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Jiang, X., and H. Tatano. "A rainfall design method for spatial flood risk assessment: considering multiple flood sources." Hydrology and Earth System Sciences Discussions 12, no. 8 (2015): 8005–33. http://dx.doi.org/10.5194/hessd-12-8005-2015.
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Abstract. Information about the spatial distribution of flood risk is important for integrated urban flood risk management. Focusing on urban areas, spatial flood risk assessment must reflect all risk information derived from multiple flood sources: rivers, drainage, coastal flooding etc. that may affect the area. However, conventional flood risk assessment deals with each flood source independently, which leads to an underestimation of flood risk in the floodplain. Even in floodplains that have no risk from coastal flooding, flooding from river channels and inundation caused by insufficient drainage capacity should be considered simultaneously. For integrated flood risk management, it is necessary to establish a methodology to estimate flood risk distribution across a floodplain. In this paper, a rainfall design method for spatial flood risk assessment, which considers the joint effects of multiple flood sources, is proposed. The concept of critical rainfall duration determined by the concentration time of flooding is introduced to connect response characteristics of different flood sources with rainfall. A copula method is then adopted to capture the correlation of rainfall amount with different critical rainfall durations. Rainfall events are designed taking advantage of the copula structure of correlation and marginal distribution of rainfall amounts within different critical rainfall durations. A case study in the Otsu River Basin, Osaka prefecture, Japan was conducted to demonstrate this methodology.
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Chiang, Yen-Ming, Kuo-Lin Hsu, Fi-John Chang, Yang Hong, and Soroosh Sorooshian. "Merging multiple precipitation sources for flash flood forecasting." Journal of Hydrology 340, no. 3-4 (2007): 183–96. http://dx.doi.org/10.1016/j.jhydrol.2007.04.007.
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Jiang, Xinyu, Lijiao Yang, and Hirokazu Tatano. "Assessing Spatial Flood Risk from Multiple Flood Sources in a Small River Basin: A Method Based on Multivariate Design Rainfall." Water 11, no. 5 (2019): 1031. http://dx.doi.org/10.3390/w11051031.
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A key issue in assessing the spatial distribution of flood risk is considering risk information derived from multiple flood sources (river flooding, drainage inundation, etc.) that may affect the risk assessment area. This study proposes a method for assessing spatial flood risk that includes flooding and inundation in small-basin areas through multivariate design rainfall. The concept of critical rainfall duration, determined by the time of concentration of flooding, is used to represent the characteristics of flooding from different sources. A copula method is adopted to capture the correlation of rainfall amounts in different critical rainfall durations to reflect the correlation of potential flooding from multiple flood sources. Rainfalls for different return periods are designed based on the copula multivariate analysis. Using the design rainfalls as input, flood risk is assessed following the rainfall–runoff–inundation–loss estimation procedure. A case study of the Otsu River Basin, Osaka Prefecture, Japan, was conducted to demonstrate the feasibility and advantages of this method. Compared to conventional rainfall design, this method considers the response characteristics of multiple flood sources, and solves the problem of flood risk assessment from multiple flood sources. It can be applied to generate a precise flood risk assessment to support integrated flood risk management.
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Saint-Martin, Clotilde, Pierre Javelle, and Freddy Vinet. "DamaGIS: a multisource geodatabase for collection of flood-related damage data." Earth System Science Data 10, no. 2 (2018): 1019–29. http://dx.doi.org/10.5194/essd-10-1019-2018.
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Abstract. Every year in France, recurring flood events result in several million euros of damage, and reducing the heavy consequences of floods has become a high priority. However, actions to reduce the impact of floods are often hindered by the lack of damage data on past flood events. The present paper introduces a new database for collection and assessment of flood-related damage. The DamaGIS database offers an innovative bottom-up approach to gather and identify damage data from multiple sources, including new media. The study area has been defined as the south of France considering the high frequency of floods over the past years. This paper presents the structure and contents of the database. It also presents operating instructions in order to keep collecting damage data within the database. This paper also describes an easily reproducible method to assess the severity of flood damage regardless of the location or date of occurrence. A first analysis of the damage contents is also provided in order to assess data quality and the relevance of the database. According to this analysis, despite its lack of comprehensiveness, the DamaGIS database presents many advantages. Indeed, DamaGIS provides a high accuracy of data as well as simplicity of use. It also has the additional benefit of being accessible in multiple formats and is open access. The DamaGIS database is available at https://doi.org/10.5281/zenodo.1241089.
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See, Koh Liew, Nayan Nasir, Saleh Yazid, Hashim Mohmadisa, Mahat Hanifah, and A. Rahaman Zullyadini. "Well Water Site Selection at Local Scale Using Geographical Information System for Flood Victim in Malaysia." Indonesian Journal of Geography 50, no. 2 (2018): 205. http://dx.doi.org/10.22146/ijg.32925.
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Clean water supply is a major problem among flood victims during flood events. This article aims to determine the sites of well water sources that can be utilised during floods in the District of Kuala Krai, Kelantan. Field methods and Geographic Information Systems (GIS) were applied in the process of selecting flood victim evacuation centres and wells. The data used were spatial data obtained primarily, namely the well data, evacuation centre data and flood area data. The well and evacuation centre data were obtained by field methods conducted to determine the position of wells using global positioning system tools, and the same for the location of the evacuation centres. Information related to evacuation centres was obtained secondarily from multiple agencies and gathered into GIS as an evacuation centre attribute. The flood area data was also obtained via secondary data and was digitised using the ArcGIS software. The data processing was divided into two stages, namely the first stage of determining the flood victim evacuation centres to be used in this research in a structural manner based on two main criteria which were the extent to which an evacuation centre was affected by the flood and the highest capacity of victims for each district with the greatest impact to the flood affected population. The second stage was to determine the location of wells based on three criteria, namely i) not affected by flood, ii) the closest distance to the selected flood victim evacuation centre and iii) located at different locations. Among the main GIS analyses used were locational analysis, overlay analysis, and proximity analysis. The results showed that four (4) flood evacuation centres had been chosen and matched the criteria set, namely SMK Sultan Yahya Petra 2, SMK Manek Urai Lama, SMK Laloh and SK Kuala Gris. While six (6) wells had been selected as water sources that could be consumed by the flood victims at 4 evacuation centres in helping to provide clean water supply, namely Kg. Keroh 16 (T1), Kg. Batu Mengkebang 10 (T2), Lepan Meranti (T3), Kg. Budi (T4), Kg. Jelawang Tengah 2 (T5) and Kg. Durian Hijau 1 (T6). With the presence of the well water sources that can be used during flood events, clean water supply can be distributed to flood victims at the evacuation centres. Indirectly, this research can reduce the impact of floods in the future, especially in terms of clean water supply even during the hit of a major flood.
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Bray, Stephanie N., and Richard H. McCuen. "Importance of the Assumption of Independence or Dependence among Multiple Flood Sources." Journal of Hydrologic Engineering 19, no. 6 (2014): 1194–202. http://dx.doi.org/10.1061/(asce)he.1943-5584.0000901.
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熊, 明. "Forecasting of Flash-Flood-Producing Precipitation by Coupling Multiple Sources of Information." Journal of Water Resources Research 06, no. 02 (2017): 91–102. http://dx.doi.org/10.12677/jwrr.2017.62013.
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Mou, Shiyu, Peng Shi, Simin Qu, et al. "Uncertainty Analysis of Two Copula-Based Conditional Regional Design Flood Composition Methods: A Case Study of Huai River, China." Water 10, no. 12 (2018): 1872. http://dx.doi.org/10.3390/w10121872.
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The issue of regional design flood composition should be considered when it comes to the analysis of multiple sections. However, the uncertainty accompanied in the process of regional design flood composition point identification is often overlooked in the literature. The purpose of this paper, therefore, is to uncover the sensibility of marginal distribution selection and the impact of sampling uncertainty caused by the limited records on two copula-based conditional regional design flood composition methods, i.e., the conditional expectation regional design flood composition (CEC) method and the conditional most likely regional design flood composition (CMLC) method, which are developed to derive the combinations of maximum 30-day flood volumes at the two sub-basins above Bengbu hydrological station for given univariate return periods. An experiment combing different marginal distributions was conducted to explore the former uncertainty source, while a conditional copula-based parametric bootstrapping (CC-PB) procedure together with five metrics (i.e., horizontal standard deviation, vertical standard deviation, area of 25%, 50%, 75% BCIs (bivariate confidence intervals)) were designed and employed subsequently to evaluate the latter uncertainty source. The results indicated that the CEC and CMLC point identification was closely bound up with the different combinations of univariate distributions in spite of the comparatively tiny difference of the fitting performances of seven candidate univariate distributions, and was greatly affected by the sampling uncertainty due to the limited observations, which should arouse critical attention. Both of the analyzed sources of uncertainty increased with the growing T (univariate return period). As for the comparison of the two proposed methods, it seemed that the uncertainty due to the marginal selection had a slight larger impact on the CEC scheme than the CMLC scheme; but in terms of sampling uncertainty, the CMLC method performed slightly stable for large floods, while when considering moderate and small floods, the CEC method performed better.
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Qi, Wei, Chi Zhang, Guangtao Fu, Huicheng Zhou, and Junguo Liu. "Quantifying Uncertainties in Extreme Flood Predictions under Climate Change for a Medium-Sized Basin in Northeastern China." Journal of Hydrometeorology 17, no. 12 (2016): 3099–112. http://dx.doi.org/10.1175/jhm-d-15-0212.1.
