Delineation of flood-prone areas using modified topographic index for a river basin

Abstract The modified topographic index () based on digital elevation models (DEMs) was employed to delineate flood-prone areas in Mahanadi basin, India. and flood inundation maps were compared to obtain the threshold () beyond which the area is assumed to be inundated by flood and the exponent of the . Scale dependence was also investigated to evaluate the sensitiveness of spatial resolution of the DEMs. DEMs of five resolutions, namely, ASTER global, SRTM, GMTED2010 (30 arc-seconds), GMTED 2010 (15 arc-seconds), and GMTED 2010 (7.5 arc-seconds), were used and ASTER global was preferred due to its low error compared to the remainder. Flood frequency analysis was conducted to obtain the relationship between flood-prone areas and flood magnitude. It was observed that (i) the exponent in the showed little variation, (ii) is reduced with reducing spatial resolution of the DEM, and (iii) error is also reduced as the DEMs' resolution is reduced.

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INTEGRATING DIGITAL ELEVATION MODEL, LANDUSE/LANDCOVER AND FLOOD FREQUENCY ANALYSIS: A DETERMINISTIC APPROACH TO FLOOD INUNDATION AND RISK MODELING OF MAKURDI ALONG ITS RIVER BENUE REACH

FUDMA Journal of Sciences ◽

10.33003/fjs-2021-0501-593 ◽

2021 ◽

Vol 5 (1) ◽

pp. 477-489

Author(s):

Kehinde T. Oyatayo ◽

C. Ndabula ◽

D. N. Jeb ◽

G. K. Adamu ◽

G. G. Jidauna

Keyword(s):

Digital Elevation Model ◽

Flood Frequency ◽

Recurrence Interval ◽

Flood Frequency Analysis ◽

Flood Inundation ◽

Return Periods ◽

Discharge Data ◽

Digital Elevation ◽

Elevation Model ◽

Flood Flow

The study applied GIS techniques to integrate Digital Elevation Model (DEM), Landuse/Landcover (LULC) and flood frequency analyses to determine extent of flood hazard inundation of Makurdi town along its River Benue reach following extreme discharges and stage levels. Annual maximum stage and discharge data from 1914 to 2015 was analyzed using Gumbel’s distribution to predict flood flow for different return periods (T): 5, 10, 25, 50, 75, and 100. A goodness of fit test was conducted using Chi square statistics, which was insignificant indicating that River Benue at Makurdi flood flow fits the Gumbel distribution. Combining this result with DEM and classified LULC data, the GIS spatial analyst tool was used to estimate the areal extent of landuse that will be inundated per return period. The result shows extent of flood inundation based on current landuse pattern for the respective return periods of predicted extreme stage / discharge likely due to climate change to be as follows: bareland (1.69, 1.74, 1.78, 1.84, 1.83, 1.89 km2); settlement/built-up (5.38, 5.50, 5.63, 5.76, 5.76, 6.02 km2); farmlands (272.27, 283.59, 295.10, 306.43, 306.43,and 317.49 km2); Vegetation (91.56, 95.26, 98.78, 102.45, 102.48, and 105.95 km2); water bodies (0.21,0.21, 0.22,0.22,0.22, and 0.22 km2) and Wetlands (44.14, 45.80, 47.48, 30.36,49.42 and 50.78 km2). This reveals a general increase in the extent of flood inundation at progressive recurrence interval, and predicted rising extreme river stage heights / discharge except for the flood with 50 year recurrence interval. The study recommends that NEMA and Benue State Urban Development Board

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Exploring stage-based flood frequency analysis for flood inundation mapping

10.5194/egusphere-egu21-1924 ◽

2021 ◽

Author(s):

Shobhit Singh ◽

Somil Swarnkar ◽

Rajiv Sinha

Keyword(s):

