐based method was applied to assess the predictions made by various machine learning models that were trained to predict the magnitude of flood events in Germany. Surprisingly, the prediction accuracy of a model and its ability to provide consistent predictions were found to be uncorrelated. This study further investigated the factors influencing the assessment result of a given input, such as its similarity to observed data. Overall, this research shows that MT is an effective and simple method for detecting inconsistent model predictions and is recommended when a model is employed to making predictions under new conditions.

Economic Evaluation of Mental Health Effects of Flooding Using Bayesian Networks.

The appraisal of appropriate levels of investment for devising flooding mitigation and to support recovery interventions is a complex and challenging task. Evaluation must account for social, political, environmental and other conditions, such as flood state expectations and local priorities. The evaluation method should be able to quickly identify evolving investment needs as the incidence and magnitude of flood events continue to grow. Quantification is essential and must consider multiple direct and indirect effects on flood related outcomes. The method proposed is this study is a Bayesian network, which may be used ex-post for evaluation, but also ex-ante for future assessment, and near real-time for the reallocation of investment into interventions. The particular case we study is the effect of flood interventions upon mental health, which is a gap in current investment analyses. Natural events such as floods expose people to negative mental health disorders including anxiety, distress and post-traumatic stress disorder. Such outcomes can be mitigated or exacerbated not only by state funded interventions, but by individual and community skills and experience. Success is also dampened when vulnerable and previously exposed victims are affected. Current measures evaluate solely the effectiveness of interventions to reduce physical damage to people and assets. This paper contributes a design for a Bayesian network that exposes causal pathways and conditional probabilities between interventions and mental health outcomes as well as providing a tool that can readily indicate the level of investment needed in alternative interventions based on desired mental health outcomes.

Illegal and unmanaged aquaculture, unregulated fisheries and extreme climatic events combine to trigger invasions in a global biodiversity hotspot

Focusing on extreme climatic events in India’s Western Ghats Biodiversity Hotspot, we demonstrate that unmanaged aquaculture and unregulated fisheries can often combine with ECE in exacerbating biological invasions through the unexpected introduction and escape of novel alien species. High magnitude flooding events in August 2018 and 2019 resulted in the escape of at least ten alien fish species that were recorded for the first time, from the natural waters of the Western Ghats. Illegal farming systems, aqua-tourism destinations and amusement parks, as well as reservoirs, facilitated the escape of alien species during the ECE. Despite expanding invasions, unmanaged stocking and aquaculture using alien species continue in the Western Ghats, necessitating urgent management and policy interventions.

Experimental flows through an array of emerged or slightly submerged square cylinders over a rough bed

The experimental dataset presented was collected in an 18 m long and 1 m wide laboratory flume. Low to high flood flows through an urbanized floodplain were modelled. The floodplain bed is rough, modelled with dense artificial grass. A square cylinder array, representing house models, was set on the rough bed. The cylinder immersion rate was varied: cylinders are emerged for three flow cases and slightly submerged for one case. The experimental dataset comprises water levels, measured using an ultrasonic transit time probe, velocities across the channel measured using an Acoustic Doppler Velocimetry with a side looking probe, and velocities in longitudinal-vertical planes measured using Particle Image Velocimetry. These data could help understanding the physical processes associated with high flood flows through urbanized floodplains, with a focus on the transition from emerged to submerged obstacles. They could also be used as benchmark data to assess the ability of numerical models from one to three-dimensions to estimate the flood hazard (water depth, velocity) over a wide range of flood event magnitudes.