How Flood Hazard Maps Improve the Understanding of Ecologically Active Floodplains

Stephanie Natho

doi:10.3390/w13070937

How Flood Hazard Maps Improve the Understanding of Ecologically Active Floodplains

Water ◽

10.3390/w13070937 ◽

2021 ◽

Vol 13 (7) ◽

pp. 937

Author(s):

Stephanie Natho

Keyword(s):

Human Impacts ◽

Flood Hazard ◽

Nutrient Retention ◽

Water Volume ◽

The European Union ◽

Hazard Maps ◽

The Past ◽

Regulation Functions ◽

Original Size ◽

Flood Hazard Maps

Floodplains are threatened ecosystems and are not only ecologically meaningful but also important for humans by creating multiple benefits. Many underlying functions, like nutrient retention, carbon sequestration or water regulation, strongly depend on regular inundation. So far, these are approached on the basis of what are called ‘active floodplains’. Active floodplains, defined as statistically inundated once every 100 years, represent less than 10% of a floodplain’s original size. Still, should this remaining area be considered as one homogenous surface in terms of floodplain function, or are there any alternative approaches to quantify ecologically active floodplains? With the European Flood Hazard Maps, the extent of not only medium floods (T-medium) but also frequent floods (T-frequent) needs to be modelled by all member states of the European Union. For large German rivers, both scenarios were compared to quantify the extent, as well as selected indicators for naturalness derived from inundation. It is assumed that the more naturalness there is, the more inundation and the better the functioning. Real inundation was quantified using measured discharges from relevant gauges over the past 20 years. As a result, land uses indicating strong human impacts changed significantly from T-frequent to T-medium floodplains. Furthermore, the extent, water depth and water volume stored in the T-frequent and T-medium floodplains is significantly different. Even T-frequent floodplains experienced inundation for only half of the considered gauges during the past 20 years. This study gives evidence for considering regulation functions on the basis of ecologically active floodplains, meaning in floodplains with more frequent inundation that T-medium floodplains delineate.

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THE USE OF GEOGRAPHIC INFORMATION SYSTEM FOR FLOOD PREDICTIONS

Journal of Engineering Science ◽

10.52326/jes.utm.2021.28(2).09 ◽

2021 ◽

Vol XXVIII (2) ◽

pp. 112-119

Author(s):

Alexandru Tabacaru ◽

◽

Livia Nistor-Lopatenco ◽

Iurie Bejan ◽

Alexandru Pantaz ◽

...

Keyword(s):

Flood Hazard ◽

Geographic Information ◽

Web Gis ◽

Hazard Maps ◽

Digital Maps ◽

The Past ◽

Gis Technologies ◽

The Republic ◽

Flood Hazard Maps ◽

The Eu

The article examines the issue of using geographic information systems (GIS) and WEBGIS technologies to predict areas likely to be flooded. Probabilistic flood hazard maps (0.5%, 0.1% and 1% flood risks) were used, obtained from a model installation in an area subject to flood risk, in this case, the municipality of Ungheni in the Republic Moldova, which has been flooded in the past. The application of GIS technologies is necessary to prevent floods affecting households, infrastructure and to minimize its effects. For this purpose, were analyzed the previous floods that occurred in the region. Also were applied and overlaid thematic digital maps such as Land Use, river network, DTM, Delineation Methodology of water bodies which represents the transposition of the EU Water Framework Directive 2000/60/EC and at the end were uploaded on an ESRI Web GIS platform http://www.dbga.md/siga.html. The Coordinate system used here was WGS-84.

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Design Floods Considering the Epistemic Uncertainty

Water ◽

10.3390/w13111601 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1601

Author(s):

Radu Drobot ◽

Aurelian Florentin Draghia ◽

Daniel Ciuiu ◽

Romică Trandafir

Keyword(s):

Flood Hazard ◽

Epistemic Uncertainty ◽

Statistical Distributions ◽

Hazard Maps ◽

Design Flood ◽

Flood Hydrograph ◽

Recorded Data ◽

Different Shapes ◽

Significant Spread ◽

Flood Hazard Maps

The Design Flood (DF) concept is an essential tool in designing hydraulic works, defining reservoir operation programs, and identifying reliable flood hazard maps. The purpose of this paper is to present a methodology for deriving a Design Flood hydrograph considering the epistemic uncertainty. Several appropriately identified statistical distributions allow for the acceptable approximation of the frequent values of maximum discharges or flood volumes, and display a significant spread for their medium/low Probabilities of Exceedance (PE). The referred scattering, as a consequence of epistemic uncertainty, defines an area of uncertainty for both recorded data and extrapolated values. In considering the upper and lower values of the uncertainty intervals as limits for maximum discharges and flood volumes, and by further combining them compatibly, a set of DFs as completely defined hydrographs with different shapes result for each PE. The herein proposed procedure defines both uni-modal and multi-modal DFs. Subsequently, such DFs help water managers in examining and establishing tailored approaches for a variety of input hydrographs, which might be typically generated in river basins.

