THE SAFETY-BEHAVIOR-INDICATIVE FLOOD HAZARD MAP

<p>Flood hazard maps are essential for development and assessment of flood risk management strategies. Conventionally, flood hazard assessment is based on deterministic approach which involves deriving inundation maps considering hydrologic and hydraulic models. A flood hydrograph corresponding to a specified return period is derived using a hydrologic model, which is then routed through flood plain of the study area to estimate water surface elevations and inundation extent with the aid of a hydraulic model. A more informative way of representing flood risk is through probabilistic hazard maps, which additionally provide information on the uncertainty associated with the extent of inundation. To arrive at a probabilistic flood hazard map, several flood hydrographs are generated, representing possible scenarios for flood events over a long period of time (e.g., 500 to 1000 years). Each of those hydrographs is routed through the flood plain and probability of inundation for all locations in the plain is estimated to derive the probabilistic flood hazard map. For gauged catchments, historical streamflow and/or rainfall data may be used to determine design flood hydrographs and the corresponding hazard maps using various strategies. In the case of ungauged catchments, however, there is a dearth of procedures for prediction of flood hazard maps. To address this, a novel multivariate regional frequency analysis (MRFA) approach is proposed. It involves (i) use of a newly proposed clustering methodology for regionalization of catchments, which accounts for uncertainty arising from ambiguity in choice of various potential clustering algorithms (which differ in underlying clustering strategies) and their initialization, (ii) fitting of a multivariate extremes model to information pooled from catchments in homogeneous region to generate synthetic flood hydrographs at ungauged target location(s), and (iii) routing of the hydrographs through the flood plain using LISFLOOD-FP model to derive probabilistic flood hazard map. The MRFA approach is designed to predict flood hydrograph related characteristics (peak flow, volume and duration of flood) at target locations in ungauged basins by considering watershed related characteristics as predictor/explanatory variables. An advantage of the proposed approach is its ability to account for uncertainty in catchment regionalization and dependency between all the flood hydrograph related characteristics reliably. Thus, the synthetic flood hydrographs generated in river basins appear more realistic depicting the observed dependence structure among flood hydrograph characteristics. The approach alleviates several uncertainties found in conventional methods (based on conceptual, probabilistic or geomorphological approaches) which affect estimation of flood hazard. Potential of the proposed approach is demonstrated through a case study on catchments in Mahanadi river basin of India, which extends over 141,600 km<sup>2</sup> and is frequently prone to floods. Comparison is shown between flood hazard map obtained based on true at-site data and that derived based on the proposed MRFA approach by considering the respective sites to be pseudo-ungauged. Coefficient of correlation and root mean squared error considered for performance evaluation indicated that the proposed approach is promising.</p>

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Analysis of Hydro-Morphometric of Flash Flood Hazard Map of Wadi Gharandal Basin, Southwestern Sinai Area, Egypt, Using GIS and RS

Bulletin de la Société de Géographie d'Egypte ◽

10.21608/bsge.2018.90307 ◽

2018 ◽

Vol 91 (1) ◽

pp. 67-87

Author(s):

Mohamed Abd El-Aziz

Keyword(s):

Flash Flood ◽

Flood Hazard ◽

Hazard Map ◽

Flood Hazard Map ◽

Gis And Rs ◽

Southwestern Sinai

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Supplementary material to "Global flood hazard map and exposed GDP comparison: a China case study"

10.5194/nhess-2020-1-supplement ◽

2020 ◽

Author(s):

Jerom P. M. Aerts ◽

Steffi Uhlemann-Elmer ◽

Dirk Eilander ◽

Philip J. Ward

Keyword(s):

Flood Hazard ◽

Hazard Map ◽

Flood Hazard Map ◽

Supplementary Material

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Sensitivity Analysis of Storm Duration for Development of Flood Map at Bertam Catchment, Cameron Highlands.

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.35.22754 ◽

2018 ◽

Vol 7 (4.35) ◽

pp. 323

Author(s):

W.N.C.W. Zanial ◽

M.A. Malek ◽

N.A.A. Aziz

Keyword(s):