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Abstract This study develops a new variance-based uncertainty assessment framework to investigate the individual and combined impacts of various uncertainty sources on future extreme floods. The Long Ashton Research Station Weather Generator (LARS-WG) approach is used to downscale multiple general circulation models (GCMs), and the dynamically dimensioned search approximation of uncertainty approach is used to quantify hydrological model uncertainty. Extreme floods in a region in northeastern China are studied for two future periods: near term (2046–65) and far term (2080–99). Six GCMs and three emission scenarios (A1B, A2, and B1) are used. Results obtained from this case study show that the 500-yr flood magnitude could increase by 4.5% in 2046–65 and by 6.4% in 2080–99 in terms of median values; in worst-case scenarios, it could increase by 63.0% and 111.8% in 2046–65 and 2080–99, respectively. It is found that the combined effect of GCMs, emission scenarios, and hydrological models has a larger influence on the discharge uncertainties than the individual impacts from emission scenarios and hydrological models. Further, results show GCMs are the dominant contributor to extreme flood uncertainty in both 2046–65 and 2080–99 periods. This study demonstrates that the developed framework can be used to effectively investigate changes in the occurrence of extreme floods in the future and to quantify individual and combined contributions of various uncertainty sources to extreme flood uncertainty, which can guide future efforts to reduce uncertainty.
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Annis, Antonio, and Fernando Nardi. "GFPLAIN and Multi-Source Data Assimilation Modeling: Conceptualization of a Flood Forecasting Framework Supported by Hydrogeomorphic Floodplain Rapid Mapping." Hydrology 8, no. 4 (2021): 143. http://dx.doi.org/10.3390/hydrology8040143.
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Hydrologic/hydraulic models for flood risk assessment, forecasting and hindcasting have been greatly supported by the rising availability of increasingly accurate and high-resolution Earth Observation (EO) data. EO-based topographic and hydrologic open geo data are, nowadays, available on large scales. Data Assimilation (DA) models allow Early Warning Systems (EWS) to produce accurate and timely flood predictions. DA-based EWS generally use river flow real-time observations and 1D hydraulic models to identify potential inundation hot spots. Detailed high-resolution 2D hydraulic modeling is usually not used in EWS for the computational burden and the numerical complexity of injecting multiple spatially distributed sources of flow observations. In recent times, DEM-based hydrogeomorphic models demonstrated their ability in characterizing river basin hydrologic forcing and floodplain domains providing data-parsimonious opportunities for data-scarce regions. This work investigates the use of hydrogeomorphic floodplain terrain processing for optimizing the ability of DA-based EWSs in using diverse distributed flow observations. A flood forecasting framework with novel applications of hydrogeomorphic floodplain processing is conceptualized for empowering flood EWSs in preliminarily identifying the computational domain for hydraulic modeling, rapid flood detection using satellite images, and filtering geotagged crowdsourced data for flood monitoring. The proposed flood forecasting framework supports the development of an integrated geomorphic-hydrologic/hydraulic modeling chain for a DA that values multiple sources of observation. This work investigates the value of floodplain hydrogeomorphic models to tackle the major challenges of DA for EWS with specific regard to the computational efficiency issues and the lack of data in ungauged river basins towards an improved flood forecasting able to use advanced hydrodynamic modeling and to inject all available sources of observations including flood phenomena captures by citizens.
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Amengual, A., D. S. Carrió, G. Ravazzani, and V. Homar. "A Comparison of Ensemble Strategies for Flash Flood Forecasting: The 12 October 2007 Case Study in Valencia, Spain." Journal of Hydrometeorology 18, no. 4 (2017): 1143–66. http://dx.doi.org/10.1175/jhm-d-16-0281.1.
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Abstract On 12 October 2007, several flash floods affected the Valencia region, eastern Spain, with devastating impacts in terms of human, social, and economic losses. An enhanced modeling and forecasting of these extremes, which can provide a tangible basis for flood early warning procedures and mitigation measures over the Mediterranean, is one of the fundamental motivations of the international Hydrological Cycle in the Mediterranean Experiment (HyMeX) program. The predictability bounds set by multiple sources of hydrological and meteorological uncertainty require their explicit representation in hydrometeorological forecasting systems. By including local convective precipitation systems, short-range ensemble prediction systems (SREPSs) provide a state-of-the-art framework to generate quantitative discharge forecasts and to cope with different sources of external-scale (i.e., external to the hydrological system) uncertainties. The performance of three distinct hydrological ensemble prediction systems (HEPSs) for the small-sized Serpis River basin is examined as a support tool for early warning and mitigation strategies. To this end, the Flash-Flood Event–Based Spatially Distributed Rainfall–Runoff Transformation–Water Balance (FEST-WB) model is driven by ground stations to examine the hydrological response of this semiarid and karstic catchment to heavy rains. The use of a multisite and novel calibration approach for the FEST-WB parameters is necessary to cope with the high nonlinearities emerging from the rainfall–runoff transformation and heterogeneities in the basin response. After calibration, FEST-WB reproduces with remarkable accuracy the hydrological response to intense precipitation and, in particular, the 12 October 2007 flash flood. Next, the flood predictability challenge is focused on quantitative precipitation forecasts (QPFs). In this regard, three SREPS generation strategies using the WRF Model are analyzed. On the one side, two SREPSs accounting for 1) uncertainties in the initial conditions (ICs) and lateral boundary conditions (LBCs) and 2) physical parameterizations are evaluated. An ensemble Kalman filter (EnKF) is also designed to test the ability of ensemble data assimilation methods to represent key mesoscale uncertainties from both IC and subscale processes. Results indicate that accounting for diversity in the physical parameterization schemes provides the best probabilistic high-resolution QPFs for this particular flash flood event. For low to moderate precipitation rates, EnKF and pure multiple physics approaches render undistinguishable accuracy for the test situation at larger scales. However, only the multiple physics QPFs properly drive the HEPS to render the most accurate flood warning signals. That is, extreme precipitation values produced by these convective-scale precipitation systems anchored by complex orography are better forecast when accounting just for uncertainties in the physical parameterizations. These findings contribute to the identification of ensemble strategies better targeted to the most relevant sources of uncertainty before flash flood situations over small catchments.
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Dawson, David A., Kim Vercruysse, and Nigel Wright. "A spatial framework to explore needs and opportunities for interoperable urban flood management." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2168 (2020): 20190205. http://dx.doi.org/10.1098/rsta.2019.0205.
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Managing current and future urban flood risks must consider the connection (i.e. interoperability) between existing (and new) infrastructure systems to manage stormwater (pluvial flooding). Yet, due to a lack of systematic approaches to identify interoperable flood management interventions, opportunities are missed to combine investments of existing infrastructure (e.g. drainage, roads, land use and buildings) with blue-green infrastructure (e.g. sustainable urban drainage systems, green roofs, green spaces). In this study, a spatial analysis framework is presented combining hydrodynamic modelling with spatial information on infrastructure systems to provide strategic direction for systems-level urban flood management (UFM). The framework is built upon three categories of data: (i) flood hazard areas (i.e. characterize the spatial flood problem); (ii) flood source areas (i.e. areas contributing the most to surface flooding); (iii) the interoperable potential of different systems (i.e. which infrastructure systems can contribute to water management functions). Applied to the urban catchment of Newcastle-Upon-Tyne (UK), the study illustrates the novelty of combining spatial data sources in a systematic way, and highlights the spatial (dis)connectivity in terms of flood source areas (where most of the flood management intervention is required) and the benefit areas (where most of the reduction in flooding occurs). The framework provides a strategic tool for managing stormwater pathways from an interoperable perspective that can help city-scale infrastructure development that considers UFM across multiple systems. This article is part of the theme issue ‘Urban flood resilience’.
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Nicholson, Suzanne W., Klaus J. Schulz, Steven B. Shirey, and John C. Green. "Rift-wide correlation of 1.1 Ga Midcontinent rift system basalts: implications for multiple mantle sources during rift development." Canadian Journal of Earth Sciences 34, no. 4 (1997): 504–20. http://dx.doi.org/10.1139/e17-041.
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Magmatism that accompanied the 1.1 Ga Midcontinent rift system (MRS) is attributed to the upwelling and decompression melting of a mantle plume beneath North America. Five distinctive flood-basalt compositions are recognized in the rift-related basalt succession along the south shore of western Lake Superior, based on stratigraphically correlated major element, trace element, and Nd isotopic analyses. These distinctive compositions can be correlated with equivalent basalt types in comparable stratigraphic positions in other MRS localities around western Lake Superior. Four of these compositions are also recognized at Mamainse Point more than 200 km away in eastern Lake Superior. These regionally correlative basalt compositions provide the basis for determining the sequential contribution of various mantle sources to flood-basalt magmatism during rift development, extending a model originally developed for eastern Lake Superior. In this refined model, the earliest basalts were derived from small degrees of partial melting at great depth of an enriched, ocean-island-type plume mantle source (εNd(1100) value of about 0), followed by magmas representing melts from this plume source and interaction with another mantle source, most likely continental lithospheric mantle (εNd(1100) < 0). The relative contribution of this second mantle source diminished with time as larger degree partial melts of the plume became the dominant source for the voluminous younger basalts (εNd(1100) value of about 0). Towards the end of magmatism, mixtures of melts from the plume and a depleted asthenospheric mantle source became dominant (εNd(1100) = 0 to +3).
