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

Abstract

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.

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

“…The multiple covariates (i.e., explanatory variables, predictors or addictive terms) indicating both population growth and climate change are incorporated to explain the variation in nonstationary time series. The impact of urbanization and water consumption on the hydrologic flood series is considered by the population (Pop) [37,43], while the annual total precipitation (Prcp), one of the important hydro-climate factors, is applied to quantify the effects of climate change [10,44].…”

“…López and Francés [9] used climate and reservoir indices as external covariates in nonstationary flood frequency analysis. Yan et al [10] considered climate change and population growth to explain the nonstationary properties of hydrological time series. Global warming, the primary factor that drives climate change, has altered the meteorological regimes in some regions [11,12].…”

Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

“…In other words, the local extreme precipitation events could increase or decrease due to increased aridity. To cope with this challenge, the nonstationary (NS) assumption has been proposed in hydrology and climate‐related literature (Hu et al, 2018; Kuang et al, 2018; Lu et al, 2019; Villarini, Serinaldi, Smith, & Krajewski, 2009; Vogel, Yaindl, & Walter, 2011; Xiong et al, 2019; Xiong et al, 2020; Xu, Jiang, Yan, Li, & Liu, 2018; Yan et al, 2019; Yan et al, 2020; Yan, Xiong, Liu, Hu, & Xu, 2017; Yang, Xiong, Xiong, Zhang, & Xu, 2020).…”

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

“…Flooding is one of the major natural disasters and has caused casualties and huge economic losses worldwide in the 21st century (Hallegatte et al 2013;Arnell & Gosling 2016;Kan et al 2016;Slater & Villarini 2016;Kuang et al 2018;Yin et al 2018;Zhang et al 2018;Yan et al 2019a;Hou et al 2020;Li et al 2020;Venvik et al 2020). In the hydrological communities, flood frequency analysis (FFA) is the most widely used approach to characterize flood risk and estimate design values for hydrological structures.…”

“…To address the problem of design flood estimation in NFFA, researchers have carried out many studies and developed several design flood methods in recent years (Olsen et al 1998;Parey et al 2007Parey et al , 2010Cooley 2013;Rootzén & Katz 2013;Acero et al 2017Acero et al , 2018Hu et al 2018;Wang et al 2019;Byun & Hamlet 2020;Lu et al 2020;Yan et al 2020). Yan et al (2019a) comprehensively compared different methods and recommended the use of average design life level (ADLL) and equivalent reliability (Hu et al 2018). Byun & Hamlet (2020) developed an NS Monte Carlo method to address NS design problems by explicitly accounting for the projected changes of extreme hydrometeorological events.…”