Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is... more Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is dominated by buoyant cyanobacterial communities that present complex spatiotemporal patterns. Increases in bloom frequency or intensity and their earlier onset in spring were shown to be linked to multiple anthropogenic disturbances, including climate change. The aim of the present study was to describe the phenology of phytoplankton blooms and its potential link with morphological, physiographic, anthropogenic, and climatic characteristics of the lakes and their watershed. The spatiotemporal dynamics of near-surface blooms were studied on 580 lakes in southern Quebec (Eastern Canada) over a 17-year period by analyzing chlorophyll-a concentrations gathered from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images. Results show a significant increase by 23% in bloom frequency across all studied lakes between 2000 and 2016. The first blooms of the year appeared increasin...
Convolutional Neural Network and Long Short-Term Memory 1 Models for Ice-Jam Prediction 2 3 Fatem... more Convolutional Neural Network and Long Short-Term Memory 1 Models for Ice-Jam Prediction 2 3 Fatemehalsadat Madaeni, Karem Chokmani, Rachid Lhissou, Saied Homayouni, Yves 4 Gauthier, and Simon Tolszczuk-Leclerc 5 INRS-ETE, Université du Québec, Québec City, G1K 9A9, Canada 6 EMGeo Operations, Natural Resources Canada, Ottawa, K1S 5K2, Canada 7 Correspondence to: Fatemehalsadat Madaeni ([email protected]) 8 9 Abstract. In cold regions, ice-jam events result in severe flooding due to a rapid rise in water levels upstream of the 10 jam. These floods threaten human safety and damage properties and infrastructures as the floods resulting from ice11 jams are sudden. Hence, the ice-jam prediction tools can give an early warning to increase response time and minimize 12 the possible corresponding damages. However, the ice-jam prediction has always been a challenging problem as there 13 is no analytical method available for this purpose. Nonetheless, ice jams form when some h...
Management zones (MZs) are delineated areas within an agricultural field with relatively homogeno... more Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties, and therefore similar crop fertility requirements. Consequently, such MZs can often be used for site-specific management of crop production inputs. This study evaluated the effectiveness of four classification methods for delineating MZs in an 8-ha commercial potato field located in Prince Edward Island, Canada. The apparent electrical conductivity (ECa) at two depths from a commercial Veris sensor were used to delineate MZs using three classification methods without spatial constraints (i.e., fuzzy k-means, ISODATA and hierarchical) and one with spatial constraints (i.e., spatial segmentation method). Soil samples (0.0–0.15 m depth) from 104 sampling points was used to measure soil physical and chemical properties and their spatial variation in the field were used as reference data to evaluate four delineation methods. Significant Pearson correlations between ECa and...
Improving the estimation of snow density is a key task in current snow research. Characterization... more Improving the estimation of snow density is a key task in current snow research. Characterization of the variability of density in time and space is essential for the estimation of water equivalent, hydroelectric power production, assessment of natural hazards (avalanches, floods, etc.). Hyperspectral imaging is proving to be a promising and reliable tool for monitoring and estimating this physical property. Indeed, the spectral reflectance of snow is partly controlled by changes in its physical properties, particularly in the near-infrared (NIR) part of the spectrum. For this purpose, several models have been designed to estimate snow density from spectral information. However, none has yet achieved significant performance. One of the major difficulties is that the relationship between snow density and spectral reflectance is non-bijective (surjective). Indeed, several reflectance amplitudes can be associated with the same density and vice versa, so the correlation between density ...
This paper proposes an innovative method for classifying the physical properties of the seasonal ... more This paper proposes an innovative method for classifying the physical properties of the seasonal snowpack using near-infrared (NIR) hyperspectral imagery to discriminate the optical classes of snow at different degrees of metamorphosis. This imaging system leads to fast and non-invasive assessment of snow properties. Indeed, the spectral similarity of two samples indicates the similarity of their chemical composition and physical characteristics. This can be used to distinguish, without a priori recognition, between different classes of snow solely based on spectral information. A multivariate data analysis approach was used to validate this hypothesis. A principal component analysis (PCA) was first applied to the NIR spectral data to analyze field data distribution and to select the spectral range to be exploited in the classification. Next, an unsupervised classification was performed on the NIR spectral data to select the number of classes. Finally, a confusion matrix was calcula...
