scholarly journals Nonstationary Design Flood Estimation in Response to Climate Change, Population Growth and Cascade Reservoir Regulation

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2687
Author(s):  
Yuzuo Xie ◽  
Shenglian Guo ◽  
Lihua Xiong ◽  
Jing Tian ◽  
Feng Xiong
Keyword(s):  
Climate Change ◽  
Population Growth ◽  
Change Point Detection ◽  
Flood Frequency Analysis ◽  
Data Series ◽  
Flood Events ◽  
Design Flood ◽  
Cascade Reservoirs ◽  
Han River ◽  
Flood Estimation

The hydrologic data series are nonstationary due to climate change and local anthropogenic activities. The existing nonstationary design flood estimation methods usually focus on the statistical nonstationarity of the flow data series in the catchment, which neglect the hydraulic approach, such as reservoir flood regulation. In this paper, a novel approach to comprehensively consider the driving factors of non-stationarities in design flood estimation is proposed, which involves three main steps: (1) implementation of the candidate predictors with trend tests and change point detection for preliminary analysis; (2) application of the nonstationary flood frequency analysis with the principle of Equivalent Reliability (ER) for design flood volumes; (3) development of a nonstationary most likely regional composition (NS-MLRC) method, and the estimation of a design flood hydrograph at downstream cascade reservoirs. The proposed framework is applied to the cascade reservoirs in the Han River, China. The results imply that: (1) the NS-MLRC method provides a much better explanation for the nonstationary spatial correlation of the flood events in Han River basin, and the multiple nonstationary driving forces can be precisely quantified by the proposed design flood estimation framework; (2) the impacts of climate change and population growth are long-lasting processes with significant risk of flood events compared with stationary distribution conditions; and (3) the swift effects of cascade reservoirs are reflected in design flood hydrographs with lower peaks and lesser volumes. This study can provide a more integrated template for downstream flood risk management under the impact of climate change and human activities.

Revisiting design flood estimation of Nam River Dam basin considering climate change

2016 ◽  
Vol 49 (8) ◽  
pp. 719-729
Author(s):  
Hyunseung Lee ◽  
Taesam Lee ◽  
Taewoong Park ◽  
Chanyoung Son
Keyword(s):  
Climate Change ◽  
Design Flood ◽  
Flood Estimation

scholarly journals Nonstationary Flood Hazard Analysis in Response to Climate Change and Population Growth

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1811 ◽  
Author(s):  
Lei Yan ◽  
Lingqi Li ◽  
Pengtao Yan ◽  
Hongmou He ◽  
Jing Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Population Growth ◽  
Physical Meaning ◽  
Flood Hazard ◽  
Hazard Analysis ◽  
Explanatory Power ◽  
Design Flood ◽  
Statistical Parameters ◽  
Xijiang River ◽  
Design Life

The predictions of flood hazard over the design life of a hydrological project are of great importance for hydrological engineering design under the changing environment. The concept of a nonstationary flood hazard has been formulated by extending the geometric distribution to account for time-varying exceedance probabilities over the design life of a project. However, to our knowledge, only time covariate is used to estimate the nonstationary flood hazard over the lifespan of a project, which lacks physical meaning and may lead to unreasonable results. In this study, we aim to strengthen the physical meaning of nonstationary flood hazard analysis by investigating the impacts of climate change and population growth. For this purpose, two physical covariates, i.e., rainfall and population, are introduced to improve the characterization of nonstationary frequency over a given design lifespan. The annual maximum flood series of Xijiang River (increasing trend) and Weihe River (decreasing trend) are chosen as illustrations, respectively. The results indicated that: (1) the explanatory power of population and rainfall is better than time covariate in the study areas; (2) the nonstationary models with physical covariates possess more appropriate statistical parameters and thus are able to provide more reasonable estimates of a nonstationary flood hazard; and (3) the confidences intervals of nonstationary design flood can be greatly reduced by employing physical covariates. Therefore, nonstationary flood design and hazard analysis with physical covariates are recommended in changing environments.