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Moving to 3-D flood hazard maps for enhancing risk communication

Environmental Modelling & Software ◽

10.1016/j.envsoft.2018.11.005 ◽

2019 ◽

Vol 111 ◽

pp. 510-522 ◽

Cited By ~ 22

Author(s):

Francesco Macchione ◽

Pierfranco Costabile ◽

Carmelina Costanzo ◽

Rosa De Santis

Keyword(s):

Risk Communication ◽

Flood Hazard ◽

Hazard Maps ◽

Flood Hazard Maps

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Seaside, Oregon Tsunami Pilot Study - modernization of FEMA flood hazard maps

Open-File Report ◽

10.3133/ofr20061234 ◽

2006 ◽

Cited By ~ 4

Author(s):

Keyword(s):

Pilot Study ◽

Flood Hazard ◽

Hazard Maps ◽

Flood Hazard Maps

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Combination of geomorphic classifiers through Machine Learning-based techniques for flood hazard assessment

10.5194/egusphere-egu21-4723 ◽

2021 ◽

Author(s):

Andrea Magnini ◽

Michele Lombardi ◽

Simone Persiano ◽

Antonio Tirri ◽

Francesco Lo Conti ◽

...

Keyword(s):

Machine Learning ◽

Hazard Assessment ◽

Water Depth ◽

Flood Hazard ◽

Research Centre ◽

Hazard Mapping ◽

Hazard Maps ◽

Flood Hazard Assessment ◽

Flood Prone Areas ◽

Flood Hazard Maps

Every year flood events cause worldwide vast economic losses, as well as heavy social and environmental impacts, which have been steadily increasing for the last five decades due to the complex interaction between climate change and anthropogenic pressure (i.e.&#160;land-use and land-cover modifications). As a result, the body of literature on flood risk assessment is constantly and rapidly expanding, aiming at developing faster, computationally lighter and more efficient methods relative to the traditional and resource-intensive hydrodynamic numerical models. Recent and reliable fast-processing techniques for flood hazard assessment and mapping consider binary geomorphic classifiers retrieved from the analysis of Digital Elevation Models (DEMs). These procedures (termed herein &#8220;DEM-based methods&#8221;) produce binary maps distinguishing between floodable and non-floodable areas based on the comparison between the local value of the considered geomorphic classifier and a threshold, which in turn is calibrated against existing flood hazard maps. Previous studies have shown the reliability of DEM-based methods using a single binary classifier, they also highlighted that different classifiers are associated with different performance, depending on the geomorphological, climatic and hydrological characteristics of the study area. The present study maps flood-prone areas and predicts water depth associated with a given non-exceedance probability by combining several geomorphic classifiers and terrain features through regression trees and random forests. We focus on Northern Italy (c.a. 100000 km2, including Po, Adige, Brenta, Bacchiglione and Reno watersheds), and we consider the recently compiled MERIT (Multi-Error Removed Improved-Terrain) DEM, with 3sec-resolution (~90m at the Equator). We select the flood hazard maps provided by (i) the Italian Institute for Environmental Protection and Research (ISPRA), and (ii) the Joint Research Centre (JRC) of the European Commission as reference maps. Our findings (a) confirm the usefulness of machine learning techniques for improving univariate DEM-based flood hazard mapping, (b) enable a discussion on potential and limitations of the approach and (c) suggest promising pathways for further exploring DEM-based approaches for predicting a likely water depth distribution with flood-prone areas.&#160;

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Concept of a Polish Database of a Multi-Dimensional Cadastral System with Particular Focus on Geo-Hazards

Proccedings of 10th International Conference "Environmental Engineering" ◽

10.3846/enviro.2017.247 ◽

2017 ◽

Author(s):

Agnieszka Trystuła

Keyword(s):

