Assessing invertebrate response to an extreme flood event at a regional scale utilizing past survey data

Abstract. Floods often affect not only a single location, but also a whole region. Flood frequency analysis should therefore be undertaken at a regional scale which requires the considerations of the dependence of events at different locations. This dependence is often neglected even though its consideration is essential to derive reliable flood estimates. A model used in regional multivariate frequency analysis should ideally consider the dependence of events at multiple sites which might show dependence in the lower and/or upper tail of the distribution. We here seek to propose a simple model that on the one hand considers this dependence with respect to the network structure of the region and on the other hand allows for the simulation of stochastic event sets at both gauged and ungauged locations. The new Fisher copula model is used for representing the spatial dependence of flood events in the nested Thur catchment in Switzerland. Flood event samples generated for the gauged stations using the Fisher copula are compared to samples generated by other dependence models allowing for modeling of multivariate data including elliptical copulas, R-vine copulas, and max-stable models. The comparison of the dependence structures of the generated samples shows that the Fisher copula is a suitable model for capturing the spatial dependence in the data. We therefore use the copula in a way such that it can be used in an interpolation context to simulate event sets comprising gauged and ungauged locations. The spatial event sets generated using the Fisher copula well capture the general dependence structure in the data and the upper tail dependence, which is of particular interest when looking at extreme flood events and when extrapolating to higher return periods. The Fisher copula was for a medium-sized catchment found to be a suitable model for the stochastic simulation of flood event sets at multiple gauged and ungauged locations.

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Modeling the spatial dependence of floods using the Fisher copula

10.5194/hess-2018-159 ◽

2018 ◽

Author(s):

Manuela I. Brunner ◽

Reinhard Furrer ◽

Anne-Catherine Favre

Keyword(s):

Frequency Analysis ◽

Spatial Dependence ◽

Regional Scale ◽

Flood Frequency ◽

Flood Frequency Analysis ◽

Flood Event ◽

Dependence Structure ◽

Suitable Model ◽

Flood Events ◽

Extreme Flood

Abstract. Floods do often not only affect a single location but a whole region. Flood frequency analysis should therefore be undertaken at a regional scale which requires the considerations of the dependence of events at different locations. This dependence is often neglected even though its consideration is essential to derive reliable flood estimates. A model used in regional multivariate frequency analysis should ideally consider the dependence of events at multiple sites which might show dependence in the lower and/or upper tail of the distribution. We here seek at proposing a simple model that on the one hand considers this dependence with respect to the network structure of the region and on the other hand, allows for the simulation of stochastic event sets at both gauged and ungauged locations. The new Fisher copula model is used for representing the spatial dependence of flood events in the nested Thur catchment in Switzerland. Flood event samples generated for the gauged stations using the Fisher copula are compared to samples generated by other dependence models allowing for modeling multivariate data including elliptical copulas, R-vine copulas, and max-stable models. The comparison of the dependence structures of the generated samples shows that the Fisher copula is a suitable model for capturing the spatial dependence in the data. We therefore use the copula in a way such that it can be used in an interpolation context to simulate event sets comprising gauged and ungauged locations. The spatial event sets generated using the Fisher copula well capture the general dependence structure in the data and the upper tail dependence, which is of particular interest when looking at extreme flood events and when extrapolating to higher return periods. The Fisher copula is therefore a suitable model for the stochastic simulation of flood event sets at multiple gauged and ungauged locations.

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Determinants of Property Damage Recovery Time Among Households Affected by an Extreme Flood Event in Metro Manila, Philippines

SSRN Electronic Journal ◽

10.2139/ssrn.2381669 ◽

2013 ◽

Cited By ~ 1

Author(s):

Jamil Paolo S. Francisco

Keyword(s):

Recovery Time ◽

Flood Event ◽

Property Damage ◽

Extreme Flood ◽

Metro Manila

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Assessing the population dynamics of Escherichia coli in a metropolitan river after an extreme flood event

Journal of Water and Health ◽

10.2166/wh.2016.285 ◽

2016 ◽

Vol 15 (2) ◽

pp. 196-208 ◽

Cited By ~ 1

Author(s):

Nicole M. Masters ◽

Aaron Wiegand ◽

Jasmin M. Thompson ◽

Tara L. Vollmerhausen ◽

Eva Hatje ◽

...