In Canada, flooding is the most common and costly natural hazard. Flooding events significantly i... more In Canada, flooding is the most common and costly natural hazard. Flooding events significantly impact communities, damage infrastructures and threaten public security. Communication, as part of a flood risk management strategy, is an essential means of countering these threats. It is therefore important to develop new and innovative tools to communicate the flood risk with citizens. From this perspective, the use of story maps can be very effectively implemented for a broad audience, particularly to stakeholders. This paper details how an interactive web-based story map was set up to communicate current and future flood risks in the Petite-Nation River watershed, Quebec (Canada). This web technology application combines informative texts and interactive maps on current and future flood risks in the Petite-Nation River watershed. Flood risk and climate maps were generated using the GARI tool, implemented using a geographic information system (GIS) supported by ArcGIS Online (Esri). ...
In Canada, climate change is expected to increase the extreme precipitation events by magnitude a... more 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...
Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is... more Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is dominated by buoyant cyanobacterial communities that present complex spatiotemporal patterns. Increases in bloom frequency or intensity and their earlier onset in spring were shown to be linked to multiple anthropogenic disturbances, including climate change. The aim of the present study was to describe the phenology of phytoplankton blooms and its potential link with morphological, physiographic, anthropogenic, and climatic characteristics of the lakes and their watershed. The spatiotemporal dynamics of near-surface blooms were studied on 580 lakes in southern Quebec (Eastern Canada) over a 17-year period by analyzing chlorophyll-a concentrations gathered from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images. Results show a significant increase by 23% in bloom frequency across all studied lakes between 2000 and 2016. The first blooms of the year appeared increasin...
IEEE Transactions on Geoscience and Remote Sensing
In this paper, an ensemble-based system (EBS) for estimating chlorophyll-a concentrations (Chl-a)... more In this paper, an ensemble-based system (EBS) for estimating chlorophyll-a concentrations (Chl-a) in inland water bodies using downscaled MODIS images was developed. Seeking additional opinions before making a decision is part of human nature, particularly for decisions involving health issues. The general concept behind EBS algorithms is based on this principle. Forty-six Chl-a measurements, collected over four water bodies between 2000 and 2008, were used to calibrate the EBS. Measurements ranged from 2.7 (oligotrophic waters) to 91 000 mg Chl-a <inline-formula> <tex-math notation="LaTeX">$\text{m}^{{-3}}$ </tex-math></inline-formula> (hypertrophic waters). The EBS performance was evaluated by cross validation, and also using an independent database (Chl-a ranging from 1 to 14 mg <inline-formula> <tex-math notation="LaTeX">$\text{m}^{{-3}}$ </tex-math></inline-formula>). Cross-validation results were satisfactory both under high-blooming conditions (<inline-formula> <tex-math notation="LaTeX">$\text{R}^{2} = 0.98$ </tex-math></inline-formula>, relative RMSE (RMSEr) = 15%, relative Bias (BIASr) = −2%, and relative Nash (NASHr) = 0.95) and at the initialization of blooms (<inline-formula> <tex-math notation="LaTeX">$\text{R}^{2} = 0.77$ </tex-math></inline-formula>, RMSEr = 37%, BIASr = −8%, and NASHr = 0.70). The EBS also performed well on the independent database (<inline-formula> <tex-math notation="LaTeX">$\text{R}^{2} =0.93$ </tex-math></inline-formula>, RMSEr = 50%, BIASr = −27%, and NASHr = 0.70). A visual comparison mapping Chl-a on the Missisquoi Bay of Lake Champlain additionally illustrates the potential of the EBS to detect early phases of algal growth contrary to other models (adaptive model, Kharu, and APProach by Elimination). This approach is a proof of concept for a more efficient way to quantify algal biomass from remote sensing and could be exported to any types of satellite imagery in a context of water quality monitoring.
A new method for sensitivity analysis of water depths is presented based on a two-dimensional hyd... more A new method for sensitivity analysis of water depths is presented based on a two-dimensional hydraulic model as a convenient and cost-effective alternative to Monte Carlo simulations. The method involves perturbation of the probability distribution of input variables. A relative sensitivity index is calculated for each variable, using the Gauss quadrature sampling, thus limiting the number of runs of the hydraulic model. The variable-related highest variation of the expected water depths is considered to be the most influential. The proposed method proved particularly efficient, requiring less information to describe model inputs and fewer model executions to calculate the sensitivity index. It was tested over a 45 km long reach of the Richelieu River, Canada. A 2D hydraulic model was used to solve the shallow water equations (SWE). Three input variables were considered: Flow rate, Manning’s coefficient, and topography of a shoal within the considered reach. Four flow scenarios wer...
