scholarly journals Intensity-Duration-Frequency (IDF) Curve and the Most Suitable Method to Determine Flood Peak Discharge in Upper Werba Sub-Watershed

2019 ◽  
Vol 21 (2) ◽  
pp. 70-75
Author(s):  
Cilcia Kusumastuti ◽  
Prasetio Sudjarwo ◽  
Marvin Christhie ◽  
Timotius Krisna
Keyword(s):  
Rainfall Intensity ◽  
Flood Frequency ◽  
Rational Method ◽  
Flood Frequency Analysis ◽  
Unit Hydrograph ◽  
Design Flood ◽  
Flood Peak ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Intensity Duration Frequency

Design flood is one of the important factors for flood risk assessment and water infrastructures planning and development in a certain location. There are several methods to estimate it, one method which has been commonly and widely use is using flood frequency analysis. This research aims to develop Intensity-Duration-Frequency (IDF) curves in Upper Werba Sub-Watershed, West Papua Province, Indonesia, to estimate design rainfall intensity. The design rainfall intensity is used to estimate peak of flood discharge using Rational Formula in the sub-watershed. Other methods, i.e. Soil Conservation Service and Nakayasu Synthetic Unit Hydrograph are also presented in this paper to provide comparison of the estimated peak of flood discharge. The result shows that the Rational method provide the closest magnitude of estimated flood discharge in Upper Werba Sub-Watershed to the observed streamflow. Therefore, it is suggested that the Rational method can be used for water infrastructure planning and development in the sub-watershed.

scholarly journals Deriving Design Flood Hydrograph Based on Conditional Distribution: A Case Study of Danjiangkou Reservoir in Hanjiang Basin

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Changjiang Xu ◽  
Jiabo Yin ◽  
Shenglian Guo ◽  
Zhangjun Liu ◽  
Xingjun Hong
Keyword(s):  
Joint Probability ◽  
Flood Frequency ◽  
Peak Discharge ◽  
Flood Frequency Analysis ◽  
Design Flood ◽  
Copula Functions ◽  
Danjiangkou Reservoir ◽  
Flood Peak ◽  
Flood Hydrograph

Design flood hydrograph (DFH) for a dam is the flood of suitable probability and magnitude adopted to ensure safety of the dam in accordance with appropriate design standards. Estimated quantiles of peak discharge and flood volumes are necessary for deriving the DFH, which are mutually correlated and need to be described by multivariate analysis methods. The joint probability distributions of peak discharge and flood volumes were established using copula functions. Then the general formulae of conditional most likely composition (CMLC) and conditional expectation composition (CEC) methods that consider the inherent relationship between flood peak and volumes were derived for estimating DFH. The Danjiangkou reservoir in Hanjiang basin was selected as a case study. The design values of flood volumes and 90% confidence intervals with different peak discharges were estimated by the proposed methods. The performance of CMLC and CEC methods was also compared with conventional flood frequency analysis, and the results show that CMLC method performs best for both bivariate and trivariate distributions which has the smallest relative error and root mean square error. The proposed CMLC method has strong statistical basis with unique design flood composition scheme and provides an alternative way for deriving DFH.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

Nonstationary Flood Frequency Analysis for Annual Flood Peak and Volume Series in Both Univariate and Bivariate Domain

2018 ◽  
Vol 32 (13) ◽  
pp. 4239-4252 ◽  
Author(s):  
Jianzhu Li ◽  
Yuming Lei ◽  
Senming Tan ◽  
Colin D. Bell ◽  
Bernard A. Engel ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Flood Peak

Comparison of Annual Maximum and Peaks Over Threshold Methods with Automated Threshold Selection in Flood Frequency Analysis: A Case Study for Australia

2021 ◽  
Author(s):  
Xiao Pan ◽  
Ataur Rahman
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
Distribution Functions ◽  
Flood Frequency Analysis ◽  
Annual Maximum ◽  
Threshold Selection ◽  
Peaks Over Threshold ◽  
Design Flood ◽  
Threshold Detection ◽  
Using Data