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 A general framework of design flood estimation for cascade reservoirs in operation period

2019 ◽  
Vol 577 ◽  
pp. 124003 ◽  
Author(s):  
Feng Xiong ◽  
Shenglian Guo ◽  
Pan Liu ◽  
C.-Y. Xu ◽  
Yixuan Zhong ◽  
...  
Keyword(s):  
General Framework ◽  
Design Flood ◽  
Cascade Reservoirs ◽  
Operation Period ◽  
Flood Estimation

scholarly journals The Effect of Involving Exceptional Outlier Data on Design Flood Magnitude

2015 ◽  
Vol 10 (2) ◽  
pp. 698-706
Author(s):  
Bagher Heidarpour ◽  
Bahram Saghafian ◽  
Saeed Golian
Keyword(s):  
Return Period ◽  
Rare Events ◽  
Flood Frequency ◽  
The Other ◽  
Flood Frequency Analysis ◽  
Data Series ◽  
Design Flood ◽  
Type Iii ◽  
Pearson Type ◽  
Outlier Data

The term "outlier" is generally used to refer to single data points that appear to depart significantly from the trend of the other data. Outliers are classified into three types: incorrect observations, rare events resulting from essentially the same phenomena as the other maxima, and rare events resulting from a different phenomenon. Flood frequency analysis was first performed on complete data series (including the outlier) and then on the series with the outlier removed. Results revealed that omission of the outlier data didn’t affect the probability distribution function (Log-Pearson type III), but the design discharge reduced by 60 percent in 10000 year return period from 3320 (m3/s) to 1340 (m3/s). Furthermore, the method proposed by the U.S. Water Resources Council (WRC), and the HEC-SSP software were applied in order to compose outlier data with other systematic data and to modify the parameters of the statistical distribution. Using WRC method, the estimated 10000-year flood was equaled to 1907 (m3/s) by designating the outlier as the 200-year return period and revising the parameters of Log-Pearson type III distribution; that is about 43 percent decrease over the scenario involving the outlier.

scholarly journals Incorporating climate change in flood estimation guidance

2021 ◽  
Vol 379 (2195) ◽  
pp. 20190548 ◽  
Author(s):  
Conrad Wasko ◽  
Seth Westra ◽  
Rory Nathan ◽  
Harriet G. Orr ◽  
Gabriele Villarini ◽  
...  
Keyword(s):  
Climate Change ◽  
Flash Flood ◽  
Flood Hazard ◽  
Research Effort ◽  
Estimation Methods ◽  
Future Research ◽  
Significant Progress ◽  
Design Flood ◽  
Deep Uncertainty ◽  
Flood Estimation

Research into potential implications of climate change on flood hazard has made significant progress over the past decade, yet efforts to translate this research into practical guidance for flood estimation remain in their infancy. In this commentary, we address the question: how best can practical flood guidance be modified to incorporate the additional uncertainty due to climate change? We begin by summarizing the physical causes of changes in flooding and then discuss common methods of design flood estimation in the context of uncertainty. We find that although climate science operates across aleatory, epistemic and deep uncertainty, engineering practitioners generally only address aleatory uncertainty associated with natural variability through standards-based approaches. A review of existing literature and flood guidance reveals that although research efforts in hydrology do not always reflect the methods used in flood estimation, significant progress has been made with many jurisdictions around the world now incorporating climate change in their flood guidance. We conclude that the deep uncertainty that climate change brings signals a need to shift towards more flexible design and planning approaches, and future research effort should focus on providing information that supports the range of flood estimation methods used in practice. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks'.

scholarly journals Swimming against the tide: resilience of a riverine turtle to recurrent extreme environmental events

2014 ◽  
Vol 10 (3) ◽  
pp. 20130782 ◽  
Author(s):  
Abigail M. Jergenson ◽  
David A. W. Miller ◽  
Lorin A. Neuman-Lee ◽  
Daniel A. Warner ◽  
Fredric J. Janzen
Keyword(s):  
Climate Change ◽  
Population Growth ◽  
Growth Rates ◽  
Chrysemys Picta ◽  
Population Parameters ◽  
Flood Events ◽  
Population Growth Rates ◽  
Painted Turtles ◽  
Annual Population ◽  
Environmental Events

Extreme environmental events (EEEs) are likely to exert deleterious effects on populations. From 1996 to 2012 we studied the nesting dynamics of a riverine population of painted turtles ( Chrysemys picta ) that experienced seven years with significantly definable spring floods. We used capture–mark–recapture methods to estimate the relationships between more than 5 m and more than 6 m flood events and population parameters. Contrary to expectations, flooding was not associated with annual differences in survival, recruitment or annual population growth rates of the adult female segment of the population. These findings suggest that female C. picta exhibit resiliency to key EEE, which are expected to increase in frequency under climate change.

Sign in / Sign up

Export Citation Format

Share Document