Probability Distribution ◽

River Basin ◽

Frequency Analysis ◽

Probability Distributions ◽

Flood Frequency ◽

Flood Frequency Analysis ◽

Flood Inundation ◽

Return Periods ◽

Theoretical Probability ◽

Inundation Maps

<p>Floods are one of the worst natural hazards around the globe and around 40% of all losses worldwide due to natural hazard have been caused by floods since 1980s. In India, more than 40 million hectares of area are affected by floods annually which makes it one of the worst affected country in the world. In particular, the Ganga river basin in northern India which hosts nearly half a billion people, is one of the worst floods affected regions in the country. The Ghaghra river is one of the highest discharge-carrying tributaries of the Ganga river, which originates from High Himalaya. Despite severally affected by floods each year, flood frequencies of the Ghaghra river are poorly understood, making it one of the least studied river basins in the Ganga basin. It is important to note that, like several other rivers in India, the Ghaghra also has several hydrological stations where only stage data is available, and therefore traditional flood frequency analysis using discharge data becomes difficult. In this work, we have performed flood frequency analysis using both stage and discharge dataset at three different gauge stations in the Ghaghra river basin to compare the results using statistical methods. The L-moment analysis is applied to assess the probability distribution for the flood frequency analysis. Further, we have used the TanDEM-x 90m digital elevation model (DEM) to map the flood inundation regions. Our results suggest the Weibull is statistically significant distribution for the discharge dataset. However, stage above danger level (SADL) follows General Pareto (GP3) and Generalized Extreme Value (GEV) distributions. The quantile-quantile plot analysis suggests that the SADL probability distributions (GP3 and GEV) are closely following the theoretical probability distributions. However, the discharge distribution (Weibull) is showing a relatively weak corelation with the theoretical probability distribution. We further used the probability distribution to assess the SADL frequencies at 5-, 10-, 20-, 50- and 100-year return periods. The magnitudes of SADL at different return periods were then used to map the water inundation areas around different gauging stations. These inundation maps were cross-validated with the globally available flooding extent maps provided by Dartmouth flood observatory. Overall, this work exhibits a simple and novel technique to generate inundation maps around the gauging locations without using any sophisticated hydraulics models.</p>

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Non-Stationary Flood Frequency Analysis Using Cubic B-Spline-Based GAMLSS Model

Water ◽

10.3390/w12071867 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1867

Author(s):

Chunlai Qu ◽

Jing Li ◽

Lei Yan ◽

Pengtao Yan ◽

Fang Cheng ◽

...

Keyword(s):

Quantile Regression ◽

Frequency Analysis ◽

Flood Frequency ◽

Flood Frequency Analysis ◽

Design Flood ◽

Statistical Parameters ◽

B Spline ◽

Quantile Regression Model ◽

Design Values ◽

The Relationship

Under changing environments, the most widely used non-stationary flood frequency analysis (NFFA) method is the generalized additive models for location, scale and shape (GAMLSS) model. However, the model structure of the GAMLSS model is relatively complex due to the large number of statistical parameters, and the relationship between statistical parameters and covariates is assumed to be unchanged in future, which may be unreasonable. In recent years, nonparametric methods have received increasing attention in the field of NFFA. Among them, the linear quantile regression (QR-L) model and the non-linear quantile regression model of cubic B-spline (QR-CB) have been introduced into NFFA studies because they do not need to determine statistical parameters and consider the relationship between statistical parameters and covariates. However, these two quantile regression models have difficulties in estimating non-stationary design flood, since the trend of the established model must be extrapolated infinitely to estimate design flood. Besides, the number of available observations becomes scarcer when estimating design values corresponding to higher return periods, leading to unreasonable and inaccurate design values. In this study, we attempt to propose a cubic B-spline-based GAMLSS model (GAMLSS-CB) for NFFA. In the GAMLSS-CB model, the relationship between statistical parameters and covariates is fitted by the cubic B-spline under the GAMLSS model framework. We also compare the performance of different non-stationary models, namely the QR-L, QR-CB, and GAMLSS-CB models. Finally, based on the optimal non-stationary model, the non-stationary design flood values are estimated using the average design life level method (ADLL). The annual maximum flood series of four stations in the Weihe River basin and the Pearl River basin are taken as examples. The results show that the GAMLSS-CB model displays the best model performance compared with the QR-L and QR-CB models. Moreover, it is feasible to estimate design flood values based on the GAMLSS-CB model using the ADLL method, while the estimation of design flood based on the quantile regression model requires further studies.

