Computational advances and innovations in flood risk mapping

Nones, Michael; Caviedes‐Voullième, Daniel

doi:10.1111/jfr3.12666

Cited by 9 publications

(8 citation statements)

References 19 publications

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“…Easy access to databases (e.g., European Environment Agency, United States Geological Survey (USGS), NASA, European Space Agency, Japanese Aerospace Exploration Agency (JAXA)) and high-speed information processing have led to the emergence of numerous publications in this field. At the beginning, survey and interview analysis methods and statistical-mathematical methods were used to study the characteristic parameters of floods; later on, the development of GIS, remote sensing, machine learning, modeling and simulation techniques contributed to the creation of new methods capable of providing a simulation of the phenomenon in different scenarios [106,[116][117][118][119][120][121][122]. The technological progress has led to the development of combined methodologies and comparative approaches to highlight the effectiveness of the methods used and their ease of implementation in risk management systems and water resources.…”

Section: Discussionmentioning

confidence: 99%

An Overview of Flood Risk Analysis Methods

Diaconu

Costache

Popa

2021

Water

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Scientific papers present a wide range of methods of flood analysis and forecasting. Floods are a phenomenon with significant socio-economic implications, for which many researchers try to identify the most appropriate methodologies to analyze their temporal and spatial development. This research aims to create an overview of flood analysis and forecasting methods. The study is based on the need to select and group papers into well-defined methodological categories. The article provides an overview of recent developments in the analysis of flood methodologies and shows current research directions based on this overview. The study was performed taking into account the information included in the Web of Science Core Collection, which brought together 1326 articles. The research concludes with a discussion on the relevance, ease of application, and usefulness of the methodologies.

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Section: Discussionmentioning

confidence: 99%

An Overview of Flood Risk Analysis Methods

Diaconu

Costache

Popa

2021

Water

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“…Aiming to account for the seasonal variability of vegetation and its influence on the roughness in real-time forecasting, innovative models should be developed in the future, possibly via a unique conceptual approach that use data assimilation for inferring trends on the vegetation encroachment and development. In the last decades, the exponential growth in computer storage and computational capacity allowed for the use of more complex algorithms and methods in flood risk computing (Nones and Caviedes-Voullième, 2020), and the spatial discretization of hydraulic models is getting smaller, suggesting for the need of adopting a similar level of detail in dynamic roughness parameterization (Abu-Aly et al, 2014).…”

Section: Future Recommendationsmentioning

confidence: 99%

Deriving Planform Morphology and Vegetation Coverage From Remote Sensing to Support River Management Applications

Boothroyd

Nones

Guerrero

2021

Front. Environ. Sci.

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With the increasing availability of big geospatial data (e.g., multi-spectral satellite imagery) and access to platforms that support multi-temporal analyses (e.g., cloud-based computing, Geographical Information Systems, GIS), the use of remotely sensed information for monitoring riverine hydro-morpho-biodynamics is growing. Opportunities to map, quantify and detect changes in the wider riverscape (i.e., water, sediment and vegetation) at an unprecedented spatiotemporal resolution can support flood risk and river management applications. Focusing on a reach of the Po River (Italy), satellite imagery from Landsat 5, 7, and 8 for the period 1988–2018 were analyzed in Google Earth Engine (GEE) to investigate changes in river planform morphology and vegetation dynamics associated with transient hydrology. An improved understanding of these correlations can help in managing sediment transport and riparian vegetation to reduce flood risk, where biogeomorphic processes are commonly overlooked in flood risk mapping. In the study, two established indices were analyzed: the Modified Normalized Difference Water Index (MNDWI) for monitoring changes in the wetted river planform morphology, inferring information about sediment dynamics, and the Normalized Difference Vegetation Index (NDVI) for evaluating changes in vegetation coverage. Results suggest that planform changes are highly localized with most parts of the reach remaining stable. Using the wetted channel occurrence as a measure of planform stability, almost two-thirds of the wetted channel extent (total area = 86.4 km2) had an occurrence frequency >90% (indicating stability). A loss of planform complexity coincided with the position of former secondary channels, or zones where the active river channel had narrowed. Time series analysis of vegetation dynamics showed that NDVI maxima were recorded in May/June and coincided with the first peak in the hydrological regime (occurring in late spring and associated with snowmelt). Seasonal variation in vegetation coverage is potentially important for local hydrodynamics, influencing flood risk. We suggest that remotely sensed information can provide river scientists with new insights to support the management of highly anthropized watercourses.

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“…The literature highlights the different software capable of integrating surface and subsurface models, such as the Storm Water Management Model (SWMM5.1) (by the US EPA), Integrate Catchment Modelling (ICM) Infoworks Package (By Innovyze), Mike Urban software (by DHI) and other tools developed by researchers, such as SIPSON [18] and CityCAT [19][20][21]. All of these models are based on the principle of solving the St. Venant equations to calculate the subsurface element of the model, but they differ in their surface water modelling techniques [8].…”

Section: Introductionmentioning

confidence: 99%

Numerical and Experimental Approaches to Estimate Discharge Coefficients and Energy Loss Coefficients in Pressurized Grated Inlets

et al. 2021

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Numerical models concerning inlet systems are run to assess the hydraulic performance of existing or new systems and estimate the flow interchanges between the surface overland and sewer flows. In most programs, these interactions are modelled using the orifice equation, with estimated discharge coefficients around 0.6. In this paper, discharge values and energy loss coefficients for several pressurized grated inlets were obtained by experimental and numerical approaches and compared. To achieve these goals, a numerical model replicating several experimental tests carried out at the hydraulic laboratory of Universitat Politècnica de Catalunya (UPC) was produced using a CFD model (Flow 3D). This numerical model was found to be highly sensitive to the mesh size used; however, it was able to accurately simulate the experimental processes. The comparison considered different combinations of pressurized flow though the grate, between 10 to 50 l/s, and different longitudinal gradients. The experimental discharge coefficient was found to increase with surcharging flowrate (ranging from 0.14 and 0.41), whereas the longitudinal gradient was found to have no effect. The discharge coefficients obtained in this study show that the standard 0.6 value commonly used by practitioners should be revised to a range between 0.14 to 0.41, depending on circulating flow and inlet type. In addition, the loss coefficient values range from 0.25 to 3.41.

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Computational advances and innovations in flood risk mapping

Cited by 9 publications

References 19 publications

An Overview of Flood Risk Analysis Methods

An Overview of Flood Risk Analysis Methods

Deriving Planform Morphology and Vegetation Coverage From Remote Sensing to Support River Management Applications

Numerical and Experimental Approaches to Estimate Discharge Coefficients and Energy Loss Coefficients in Pressurized Grated Inlets

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