A reliable knowledge and assessment of the sea ice conditions and their evolution in time is a pr... more A reliable knowledge and assessment of the sea ice conditions and their evolution in time is a priority for numerous decision makers in the domains of coastal and offshore management and engineering as well as in commercial navigation. As of today, countless research projects aimed at both modelling and mapping past, actual and future sea ice conditions were completed using sea ice numerical models, statistical models, educated guesses or remote sensing imagery. From these research, reliable information helping to understand sea ice evolution in space and in time are available to stakeholders. However, no research has, as of today, assessed the evolution of the sea ice cover with a frequency modelling approach, by identifying the underlying theoretical distribution describing the sea ice behaviour at a given point in space and time. This project suggests the development of a probabilistic tool, named IcePAC, based on frequency modelling of historical 1978-2015 passive microwave sea ice concentrations maps from EUMETSAT OSI-409 product, to study the sea ice spatiotemporal behaviour in the waters of the Hudson Bay System in Northeastern Canada. Pixel scale models are based on the generalized Beta distribution and generated at a weekly temporal resolution. Results showed coherent with the Canadian Ice Service 1980-2010 Sea Ice Climatic Atlas average freeze-up and meltdown dates for numerous coastal communities in the study area and showed that it is possible to evaluate a range of plausible events, such as the shortest and longest probable ice free season duration, for any given location on the simulation domain. Results obtained in this project open a path towards various analyses on sea ice dynamics that would gain in informative content and value by relying on the kind of probabilistic information and simulation data available from the IcePAC tool.
In this paper, we assess the flood mapping capabilities of the X-band Synthetic Aperture Radar (S... more In this paper, we assess the flood mapping capabilities of the X-band Synthetic Aperture Radar (SAR) imagery acquired by the bistatic pair TanDEM-X/TerraSAR-X (TDX/TSX). The main objective is to investigate the added value of the bistatic TDX/TSX Interferometric Synthetic Aperture Radar (InSAR) coherence in addition to the SAR backscatter in the context of inundation mapping. As a classifier, we consider a Random Forest (RF) classification scheme using TDX/TSX SAR intensities and their bistatic InSAR coherence to extract the flood extent map. To evaluate the classification results and as no “ground truth” was available at the SAR data acquisition time, we set up a LISFLOOD-FP hydraulic model for simulating the temporal evolution of the flood water. The flood map simulated by the model shows good performances with an Overall Accuracy (OA) of 97.92 % and a Critical Success Index (CSI) of 94 . 01 % . The SAR-derived flood map is then compared to the LISFLOOD-FP extent map simulated at ...
A reliability approach referred to as the point estimate method (PEM) is presented to assess the ... more A reliability approach referred to as the point estimate method (PEM) is presented to assess the uncertainty of a two-dimensional hydraulic model. PEM is a special case of numerical quadrature based on orthogonal polynomials, which evaluates the statistical moments of a performance function involving random variables. When applied to hydraulic problems, the variables are the inputs to the hydraulic model, and the first and second statistical moments refer to the mean and standard deviation of the model's output. In providing approximate estimates of the uncertainty, PEM appears considerably simpler and requires less information and fewer runs than standard Monte Carlo methods. An example of uncertainty assessment is shown for simulated water depths in a 46 km reach of the Richelieu River, Canada. The 2D hydraulic model, H2D2, was used to solve the shallow water equations. Standard deviations around the mean water depths were estimated by considering the uncertainties of three main input variables: flow rate, Manning's coefficient and topography. Results indicate that the mean standard deviation is <27 cm for the considered flow rates of 759, 824, 936, 1113 m 3 /s. Higher standard deviations were obtained upstream of the topographic shoal at the municipality of Saint-Jean-sur-Richelieu. The PEM method adds further value to the H2D2 model predictions as it indicates the magnitude and the spatial variation in uncertainties. The effort required to complete an uncertainty analysis using the PEM method is minimal and the resulting insight is meaningful. This knowledge should be incorporated into decision-making in the context of flood risk assessment.
Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is... more Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is dominated by buoyant cyanobacterial communities that present complex spatiotemporal patterns. Increases in bloom frequency or intensity and their earlier onset in spring were shown to be linked to multiple anthropogenic disturbances, including climate change. The aim of the present study was to describe the phenology of phytoplankton blooms and its potential link with morphological, physiographic, anthropogenic, and climatic characteristics of the lakes and their watershed. The spatiotemporal dynamics of near-surface blooms were studied on 580 lakes in southern Quebec (Eastern Canada) over a 17-year period by analyzing chlorophyll-a concentrations gathered from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images. Results show a significant increase by 23% in bloom frequency across all studied lakes between 2000 and 2016. The first blooms of the year appeared increasin...
Convolutional Neural Network and Long Short-Term Memory 1 Models for Ice-Jam Prediction 2 3 Fatem... more Convolutional Neural Network and Long Short-Term Memory 1 Models for Ice-Jam Prediction 2 3 Fatemehalsadat Madaeni, Karem Chokmani, Rachid Lhissou, Saied Homayouni, Yves 4 Gauthier, and Simon Tolszczuk-Leclerc 5 INRS-ETE, Université du Québec, Québec City, G1K 9A9, Canada 6 EMGeo Operations, Natural Resources Canada, Ottawa, K1S 5K2, Canada 7 Correspondence to: Fatemehalsadat Madaeni ([email protected]) 8 9 Abstract. In cold regions, ice-jam events result in severe flooding due to a rapid rise in water levels upstream of the 10 jam. These floods threaten human safety and damage properties and infrastructures as the floods resulting from ice11 jams are sudden. Hence, the ice-jam prediction tools can give an early warning to increase response time and minimize 12 the possible corresponding damages. However, the ice-jam prediction has always been a challenging problem as there 13 is no analytical method available for this purpose. Nonetheless, ice jams form when some h...
Management zones (MZs) are delineated areas within an agricultural field with relatively homogeno... more Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties, and therefore similar crop fertility requirements. Consequently, such MZs can often be used for site-specific management of crop production inputs. This study evaluated the effectiveness of four classification methods for delineating MZs in an 8-ha commercial potato field located in Prince Edward Island, Canada. The apparent electrical conductivity (ECa) at two depths from a commercial Veris sensor were used to delineate MZs using three classification methods without spatial constraints (i.e., fuzzy k-means, ISODATA and hierarchical) and one with spatial constraints (i.e., spatial segmentation method). Soil samples (0.0–0.15 m depth) from 104 sampling points was used to measure soil physical and chemical properties and their spatial variation in the field were used as reference data to evaluate four delineation methods. Significant Pearson correlations between ECa and...
Improving the estimation of snow density is a key task in current snow research. Characterization... more Improving the estimation of snow density is a key task in current snow research. Characterization of the variability of density in time and space is essential for the estimation of water equivalent, hydroelectric power production, assessment of natural hazards (avalanches, floods, etc.). Hyperspectral imaging is proving to be a promising and reliable tool for monitoring and estimating this physical property. Indeed, the spectral reflectance of snow is partly controlled by changes in its physical properties, particularly in the near-infrared (NIR) part of the spectrum. For this purpose, several models have been designed to estimate snow density from spectral information. However, none has yet achieved significant performance. One of the major difficulties is that the relationship between snow density and spectral reflectance is non-bijective (surjective). Indeed, several reflectance amplitudes can be associated with the same density and vice versa, so the correlation between density ...
This paper proposes an innovative method for classifying the physical properties of the seasonal ... more This paper proposes an innovative method for classifying the physical properties of the seasonal snowpack using near-infrared (NIR) hyperspectral imagery to discriminate the optical classes of snow at different degrees of metamorphosis. This imaging system leads to fast and non-invasive assessment of snow properties. Indeed, the spectral similarity of two samples indicates the similarity of their chemical composition and physical characteristics. This can be used to distinguish, without a priori recognition, between different classes of snow solely based on spectral information. A multivariate data analysis approach was used to validate this hypothesis. A principal component analysis (PCA) was first applied to the NIR spectral data to analyze field data distribution and to select the spectral range to be exploited in the classification. Next, an unsupervised classification was performed on the NIR spectral data to select the number of classes. Finally, a confusion matrix was calcula...