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Evaluasi Perencanaan Sistem Penyaluran Drainase di Kelurahan Jurumudi Kecamatan Benda Kota Tangerang

Jurnal Reka Lingkungan ◽

10.26760/rekalingkungan.v8i2.90-100 ◽

2020 ◽

Vol 8 (2) ◽

pp. 90-100

Author(s):

MIRZA KHOERUN FURQON MULYA ◽

EKA WARDHANI ◽

AGUNG GHANI KRAMAWIJAYA

Keyword(s):

Frequency Analysis ◽

Spatial Planning ◽

Flood Frequency ◽

Flood Frequency Analysis ◽

Mathematical Approach ◽

Intensity Analysis ◽

Rain Intensity ◽

Evaluation Result ◽

Drainage Channels ◽

Flood Prone Areas

AbstrakBerdasarkan Peraturan Daerah Kota Tangerang nomor 6 Tahun 2012 Tentang RTRW, Kelurahan Jurumudi termasuk dalam kawasan rawan banjir. Terdapat dua titik banjir yaitu Jalan Permata Bandara dan Jalan Pergudangan. Evaluasi dilakukan dengan membandingan dimensi saluran eksisting dan rencana. Tahapan perencanaan meliputi analisis CHHM dengan Metode Gumbel, Log Pearson III, dan Iwai Kedoya. Analisis intensitas hujan dilakukan dengan Metode Van Breen, Bell-Tanimoto, dan Hasper der Weduwen melalui pendekatan matematis persamaan Talbot, Sherman, dan Ishiguro. Perhitungan debit rencana dilakukan dengan metode rasional. Perhitungan dimensi saluran dilakukan berdasarkan persamaan Manning. Hasil dari perencanaan dimensi rencana yaitu 50x30 cm – 240x80 cm. Hasil evaluasi menunjukkan bahwa saluran pada Jalan Permata Bandara dan Jalan Pergudangan tidak memadai karena saluran drainase eksiting kurang dari rencana.Kata kunci: Banjir, Dimensi Saluran, Kelurahan JurumudiAbstractAccording to Tangerang City Regional Regulation number 6 of 2012 about Regional Spatial Planning, Kelurahan Jurumudi is categorized as flood-prone areas. There are two flooding points which are Permata Bandara Street and Pergudangan Street. Evaluation is done by comparing the existing dimensions and dimensions of planning results. The steps include Flood Frequency Analysis with Gumbel, Log Pearson III, and Iwai Kedoya methods. Rain intensity analysis is carried out by the Van Breen, Bell-Tanimoto, and Hasper der Weduwen methods through a mathematical approach of Talbot, Sherman, and Ishiguro equations. Flowrate calculation plan is done with rational method. Calculation of channel dimensions is done based on the Manning equation. The planning result shows 50x30 cm – 240x80 cm of dimensions. The evaluation result shows that the channels on Permata Bandara Street and Pergudangan Street are inadequate because the existing drainage channels are less than what has been planned.Kata kunci: Flood, Channels Dimension, Kelurahan Jurumudi

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Flood frequency analysis for the Red River at Winnipeg

Canadian Journal of Civil Engineering ◽

10.1139/l00-122 ◽

2001 ◽

Vol 28 (3) ◽

pp. 355-362 ◽

Cited By ~ 4

Author(s):

Donald H Burn ◽

N K Goel

Keyword(s):