Abstract Flood frequency analysis (FFA) enables fitting of distribution functions to observed flow data for estimation of flood quantiles. Two main approaches, Annual Maximum (AM) and peaks-over-threshold (POT) are adopted for FFA. POT approach is under-employed due to its complexity and uncertainty associated with the threshold selection and independence criteria for selecting peak flows. This study evaluates the POT and AM approaches using data from 188 gauged stations in south-east Australia. POT approach adopted in this study applies a different average numbers of events per year fitted with Generalised Pareto (GP) distribution with an automated threshold detection method. The POT model extends its parametric approach to Maximum Likelihood Estimator (MLE) and Point Moment Weighted Unbiased (PMWU) method. Generalised Extreme Value (GEV) distribution using L-moment estimator is used for AM approach. It has been found that there is a large difference in design flood estimates between the AM and POT approaches for smaller average recurrence intervals (ARI), with a median difference of 25% for 1.01 year ARI and 5% for 50 and 100 years ARIs.

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

Water ◽  
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.

scholarly journals Historical changes in frequency of extreme floods in Prague

2015 ◽  
Vol 19 (10) ◽  
pp. 4307-4315 ◽  
Author(s):  
L. Elleder
Keyword(s):  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Flood Events ◽  
Central European ◽  
Extreme Floods ◽  
Flood Peak ◽  
The Past ◽  
Documentary Sources ◽  
Instrumental Period ◽  
Peak Discharges

Abstract. This study presents a flood frequency analysis for the Vltava River catchment using a major profile in Prague. The estimates of peak discharges for the pre-instrumental period of 1118–1824 based on documentary sources were carried out using different approaches. 187 flood peak discharges derived for the pre-instrumental period augmented 150 records for the instrumental period of 1825–2013. Flood selection was based on Q10 criteria. Six flood-rich periods in total were identified for 1118–2013. Results of this study correspond with similar studies published earlier for some central European catchments, except for the period around 1750. Presented results indicate that the territory of the present Czech Republic might have experienced extreme floods in the past, comparable – with regard to peak discharge (higher than or equal to Q10) and frequency – to the flood events recorded recently.

A knowledge-based expert system for flood frequency analysis

1990 ◽  
Vol 17 (4) ◽  
pp. 597-609 ◽  
Author(s):  
K. C. Ander Chow ◽  
W. E. Watt
Keyword(s):  
Expert System ◽  
Frequency Analysis ◽  
Sampling Error ◽  
Inductive Reasoning ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Design Flood ◽  
Knowledge Based ◽  
Single Station ◽  
Quantile Estimates

Single-station flood frequency analysis is an important element in hydrotechnical planning and design. In Canada, no single statistical distribution has been specified for floods; hence, the conventional approach is to select a distribution based on its fit to the observed sample. This selection is not straightforward owing to typically short record lengths and attendant sampling error, magnified influence of apparent outliers, and limited evidence of two populations. Nevertheless, experienced analysts confidently select a distribution for a station based only on a few heuristics. A knowledge-based expert system has been developed to emulate these expert heuristics. It can perform data analyses, suggest an appropriate distribution, detect outliers, and provide means to justify a design flood on physical grounds. If the sample is too small to give reliable quantile estimates, the system performs a Bayesian analysis to combine regional information with station-specific data. The system was calibrated and tested for 52 stations across Canada. Its performance was evaluated by comparing the distributions selected by experts with those given by the developed system. The results indicated that the system can perform at an expert level in the task of selecting distributions. Key words: flood frequency, expert system, single-station, fuzzy logic, inductive reasoning, production system.

scholarly journals Use of historical data in flood frequency analysis: a case study for four catchments in Norway

