scholarly journals Bivariate Return Period for Design Hyetograph and Relationship with T-Year Design Flood Peak

Water ◽  
2017 ◽  
Vol 9 (9) ◽  
pp. 673 ◽  
Author(s):  
Davide Luciano De Luca ◽  
Daniela Biondi
Keyword(s):  
Return Period ◽  
Design Flood ◽  
Flood Peak ◽  
Bivariate Return Period

scholarly journals A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

2013 ◽  
Vol 17 (8) ◽  
pp. 3023-3038 ◽  
Author(s):  
A. I. Requena ◽  
L. Mediero ◽  
L. Garrote
Keyword(s):  
Return Period ◽  
Risk Estimation ◽  
Design Flood ◽  
Flood Peak ◽  
Probability Of Occurrence ◽  
Reservoir Routing ◽  
Maximum Water ◽  
Dam Overtopping ◽  
Bivariate Return Period ◽  
Water Elevation

Abstract. A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping.

scholarly journals Bivariate return period based on copulas for hydrologic dam design: comparison of theoretical and empirical approach

2013 ◽  
Vol 10 (1) ◽  
pp. 557-596 ◽  
Author(s):  
A. I. Requena ◽  
L. Mediero ◽  
L. Garrote
Keyword(s):  
Return Period ◽  
Design Flood ◽  
Flood Peak ◽  
Probability Of Occurrence ◽  
Maximum Water ◽  
Bivariate Copula ◽  
Dam Overtopping ◽  
Bivariate Return Period ◽  
Water Elevation

Abstract. Hydrologic frequency analyses are usually focused on flood peaks. Multivariate analyses on flood variables have not been so exhaustively studied despite the fact that they are required to represent the full hydrograph, which is essential for designing some structures like dams. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume. An empirical bivariate return period was defined in terms of acceptable risk to the dam through the maximum water elevation reached during the routing process, in order to perform a risk assessment of dam overtopping. A Monte Carlo procedure was developed to compare the probability of occurrence of a flood with the return period linked to the risk of dam overtopping. The procedure is applied to the case study of the Santillana reservoir in Spain. A set of synthetic peak-volume pairs was generated by the fitted copula and synthetic hydrographs were routed through the reservoir. Different reservoir volumes and spillway lengths were considered. Hydrographs with the same risk were represented by a curve in the peak-volume space. These curves were compared to those linked to the probability of occurrence of a flood event, in order to improve the estimation of the Design Flood Hydrograph.

scholarly journals ANALISIS BANJIR DAN TINGGI MUKA AIR PADA RUAS SUNGAI CILIWUNG STA 7+646 s/d STA 15+049

2018 ◽  
Vol 7 (1) ◽  
pp. 43-49
Author(s):  
Redaksi Tim Jurnal
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Synthetic Data ◽  
Gumbel Distribution ◽  
Peak Discharge ◽  
Design Flood ◽  
Distribution Method ◽  
Flood Peak ◽  
Method Of Calculation ◽  
Flood Discharge

The problem of flooding in DKI Jakarta is considered normal because almost every year can hit the city of Jakarta especially during the rainy season. In DKI Jakarta itself there are several rivers, one of which is Ciliwung River which is the most influential river in DKI Jakarta which often cause flood every year. The purpose of this research is to know the location of flood / river flood that occurs in the segments along Ciliwung River STA 7 + 646 s / d STA 15 + 049. Data processing begins with the calculation of average rainfall, frequency analysis, and then hour-time rain distribution. Method of calculation of flood discharge using the synthetic unit of Nakayasu and Gama I synthetic data. Rainfall data using 2 observation stations for 3 years rain (2014-2016). In the frequency analysis used Gumbel distribution berdasrkan test results suitability data Smirnov- Kolmogorov and Chi-Square. The result of flood peak discharge design with HSS Nakayasu on return period Q5 = 687,80 m3 / dt, Q10 = 743,21 m3 / dt, Q20 = 796,36 m3 / s, Q50 = 865,15 m3 / dt, Q100 = 916,71 m3 / s, while flood peak discharge design with HSS Gama I on return period Q5 = 347,03 m3 / s, Q10 = 372,12 m3 / s, Q20 = 396,20 m3 / s, Q50 = 427, 36 m3 / s, Q100 = 450,71 m3 / s. The design flood discharge value approaching the measured debit value is HSS Nakayasu. Steps continued using HEC-RAS 4.1.0 software to determine the capacity of river catchment by using Nakayasu discharge. After analyzing using the software, most stationing of the Ciliwung River at STA 7 + 646 to STA 15 + 049 can not accommodate the planned discharge during the 20th anniversary period, hence the need for river improvements in the form of river normalization and elevation of dikes.