In Canada, flooding is the most common and costly natural hazard. Flooding events significantly i... more In Canada, flooding is the most common and costly natural hazard. Flooding events significantly impact communities, damage infrastructures and threaten public security. Communication, as part of a flood risk management strategy, is an essential means of countering these threats. It is therefore important to develop new and innovative tools to communicate the flood risk with citizens. From this perspective, the use of story maps can be very effectively implemented for a broad audience, particularly to stakeholders. This paper details how an interactive web-based story map was set up to communicate current and future flood risks in the Petite-Nation River watershed, Quebec (Canada). This web technology application combines informative texts and interactive maps on current and future flood risks in the Petite-Nation River watershed. Flood risk and climate maps were generated using the GARI tool, implemented using a geographic information system (GIS) supported by ArcGIS Online (Esri). ...
In Canada, climate change is expected to increase the extreme precipitation events by magnitude a... more 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...
Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is... more Phytoplankton bloom monitoring in freshwaters is a challenging task, particularly when biomass is dominated by buoyant cyanobacterial communities that present complex spatiotemporal patterns. Increases in bloom frequency or intensity and their earlier onset in spring were shown to be linked to multiple anthropogenic disturbances, including climate change. The aim of the present study was to describe the phenology of phytoplankton blooms and its potential link with morphological, physiographic, anthropogenic, and climatic characteristics of the lakes and their watershed. The spatiotemporal dynamics of near-surface blooms were studied on 580 lakes in southern Quebec (Eastern Canada) over a 17-year period by analyzing chlorophyll-a concentrations gathered from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images. Results show a significant increase by 23% in bloom frequency across all studied lakes between 2000 and 2016. The first blooms of the year appeared increasin...
IEEE Transactions on Geoscience and Remote Sensing
In this paper, an ensemble-based system (EBS) for estimating chlorophyll-a concentrations (Chl-a)... more In this paper, an ensemble-based system (EBS) for estimating chlorophyll-a concentrations (Chl-a) in inland water bodies using downscaled MODIS images was developed. Seeking additional opinions before making a decision is part of human nature, particularly for decisions involving health issues. The general concept behind EBS algorithms is based on this principle. Forty-six Chl-a measurements, collected over four water bodies between 2000 and 2008, were used to calibrate the EBS. Measurements ranged from 2.7 (oligotrophic waters) to 91 000 mg Chl-a <inline-formula> <tex-math notation="LaTeX">$\text{m}^{{-3}}$ </tex-math></inline-formula> (hypertrophic waters). The EBS performance was evaluated by cross validation, and also using an independent database (Chl-a ranging from 1 to 14 mg <inline-formula> <tex-math notation="LaTeX">$\text{m}^{{-3}}$ </tex-math></inline-formula>). Cross-validation results were satisfactory both under high-blooming conditions (<inline-formula> <tex-math notation="LaTeX">$\text{R}^{2} = 0.98$ </tex-math></inline-formula>, relative RMSE (RMSEr) = 15%, relative Bias (BIASr) = −2%, and relative Nash (NASHr) = 0.95) and at the initialization of blooms (<inline-formula> <tex-math notation="LaTeX">$\text{R}^{2} = 0.77$ </tex-math></inline-formula>, RMSEr = 37%, BIASr = −8%, and NASHr = 0.70). The EBS also performed well on the independent database (<inline-formula> <tex-math notation="LaTeX">$\text{R}^{2} =0.93$ </tex-math></inline-formula>, RMSEr = 50%, BIASr = −27%, and NASHr = 0.70). A visual comparison mapping Chl-a on the Missisquoi Bay of Lake Champlain additionally illustrates the potential of the EBS to detect early phases of algal growth contrary to other models (adaptive model, Kharu, and APProach by Elimination). This approach is a proof of concept for a more efficient way to quantify algal biomass from remote sensing and could be exported to any types of satellite imagery in a context of water quality monitoring.
A new method for sensitivity analysis of water depths is presented based on a two-dimensional hyd... more A new method for sensitivity analysis of water depths is presented based on a two-dimensional hydraulic model as a convenient and cost-effective alternative to Monte Carlo simulations. The method involves perturbation of the probability distribution of input variables. A relative sensitivity index is calculated for each variable, using the Gauss quadrature sampling, thus limiting the number of runs of the hydraulic model. The variable-related highest variation of the expected water depths is considered to be the most influential. The proposed method proved particularly efficient, requiring less information to describe model inputs and fewer model executions to calculate the sensitivity index. It was tested over a 45 km long reach of the Richelieu River, Canada. A 2D hydraulic model was used to solve the shallow water equations (SWE). Three input variables were considered: Flow rate, Manning’s coefficient, and topography of a shoal within the considered reach. Four flow scenarios wer...