Flood Frequency ◽

Red River ◽

Noise Model ◽

Flood Frequency Analysis ◽

Data Series ◽

Correlation Structures ◽

Flood Magnitude ◽

Mixed Noise ◽

Flood Quantiles

This paper reviews the flood frequency characteristics of the Red River at Winnipeg. The impacts of persistence in the flood series on estimates of flood quantiles and their associated confidence intervals are examined. This is done by generating a large number of data sequences using a mixed noise model that preserves the short-term and long-term correlation structures of the observed flood series. The results reveal that persistence in the data series can lead to a slight increase in the expected flood magnitude for a given return period. More importantly, persistence is shown to dramatically increase the uncertainty associated with estimated flood quantiles. The 117-year flood series for the Red River at Winnipeg is demonstrated to be equivalent to roughly 45 years of independent data.Key words: flood frequency, extreme events, simulation, historical data.

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Flood frequency analysis of historical flood data under stationary and non-stationary modelling

Hydrology and Earth System Sciences ◽

10.5194/hess-19-2561-2015 ◽

2015 ◽

Vol 19 (6) ◽

pp. 2561-2576 ◽

Cited By ~ 53

Author(s):

M. J. Machado ◽

B. A. Botero ◽

J. López ◽

F. Francés ◽

A. Díez-Herrero ◽

...

Keyword(s):

Frequency Analysis ◽

Flood Frequency ◽

City Council ◽

Additive Models ◽

Water Levels ◽

Flood Frequency Analysis ◽

Environmental Drivers ◽

Historical Records ◽

Nao Index ◽

Flood Magnitude

Abstract. Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged records) improved the estimates of the probabilities of rare floods (return intervals of 100 yr and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 yr) has changed over the last 500 yr due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful in providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

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Flood frequency analysis of historical flood data under stationary and non-stationary modelling

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-525-2015 ◽

2015 ◽

Vol 12 (1) ◽

pp. 525-568 ◽

Cited By ~ 12

Author(s):

M. J. Machado ◽

B. A. Botero ◽

J. López ◽

F. Francés ◽

A. Díez-Herrero ◽

...

Keyword(s):

Frequency Analysis ◽

Flood Frequency ◽

City Council ◽

Additive Models ◽

Water Levels ◽

Flood Frequency Analysis ◽

Environmental Drivers ◽

Exceedance Probability ◽

Nao Index ◽

Flood Magnitude

Abstract. Historical records are an important source of information about extreme and rare floods with a great value to establish a reliable flood return frequency. The use of long historic records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 year flood record from the Tagus River in Aranjuez (Central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their implications on hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations on flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation index (NAO index). Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators; (b) a time–varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, that incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged record) improved the estimates of the probabilities of rare floods (return intervals of 100 year and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 year) has changed over the last 500 year due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful on providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

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Hydrological and hydraulic models for determination of flood-prone and flood inundation areas

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-373-137-2016 ◽

2016 ◽

Vol 373 ◽

pp. 137-141 ◽

Cited By ~ 7

Author(s):

Hafzullah Aksoy ◽

Veysel Sadan Ozgur Kirca ◽

Halil Ibrahim Burgan ◽

Dorukhan Kellecioglu

Keyword(s):

Cross Sections ◽

Urban Areas ◽

Work Load ◽

Hydraulic Model ◽

Flood Inundation ◽

Detailed Data ◽

Wetness Index ◽

Digital Elevation ◽

Elevation Model ◽

Flood Prone Areas

Abstract. Geographic Information Systems (GIS) are widely used in most studies on water resources. Especially, when the topography and geomorphology of study area are considered, GIS can ease the work load. Detailed data should be used in this kind of studies. Because of, either the complication of the models or the requirement of highly detailed data, model outputs can be obtained fast only with a good optimization. The aim in this study, firstly, is to determine flood-prone areas in a watershed by using a hydrological model considering two wetness indexes; the topographical wetness index, and the SAGA (System for Automated Geoscientific Analyses) wetness index. The wetness indexes were obtained in the Quantum GIS (QGIS) software by using the Digital Elevation Model of the study area. Flood-prone areas are determined by considering the wetness index maps of the watershed. As the second stage of this study, a hydraulic model, HEC-RAS, was executed to determine flood inundation areas under different return period-flood events. River network cross-sections required for this study were derived from highly detailed digital elevation models by QGIS. Also river hydraulic parameters were used in the hydraulic model. Modelling technology used in this study is made of freely available open source softwares. Based on case studies performed on watersheds in Turkey, it is concluded that results of such studies can be used for taking precaution measures against life and monetary losses due to floods in urban areas particularly.