Probabilistic nature of storage delay parameter of the hydrologic model RORB: a case study for the Cooper's Creek catchment in Australia

2014 ◽  
Vol 46 (3) ◽  
pp. 400-410 ◽  
Author(s):  
Hitesh Patel ◽  
Ataur Rahman
Keyword(s):  
Hydrologic Model ◽  
Exceedance Probability ◽  
Design Flood ◽  
Flood Peak ◽  
Monte Carlo Simulation Technique ◽  
South Wales ◽  
Accurate Design ◽  
High Degree ◽  
Probabilistic Nature

In rainfall–runoff modeling, Design Event Approach is widely adopted in practice, which assumes that the rainfall depth of a given annual exceedance probability (AEP), can be converted to a flood peak of the same AEP by assuming a representative fixed value for the other model inputs/parameters such as temporal pattern, losses and storage-delay parameter of the runoff routing model. This paper presents a case study which applies Monte Carlo simulation technique (MCST) to assess the probabilistic nature of the storage delay parameter (kc) of the RORB model for the Cooper's Creek catchment in New South Wales, Australia. It has been found that the values of kc exhibit a high degree of variability, and different sets of plausible values of kc result in quite different flood peak estimates. It has been shown that a stochastic kc in the MCST provides more accurate design flood estimates than a fixed representative value of kc. The method presented in this study can be adapted to other catchments/countries to derive more accurate design flood estimates, in particular for important flood study projects, which require a sensitivity analysis to investigate the impacts of parameter uncertainty on design flood estimates.

scholarly journals On the asymptotic behavior of flood peak distributions

2006 ◽  
Vol 10 (2) ◽  
pp. 233-243 ◽  
Author(s):  
E. Gaume
Keyword(s):  
Frequency Distribution ◽  
Return Period ◽  
Asymptotic Properties ◽  
Flood Frequency ◽  
Point Of View ◽  
Rainfall Runoff ◽  
New Approach ◽  
Flood Peak ◽  
Flood Quantiles ◽  
The Impact

Abstract. This paper presents some analytical results and numerical illustrations on the asymptotic properties of flood peak distributions obtained through derived flood frequency approaches. It confirms and extends the results of previous works: i.e. the shape of the flood peak distributions are asymptotically controlled by the rainfall statistical properties, given limited and reasonable assumptions concerning the rainfall-runoff process. This result is partial so far: the impact of the rainfall spatial heterogeneity has not been studied for instance. From a practical point of view, it provides a general framework for analysis of the outcomes of previous works based on derived flood frequency approaches and leads to some proposals for the estimation of very large return-period flood quantiles. This paper, focussed on asymptotic distribution properties, does not propose any new approach for the extrapolation of flood frequency distribution to estimate intermediate return period flood quantiles. Nevertheless, the large distance between frequent flood peak values and the asymptotic values as well as the simulations conducted in this paper help quantifying the ill condition of the problem of flood frequency distribution extrapolation: it illustrates how large the range of possibilities for the shapes of flood peak distributions is.

scholarly journals The Simulation Of Return Period Design Flood At KG2 Setail Storage Planning In Yosomulyo Village Gambiran Sub District Banyuwangi

2020 ◽  
Vol 1 (1) ◽  
pp. 30-42
Author(s):  
Yuda Pratama Gumelar ◽  
Zulis Erwanto ◽  
Andi Wijanarko
Keyword(s):  
Cross Section ◽  
Return Period ◽  
Design Flood ◽  
Analysis System