A reliable knowledge and assessment of the sea ice conditions and their evolution in time is a pr... more A reliable knowledge and assessment of the sea ice conditions and their evolution in time is a priority for numerous decision makers in the domains of coastal and offshore management and engineering as well as in commercial navigation. As of today, countless research projects aimed at both modelling and mapping past, actual and future sea ice conditions were completed using sea ice numerical models, statistical models, educated guesses or remote sensing imagery. From these research, reliable information helping to understand sea ice evolution in space and in time are available to stakeholders. However, no research has, as of today, assessed the evolution of the sea ice cover with a frequency modelling approach, by identifying the underlying theoretical distribution describing the sea ice behaviour at a given point in space and time. This project suggests the development of a probabilistic tool, named IcePAC, based on frequency modelling of historical 1978-2015 passive microwave sea ice concentrations maps from EUMETSAT OSI-409 product, to study the sea ice spatiotemporal behaviour in the waters of the Hudson Bay System in Northeastern Canada. Pixel scale models are based on the generalized Beta distribution and generated at a weekly temporal resolution. Results showed coherent with the Canadian Ice Service 1980-2010 Sea Ice Climatic Atlas average freeze-up and meltdown dates for numerous coastal communities in the study area and showed that it is possible to evaluate a range of plausible events, such as the shortest and longest probable ice free season duration, for any given location on the simulation domain. Results obtained in this project open a path towards various analyses on sea ice dynamics that would gain in informative content and value by relying on the kind of probabilistic information and simulation data available from the IcePAC tool.
In this paper, we assess the flood mapping capabilities of the X-band Synthetic Aperture Radar (S... more In this paper, we assess the flood mapping capabilities of the X-band Synthetic Aperture Radar (SAR) imagery acquired by the bistatic pair TanDEM-X/TerraSAR-X (TDX/TSX). The main objective is to investigate the added value of the bistatic TDX/TSX Interferometric Synthetic Aperture Radar (InSAR) coherence in addition to the SAR backscatter in the context of inundation mapping. As a classifier, we consider a Random Forest (RF) classification scheme using TDX/TSX SAR intensities and their bistatic InSAR coherence to extract the flood extent map. To evaluate the classification results and as no “ground truth” was available at the SAR data acquisition time, we set up a LISFLOOD-FP hydraulic model for simulating the temporal evolution of the flood water. The flood map simulated by the model shows good performances with an Overall Accuracy (OA) of 97.92 % and a Critical Success Index (CSI) of 94 . 01 % . The SAR-derived flood map is then compared to the LISFLOOD-FP extent map simulated at ...
A reliability approach referred to as the point estimate method (PEM) is presented to assess the ... more A reliability approach referred to as the point estimate method (PEM) is presented to assess the uncertainty of a two-dimensional hydraulic model. PEM is a special case of numerical quadrature based on orthogonal polynomials, which evaluates the statistical moments of a performance function involving random variables. When applied to hydraulic problems, the variables are the inputs to the hydraulic model, and the first and second statistical moments refer to the mean and standard deviation of the model's output. In providing approximate estimates of the uncertainty, PEM appears considerably simpler and requires less information and fewer runs than standard Monte Carlo methods. An example of uncertainty assessment is shown for simulated water depths in a 46 km reach of the Richelieu River, Canada. The 2D hydraulic model, H2D2, was used to solve the shallow water equations. Standard deviations around the mean water depths were estimated by considering the uncertainties of three main input variables: flow rate, Manning's coefficient and topography. Results indicate that the mean standard deviation is <27 cm for the considered flow rates of 759, 824, 936, 1113 m 3 /s. Higher standard deviations were obtained upstream of the topographic shoal at the municipality of Saint-Jean-sur-Richelieu. The PEM method adds further value to the H2D2 model predictions as it indicates the magnitude and the spatial variation in uncertainties. The effort required to complete an uncertainty analysis using the PEM method is minimal and the resulting insight is meaningful. This knowledge should be incorporated into decision-making in the context of flood risk assessment.
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Papers by Karem Chokmani