Keyword(s):

Escherichia Coli ◽

Population Dynamics ◽

Antibiotic Resistance ◽

Virulence Genes ◽

Wastewater Treatment Plants ◽

Vero Cells ◽

Flood Event ◽

Typing Method ◽

E Coli ◽

Extreme Flood

We investigated Escherichia coli populations in a metropolitan river after an extreme flood event. Between nine and 15 of the 23 selected sites along the river were sampled fortnightly over three rounds. In all, 307 E. coli were typed using the PhP typing method and were grouped into common (C) or single (S) biochemical phenotypes (BPTs). A representative from each of the 31 identified C-BPTs was tested for 58 virulence genes (VGs) associated with intestinal and extra-intestinal E. coli, resistance to 22 antibiotics, production of biofilm and cytotoxicity to Vero cells. The number of E. coli in the first sampling round was significantly (P < 0.01) higher than subsequent rounds, whereas the number of VGs was significantly (P < 0.05) higher in isolates from the last sampling round when compared to previous rounds. Comparison of the C-BPTs with an existing database from wastewater treatment plants (WWTPs) in the same catchment showed that 40.6% of the river isolates were identical to the WWTP isolates. The relatively high number of VGs and antibiotic resistance among the C-BPTs suggests possessing and retaining these genes may provide niche advantages for those naturalised and/or persistent E. coli populations which may pose a health risk to the community.

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Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

10.5194/hess-2016-620 ◽

2017 ◽

Cited By ~ 1

Author(s):

Cherry May R. Mateo ◽

Dai Yamazaki ◽

Hyungjun Kim ◽

Adisorn Champathong ◽

Jai Vaze ◽

...

Keyword(s):

Spatial Resolution ◽

Large Scale ◽

Flood Hazard ◽

Regional Scale ◽

Global Scale ◽

Test Case ◽

Efficiency Coefficient ◽

Computational Power ◽

Extreme Flood ◽

Simulation Results

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

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Towards assimilation of crowdsourced observations for different levels of citizen engagement: the flood event of 2013 in the Bacchiglione catchment

10.5194/hess-2017-59 ◽

2017 ◽

Cited By ~ 1

Author(s):

Maurizio Mazzoleni ◽

Vivian Juliette Cortes Arevalo ◽

Uta Wehn ◽

Leonardo Alfonso ◽

Daniele Norbiato ◽

...

Keyword(s):

Real Time ◽

Hydrological Model ◽

Population Distribution ◽

Model Performance ◽

Flood Event ◽

Target Point ◽

Citizen Engagement ◽

Physical Sensors ◽

Extreme Flood ◽

Social Sensors

Abstract. Accurate flood predictions are essential to reduce the risk and damages over large urbanized areas. To improve prediction capabilities, hydrological measurements derived by traditional physical sensors are integrated in real-time within mathematic models. Recently, traditional sensors are complemented with low-cost social sensors. However, measurements derived by social sensors (i.e. crowdsourced observations) can be more spatially distributed but less accurate. In this study, we assess the usefulness for model performance of assimilating crowdsourced observations from a heterogeneous network of static physical, static social and dynamic social sensors. We assess potential effects on the model predictions to the extreme flood event occurred in the Bacchiglione catchment on May 2013. Flood predictions are estimated at the target point of Ponte degli Angeli (Vicenza), outlet of the Bacchiglione catchment, by means of a semi-distributed hydrological model. The contribution of the upstream sub-catchment is calculated using a conceptual hydrological model. The flow is propagated along the river reach using a hydraulic model. In both models, a Kalman filter is implemented to assimilate the real-time crowdsourced observations. We synthetically derived crowdsourced observations for either static social or dynamic social sensors because crowdsourced measures were not available. We consider three sets of experiments: (1) only physical sensors are available; (2) probability of receiving crowdsourced observations and (3) realistic scenario of citizen engagement based on population distribution. The results demonstrated the importance of integrating crowdsourced observations. Observations from upstream sub-catchments assimilated into the hydrological model ensures high model performance for high lead time values. Observations next to the outlet of the catchments provide good results for short lead times. Furthermore, citizen engagement level scenarios moved by a feeling of belonging to a community of friends indicated flood prediction improvements when such small communities are located upstream a particular target point. Effective communication and feedback is required between water authorities and citizens to ensure minimum engagement levels and to minimize the intrinsic low-variable accuracy of crowdsourced observations.

