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Abstract A major challenge in ecology is to link patterns and processes across different spatial and temporal scales. Flood plains are ideal model ecosystems to study (i) the processes that create and maintain environmental heterogeneity and (ii) to quantify the effects of environmental heterogeneity on ecosystem functioning and biodiversity. Fluvial processes of cut‐and‐fill alluviation create new channels, bars and benches within a flood plain that in turn provides new surface for subsequent vegetative recruitment and growth resulting in a shifting mosaic of interconnected aquatic and terrestrial habitat patches. Composition and spatial arrangement of these habitat patches control the movement of organisms and matter among adjacent patches; and the capacity of a habitat to process matter depends on the productivity of adjacent patches and on the exchange among these patches. The exchange of matter and organisms among habitats of different age and productivity is often pulsed in nature. Small pulses of a physical driver (e.g. short‐term increase in flow) can leach large amounts of nutrients thereby stimulating primary production in adjacent aquatic patches, or trigger mass emergence of aquatic insects that may in turn impact recipient terrestrial communities. Hence, biodiversity in a river corridor context is hierarchically structured and strongly linked to the dynamic biophysical processes and feedback mechanisms that drive these chronosequences over broad time and space scales. Today, the active conversion of degraded ecosystems back to a more heterogeneous and dynamic state has become an important aspect of restoration and management where maintaining or allowing a return to the shifting habitat mosaic dynamism is the goal with the expected outcome greater biodiversity and clean water among other valuable ecosystem goods and services. Copyright © 2009 John Wiley & Sons, Ltd.
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Abstract Disasters worldwide tend to affect the poorest more severely and increase inequality. Brazil is one of the countries with high income‐inequality rates and has unplanned urbanization issues and an extensive disaster risk profile with little knowledge on how those disasters affect people's welfare. Thus, disasters often hit the poorest hardest, increasing the country's income inequality and poverty rates. This study proposes a method to assess the impact of floods on households spatially based on their income levels by conducting flood analysis and income analysis. The method is applied to the Itapocu River basin (IRB) located in Santa Catarina State, Brazil. The flood is assessed by conducting rainfall analysis and hydrological simulation and generating flood inundation maps. The income is evaluated using downloaded 2010 census data and a dasymetric approach. Flood and income information is combined to analyze flood‐impacted households by income level and flood return period. The results confirm the initial assumption that flood events in the IRB are more likely to affect the lowest‐income households rather than the highest‐income levels, thus, increasing the income inequality.
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In June 2005, the headwater tributaries of the Saskatchewan River Basin in the western Canadian province of Alberta were struck by four heavy rain events. Runoff from the rainfalls resulted in three floods which extended from Alberta through the provinces of Saskatchewan and Manitoba, causing at least four deaths and property damages of CAD $400 million.
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The impact of climate change on the frequency distribution of spring floods in the Red River basin is investigated. Several major floods in the last couple of decades have caused major damages and inconvenience to people living in the Red River flood plain south of Winnipeg, and have raised the question of whether climate change is at least partly responsible for what appears to be more frequent occurrences of high spring runoff. To investigate whether this is the case, a regression model is used to associate spring peak flow at the US–Canada border with predictor variables that include antecedent precipitation in the previous fall (used as a proxy for soil moisture at freeze-up), winter snow accumulation and spring precipitation. Data from the Coupled Model Intercomparison Project – Phase 5 (CMIP5) are used to derive information about possible changes to the predictor variables in the future, and this information is then used to derive flood distributions for future climate conditions. While mean monthly...
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In late June 2013, heavy rainfall and rapidly melting alpine snow triggered flooding throughout much of the southern half of Alberta. Heavy rainfall commenced on 19 June and continued for 3 days. When the event was over, more than 200 mm and as much as 350 mm of precipitation had fallen over the Front Ranges of the Canadian Rocky Mountains. Tributaries to the Bow River including the Ghost, Kananaskis, Elbow, Sheep and Highwood, and many of their tributaries, all reached flood levels. The storm had a large spatial extent causing flooding to the north and south in the Red Deer and Oldman Basins, and also to the west in the Elk River in British Columbia. Convergence of the nearly synchronous floodwaters downstream in the South Saskatchewan River system caused record high releases from Lake Diefenbaker through Gardiner Dam. Dam releases in Alberta and Saskatchewan attenuated the downstream flood peak such that only moderate flooding occurred in Saskatchewan and Manitoba. More than a dozen municipalities decla...
