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

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.

scholarly journals Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

2014 ◽  
Vol 18 (1) ◽  
pp. 353-365 ◽  
Author(s):  
U. Haberlandt ◽  
I. Radtke
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Model Calibration ◽  
Hydrological Model ◽  
Probability Distributions ◽  
Flood Frequency ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Peak Flows ◽  
Hourly Rainfall

Abstract. Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

Exploring frequency analysis alternatives on instantaneous peak flow, in the context of flood plain delineation in Southern Québec, Canada.

2021 ◽  
Author(s):  
Simon Ricard ◽  
Alexis Bédard-Therrien ◽  
Annie-Claude ACP Parent ◽  
Brian Morse ◽  
François Anctil
Keyword(s):  
Frequency Analysis ◽  
Peak Flow ◽  
Flood Plain ◽  
Flood Frequency ◽  
Regional Frequency Analysis ◽  
Flood Frequency Analysis ◽  
Flow Data ◽  
Specific Context ◽  
Pros And Cons ◽  
Regional Frequency

A flood frequency analysis is conducted using instantaneous peak flow data over a hydrologic sub-region of southern Québec following three distinct methodological frameworks. First, the analysis is conducted locally using available instantaneous peak flow data. Second, the analysis is conducted locally using daily peak flow data processed in order to consider the peak flow effect. Third, a regional frequency analysis is conducted pooling all available instantaneous peak flow data over the study area. Results reveal a notable diversity in the resulting recurrence peak flow estimates and related uncertainties from one analysis to another. Expert judgement appears essential to arbitrate which alternative should be operated considering a specific context of application for flood plain delineation. Pros and cons for each approach are discussed. We finally encourage the use of a diversity of approaches in order to provide a robust assessment of uncertainty affecting peak flow estimates.

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

2020 ◽  
Vol 3 (1) ◽  
pp. 58-68
Author(s):  
D. Nagesh Kumar ◽  
Apoorva R. Shastry ◽  
K. Srinivasa Raju
Keyword(s):  
Spatial Resolution ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Flood Inundation ◽  
Topographic Index ◽  
Inundation Maps ◽  
Digital Elevation ◽  
Flood Magnitude ◽  
The Relationship ◽  
Flood Prone Areas

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.

scholarly journals Frequency Analysis of Snowmelt Flood Based on GAMLSS Model in Manas River Basin, China

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2007
Author(s):  
Chaofei He ◽  
Fulong Chen ◽  
Aihua Long ◽  
Chengyan Luo ◽  
Changlu Qiao
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Flood Frequency ◽  
Additive Models ◽  
Flood Frequency Analysis ◽  
Climate Indices ◽  
Design Flood ◽  
Stationary Model ◽  
Snowmelt Flood ◽  
The Impact

With the acceleration of human economic activities and dramatic changes in climate, the validity of the stationarity assumption of flood time series frequency analysis has been questioned. In this study, a framework for flood frequency analysis is developed on the basis of a tool, namely, the Generalized Additive Models for Location, Scale, and Shape (GAMLSS). We introduced this model to construct a non-stationary model with time and climate factor as covariates for the 50-year snowmelt flood time series in the Kenswat Reservoir control basin of the Manas River. The study shows that there are clear non-stationarities in the flood regime, and the characteristic series of snowmelt flood shows an increasing trend with the passing of time. The parameters of the flood distributions are modelled as functions of climate indices (temperature and rainfall). The physical mechanism was incorporated into the study, and the simulation results are similar to the actual flood conditions, which can better describe the dynamic process of snowmelt flood characteristic series. Compared with the design flood results of Kenswat Reservoir approved by the China Renewable Energy Engineering Institute in December 2008, the design value of the GAMLSS non-stationary model considers that the impact of climate factors create a design risk in dry years by underestimating the risk.

scholarly journals A space-time hybrid hourly rainfall model for derived flood frequency analysis

2008 ◽  
Vol 5 (4) ◽  
pp. 2459-2490 ◽  
Author(s):  
U. Haberlandt ◽  
A.-D. Ebner von Eschenbach ◽  
I. Buchwald
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Hydrological Model ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Second Step ◽  
Precipitation Time Series ◽  
Rainfall Characteristics ◽  
Renewal Model ◽  
Event Series

Abstract. For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, so stochastic precipitation synthesis is a good alternative. Here, a hybrid two step procedure is proposed to provide suitable space-time precipitation fields as input for hydrological modelling. First, a univariate alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. The alternating renewal model describes wet spell durations, dry spell durations and wet spell amounts using univariate frequency distributions separately for two seasons. The dependence between wet spell amount and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for two mesoscale catchments in the Bode river basin of northern Germany and applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. However, they also show that it is important to consider the same rainfall station network for calibration of the hydrological model with observed data as for application using synthetic rainfall data.

scholarly journals Derived flood frequency analysis using different model calibration strategies based on various types of rainfall–runoff data – a comparison

2013 ◽  
Vol 10 (8) ◽  
pp. 10379-10417
Author(s):  
U. Haberlandt ◽  
I. Radtke
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Model Calibration ◽  
Hydrological Model ◽  
Probability Distributions ◽  
Flood Frequency ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Peak Flows ◽  
Hourly Rainfall

Abstract. Derived flood frequency analysis allows to estimate design floods with hydrological modelling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices about precipitation input, discharge output and consequently regarding the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets. Event based and continuous observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in Northern Germany with the hydrological model HEC-HMS. The results show that: (i) the same type of precipitation input data should be used for calibration and application of the hydrological model, (ii) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, (iii) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

Sign in / Sign up

Export Citation Format

Share Document