Berdasarkan Peraturan Daerah Kabupaten Banyuwangi Nomor 08 Tahun 2012 Tentang Rencana Tata Ruang Wilayah Kabupaten Banyuwangi Tahun 2012 terkait pengembangan waduk dan embung. Untuk memenuhi kebutuhan air irigasi di Desa Yosomulyo diperlukan pembangunan embung Setail KG2. Tujuan penelitian adalah untuk mengetahui hasil simulasi debit banjir rancangan kala ulang pada perencanaan Embung Setail KG2 menggunakan bantuan program HEC-RAS. Untuk perhitungan debit banjir kala ulang menggunakan metode Rasional. Untuk simulasi banjir rancangan dengan menggunakan bantuan program HEC-RAS (Hidrology Engineering Center – River Analysis System) dengan memasukkan cross section embung. Dari hasil simulasi banjir dengan bantuan program HEC-RAS pada perencanaan Embung Setail KG2 dengan debit rancangan kala ulang 1 tahun sebesar 41,21 m3/det, kala ulang 2 tahun sebesar 90,30 m3/det, kala ulang 5 tahun sebesar 112,78 m3/det, kala ulang 10 tahun sebesar 125, 16 m3/det, kala ulang 20 tahun sebesar 136,29 m3/det dan kala ulang 25 tahun sebesar 138,63 m3/det, tidak ada air yang meluap pada desain penampang sehingga perencanaan Embung Setail KG2 dapat disimpulkan mampu menampung debit banjir hingga kala ulang 25 tahunan sesuai dengan perencanaan awal dengan volume kapasitas embung 384,37x103 m3.

scholarly journals Analyses of flood peak discharge in Cimadur river basin, Banten Province, Indonesia

2021 ◽  
Vol 331 ◽  
pp. 08006
Author(s):  
Arniza Fitri ◽  
Muhammad Shubhi Nurul Hadie ◽  
Adelia Agustina ◽  
Dian Pratiwi ◽  
Susarman ◽  
...  
Keyword(s):  
River Basin ◽  
Return Period ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Distribution ◽  
Flood Peak ◽  
Type Iii ◽  
Pearson Type ◽  
Catchment Areas ◽  
Peak Discharges

Cimadur river basin is one of the most important catchment areas in Lebak District, Banten Province. For the past few years, the catchment has experienced floods during the rainy season. The big issue of flooding has been recorded recently in December 2019 which has caused damage and negative impacts to the local people and surrounding community. This study aims to analyze the possibility of flood peak discharges in the catchment area of the Cimadur river. The flood discharges are calculated for 2, 5, 10, 25, 50, and 100 years return period based on the daily rainfall data from the year 2011 to 2020. The rainfall and land use data are obtained from PT Saeba Consultant. In this study, the hydrological analyses are including 1) analyses of average annual rainfall using the Thiessen method; 2) analyses of rainfall distribution and estimation of design rainfall by considering three methods involving: Log-Normal, Log Pearson Type III, and Gumbel Type 1; and 3) analyses of flood discharges by adopting Nakayasu Synthetic Hydrograph Unit (SHU). The rainfall distribution analyses show that the Log Pearson Type III provided the best fit. Based on the flood peak discharges analyses, the results show that the flood discharges for the 5, 10, 25, and 50 years return period in the Cimadur river basin are 470.71 m3/s, 560.16 m3/s, 698 m3/s, and 820.4 m3/s, respectively.

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.

scholarly journals Assessment of Flood Extremes Using Downscaled CMIP5 High-Resolution Ensemble Projections of Near-Term Climate for the Upper Thu Bon Catchment in Vietnam

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 634 ◽  
Author(s):  
Do Nam ◽  
Tran Hoa ◽  
Phan Duong ◽  
Duong Thuan ◽  
Dang Mai
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Coupled Model ◽  
Daily Rainfall ◽  
Flood Peak ◽  
Basin Scale ◽  
The Future ◽  
Near Term ◽  
Baseline Climate ◽  
Ensemble Projections

Exploring potential floods is both essential and critical to making informed decisions for adaptation options at a river basin scale. The present study investigates changes in flood extremes in the future using downscaled CMIP5 (Coupled Model Intercomparison Project—Phase 5) high-resolution ensemble projections of near-term climate for the Upper Thu Bon catchment in Vietnam. Model bias correction techniques are utilized to improve the daily rainfall simulated by the multi-model climate experiments. The corrected rainfall is then used to drive a calibrated supper-tank model for runoff simulations. The flood extremes are analyzed based on the Gumbel extreme value distribution and simulation of design hydrograph methods. Results show that the former method indicates almost no changes in the flood extremes in the future compared to the baseline climate. However, the later method explores increases (approximately 20%) in the peaks of very extreme events in the future climate, especially, the flood peak of a 50-year return period tends to exceed the flood peak of a 100-year return period of the baseline climate. Meanwhile, the peaks of shorter return period floods (e.g., 10-year) are projected with a very slight change. Model physical parameterization schemes and spatial resolution seem to cause larger uncertainties; while different model runs show less sensitivity to the future projections.

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