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Integrating Water Observation from Space Product and Time-Series Flow Data for Modeling Spatio-Temporal Flood Inundation Dynamics

Remote Sensing ◽

10.3390/rs11212535 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2535

Author(s):

Chang Huang ◽

Yun Chen ◽

Shiqiang Zhang ◽

Linyi Li ◽

Junfeng Shui ◽

...

Keyword(s):

Time Series ◽

Surface Water ◽

Well Being ◽

Flood Frequency ◽

Flood Frequency Analysis ◽

Flood Inundation ◽

Riparian Ecosystems ◽

Flow Data ◽

Inundation Frequency ◽

Spatio Temporal

Periodic inundation of floodplains and wetlands is critical for the well being of ecosystems. This study proposes a simple but efficient model that integrates time series daily flow data and the Landsat-derived Water Observation from Space (WOfS) product to model the spatio-temporal flood inundation dynamics of the Murray-Darling Basin. A zone-gauge framework is adopted in order to reduce the hydrologic complexity of the large river basin. Under this framework, flood frequency analysis was conducted at each gauge station to identify historical peak flows and their annual exceedance probabilities. The results were then linked with the WOfS dataset through date to model the inundation probability in each zone. Inundation frequency was derived by simply overlaying the yearly inundation extent from 1988 to 2015 and counting the inundation times. Both the resultant inundation frequency map and inundation probability map are of ecological significance for the survival and prosperity of riparian ecosystems. The assumptions of the model were validated carefully to enhance its theoretical basis. The WOfS dataset was also compared with another independent water observation dataset to cross-validate its reliability. It is hoped that with the development of more and more global high-resolution surface water datasets, this study could inspire more studies that integrate surface water datasets with hydrological observations for flood inundation modeling.

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Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh

Remote Sensing ◽

10.3390/rs11131581 ◽

2019 ◽

Vol 11 (13) ◽

pp. 1581 ◽

Cited By ~ 34

Author(s):

Uddin ◽

Matin ◽

Meyer

Keyword(s):

Land Cover ◽

Flood Frequency ◽

Landsat 8 ◽

Flood Inundation ◽

Inundation Maps ◽

Flood Inundation Mapping ◽

Multi Temporal ◽

Land Cover Map ◽

Hazard Response ◽

Land Cover Maps

Bangladesh is one of the most flood-affected countries in the world. In the last few decades, flood frequency, intensity, duration, and devastation have increased in Bangladesh. Identifying flood-damaged areas is highly essential for an effective flood response. This study aimed at developing an operational methodology for rapid flood inundation and potential flood damaged area mapping to support a quick and effective event response. Sentinel-1 images from March, April, June, and August 2017 were used to generate inundation extents of the corresponding months. The 2017 pre-flood land cover maps were prepared using Landsat-8 images to identify major land cover on the ground before flooding. The overall accuracy of flood inundation mapping was 96.44% and the accuracy of the land cover map was 87.51%. The total flood inundated area corresponded to 2.01%, 4.53%, and 7.01% for the months April, June, and August 2017, respectively. Based on the Landsat-8 derived land cover information, the study determined that cropland damaged by floods was 1.51% in April, 3.46% in June, 5.30% in August, located mostly in the Sylhet and Rangpur divisions. Finally, flood inundation maps were distributed to the broader user community to aid in hazard response. The data and methodology of the study can be replicated for every year to map flooding in Bangladesh.

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