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Uhlemann, S., A. H. Thieken, and B. Merz. "A quality assessment framework for natural hazard event documentations: application to trans-basin flood reports in Germany." Natural Hazards and Earth System Sciences Discussions 1, no. 1 (2013): 143–92. http://dx.doi.org/10.5194/nhessd-1-143-2013.
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Abstract. Written sources that aim at documenting and analysing a particular natural hazard event in the recent past are published at vast majority as grey literature (e.g. as technical reports) and therefore outside of the scholarly publication routes. In consequence, the application of event specific documentations in natural hazard research has been constrained by barriers in accessibility and concerns of credibility towards these sources and by limited awareness of their content and its usefulness for research questions. In this study we address the concerns of credibility for the first time and present a quality assessment framework for written sources from a user's perspective, i.e. we assess the documents' fitness for use to enhance the understanding of trans-basin floods in Germany in the period 1952–2002. The framework is designed to be generally applicable for any natural hazard event documentation and assesses the quality of a document addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. We introduce an ordinal scaling scheme to grade the quality in the single quality dimensions and the Pedigree score which serves as a measure for the overall document quality. We present results of an application of the framework to a set of 133 event specific documentations relevant for understanding trans-basin floods in Germany. Our results show that the majority of flood event specific reports are of a good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The validation of our results against assessments of two independent peers confirms the objectivity and transparency of the quality assessment framework. Using an example flood event that occurred in October/November 1998 we demonstrate how the information from multiple reports can be synthesised under consideration of their quality.
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Uhlemann, S., A. H. Thieken, and B. Merz. "A quality assessment framework for natural hazard event documentation: application to trans-basin flood reports in Germany." Natural Hazards and Earth System Sciences 14, no. 2 (2014): 189–208. http://dx.doi.org/10.5194/nhess-14-189-2014.
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Abstract. Written sources that aim at documenting and analysing a particular natural hazard event in the recent past are published at vast majority as grey literature (e.g. as technical reports) and therefore outside of the scholarly publication routes. In consequence, the application of event-specific documentation in natural hazard research has been constrained by barriers in accessibility, concerns of credibility towards these sources and by limited awareness of their content and its usefulness for research questions. In this study we address the concerns of credibility for the first time and present a quality assessment framework for written sources from a user's perspective, i.e. we assess the documents' fitness for use to enhance the understanding of trans-basin floods in Germany in the period 1952–2002. The framework is designed to be generally applicable for any natural hazard event documentation and assesses the quality of a document, addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. We introduce an ordinal scaling scheme to grade the quality in the individual quality dimensions and the Pedigree score which serves as a measure for the overall document quality. We present results of an application of the framework to a set of 133 cases of event-specific documentation relevant for understanding trans-basin floods in Germany. Our results show that the majority of flood event-specific reports are of good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The validation of our results against assessments of two independent peers confirms the objectivity and transparency of the quality assessment framework. Using an example flood event that occurred in October/November 1998 we demonstrate how the information from multiple reports can be synthesised.
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Brenner, Claire, Claude Meisch, Benjamin Apperl, and Karsten Schulz. "Towards periodic and time-referenced flood risk assessment using airborne remote sensing." Journal of Hydrology and Hydromechanics 64, no. 4 (2016): 438–47. http://dx.doi.org/10.1515/johh-2016-0034.
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Abstract Flood risk management is founded on the regular assessment of damage potential. A significant parameter for assessing damage potential is the number of at-risk objects. However, data sets on exposure are often incomplete and/or lack time-references. Airborne remote sensing data, such as orthophotos, offers a regularly-updated, time-referenced depiction of land use. As such, remote sensing data compensates for incomplete data sources (such as digital cadastral maps). Orthophotos can even be used to analyze the temporal dynamics of flood damage potential, providing that time-referenced information is available for multiple time points. This paper describes a method for integrating orthophotos into flood risk analyses. In Austria, orthophotos are updated every three years, allowing their integration into cyclical flood risk assessments. The results of a case study presented in this paper demonstrate that orthophotos are most useful where other data sources, such as digital cadastral maps, are incomplete. In such situations, orthophotos lead to a significant increase in estimated damage potential. Orthophoto analysis allows damage potentials to be re-assessed at regular intervals, another major advantage over digital cadastral maps. Orthophoto analysis thus supports the evaluation of flood risk management options.
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Villani, Giulia, Stefania Nanni, Fausto Tomei, et al. "The RainBO Platform for Enhancing Urban Resilience to Floods: An Efficient Tool for Planning and Emergency Phases." Climate 7, no. 12 (2019): 145. http://dx.doi.org/10.3390/cli7120145.
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Many urban areas face an increasing flood risk, which includes the risk of flash floods. Increasing extreme precipitation events will likely lead to greater human and economic losses unless reliable and efficient early warning systems (EWS) along with other adaptation actions are put in place in urban areas. The challenge is in the integration and analysis in time and space of the environmental, meteorological, and territorial data from multiple sources needed to build up EWS able to provide efficient contribution to increase the resilience of vulnerable and exposed urban communities to flooding. Efficient EWS contribute to the preparedness phase of the disaster cycle but could also be relevant in the planning of the emergency phase. The RainBO Life project addressed this matter, focusing on the improvement of knowledge, methods, and tools for the monitoring and forecast of extreme precipitation events and the assessment of the associated flood risk for small and medium watercourses in urban areas. To put this into practice, RainBO developed a webGIS platform, which contributes to the “planning” of the management of river flood events through the use of detailed data and flood risk/vulnerability maps, and the “event management” with real-time monitoring/forecast of the events through the collection of observed data from real sensors, estimated/forecasted data from hydrologic models as well as qualitative data collected through a crowdsourcing app.
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Eder, A., M. Exner-Kittridge, P. Strauss, and G. Blöschl. "Re-suspension of bed sediment in a small stream – results from two flushing experiments." Hydrology and Earth System Sciences Discussions 10, no. 10 (2013): 12077–104. http://dx.doi.org/10.5194/hessd-10-12077-2013.
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Abstract. Streams draining small watersheds often exhibit multiple peaking sedigraphs associated with single peaking hydrographs. The process reasons of the multiple sediment peaks are not fully understood but they may be related to the activation of different sediment sources such as the streambed itself where deposited sediments from previous events may be available for resuspension. To understand resuspension of stream bed sediments at the reach scale we artificially flooded the small stream of the HOAL Petzenkirchen catchment in Austria by pumping sediment-free water into the stream. Two short floods were produced and flow, sediment and bromide concentrations were measured at three sites with high temporal resolution. Hydrologically, the two flood events were almost identical. The peak flows decreased from 57 to 7.9 L s−1 and the flow volumes decreased from 17 to 11.3 m3 along the 590 m reach of the stream. However, a considerably smaller sediment load was resuspended and transported during the second flood due to depletion of stream bed sediments. The exception was the middle section of the stream where more sediment was transported during the second flood event which can be explained by differences between flow velocity and wave celerity and the resulting displacement of sediments within the stream. The results indicate that the first peak of the sedigraphs of natural events in this stream is indeed caused by the resuspension of streambed sediments, accounting for up to six percent of the total sediment load depending on total flow volume.
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Wang, Yuntao, Albert S. Chen, Guangtao Fu, Slobodan Djordjević, Chi Zhang, and Dragan A. Savić. "An integrated framework for high-resolution urban flood modelling considering multiple information sources and urban features." Environmental Modelling & Software 107 (September 2018): 85–95. http://dx.doi.org/10.1016/j.envsoft.2018.06.010.
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Qin, Guoshuai, Jianwei Liu, Shiguo Xu, and Ya Sun. "Pollution Source Apportionment and Water Quality Risk Evaluation of a Drinking Water Reservoir during Flood Seasons." International Journal of Environmental Research and Public Health 18, no. 4 (2021): 1873. http://dx.doi.org/10.3390/ijerph18041873.
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Reservoirs play an important role in the urban water supply, yet reservoirs receive an influx of large amounts of pollutants from the upper watershed during flood seasons, causing a decline in water quality and threatening the water supply. Identifying major pollution sources and assessing water quality risks are important for the environmental protection of reservoirs. In this paper, the principal component/factor analysis-multiple linear regression (PCA/FA-MLR) model and Bayesian networks (BNs) are integrated to identify water pollution sources and assess the water quality risk in different precipitation conditions, which provides an effective framework for water quality management during flood seasons. The deterioration of the water quality of rivers in the flood season is found to be the main reason for the deterioration in the reservoir water quality. The nonpoint source pollution is the major pollution source of the reservoir, which contributes 53.20%, 48.41%, 72.69%, and 68.06% of the total nitrogen (TN), phosphorus (TP), fecal coliforms (F.coli), and turbidity (TUB), respectively. The risk of the water quality parameters exceeding the surface water standard under different hydrological conditions is assessed. The results show that the probability of the exceedance rate of TN, TP, and F.coli increases from 91.13%, 3.40%, and 3.34%, to 95.75%, 25.77%, and 12.76% as the monthly rainfall increases from ≤68.25 mm to >190.18 mm. The risk to the water quality of the Biliuhe River reservoir is found to increase with the rising rainfall intensity, the water quality risk at the inlet during the flood season is found to be much greater than that at the dam site, and the increasing trend of TP and turbidity is greater than that of TN and F.coli. The risk of five-day biochemical oxygen demand (BOD5) does not increase with increasing precipitation, indicating that it is less affected by nonpoint source pollution. The results of this study can provide a research basis for water environment management during flood seasons.