Sensitivity Analysis ◽

Water Level ◽

Stream Flow ◽

River Flow ◽

Flood Hazard ◽

Mitigation Measures ◽

Hazard Map ◽

Design Storm ◽

Flood Hazard Map ◽

Storm Duration

The current changes in climate have marked significant impacts in our daily weather. The changes have affected the trend, pattern and magnitude of rainfall-runoff as compared to the events commonly experienced. Flood is one of the effects of weather and climate change. Floods can be classified as one of the most devastating natural hazards and is a major concern to the country as it causes damages to human lives, environment, agriculture, land and structures. Therefore, effective flood planning and mitigation measures should be carried out in order to reduce the effects of flooding. Flood hazard map is one of the non-structural mitigation measures that can be used for planning purposes. Flood can be directly estimated or derived from frequency analysis when long duration of stream flow records is available. However, in the case of limited or no stream flow data available, design storm are generally used to estimate design flood. Downstream of Bertam Catchment is an ungauged river station where no flow records are available. Based on this limitation, in this study, design storm was used to design the flood map. Info Works RS was used to develop the flood model and sensitivity analysis of the design storm was performed. Results obtained in this study presented the comparison of flow between 100-years Annual Recurrence Interval (ARI) at various storm durations of 0.25hr, 0.5hr, 1hr, 3hrs, 6hrs, 12hrs, 1 day, 2days and 3 days. The maximum flow is found to be at 6hrs storm duration at 1103.418m3/s. Besides river flow, comparison of water level at 100-year ARI of various storm durations was also conducted. Results obtained from this study found that 24hrs storm duration will produce the highest water level at 1034.753m. By comparing the flow and water level, the result from river flow produces the maximum at 6hrs storm duration while the result of water level gives the maximum at 24hrs storm duration. Since, water level is preferable in producing flood hazard mapping at 2-D view, therefore, the storm duration is chosen based on results of sensitivity storm duration on water level conducted. Comparison is then conducted between 24-hrs storm duration at various ARIs. It can be concluded that 100-years ARI will lead to the maximum value of 1034.910m water level. Suitable storm duration and Annual Recurrence Interval (ARI) are to be determined in order to produce the best flood hazard map. In this study, it is found that 100-years ARI and 24hrs storm duration are the best combination, performed based on water level.

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Flood Hazard Assessment Using AHP in Corum, Turkey

Tecnología y Ciencias del Agua ◽

10.24850/j-tyca-2021-02-08 ◽

2021 ◽

Vol 12 (2) ◽

pp. 01-26

Author(s):

Derya Ozturk ◽

◽

Ilknur Yilmaz ◽

Ufuk Kirbas ◽

◽

...

Keyword(s):

Hazard Assessment ◽

Flood Hazard ◽

Hazard Mapping ◽

Hazard Map ◽

Analytic Hierarchy ◽

Flood Hazard Map ◽

Structural Measures ◽

High Flood ◽

Hierarchy Process ◽

Very High

In this study, the flood hazard of Corum province (Turkey) was investigated using the Analytic Hierarchy Process (AHP), which is one of the most popular Multi-criteria Decision Analysis (MCDA) methods, based on Geographic Information System (GIS). As a result of the AHP process, Corum province was categorized into five flood hazard classes: very high, high, medium, low, and very low. It was determined that 3% of the total area is under a very high flood hazard, and 25% is considered a high flood hazard. To assess the validity of the flood hazard map, the results were compared with the historical flood inventory. Our hazard map was compatible with the historical flood inventory, and our hazard map can now be used to estimate the areas that are threatened by possible floods. When the existing structural measures are overlapped with the hazard map in Corum, it is understood that a large part of the structural measures carried out to date have focused on the areas of very high and high flood hazard in the flood hazard map. Future structural measures and detailed studies should now address other areas identified as under threat in the flood hazard map. Our results suggest that the hazard assessment based on MCDA is suitable for flood hazard mapping.

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The use of rapid assessment for flood hazard map development in upper citarum river basin

MATEC Web of Conferences ◽

10.1051/matecconf/201822904011 ◽

2018 ◽

Vol 229 ◽

pp. 04011

Author(s):

Idham Riyando Moe ◽

Akbar Rizaldi ◽

Mohammad Farid ◽

Arie Setiadi Moerwanto ◽

Arno Adi Kuntoro

Keyword(s):

River Basin ◽

Early Warning ◽

Early Warning System ◽

Flood Hazard ◽

Rapid Assessment ◽

Warning System ◽

Observation Data ◽

Hazard Map ◽

Material Loss ◽

Flood Hazard Map

Flood is a natural disaster that can occur at any time and anywhere. The flood disaster causes material and non-material loss, then in order to increase the resilience to disaster, an early warning system is needed. The data is indispensable as a reference to make an early warning system. Unfortunately, flood assessment in purpose to record the data is often conducted much later after the event occurs. Therefore, this research was conducted to do modelling of flood hazard map is quantitatively and validated with observation data as a form of rapid flood assessment. The location of this study is in the Upper Citarum River Basin, around Bandung basin. The model is well done if the result shows the location of the flood as illustrated as the observational data. The result shows fair agreement with observed data where some points of inundated areas are captured and the location of inundated areas from modelling result looks similar to the inundated area from observation data.

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