Crisis Management ◽

New Technologies ◽

Flood Hazard ◽

Data Visualisation ◽

Hazard Maps ◽

Multiple Factors ◽

Dynamic Growth ◽

Cadastral System ◽

Flood Hazard Maps ◽

Cadastral Systems

The dynamic growth of contemporary cadastral systems depends on multiple factors, which include, e.g. economic policy of a given country and possibilities of implementing activities supporting innovation and transfer of new technologies. A modern cadastre should satisfy not only its leading functions, which include, e.g. fiscal, information, legal or record functions. It should also be oriented towards new challenges, including 3D geovisualisation, which will enable multidimensional visualisation of cadastral objects. New data visualisation methods will contribute to extending the existing functions of cadastral systems and to emergence of new functions, e.g. related to ensuring public safety as a basic aim of crisis management, being an important element of sustainable development. This paper presents a concept of a database of multidimensional cadastral system enabling, for instance, 3D visualisation of system objects, incorporating its known functions (e.g. fiscal, information or legal functions), and also a new purpose –support for crisis management. Additionally, the study indicates sources of data that should be used for this type of undertaking (e.g. flood hazard maps, maps of areas at risk of mass land movements, orthophotomaps).

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Flood hazard assessment of a flood-prone intensively urbanized area – A case study from Samsun Province, Turkey

Geofizika ◽

10.15233/gfz.2020.37.2 ◽

2020 ◽

Vol 37 (1) ◽

pp. 1-25

Author(s):

Neslihan Beden ◽

Aslı Ülke Keskin

Keyword(s):

Flood Hazard ◽

Wide Spectrum ◽

Flood Plain ◽

Flood Management ◽

Flood Damage ◽

The Black Sea ◽

Hazard Maps ◽

Flood Depth ◽

The Social ◽

Flood Hazard Maps

Flooding is one of the most catastrophic events among the wide spectrum of natural disasters that impact human communities. The identification of floodprone areas and the probability of occurrence, or estimated return period, of flood events are fundamental to proper planning for flood management and minimization of the social and economic costs of flood damage. In this study, 1D/2D coupled flood models of the Mert River, which flows into the Black Sea at Samsun in north-central Turkey, were developed. Based on the flood modeling results, flood extent, flood depth and flood hazard maps for the river were produced and they showed that the study area is particularly flood prone, as evidenced by catastrophic flooding in 2012. Specifically, the estimated 100, 500 and 1000-year peak discharges would affect 184 ha, 262 ha and 304 ha, respectively, of the 1,200 ha study area. Hazard ratings for the areas expected to be affected are shown in the flood hazard maps generated. The results of this research can be used by local government agencies in Samsun for the development of policies, strategies and actions that would help minimize the social and economic impacts of flooding, especially adjacent to the downstream sections where there is intensive development on the flood plain.

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Using 1D HEC-RAS Modeling and LiDAR Data to Improve Flood Hazard Maps Accuracy: A Case Study from Jijia Floodplain (NE Romania)

Water ◽

10.3390/w12061624 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1624 ◽

Cited By ~ 1

Author(s):

Elena Huţanu ◽

Alin Mihu-Pintilie ◽

Andrei Urzica ◽

Larisa Elena Paveluc ◽

Cristian Constantin Stoleriu ◽

...

Keyword(s):

Geographical Information Systems ◽

Large Scale ◽

Flood Hazard ◽

Hydraulic Modeling ◽

Geographical Information ◽

Computer Algorithms ◽

Hazard Maps ◽

Modeling Software ◽

Recurrence Intervals ◽

Flood Hazard Maps

The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D hydraulic models, which were generated based on a Light Detection and Ranging (LiDAR) derivate Digital Elevation Model (DEM) and processed within Geographical Information Systems (GIS), can improve large-scale flood hazard maps accuracy. In this study, we developed the first flood vulnerability assessment for 1% (100-year) and 0.1% (1000-year) recurrence intervals within the Jijia floodplain (north-eastern Romania), based on 1D HEC-RAS hydraulic modeling and LiDAR derivate DEM with 0.5 m spatial resolution. The results were compared with official flood hazards maps developed for the same recurrence intervals by the hydrologists of National Administration “Romanian Waters” (NARW) based on MIKE SHE modeling software and a DEM with 2 m spatial resolutions. It was revealed that the 1D HEC-RAS provides a more realistic perspective about the possible flood threats within Jijia floodplain and improves the accuracy of the official flood hazard maps obtained according to Flood Directive 2007/60/EC.

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