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Schulte, L., J. C. Peña, F. Carvalho, et al. "A 2600-year history of floods in the Bernese Alps, Switzerland: frequencies, mechanisms and climate forcing." Hydrology and Earth System Sciences 19, no. 7 (2015): 3047–72. http://dx.doi.org/10.5194/hess-19-3047-2015.
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Abstract. A 2600-year long composite palaeoflood record is reconstructed from high-resolution delta plain sediments of the Hasli–Aare floodplain on the northern slope of the Swiss Alps. Natural proxies compiled from sedimentary, geochemical and geomorphological data were calibrated by textual and factual sources and instrumental data. No fewer than 12 of the 14 historically recorded extreme events between 1480 and the termination of the Hasli–Aare river channel correction in 1875 were also identified by coarse-grained flood layers, log(Zr / Ti) peaks and factor 1 anomalies. Geomorphological, historical and instrumental data provide evidence for flood damage intensities and discharge estimations of severe and catastrophic historical floods. Spectral analysis of the geochemical and documentary flood series and several climate proxies (TSI, δ18O, tree-rings, NAO, SNAO) identify similar periodicities of around 60, 80, 100, 120 and 200 years during the last millennia, indicating the influence of the North Atlantic circulation and solar forcing on alpine flood dynamics. The composite floodplain record illustrates that periods of organic soil formation and deposition of phyllosilicates (from the medium high catchment area) match those of total solar irradiance maxima, suggesting reduced flood activity during warmer climate pulses. Aggradation with multiple sets of flood layers with increased contribution of siliciclasts from the highest catchment area (plutonic bedrock) (e.g. 1300–1350, 1420–1480, 1550–1620, 1650–1720 and 1811–1851 cal yr AD) occurred predominantly during periods with reduced solar irradiance, lower δ18O anomalies, cooler summer temperatures and phases of drier spring climate in the Alps. Increased water storage by glaciers, snow cover and snow patches susceptible to melting processes associated with rainfall episodes and abrupt rises in temperature substantially increased surface runoff on slopes and discharges of alpine rivers. This interpretation is in agreement with the findings that the severe and catastrophic historical floods in the Aare since 1670 occurred mostly during positive SNAO (Summer North Atlantic Oscillation) pulses after years or even decades dominated by negative SNAO and cooler annual temperatures.
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Dwirahmadi, Rutherford, Phung, and Chu. "Understanding the Operational Concept of a Flood-Resilient Urban Community in Jakarta, Indonesia, from the Perspectives of Disaster Risk Reduction, Climate Change Adaptation and Development Agencies." International Journal of Environmental Research and Public Health 16, no. 20 (2019): 3993. http://dx.doi.org/10.3390/ijerph16203993.
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Climate change-related extreme events such as floods have and will continue to present a great challenge to disaster risk management. There is a pressing need to develop a robust management strategy via enhancing the resiliency of the community, particularly in the context of complex urban environments, like Jakarta. Resilience is conceptualized within specific contexts and uniquely tailored to the targeted setting, yet research regarding the operational concept of a flood-resilient community in the context of Jakarta remains limited. This paper will elaborate this operational concept through understanding the desirable features and influential barriers of a flood-resilient community through the lenses of three main stakeholder groups: disaster risk reduction (DRR), climate change adaptation (CCA), and development. It will also discuss the ways in which the synergies that exist across these groups can be enhanced. Both quantitative and qualitative approaches were applied in this study, and multiple sources of data were used. The findings indicate that these groups share common views regarding the importance of human aspects being central to resilience building efforts. We argue there is an urgent need to shift the flood resilience building paradigm towards building community resilience from the people and to apply a collaborative governance approach to facilitate effective partnership between the actors involved.
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Eder, A., M. Exner-Kittridge, P. Strauss, and G. Blöschl. "Re-suspension of bed sediment in a small stream – results from two flushing experiments." Hydrology and Earth System Sciences 18, no. 3 (2014): 1043–52. http://dx.doi.org/10.5194/hess-18-1043-2014.
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Abstract. Streams draining small watersheds often exhibit multiple peaking sedigraphs associated with single peaking hydrographs. The process reasons of the multiple sediment peaks are not fully understood but they may be related to the activation of different sediment sources such as the stream bed itself, where deposited sediments from previous events may be available for resuspension. To understand resuspension of stream bed sediments at the reach scale we artificially flooded the small stream of the HOAL Petzenkirchen catchment in Austria by pumping sediment-free water into the stream. Two short floods were produced and flow, sediment and bromide concentrations were measured at three sites with high temporal resolution. Hydrologically, the two flood events were almost identical. The peak flows decreased from 57 to 7.9 L s−1 and the flow volumes decreased from 17 to 11.3 m2 along the 590 m reach of the stream. However, a considerably smaller sediment load was resuspended and transported during the second flood due to depletion of stream bed sediments. The exception was the middle section of the stream, where more sediment was transported during the second flood event which can be explained by differences between flow velocity and wave celerity and the resulting displacement of sediments within the stream. The results indicate that the first peak of the sedigraphs of natural events in this stream is indeed caused by the resuspension of stream bed sediments, accounting for up to six percent of the total sediment load depending on total flow volume.
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Shepherd, Jeanette, and Kitty van Vuuren. "The Brisbane flood: CALD gatekeepers’ risk communication role." Disaster Prevention and Management 23, no. 4 (2014): 469–83. http://dx.doi.org/10.1108/dpm-08-2013-0133.
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Purpose – The purpose of this paper is to present the results of an original research project that explored the experiences and actions of immigrant and refugee communities during the 2011 Brisbane flood. It specifically examines the role of culturally and linguistically diverse (CALD) community leaders who acted as “gatekeepers” in communicating emergency responses to the disaster to their communities. Design/methodology/approach – Semi-structured interviews were conducted with eight “gatekeepers” who met the study's selection criteria. Findings – The study found that the characteristics and demographics of CALD gatekeepers in Brisbane, their use of multiple sources related to their involvement in the community, their use of interpersonal sources for information-seeking and use of the mass media, is largely consistent with previous studies. Research limitations/implications – This study departed from previous research with respect to issues of trust in government sources, gender and warning confirmation behaviour. These differences affected the behaviour of the CALD gatekeepers, especially around risk perception, information dissemination and filtering. Although the study points to the potential challenges facing emergency management services in fully incorporating the needs of all CALD communities, implications are limited given the small number of gatekeepers who agreed to be interviewed. Practical implications – Despite its limitation, the study does indicate that a critical gap exists in understanding CALD community responses to natural disasters. Social implications – The paper concludes with suggestions for a research agenda to gain better knowledge of the ethnic, demographic and personal factors that influence gatekeeping behaviour. Originality/value – The study is original because no prior research has directed attention to Brisbane's CALD community responses to disasters.
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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (2021): 144. http://dx.doi.org/10.3390/w13020144.
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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.
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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (2021): 144. http://dx.doi.org/10.3390/w13020144.
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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.
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Driessen, T. L. A., and M. van Ledden. "The large-scale impact of climate change to Mississippi flood hazard in New Orleans." Drinking Water Engineering and Science Discussions 5, no. 1 (2012): 333–49. http://dx.doi.org/10.5194/dwesd-5-333-2012.
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Abstract. The objective of this paper is to describe the impact of climate change on the Mississippi River flood hazard in the New Orleans area. This city has a unique flood risk management challenge, heavily influenced by climate change, since it faces flood hazards from multiple geographical locations (e.g. Lake Pontchartrain and Mississippi River) and multiple sources (hurricane, river, rainfall). Also the low elevation and significant subsidence rate of the Greater New Orleans area poses a high risk and challenges the water management of this urban area. Its vulnerability to flooding became dramatically apparent during Hurricane Katrina in 2005 with huge economic losses and a large number of casualties. A SOBEK Rural 1DFLOW model was set up to simulate the general hydrodynamics. This improved model includes two important spillways that are operated during high flow conditions. Subsequently, a weighted multi-criteria calibration procedure was performed to calibrate the model for high flows. Validation for floods in 2011 indicates a very reasonable performance for high flows and clearly demonstrates the necessity of the spillways. 32 different scenarios are defined which includes the relatively large sea level rise and the changing discharge regime that is expected due to climate change. The impact of these scenarios is analysed by the hydrodynamic model. Results show that during high flows New Orleans will not be affected by varying discharge regimes, since the presence of the spillways ensures a constant discharge through the city. In contrary, sea level rise is expected to push water levels upwards. The effect of sea level rise will be noticeable even more than 470 km upstream. Climate change impacts necessitate a more frequent use of the spillways and opening strategies that are based on stages. Potential alternatives on how to cope with the flood hazard of this river in the long term, such as river widening and large-scale redistribution of the flow through diversions, are proposed.
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Kuczynska-Siehien, Joanna, Dimitrios Piretzidis, Michael G. Sideris, Tomasz Olszak, and Viktor Szabó. "Monitoring of extreme land hydrology events in central Poland using GRACE, land surface models and absolute gravity data." Journal of Applied Geodesy 13, no. 3 (2019): 229–43. http://dx.doi.org/10.1515/jag-2019-0003.
