The 2011 flood event in the Richelieu River basin: Causes, assessment and damages

Saad, Christian; St‐Hilaire, André; Gachon, Philippe; Adlouni, Salaheddine El

doi:10.1080/07011784.2014.999825

Cited by 8 publications

(7 citation statements)

References 5 publications

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“…In Canada, flood types are related to regional and landscape settings (Buttle et al, 2016). Snowmelt floods are generated from large winter snow accumulation and rapid melt rates and are common in many regions of Canada (Lawford et al, 1995;Pomeroy et al, 2014;Rannie, 2016;Saad et al, 2016;Stadnyk et al, 2016). Snowmelt floods usually occur during the spring freshet, which can be coupled with heavy rainfall that can result in even more severe flooding because of rain-on-snow processes (Dumanski et al, 2015;Newton and Burrell, 2016).…”

Section: Introductionmentioning

confidence: 99%

Impact of antecedent conditions on simulations of a flood in a mountain headwater basin

Fang

Pomeroy

2016

Hydrol. Process.

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A devastating flood struck Southern Alberta in late June 2013, with much of its streamflow generation in the Front Ranges of the Rocky Mountains, west of Calgary. To better understand streamflow generation processes and their sensitivity to initial conditions, a physically based hydrological model was developed using the Cold Regions Hydrological Modelling platform (CRHM) to simulate the flood for the Marmot Creek Research Basin (~9.4 km2). The modular model includes major cold and warm season hydrological processes including snow redistribution, sublimation, melt, runoff over frozen and unfrozen soils, evapotranspiration, subsurface runoff on hillslopes, groundwater recharge and discharge and streamflow routing. Uncalibrated simulations were conducted for eight hydrological years and generally matched streamflow observations well, with a NRMSD of 52%, small model bias (−3%) and a Nash–Sutcliffe efficiency (NSE) of 0.71. The model was then used to diagnose the responses of hydrological processes in 2013 flood from different ecozones in Marmot Creek: alpine, treeline, montane forest and large and small forest clearings to better understand spatial variations in the flood runoff generation mechanisms. To examine the sensitivity to antecedent conditions, ‘virtual’ flood simulations were conducted using a week (17 to 24 June 2013) of flood meteorology imposed on the meteorology of the same period in other years (2005 to 2012), or switched with the meteorology of one week in different months (May to July) of 2013. Sensitivity to changing precipitation and land cover was assessed by varying the precipitation amount during the flood and forest cover and soil storage capacity in forest ecozone. The results show that runoff efficiency increases rapidly with antecedent snowpack and soil moisture storage with the highest runoff response to rainfall from locations in the basin where there are recently melted or actively melting snowpacks and resulting high soil moisture or frozen soils. The impact of forest canopy on flooding is negligible, but flood peak doubles if forest canopy removal is accompanied by 50% reduction in water storage capacity in the basin. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Impact of antecedent conditions on simulations of a flood in a mountain headwater basin

Fang

Pomeroy

2016

Hydrol. Process.

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“…However, in June FIGURE 1 Satellite photo from August 8, 2008 of study site (left) and digital elevation model of peatland (right) with the location of wells in the well network. Wells are shaded relative to the depth of the peat measured at each location 2013, a major flood event, caused by heavy rain on snow (Pomeroy, Stewart, & Whitfield, 2015), swept through the basin, breaching the active dams and displacing the resident beaver colony from the immediate area. By September 2015, there was no field evidence that beaver had returned to the site to repair any of the dams.…”

Section: History Of Beaver Activity At the Sitementioning

confidence: 99%

Beaver‐mediated water table dynamics in a Rocky Mountain fen

2017

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Beaver dams are known to raise water tables in mineral soil environments, but very little is known about their impact in wetlands, such as peatlands. Peatlands tend to have shallow water tables, and the position and tendency of the water table to fluctuate (i.e., stability) is a factor controlling the system's ability to store carbon and water. Many peatland environments, especially fens, offer ideal habitat for beaver, and the potential for beaver dams to influence this link by manipulating water tables requires investigation. Our objective was to determine the influence of beaver dams on the water table dynamics of a Rocky Mountain fen. We monitored water tables in the peatland for 4 years while beaver dams were intact and 2 years after they were breached by an extreme flood event. We found that, because of the unique way in which dams were built, they connected the peatland to the stream and raised and stabilized already high water tables within a 150‐m radius. Beaver‐mediated changes to peatland water table regimes have the potential to enhance carbon sequestration and the peatland's ability to respond to external pressures such as climate change. Furthermore, beaver dams increased surface and groundwater storage, which has implications for regional water balances, especially in times of drought.

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“…Nonetheless, it is often not clear which type of nonstationarity is included in the target hydroclimatological time series, and its impact on water management is significant according to the definition of nonstationarity. Meanwhile, the record‐breaking floods of 2011 in Lake Champlain (LC) in Vermont and New York, U.S. and the Richelieu River (RR) in the province of Quebec, Canada prompted the U.S. and Canadian governments to work on identifying how flood forecasting, preparedness and mitigation can be improved in the Lake Champlain and Richelieu River (LCRR) basin (Saad et al., 2016). The International Joint Commission (IJC) submitted the LCRR Plan of Study (PoS) to the Governments of Canada and the United States in 2013.…”

Section: Introductionmentioning

confidence: 99%

Trends, Shifting, or Oscillations? Stochastic Modeling of Nonstationary Time Series for Future Water‐Related Risk Management

Lee

Ouarda

2023

Earth's Future

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Hydrological time series often present nonstationarities such as trends, shifts, or oscillations due to anthropogenic effects and hydroclimatological variations, including global climate change. For water managers, it is crucial to recognize and define the nonstationarities in hydrological records. The nonstationarities must be appropriately modeled and stochastically simulated according to the characteristics of observed records to evaluate the adequacy of flood risk mitigation measures and future water resources management strategies. Therefore, in the current study, three approaches were suggested to address stochastically nonstationary behaviors, especially in the long‐term variability of hydrological variables: as an overall trend, shifting mean, or as a long‐term oscillation. To represent these options for hydrological variables, the autoregressive model with an overall trend, shifting mean level (SML), and empirical mode decomposition with nonstationary oscillation resampling (EMD‐NSOR) were employed in the hydrological series of the net basin supply in the Lake Champlain‐River Richelieu basin, where the International Joint Committee recently managed and significant flood damage from long consistent high flows occurred. The detailed results indicate that the EMD‐NSOR model can be an appropriate option by reproducing long‐term dependence statistics and generating manageable scenarios, while the SML model does not properly reproduce the observed long‐term dependence, that are critical to simulate sustainable flood events. The trend model produces too many risks for floods in the future but no risk for droughts. The overall results conclude that the nonstationarities in hydrological series should be carefully handled in stochastic simulation models to appropriately manage future water‐related risks.

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The 2011 flood event in the Richelieu River basin: Causes, assessment and damages

Cited by 8 publications

References 5 publications

Impact of antecedent conditions on simulations of a flood in a mountain headwater basin

Impact of antecedent conditions on simulations of a flood in a mountain headwater basin

Beaver‐mediated water table dynamics in a Rocky Mountain fen

Trends, Shifting, or Oscillations? Stochastic Modeling of Nonstationary Time Series for Future Water‐Related Risk Management

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