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Hydraulic modelling of extreme flood event of semi-arid river basin

10.5194/egusphere-egu21-10218 ◽

2021 ◽

Author(s):

Mohamedmaroof Shaikh ◽

Sanjaykumar Yadav ◽

Vivek Manekar

Keyword(s):

Cross Sections ◽

Management Strategy ◽

Retaining Wall ◽

Hydraulic Model ◽

Flood Event ◽

Railway Bridge ◽

Hydraulic Modelling ◽

One Dimensional ◽

Extreme Flood ◽

High Flood

Floods are among the severe weather disasters that cause catastrophic damage to surroundings and adversely impact populations. This study aims to create a one-dimensional (1D) hydraulic model using HEC-RAS for the Rel River in Banaskantha, Gujarat, India. The model has been developed for the extreme flood event of July 2017. A total of hundred cross-sections have been used as geometric data. The peak discharge of 3355 m3/s and the river slope has been applied as upstream and downstream boundary conditions. The model has been calibrated and validated using observed water depth at Railway bridge and Highway bridge. Critical cross-sections have been identified using the 1D hydraulic model. Eight out of the hundred cross-sections were safe for a flood discharge of 3355 m3/s. The villages at high flood risk are identified for this discharge. To mitigating floods, the construction of a retaining wall or levees is recommended to protect these villages. This study can help a disaster management strategy for the cities and town in the River&#8217;s vicinity.

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Successful Small-Scale Household Relocation after a Millennial Flood Event in Simbach, Germany 2016

Water ◽

10.3390/w12010156 ◽

2020 ◽

Vol 12 (1) ◽

pp. 156 ◽

Cited By ~ 1

Author(s):

Barbara Mayr ◽

Thomas Thaler ◽

Johannes Hübl

Keyword(s):

Risk Management ◽

Flood Risk ◽

Planning Process ◽

Flood Risk Management ◽

Flood Event ◽

Small Scale ◽

Successful Implementation ◽

Adaptive Planning ◽

Extreme Flood ◽

Household Relocation

International and national laws promote stakeholder collaboration and the inclusion of the community in flood risk management (FRM). Currently, relocation as a mitigation strategy against river floods in Central Europe is rarely applied. FRM needs sufficient preparation and engagement for successful implementation of household relocation. This case study deals with the extreme flood event in June 2016 at the Simbach torrent in Bavaria (Germany). The focus lies on the planning process of structural flood defense measures and the small-scale relocation of 11 households. The adaptive planning process started right after the damaging event and was executed in collaboration with authorities and stakeholders of various levels and disciplines while at the same time including the local citizens. Residents were informed early, and personal communication, as well as trust in actors, enhanced the acceptance of decisions. Although technical knowledge was shared and concerns discussed, resident participation in the planning process was restricted. However, the given pre-conditions were found beneficial. In addition, a compensation payment contributed to a successful process. Thus, the study illustrates a positive image of the implementation of the alleviation scheme. Furthermore, preliminary planning activities and precautionary behavior (e.g., natural hazard insurance) were noted as significant factors to enable effective integrated flood risk management (IFRM).

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An application of a large scale conceptual hydrological model over the Elbe region

Hydrology and Earth System Sciences ◽

10.5194/hess-3-363-1999 ◽

1999 ◽

Vol 3 (3) ◽

pp. 363-374 ◽

Cited By ~ 7

Author(s):

M. Lobmeyr ◽

D. Lohmann ◽

C. Ruhe

Keyword(s):

Land Surface ◽

Large Scale ◽

Sunshine Duration ◽

Regional Scale ◽

Scale Model ◽

Surface Parameterization ◽

Extreme Flood ◽

Daily Sunshine ◽

Surface Scheme ◽

The Baltic

Abstract. This paper investigates the ability of the VIC-2L model coupled to a routing model to reproduce streamflow in the catchment of the lower Elbe River, Germany. The VIC-2L model, a hydrologically-based land surface scheme (LSS) which has been tested extensively in the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS), is put up on the rotated grid of 1/6 degree of the atmospheric regional scale model (REMO) used in the Baltic Sea Experiment (BALTEX). For a 10 year period, the VIC-2L model is forced in daily time steps with measured daily means of precipitation, air temperature, pressure, wind speed, air humidity and daily sunshine duration. VIC-2L model output of surface runoff and baseflow is used as input for the routing model, which transforms modelled runoff into streamflow, which is compared to measured streamflow at selected gauge stations. The water balance of the basin is investigated and the model results on daily, monthly and annual time scales are discussed. Discrepancies appear in time periods where snow and ice processes are important. Extreme flood events are analyzed in more dital. The influence of calibration with respect to runoff is examined.

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