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Abstract This study deals with the analysis of temporal gravity variations in central Poland, deduced from multiple sources and covering the period from 2002–2016. The gravity data sets used comprise GRACE monthly solutions, GLDAS land surface models and absolute gravimeter measurements from the FG-5 gravimeter located in Józefosław, Poland. All data are corrected using standard processing methods in order to include the same gravity effects. After removing the annual and semi-annual components from all data using least-squares spectral analysis and seasonal-trend decomposition, the deseasoned time series are derived and examined for signatures of extreme hydrological events. The signatures of several severe drought and flood conditions affecting Poland and central Europe are identified. A complementary correlation analysis is performed to assess the level of agreement between different data sources. A higher correlation is shown when the analysis is restricted in the 2009–2012 period that includes the 2010 extreme flood and 2011 increased precipitation events, both affecting Poland.
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Vito, D. "USE OF MULTIVARIATE MACHINE LEARNING ANALYSIS TECHNIQUES FOR FLOOD RISK PREVENTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W4 (March 6, 2018): 549–54. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w4-549-2018.
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<p><strong>Abstract.</strong> Natural disasters such as flood are regarded to be caused by extreme weather conditions as well as changes in global and regional climate.<br> The prediction of flood incoming is a key factor to ensure civil protection in case of emergency and to provide effective early warning system. The risk of flood is affected by several factors such as land use, meteorological events, hydrology and the topology of the land.<br> Predict such a risk implies the use of data coming from different sources such satellite images, water basin levels, meteorological and GIS data, that nowadays are easily produced by the availability new satellite portals as SENTINEL and distributed sensor networks on the field.<br> In order to have a comprehensive and accurate prediction of flood risk is essential to perform a selective and multivariate analyses among the different types of inputs.<br> Multivariate Analysis refers to all statistical techniques that simultaneously analyse multiple variables.<br> Among multivariate analyses, Machine learning to provide increasing levels of accuracy precision and efficiency by discovering patterns in large and heterogeneous input datasets.<br> Basically, machine learning algorithms automatically acquire experience information from data.<br> This is done by the process of learning, by which the algorithm can generalize beyond the examples given by training data in input. Machine learning is interesting for predictions because it adapts the resolution strategies to the features of the data. This peculiarity can be used to predict extreme from high variable data, as in the case of floods.<br> This work propose strategies and case studies on the application on machine learning algorithms on floods events prediction.<br> Particullarly the study will focus on the application of Support Vector Machines and Artificial Neural Networks on a multivariate set of data related to river Seveso, in order to propose a more general framework from the case study.</p>
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Driessen, T. L. A., and M. van Ledden. "The large-scale impact of climate change to Mississippi flood hazard in New Orleans." Drinking Water Engineering and Science 6, no. 2 (2013): 81–87. http://dx.doi.org/10.5194/dwes-6-81-2013.
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Abstract. The objective of this paper was to describe the impact of climate change on the Mississippi River flood hazard in the New Orleans area. This city has a unique flood risk management challenge, heavily influenced by climate change, since it faces flood hazards from multiple geographical locations (e.g. Lake Pontchartrain and Mississippi River) and multiple sources (hurricane, river, rainfall). Also the low elevation and significant subsidence rate of the Greater New Orleans area poses a high risk and challenges the water management of this urban area. Its vulnerability to flooding became dramatically apparent during Hurricane Katrina in 2005 with huge economic losses and a large number of casualties. A SOBEK Rural 1DFLOW model was set up to simulate the general hydrodynamics. This model included the two important spillways that are operated during high flow conditions. A weighted multi-criteria calibration procedure was performed to calibrate the model for high flows. Validation for floods in 2011 indicated a reasonable performance for high flows and clearly demonstrated the influence of the spillways. 32 different scenarios were defined which included the relatively large sea level rise and the changing discharge regime that is expected due to climate change. The impact of these scenarios on the water levels near New Orleans were analysed by the hydrodynamic model. Results showed that during high flows New Orleans will not be affected by varying discharge regimes, since the presence of the spillways ensures a constant discharge through the city. In contrary, sea level rise is expected to push water levels upwards. The effect of sea level rise will be noticeable even more than 470 km upstream. Climate change impacts necessitate a more frequent use of the spillways and opening strategies that are based on stages.
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Lian, J. J., K. Xu, and C. Ma. "Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China." Hydrology and Earth System Sciences 17, no. 2 (2013): 679–89. http://dx.doi.org/10.5194/hess-17-679-2013.
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Abstract. Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms. The combined effect of multiple sources and the joint probability of extremes should be considered to assess and manage flood risk better. This paper aims to study the combined effect of rainfall and the tidal level of the receiving water body on flood probability and severity in Fuzhou City, which has a complex river network. Flood severity under a range of precipitation intensities, with return periods (RPs) of 5 yr to 100 yr, and tidal levels was assessed through a hydrodynamic model verified by data observed during Typhoon Longwang in 2005. According to the percentages of the river network where flooding occurred, the threshold conditions for flood severity were estimated in two scenarios: with and without working pumps. In Fuzhou City, working pumps efficiently reduce flood risk from precipitation within a 20-yr RP. However, the pumps may not work efficiently when rainfall exceeds a 100-yr RP because of the limited conveyance capacity of the river network. Joint risk probability was estimated through the optimal copula. The joint probability of rainfall and tidal level both exceeding their threshold values is very low, and the greatest threat in Fuzhou comes from heavy rainfall. However, the tidal level poses an extra risk of flood. Given that this extra risk is ignored in the design of flood defense in Fuzhou, flood frequency and severity may be higher than understood during design.
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Liévanos, Raoul S. "Racialised uneven development and multiple exposure: sea-level rise and high-risk neighbourhoods in Stockton, CA." Cambridge Journal of Regions, Economy and Society 13, no. 2 (2020): 381–404. http://dx.doi.org/10.1093/cjres/rsaa009.
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Abstract This article advances a conceptual framework that illuminates how racialised uneven development inscribes overlapping and interacting risks from climate, environmental and economic riskscapes into ‘high-risk neighbourhoods’. Drawing on archival sources, geographic information systems and qualitative comparative analysis, it examines the production of high-risk neighbourhoods in Stockton, CA. With significant scholarly and practical implications, the findings reveal how different historical configurations of devalued racialised people and places, adverse housing market incorporation and displacement, and unequal flood protections are associated with elevated risk of exposure to climate-related sea-level rise in Stockton’s high-risk neighbourhoods.
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Wolfe, Brent B., Roland I. Hall, Johan A. Wiklund, and Mitchell L. Kay. "Past variation in Lower Peace River ice-jam flood frequency." Environmental Reviews 28, no. 3 (2020): 209–17. http://dx.doi.org/10.1139/er-2019-0047.
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Opposing interpretations of Lower Peace River ice-jam flood frequency data sets are at the centre of identifying causes of reduced freshwater availability in the Peace-Athabasca Delta (northern Alberta), a Ramsar Wetland of International Importance and a major contributor to Wood Buffalo National Park’s listing as a UNESCO World Heritage Site. Recently, conclusions drawn from statistical inference of traditional knowledge and historical observation sources suggested that flood frequency was accelerating during 1880–1967 and then declined coincident with hydroelectric regulation of Peace River flow since 1968 that altered the river’s hydrograph. In contrast, prior paleolimnological measurements of laminated sediments from oxbow lakes proximal to the Peace River have, along with alternate presentation of the traditional knowledge and historical observation sources, identified flood frequency was in decline for decades preceding river regulation due to climate change since the Little Ice Age. Here we revisit these data sets and, specifically, review their inherent uncertainties to assess their value and limitations. The notion of increasing versus decreasing flood frequency in the decades preceding river regulation (1880–1967) is tested using previously published paleohydrological records from perched lakes in the delta. Those records from lakes most proximal and sensitive to changes in the flow regime of the Peace River show increasing influence of lake evaporation during 1880–1967, consistent with long-term decline in flood frequency. Reconciling uncertainties of multiple lines-of-evidence and their findings should inform decisions by UNESCO on the World Heritage status of Wood Buffalo National Park and execution of the park’s federally funded Action Plan. New paleolimnological studies that have recently been launched will continue to probe the hydrological history of the Peace-Athabasca Delta to serve as a foundation for effective stewardship.
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Joshi, S., K. Abdul Hakeem, P. V. Raju, et al. "Retrospective Analysis of Recent Flood Events With Persistent High Surface Runoff From Hydrological Modelling." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 359–65. http://dx.doi.org/10.5194/isprsarchives-xl-8-359-2014.