2017 ◽  
Vol 49 (2) ◽  
pp. 466-486 ◽  
Author(s):  
Kolbjørn Engeland ◽  
Donna Wilson ◽  
Péter Borsányi ◽  
Lars Roald ◽  
Erik Holmqvist
Keyword(s):  
Flood Frequency ◽  
Water Levels ◽  
Added Value ◽  
Flood Frequency Analysis ◽  
Return Periods ◽  
Design Flood ◽  
Historical Information ◽  
Improve Design ◽  
Estimation Uncertainty ◽  
Flood Estimation

Abstract There is a need to estimate design floods for areal planning and the design of important infrastructure. A major challenge is the mismatch between the length of the flood records and needed return periods. A majority of flood time series are shorter than 50 years, and the required return periods might be 200, 500, or 1,000 years. Consequently, the estimation uncertainty is large. In this paper, we investigated how the use of historical information might improve design flood estimation. We used annual maximum data from four selected Norwegian catchments, and historical flood information to provide an indication of water levels for the largest floods in the last two to three hundred years. We assessed the added value of using historical information and demonstrated that both reliability and stability improves, especially for short record lengths and long return periods. In this study, we used information on water levels, which showed the stability of river profiles to be a major challenge.

scholarly journals Design flood estimation with varying record lengths in Norway under stationarity and nonstationarity scenarios

2021 ◽  
Author(s):  
Lei Yan ◽  
Lihua Xiong ◽  
Gusong Ruan ◽  
Chong-Yu Xu ◽  
Mengjie Zhang
Keyword(s):  
Frequency Analysis ◽  
Location Parameter ◽  
Extreme Value ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Design Flood ◽  
Generalized Extreme Value ◽  
Record Length ◽  
Flood Estimation ◽  
The Stability

Abstract In traditional flood frequency analysis, a minimum of 30 observations is required to guarantee the accuracy of design results with an allowable uncertainty; however, there has not been a recommendation for the requirement on the length of data in NFFA (nonstationary flood frequency analysis). Therefore, this study has been carried out with three aims: (i) to evaluate the predictive capabilities of nonstationary (NS) and stationary (ST) models with varying flood record lengths; (ii) to examine the impacts of flood record lengths on the NS and ST design floods and associated uncertainties; and (iii) to recommend the probable requirements of flood record length in NFFA. To achieve these objectives, 20 stations with record length longer than 100 years in Norway were selected and investigated by using both GEV (generalized extreme value)-ST and GEV-NS models with linearly varying location parameter (denoted by GEV-NS0). The results indicate that the fitting quality and predictive capabilities of GEV-NS0 outperform those of GEV-ST models when record length is approximately larger than 60 years for most stations, and the stability of the GEV-ST and GEV-NS0 is improved as record lengths increase. Therefore, a minimum of 60 years of flood observations is recommended for NFFA for the selected basins in Norway.

scholarly journals Flood frequency analysis using mean daily flows vs. instantaneous peak flows

2021 ◽  
Author(s):  
Anne Bartens ◽  
Uwe Haberlandt
Keyword(s):  
Frequency Analysis ◽  
Linear Models ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Estimation Methods ◽  
Entire Study ◽  
Flood Peak ◽  
Flood Dynamics ◽  
Event Based ◽  
Available Information

Abstract. In many cases flood frequency analysis needs to be carried out on mean daily flow (MDF) series without any available information on the instantaneous peak flow (IPF). We analyze the error of using MDFs instead of IPFs for flood quantile estimation on a German dataset and assess spatial patterns and factors that influence the deviation of MDF floods from their IPF counterparts. The main dependence could be found for catchment area but also gauge elevation appeared to have some influence. Based on the findings we propose simple linear models to correct both MDF flood peaks of individual flood events and overall MDF flood statistics. Key predictor in the models is the event-based ratio of flood peak and flood volume obtained directly from the daily flow records. This correction approach requires a minimum of data input, is easily applied, valid for the entire study area and successfully estimates IPF peaks and flood statistics. The models perform particularly well in smaller catchments, where other IPF estimation methods fall short. Still, the limit of the approach is reached for catchment sizes below 100 km2, where the hydrograph information from the daily series is no longer capable of approximating instantaneous flood dynamics.

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