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In Canada, climate change is expected to increase the extreme precipitation events by magnitude and frequency, leading to more intense and frequent river flooding. In this study, we attempt to map the flood hazard and damage under projected climate scenarios (2050 and 2080). The study was performed in the two most populated municipalities of the Petite Nation River Watershed, located in southern Quebec (Canada). The methodology follows a modelling approach, in which climate projections are derived from the Hydroclimatic Atlas of Southern Quebec following two representative concentration pathways (RCPs) scenarios, i.e., RCP 4.5 and RCP 8.5. These projections are used to predict future river flows. A frequency analysis was carried out with historical data of the peak flow (period 1969–2018) to derive different return periods (2, 20, and 100 years), which were then fed into the GARI tool (Gestion et Analyse du Risque d’Inondation). This tool is used to simulate flood hazard maps and to quantify future flood risk changes. Projected flood hazard (extent and depth) and damage maps were produced for the two municipalities under current and for future scenarios. The results indicate that the flood frequencies are expected to show a minor decrease in peak flows in the basin at the time horizons, 2050 and 2080. In addition, the depth and inundation areas will not significantly change for two time horizons, but instead show a minor decrease. Similarly, the projected flood damage changes in monetary losses are projected to decrease in the future. The results of this study allow one to identify present and future flood hazards and vulnerabilities, and should help decision-makers and the public to better understand the significance of climate change on flood risk in the Petite Nation River watershed.
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Data include sample replication (N) and flood-ring frequencies (F1, F2) derived from black ash (Fraxinus nigra Marsh.) trees growing in the floodplain of the Driftwood River in northwestern Ontario reported in "Flood ring production modulated by river regulation in eastern boreal Canada" published in "Frontiers in Plant Science - Quantitative Wood Anatomy to Explore Tree Responses to Global Change" by Nolin et al. in 2021c. DriftwoodFR.csv, as in Fig. 4, F1 and F2 flood-rings chronologies per sites and distance class with sample replication (N) to reproduce the flood-ring frequencies. Harricana River F1 and F2 flood ring chronologies from Nolin et al., 2021b are also provided. DriftwoodRW.csv, as in Fig. 5, the mean site chronologies of total ring width with sample replication (N). LAT_LON_Driftwood.kml, the coordinate data for each F. nigra stand sampled on the Driftwood River, including Monteith dam location, in Google Earth format (.kml) meatadatas.txt, a set of self-explanatory instructions and descriptions for data files. All other data are available upon request to the corresponding author at alexandreflorent.nolin@uqat.ca (institutional email), alexandreflorent.nolin@gmail.com (permanent email).
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Disastrous floods have caused millions of fatalities in the twentieth century, tens of billions of dollars of direct economic loss each year and serious disruption to global trade. In this Review, we provide a synthesis of the atmospheric, land surface and socio-economic processes that produce river floods with disastrous consequences. Disastrous floods have often been caused by processes fundamentally different from those of non-disastrous floods, such as unusual but recurring atmospheric circulation patterns or failures of flood defences, which lead to high levels of damage because they are unexpected both by citizens and by flood managers. Past trends in economic flood impacts show widespread increases, mostly driven by economic and population growth. However, the number of fatalities and people affected has decreased since the mid-1990s because of risk reduction measures, such as improved risk awareness and structural flood defences. Disastrous flooding is projected to increase in many regions, particularly in Asia and Africa, owing to climate and socio-economic changes, although substantial uncertainties remain. Assessing the risk of disastrous river floods requires a deeper understanding of their distinct causes. Transdisciplinary research is needed to understand the potential for surprise in flood risk systems better and to operationalize risk management concepts that account for limited knowledge and unexpected developments. River floods have direct and indirect consequences for society, and can cause fatalities, displacement and economic loss. This Review examines the physical and socioeconomic causes and impacts of disastrous river flooding, and past and projected trends in their occurrence.
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Abstract Floods are among the most devastating natural hazards worldwide. While rainfall is the primary trigger of floods, human activities and climate change can exacerbate the impacts of floods and lead to more significant economic and social consequences. In this research, fluvial flood fatalities in the 1951–2020 period have been studied, analyzing the information reported in the Emergency Database (EM‐DAT). The EM‐DAT data were classified into five categories in terms of the number of events and fatalities connected with riverine floods, considering only events that caused more than 10 fatalities. The results show that the severity of flood‐related fatalities is not equally distributed worldwide, but presents specific geographical patterns. The flood fatality coefficient, which represents the ratio between the total number of fatalities and the number of flood events, calculated for different countries, identified that the Southern, Eastern, and South‐Eastern regions of Asia have the deadliest floods in the world. The number of flood events has been increasing since 1951 and peaked in 2007, following a relative decline since then. Though, the resulting fatalities do not follow a statistically significant trend. An analysis of the number of flood events in different decades shows that the 2001–2010 decade saw the highest number of events, which corresponds to the largest precipitation anomaly in the world. The lethality of riverine floods decreased over time, from 412 per flood in 1951–1960 to 67 in the 2011–2020 decade. This declining trend is probably a consequence of a more resilient environment and better risk reduction strategies. Based on the presented data and using regression analysis, relationships between flood fatalities and the number of flood events with population density and gross domestic product are developed and discussed.