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Floods are one of the most common and widespread disasters in India, with an estimated 40Mha of land prone to this natural disaster (National Flood Commission, India). Significant loss of property, infrastructure, livestock, public utilities resulting in large economic losses due to floods are recurrent every year in many parts of India. Flood forecasting and early warning is widely recognized and adopted as non-structural measure to lower the damages caused by the flood events. Estimating the rainfall excess that results into excessive river flow is preliminary effort in riverine flood estimation. Flood forecasting models are in general, are event based and do not fully account for successive and persistent excessive surface runoff conditions. Successive high rainfall events result in saturated soil moisture conditions, favourable for high surface runoff conditions. <br><br> The present study is to explore the usefulness of hydrological model derived surface runoff, running on continuous times-step, to relate to the occurrence of flood inundation due to persistent and successive high surface runoff conditions. Variable Infiltration Capacity (VIC), a macro-scale hydrological model, was used to simulate daily runoff at systematic grid level incorporating daily meteorological data and land cover data. VIC is a physically based, semi-distributed macroscale hydrological model that represents surface and subsurface hydrologic process on spatially distributed grid cell. It explicitly represents sub-grid heterogeneity in land cover classes, taking their phenological changes into account. In this study, the model was setup for entire India using geo-spatial data available from multiple sources (NRSC, NBSS&LUP, NOAA, and IMD) and was calibrated with river discharge data from CWC at selected river basins. Using the grid-wise surface runoff estimates from the model, an algorithm was developed through a set of thresholds of successive high runoff values in order to identify grids/locations with probable flooding conditions. These thresholds were refined through iterative process by comparing with satellite data derived flood maps of 2013 and 2014 monsoon season over India. <br><br> India encountered many cyclonic flood events during Oct&ndash;Dec 2013, among which Phailin, Lehar, and Madi were rated to be very severe cyclonic storm. The path and intensity of these cyclonic events was very well captured by the model and areas were marked with persistent coverage of high runoff risk/flooded area. These thresholds were used to monitor floods in Jammu Kashmir during 4&ndash;5 Sep and Odisha during 8&ndash;9 Aug, 2014. The analysis indicated the need to vary the thresholds across space considering the terrain and geographical conditions. With respect to this a sub-basin wise study was made based on terrain characteristics (slope, elevation) using Aster DEM. It was found that basins with higher elevation represent higher thresholds as compared to basins with lesser elevation. The results show very promising correlation with the satellite derived flood maps. <br><br> Further refinement and optimization of thresholds, varying them spatially accounting for topographic/terrain conditions, would lead to estimation of high runoff/flood risk areas for both riverine and drainage congested areas. Use of weather forecast data (NCMWRF, (GEFS/R)), etc. would enhance the scope to develop early warning systems.
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Sharma, Vimal Chandra, and Satish Kumar Regonda. "Two-Dimensional Flood Inundation Modeling in the Godavari River Basin, India—Insights on Model Output Uncertainty." Water 13, no. 2 (2021): 191. http://dx.doi.org/10.3390/w13020191.
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Most flood inundation models do not come with an uncertainty analysis component chiefly because of the complexity associated with model calibration. Additionally, the fact that the models are both data- and compute-intensive, and since uncertainty results from multiple sources, adds another layer of complexity for model use. In the present study, flood inundation modeling was performed in the Godavari River Basin using the Hydrologic Engineering Center—River Analysis System 2D (HEC-RAS 2D) model. The model simulations were generated for six different scenarios that resulted from combinations of different geometric, hydraulic and hydrologic conditions. Thus, the resulted simulations account for multiple sources of uncertainty. The SRTM-30 m and MERIT-90 m Digital elevation Model (DEM), two sets of Manning’s roughness coefficient (Manning’s n) and observed and estimated boundary conditions, were used to reflect geometric, hydraulic and hydrologic uncertainties, respectively. The HEC-RAS 2D model ran in an unsteady state mode for the abovementioned six scenarios for the selected three flood events that were observed in three different years, i.e., 1986, 2005 and 2015. The water surface elevation (H) was compared in all scenarios as well as with the observed values at selected locations. In addition, ‘H’ values were analyzed for two different structures of the computational model. The average correlation coefficient (r) between the observed and simulated H values is greater than 0.85, and the highest r, i.e., 0.95, was observed for the combination of MERIT-90 m DEM and optimized (obtained via trial and error) Manning’s n. The analysis shows uncertainty in the river geometry information, and the results highlight the varying role of geometric, hydraulic and hydrologic conditions in the water surface elevation estimates. In addition to the role of the abovementioned, the study recommends a systematic model calibration and river junction modeling to understand the hydrodynamics upstream and downstream of the junction.
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Liang, Jiayong, and Desheng Liu. "Estimating Daily Inundation Probability Using Remote Sensing, Riverine Flood, and Storm Surge Models: A Case of Hurricane Harvey." Remote Sensing 12, no. 9 (2020): 1495. http://dx.doi.org/10.3390/rs12091495.
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Heavy precipitation and storm surges often co-occur and compound together to form sudden and severe flooding events. However, we lack comprehensive observational tools with high temporal and spatial resolution to capture these fast-evolving hazards. Remotely sensed images provide extensive spatial coverage, but they may be limited by adverse weather conditions or platform revisiting schedule. River gauges could provide frequent water height measurement but they are sparsely distributed. Riverine flood and storm surge models, depending on input data quality and calibration process, have various uncertainties. These lead to inevitable temporal and spatial gaps in monitoring inundation dynamics. To fill in the observation gaps, this paper proposes a probabilistic method to estimate daily inundation probability by combining the information from multiple sources, including satellite remote sensing, riverine flood depth, storm surge height, and land cover. Each data source is regarded as a spatial evidence layer, and the weight of evidence is calculated by assessing the association between the evidence presence and inundation occurrence. Within a Bayesian model, the fusion results are daily inundation probability whenever at least one data source is available. The proposed method is applied to estimate daily inundation in Harris, Texas, impacted by Hurricane Harvey. The results agree with the reference water extent, high water mark, and extracted tweet locations. This method could help to further understand flooding as an evolving time-space process and support response and mitigation decisions.
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Raška, Pavel, Martin Dolejš, Jan Pacina, Jan Popelka, Jan Píša, and Kristýna Rybová. "Review of current approaches to spatially explicit urban vulnerability assessments: hazard complexity, data sources, and cartographic representations." GeoScape 14, no. 1 (2020): 47–61. http://dx.doi.org/10.2478/geosc-2020-0005.
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AbstractSocio-ecological hazards are processes that − depending on the vulnerability of societal systems − may have profound adverse impacts. For this reason, the current discourse in disaster risk reduction (DRR) has been experiencing a shift toward a vulnerability-led paradigm, raising new questions about how to address (i) the complexity of vulnerabilities to multiple hazards, (ii) their cultural, dynamic, and subjective character, and (iii) the effectiveness and legitimacy of vulnerability assessments as decision-support tools. In this paper, we present a review of 707 vulnerability studies (derived from the Clarivate WoS database; 1988−2018) with a particular focus on urban settings and spatially explicit assessments in order to evaluate current efforts to meet the aforementioned issues. The reviewed studies assessed vulnerabilities to 35 hazard types that were predominantly (n=603, 85%) analysed as single hazards (mostly seismic, flood, and groundwater contamination hazards, as well as climate change), whereas only 15% (n=104) of studies focused on multiple hazards (mostly atmospheric hazards). Within the spatially explicit vulnerability studies, almost 60% used data collected by the study itself (mostly seismic hazards), while statistical and combined data were both employed in 20% of cases (mostly floods, climate change, and social and political hazards). Statistical data were found to have only limited transferability, often being generalised to be applicable in small-scale studies, while reducing the role of cultural and contextual factors. Field research data provided high-resolution information, but their acquisition is time-consuming, and therefore fixed at a local scale and single temporal stage. Underlying hazard types and suitable data sources resulting in other differences found a preference towards the specific coverage and resolution of vulnerability maps that appeared in 44% of all reviewed studies. Altogether, the differences we found indicated a division of spatially explicit vulnerability research in two major directions: (i) geological and geomorphological studies focusing on physical vulnerability, using their own data surveys at a detailed scale and lacking links to other hazards, and (ii) other studies (mostly atmospheric hazards and socialpolitical hazards) focusing on social or combined vulnerabilities, using primarily statistical or combined data at a municipal, regional, and country scale with occasional efforts to integrate multiple hazards. Finally, although cartographic representations have become a frequent component of vulnerability studies, our review found only vague rationalisations for the presentation of maps, and a lack of guidelines for the interpretation of uncertainties and the use of maps as decision-support tools.
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Cartwright, I., B. Gilfedder, and H. Hofmann. "Contrasts between chemical and physical estimates of baseflow help discern multiple sources of water contributing to rivers." Hydrology and Earth System Sciences Discussions 10, no. 5 (2013): 5943–74. http://dx.doi.org/10.5194/hessd-10-5943-2013.
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Abstract. This study compares geochemical and physical methods of estimating baseflow in the upper reaches of the Barwon River, southeast Australia. Estimates of baseflow from physical techniques such as local minima and recursive digital filters are higher than those based on chemical mass balance using continuous electrical conductivity (EC). Between 2001 and 2011 the baseflow flux calculated using chemical mass balance is between 1.8 × 103 and 1.5 × 104 ML yr−1 (15 to 25% of the total discharge in any one year) whereas recursive digital filters yield baseflow fluxes of 3.6 × 103 to 3.8 × 104 ML yr−1 (19 to 52% of discharge) and the local minimum method yields baseflow fluxes of 3.2 × 103 to 2.5 × 104 ML yr−1 (13 to 44% of discharge). These differences most probably reflect how the different techniques characterise baseflow. Physical methods probably aggregate much of the water from delayed sources as baseflow. However, as many delayed transient water stores (such as bank return flow or floodplain storage) are likely to be geochemically similar to surface runoff, chemical mass balance calculations aggregate them with the surface runoff component. The mismatch between geochemical and physical estimates is greatest following periods of high discharge in winter, implying that these transient stores of water feed the river for several weeks to months. Consistent with these interpretations, modelling of bank storage indicates that bank return flows provide water to the river for several weeks after flood events. EC vs. discharge variations during individual flow events also imply that an inflow of low EC water stored within the banks or on the floodplain occurs as discharge falls. The joint use of physical and geochemical techniques allows a better understanding of the different components of water that contribute to river flow, which is important for the management and protection of water resources.
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Almeida, Maria do Céu, Maria João Telhado, Marco Morais, João Barreiro, and Ruth Lopes. "Urban Resilience to Flooding: Triangulation of Methods for Hazard Identification in Urban Areas." Sustainability 12, no. 6 (2020): 2227. http://dx.doi.org/10.3390/su12062227.
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The effects of climate dynamics on urban areas involve the aggravation of existing conditions and the potential for emergence of new hazards or risk factors. Floods are recognized as a leading source of consequences to society, including disruption of critical functions in urban areas, and to the environment. Consideration of the interplay between services providers ensuring urban functions is essential to deal with climate dynamics and associated risks. Assessment of resilience to multiple hazards requires integrated and multi-sectoral approaches embracing each strategic urban sector and interactions between them. A common limitation resides in the limited data and tools available for undertaking these complex assessments. The paper proposes a methodology to undertake the spatial characterization of the flood related hazards and exposure of both essential functions and services providers in urban areas, in the context of limitations in data and in ready-to-use tools. Results support the resilience assessment of these hazards, taking into account interdependencies and cascading effects. The approach is applied to Lisbon city as the study case. Results are promising in demonstrating the potential of combining data and knowledge from different sources with dual modelling approaches, allowing us to obtain trends on the magnitude of effects of climate scenarios and to assess potential benefits of adaptation strategies. Quantification of the effects is reached, but results need to be assessed together with the underlying levels of uncertainty. The methodology can facilitate dialogue among stakeholders and between different decision levels.
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Camus, Paula, Ivan D. Haigh, Ahmed A. Nasr, Thomas Wahl, Stephen E. Darby, and Robert J. Nicholls. "Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns." Natural Hazards and Earth System Sciences 21, no. 7 (2021): 2021–40. http://dx.doi.org/10.5194/nhess-21-2021-2021.
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Abstract. In coastal regions, floods can arise through a combination of multiple drivers, including direct surface run-off, river discharge, storm surge, and waves. In this study, we analyse compound flood potential in Europe and environs caused by these four main flooding sources using state-of-the-art databases with coherent forcing (i.e. ERA5). First, we analyse the sensitivity of the compound flooding potential to several factors: (1) sampling method, (2) time window to select the concurrent event of the conditioned driver, (3) dependence metrics, and (4) wave-driven sea level definition. We observe higher correlation coefficients using annual maxima than peaks over threshold. Regarding the other factors, our results show similar spatial distributions of the compound flooding potential. Second, the dependence between the pairs of drivers using the Kendall rank correlation coefficient and the joint occurrence are synthesized for coherent patterns of compound flooding potential using a clustering technique. This quantitative multi-driver assessment not only distinguishes where overall compound flooding potential is the highest, but also discriminates which driver combinations are more likely to contribute to compound flooding. We identify that hotspots of compound flooding potential are located along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea.
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Fourour, Said, and Yahia Lebbah. "Equitable Optimization for Multicast Communication." International Journal of Decision Support System Technology 12, no. 3 (2020): 1–25. http://dx.doi.org/10.4018/ijdsst.2020070101.
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Multicast communication is characterized by the multiplicity of streams defining different groups, where each stream has multiple sources. A multicast communication tends to flood the network with a large number of flows that can overload some nodes and unload others. This imbalance in the load distribution weakens network performance and could produce bottlenecks around overloaded nodes. We propose in this article an approach based on a combination of a flow approach and a multi-agent optimization to resolve the load balancing issue of multicast communication. We use ordered weighted average (OWA), a multi-criteria optimization method, to balance the degree of the nodes, ensuring a balanced load distribution across the network. The experiments conducted on a series of networks show that our approach provides a better equitable load assignment.
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Duan, Guosheng, Anping Shu, Matteo Rubinato, Shu Wang, and Fuyang Zhu. "Collapsing Mechanisms of the Typical Cohesive Riverbank along the Ningxia–Inner Mongolia Catchment." Water 10, no. 9 (2018): 1272. http://dx.doi.org/10.3390/w10091272.
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As one of the major sediment sources in rivers, bank collapse often occurs in the Ningxia–Inner Mongolia catchment and, to date, it caused substantial social, economic and environmental problems in both local areas and downstream locations. To provide a better understanding of this phenomenon, this study consisted of modifying the existing Bank Stability and Toe Erosion Model (BSTEM), commonly used to investigate similar phenomena, introducing new assumptions and demonstrating its applicability by comparing numerical results obtained against field data recorded at six gauging stations (Qingtongxia, Shizuishan, Bayan Gol, Sanhuhekou, Zhaojunfen, and Toudaoguai). Furthermore, the impact of multiple factors typical of flood and dry seasons on the collapse rate was investigated, and insights obtained should be taken into consideration when completing future projects of river adaptation and river restoration.
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Pusey, Bradley J., Timothy D. Jardine, Leah S. Beesley, et al. "Corrigendum to: Carbon sources supporting Australia's most widely distributed freshwater fish, Nematalosa erebi (Günther) (Clupeidae: Dorosomatinae)." Marine and Freshwater Research 72, no. 2 (2021): 299. http://dx.doi.org/10.1071/mf20014_co.
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Both brown (detrital-based) and green (algal-based) food pathways support freshwater food webs, although the importance of either source may vary within species, regions and different phases of the flow regime. The bony bream (Nematalosa erebi Clupeidae: Dorosomatinae) is one of Australia's most widely distributed freshwater fish species and is a key component of freshwater food webs, especially in northern Australia. We sought to better define the feeding habits of this species, previously classified as a detritivore, algivore or zooplanktivore (or combinations thereof), by undertaking meta-analyses of published accounts based on stomach content analysis and 13C and 15N stable isotope analysis. Stomach content analysis clearly indicated that detritus was the dominant food item, although benthic algae could be an important dietary component in some habitats (inland river flood plains) and during the wet season. Zooplankton were important for small fish (i.e. juveniles 13C enriched, indicating the latter source was not the dominant contributor to the biomass of this species. However, using site-specific data and a regression approach, a significant relationship was revealed between algal carbon and that of large fish, suggesting that carbon derived from benthic algae contributed ~20% of the carbon of adult bony bream. Zooplankton contributed a similar amount. Zooplankton provided the majority of carbon for small fish. We contend that detritus derived from terrestrial vegetation is the likely remaining carbon source for large bony bream, and this interpretation was supported by the outcomes of multiple regression analyses. Although previous studies of aquatic food webs in northern Australia have emphasised the importance of high-quality algal basal resources, this study indicates that terrestrial sources may be important for some species and demonstrates the need to better consider the circumstances that cause biota to switch between different food sources.
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Wolkin, Amy F., Amy H. Schnall, Nicole K. Nakata, and Esther M. Ellis. "Getting the Message Out: Social Media and Word-of-Mouth as Effective Communication Methods during Emergencies." Prehospital and Disaster Medicine 34, no. 1 (2018): 89–94. http://dx.doi.org/10.1017/s1049023x1800119x.
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AbstractEffective communication is a critical part of managing an emergency. During an emergency, the ways in which health agencies normally communicate warnings may not reach all of the intended audience. Not all communities are the same, and households within communities are diverse. Because different communities prefer different communication methods, community leaders and emergency planners need to know their communities’ preferred methods for seeking information about an emergency. This descriptive report explores findings from previous community assessments that have collected information on communication preferences, including television (TV), social media, and word-of-mouth (WoM) delivery methods. Data were analyzed from 12 Community Assessments for Public Health Emergency Response (CASPERs) conducted from 2014-2017 that included questions regarding primary and trusted communication sources. A CASPER is a rapid needs assessment designed to gather household-based information from a community. In 75.0% of the CASPERs, households reported TV as their primary source of information for specific emergency events (range = 24.0%-83.1%). Households reporting social media as their primary source of information differed widely across CASPERs (3.2%-41.8%). In five of the CASPERs, nearly one-half of households reported WoM as their primary source of information. These CASPERs were conducted in response to a specific emergency (ie, chemical spill, harmful algal bloom, hurricane, and flood). The CASPERs conducted as part of a preparedness activity had lower percentages of households reporting WoM as their primary source of information (8.3%-10.4%). The findings in this report demonstrate the need for emergency plans to include hybrid communication models, combining traditional methods with newer technologies to reach the broadest audience. Although TV was the most commonly reported preferred source of information, segments of the population relied on social media and WoM messaging. By using multiple methods for risk communication, emergency planners are more likely to reach the whole community and engage vulnerable populations that might not have access to, trust in, or understanding of traditional news sources. Multiple communication channels that include user-generated content, such as social media and WoM, can increase the timeliness of messaging and provide community members with message confirmation from sources they trust encouraging them to take protective public health actions.WolkinAF, SchnallAH, NakataNK, EllisEM. Getting the message out: social media and word-of-mouth as effective communication methods during emergencies. Prehosp Disaster Med. 2019;34(1):89–94.