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Gravel-bed rivers are disproportionately important to regional biodiversity, species interactions, connectivity, and conservation. , Gravel-bed river floodplains in mountain landscapes disproportionately concentrate diverse habitats, nutrient cycling, productivity of biota, and species interactions. Although stream ecologists know that river channel and floodplain habitats used by aquatic organisms are maintained by hydrologic regimes that mobilize gravel-bed sediments, terrestrial ecologists have largely been unaware of the importance of floodplain structures and processes to the life requirements of a wide variety of species. We provide insight into gravel-bed rivers as the ecological nexus of glaciated mountain landscapes. We show why gravel-bed river floodplains are the primary arena where interactions take place among aquatic, avian, and terrestrial species from microbes to grizzly bears and provide essential connectivity as corridors for movement for both aquatic and terrestrial species. Paradoxically, gravel-bed river floodplains are also disproportionately unprotected where human developments are concentrated. Structural modifications to floodplains such as roads, railways, and housing and hydrologic-altering hydroelectric or water storage dams have severe impacts to floodplain habitat diversity and productivity, restrict local and regional connectivity, and reduce the resilience of both aquatic and terrestrial species, including adaptation to climate change. To be effective, conservation efforts in glaciated mountain landscapes intended to benefit the widest variety of organisms need a paradigm shift that has gravel-bed rivers and their floodplains as the central focus and that prioritizes the maintenance or restoration of the intact structure and processes of these critically important systems throughout their length and breadth.
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Abstract Topo‐bathymetric LiDAR (TBL) can provide a continuous digital elevation model (DEM) for terrestrial and submerged portions of rivers. This very high horizontal spatial resolution and high vertical accuracy data can be promising for flood plain mapping using hydrodynamic models. Despite the increasing number of papers regarding the use of TBL in fluvial environments, its usefulness for flood mapping remains to be demonstrated. This review of real‐world experiments focusses on three research questions related to the relevance of TBL in hydrodynamic modelling for flood mapping at local and regional scales: (i) Is the accuracy of TBL sufficient? (ii) What environmental and technical conditions can optimise the quality of acquisition? (iii) Is it possible to predict which rivers would be good candidates for TBL acquisition? With a root mean square error (RMSE) of 0.16 m, results from real‐world experiments confirm that TBL provides the required vertical accuracy for hydrodynamic modelling. Our review highlighted that environmental conditions, such as turbidity, overhanging vegetation or riverbed morphology, may prove to be limiting factors in the signal's capacity to reach the riverbed. A few avenues have been identified for considering whether TBL acquisition would be appropriate for a specific river. Thresholds should be determined using geometric or morphological criteria, such as rivers with steep slopes, steep riverbanks, and rivers too narrow or with complex morphologies, to avoid compromising the quality or the extent of the coverage. Based on this review, it appears that TBL acquisition conditions for hydrodynamic modelling for flood mapping should optimise the signal's ability to reach the riverbed. However, further research is needed to determine the percentage of coverage required for the use of TBL as a source of bathymetry in a hydrodynamic model, and whether specific river sections must be covered to ensure model performance for flood mapping.
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Floodplains, one of the most biologically diverse and productive ecosystems, are under threat from intensive crop production. Implementing perennial strips alongside agricultural ditches and streams could reduce negative impacts of intensive agriculture and restore wildlife habitats in cultivated floodplains. To successfully set up perennial strips, it is important to understand the parameters that drive their establishment. Here we assessed the establishment success of reed canarygrass (RCG; Phalaris arundinacea ) strips in the lake Saint Pierre (LSP) floodplain, Québec, Canada by monitoring RCG biomass and vegetation height over 4 years and identify the factors driving its establishment. A total of 26 RCG strips across six municipalities of LSP were monitored. Biomass and vegetation height of RCG increased over time to reach an average of 5048 kg/ha in year 4 and 104 cm in year 3 in established strips. The RCG established successfully in 62% of surveyed plots and three environmental parameters explained 61% of this success. Establishment of RCG was most successful when a first rain came right after seeding (<3 days). High clay content and low elevation were associated with establishment failures. Overall, our results highlight the ability of RCG strips to restore dense perennial vegetation cover in cultivated floodplain, thereby providing suitable habitat for fish spawning during spring floods. This study provides significant insight into the drivers of establishment of perennial grass strips in highly constrained cultivated areas such as floodplains.
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Floods are among natural disasters that increasingly threaten society, especially with current and future climate change trends. Several tools have been developed to help planners manage the risks associated to flooding, including the mapping of flood-prone areas, but one of the major challenges is still the availability of detailed data, particularly bathymetry. This manuscript compares two modeling approaches to produce flood maps. An innovative large-scale approach that, without bathymetric data, estimates by inverse modeling the bed section for a given flow and a given roughness coefficient through 1 D/2D hydraulic modeling (LISFLOOD-FP). And a local approach, with a detailed coupled 1 D/2D hydraulic model (HEC-RAS) that uses all available information at the bed and floodplain (LiDAR and bathymetry). Both implementations revealed good performance values for flood peak levels as well as excellent fit indices in describing the areal extent of flooding. As expected, the local approach is more accurate, but the results of the large-scale approach are very promising especially for areas lacking bathymetric data and for large-scale governmental programs.