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Krajewski, Witold F., Anton Kruger, Satpreet Singh, Bong-Chul Seo, and James A. Smith. "Hydro-NEXRAD-2: real-time access to customized radar-rainfall for hydrologic applications." Journal of Hydroinformatics 15, no. 2 (2012): 580–90. http://dx.doi.org/10.2166/hydro.2012.227.
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Hydro-NEXRAD-2 (HNX2) is a prototype system that allows hydrologic users real-time access to NEXRAD radar data in support of a wide range of research. The system processes basic radar data (Level II) and delivers radar-rainfall products based on the user's custom selection of features such as spatial domain, rainfall product space and time resolution, and rainfall estimation algorithms. HNX2 collects real-time, unprocessed data from multiple NEXRAD radars as they become available, processes them through a user-configurable pipeline of data-processing modules, and publishes the processed data-products at regular intervals. Modules in the data-processing pipeline encapsulate algorithms such as non-meteorological echo detection, radar range correction, radar-reflectivity-rain rate (Z-R) conversion, echo advection correction, mosaicking of products from multiple radars, and grid projections and transformations. This paper describes the challenges involved in HNX2's development and implementation, which include real-time error-handling, time-synchronization of data from multiple asynchronous sources, generation of multiple-radar metadata products, and distribution of products to a user base with diverse needs and constraints. HNX2 publishes products through automation and allows multiple users access to published products. Currently, HNX2 is serving near real-time rain-rate maps for Iowa in the USA using data from seven radars covering the state. Hydrologic models operated by The University of Iowa's Iowa Flood Center use these products.
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Olasz, A., D. Kristóf, M. Belényesi, et al. "IQPC 2015 TRACK: WATER DETECTION AND CLASSIFICATION ON MULTISOURCE REMOTE SENSING AND TERRAIN DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (August 20, 2015): 583–88. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-583-2015.
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Since 2013, the EU FP7 research project “IQmulus” encourages the participation of the whole scientific community as well as specific user groups in the IQmulus Processing Contest (IQPC). This year, IQPC 2015 consists of three processing tasks (tracks), from which “Water detection and classification on multi-source remote sensing and terrain data” is introduced in the present paper. This processing track addresses a particular problem in the field of big data processing and management with the objective of simulating a realistic remote sensing application scenario. The main focus is on the detection of water surfaces (natural waters, flood, inland excess water, other water-affected categories) using remotely sensed data. Multiple independent data sources are available and different tools could be used for data processing and evaluation. The main challenge is to identify the right combination of data and methods to solve the problem in the most efficient way. Although the first deadline for submitting track solutions has passed and the track has been successfully concluded, the track organizers decided to keep the possibility of result submission open to enable collecting a variety of approaches and solutions for this interesting problem.
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Almeida, Maria do Céu, Maria João Telhado, Marco Morais, and João Barreiro. "Multisector Risk Identification to Assess Resilience to Flooding." Climate 9, no. 5 (2021): 73. http://dx.doi.org/10.3390/cli9050073.
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Climate trends suggest an increase in the frequency of intense rainfall events and the aggravation of existing conditions in terms of flooding in urban areas. In coastal areas, conditions are aggravated by coexistence with coastal overtopping. Flood risk control is complex, and the interdependencies among the services and sectors in urban areas imply the need for adoption of approaches that embrace the interplay between service providers to ensure critical urban functions. Flooding incorporates several hazards. Assessment of resilience to multiple hazards in complex environments benefits from integrated and multi-sectoral approaches. A common constraint resides in the limited data and tools available for undertaking these complex assessments. This paper proposes a risk-based methodology to assess urban areas’ resilience to flooding by addressing sectors’ interdependencies in a context of limited data and ready-to-use tools. Multisector flood risk identification is pursued with the support of a geographic information system and is applied to Lisbon with a focus on the cascading effects of drainage system failures on buildings, populations, mobility, waste management, and electricity supply. The results demonstrate the potential for combining data and knowledge from different sources with dual modelling approaches, thus allowing one to obtain trends of exposure and vulnerability to flooding for current and climate change scenarios. This methodology facilitates dialogue among stakeholders and decision levels by contributing to capacity building, and it contributes to sustainable development.
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Sulistyah, U. D., and J. H. Hong. "THE USE OF 3D BUILDING DATA FOR DISASTER MANAGEMENT: A 3D SDI PERSPECTIVE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W8 (August 22, 2019): 395–402. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w8-395-2019.
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<p><strong>Abstract.</strong> In recent years, the demands of 3D cyber-city have been steadily growing. With strong links to the citizens’ lives, building information is considered as the most important component in the 3D urban model. To further facilitate the best usage of 3D data, the development of 3D SDI requires creative thinking to meet different application needs. While many current applications are restricted to visualization only, we argue the 3D building data in 3D SDI must at least consider the issues of feature modelling, identification, semantics, level of details, cross-domain linking and services. This paper intends to assess the use of the semantic-enriched 3D building data in the applications of disaster management. Based on CityGML, we first create 3D building data based on a hierarchy of building-storey-household representation. Identifier systems are respectively developed for each level of features for the purpose of identifying individual features and linking to other sources of data, e.g., the household registration information. By reviewing and comparing the outcomes of the past research of 3D flood simulation, we demonstrate the improved 3D building data additionally enables the direct impact analysis at the chosen level of features, as well as visually present enriched analyzed outcomes for decision making, e.g., the number of trapped people in specific floor. As the merits of the SDI is to share reliable information, encourage multiple-purpose applications and avoid duplicated spending, we thereby conclude the necessity to further examine the level of details and multiple representation of the serviced 3D building data for cost-effective and cross-domain application development.</p>
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Balasundareshwaran, A., K. Kumaraswamy, and K. Balasubramani. "Multi-Hazard Zonation For Effective Management of Disasters in Tamil Nadu." Geosfera Indonesia 5, no. 1 (2020): 65. http://dx.doi.org/10.19184/geosi.v5i1.16710.
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Natural hazards are a long existing threat to human and their surroundings which may occur throughout the world. Tamil Nadu is one of the Indian States with a number of natural hazard incidences. The occurrence of natural hazards, such as cyclone, storm surge, flood, drought, landslide, forest fire etc., has increased manifold in the recent decades.The multi-hazard zonation is one of the preliminary studies in disaster management scenario, which is used to understand the product of all prominent natural hazards. At the state level, it is imperative for the government to know the regions affected by multiple hazardsto help them prepare the management plans appropriately to protect the local communities and infrastructures. However, such systematic hazard assessment and integration in an administrative unit is largely missing in Tamil Nadu. Further, the utilisation of geoinformatics in the preparation of multi-hazard zonation helps to identify the most endangered areas of the State precisely and offers insights to detailed studies in highly risk zones. This paper attempts on these lines toprepare Multi Hazard Zones (MHZ) based on natural hazards viz. earthquake, landslide, cyclone, storm surge, flood, drought and forest fire of Tamil Nadu. The data for the study were generated from multiple sources, which were all generalised and integrated in a normalised scale. The occurrences, intensities and frequencies of hazards, namely seismic, landslide, and forest fire are the reasons for a very high multi-hazard in hilly tracts of the Nilgiris and parts of Shayadhri hills in Coimbatore and Theni Districts, whereas cyclone, storm surge, and flood caused a very high risk along the coastal stretch of Chennai, Kancheepuram, Cuddalore and Ramanathapuram Districts. The segregation of the results into administrative division’s which was then categorised in an order of high risk zones may providea powerful tool to the State authorities to allocate fund and resources. The output of this study also offers zonation for immediate knowledge, policy briefs, and proper disaster management plan at State level.
 Keywords : Disaster Management Natural Hazards; Geoinformatics; Tamil Nadu
 
 
 Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
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Hunter, N. M., P. D. Bates, M. S. Horritt, A. P. J. De Roo, and M. G. F. Werner. "Utility of different data types for calibrating flood inundation models within a GLUE framework." Hydrology and Earth System Sciences 9, no. 4 (2005): 412–30. http://dx.doi.org/10.5194/hess-9-412-2005.
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Abstract. To translate a point hydrograph forecast into products for use by environmental agencies and civil protection authorities, a hydraulic model is necessary. Typical one- and two-dimensional hydraulic models are able to predict dynamically varying inundation extent, water depth and velocity for river and floodplain reaches up to 100 km in length. However, because of uncertainties over appropriate surface friction parameters, calibration of hydraulic models against observed data is a necessity. The value of different types of data is explored in constraining the predictions of a simple two-dimensional hydraulic model, LISFLOOD-FP. For the January 1995 flooding on the River Meuse, The Netherlands, a flow observation data set has been assembled for the 35-km reach between Borgharen and Maaseik, consisting of Synthetic Aperture Radar and air photo images of inundation extent, downstream stage and discharge hydrographs, two stage hydrographs internal to the model domain and 84 point observations of maximum free surface elevation. The data set thus contains examples of all the types of data that potentially can be used to calibrate flood inundation models. 500 realisations of the model have been conducted with different friction parameterisations and the performance of each realisation has been evaluated against each observed data set. Implementation of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology is then used to determine the value of each data set in constraining the model predictions as well as the reduction in parameter uncertainty resulting from the updating of generalised likelihoods based on multiple data sources.