Estimating the design flood under the influence of check dams by removing nonstationarity from the flood peak discharge series

Abstract

The construction of check dams in northwestern China has resulted in nonstationary changes in flood peak discharge series; the stationary assumption of the conventional hydrological frequency analysis is no longer satisfied. According to the characteristics of the construction and operation of check dams, the nonstationarity of flood peak discharge series are largely induced by changes in the effective runoff generation area (i.e., the basin area minus the area controlled by check dams). Knowing the power function relationship between the flood peak discharge and the basin area, we can remove the influence of the effective runoff generation area and convert the original nonstationary series into a stationary series. This de-nonstationarity method can achieve stationarity in the first and second moments simultaneously. Therefore, we can calculate the design value of the reconstructed series using the conventional frequency analysis method. According to the effective runoff generation area under design conditions, we can then obtain the corresponding design flood of the original series. We applied this method to the Mahuyu River basin to obtain the design flood under nonstationarity. Due to the consideration of the deterministic influence of check dams during the de-nonstationarity process, the uncertainty analyzed by the bootstrap method is obviously small.

Attribution of nonstationary changes in the annual runoff of the Weihe River using the de-nonstationarity method

“…The de-nonstationarity method is proposed by Li et al (2020) for the nonstationary frequency analysis. This method can achieve the transformation from an original nonstationary series to a new stationary reconstructed series by removing the nonstationary influence of the driving factors.…”

“…The influence law of a driving factor of the research variable can be defined as f i (X i ). In the study of Li et al (2020), the research variable is the flood peak discharge, the influence factor X i is the effective runoff generation area; the influence law f i (•) is a power law function.…”

“…While the simulation-based attribution method attempts to model the hydrological process from the perspective of physical mechanism, the reliability of the model itself is the biggest constraint of this attribution method because our understanding of these mechanisms is incomplete. In this study, a de-nonstationarity method proposed by Li et al (2020) was used for the attribution analysis. By identifying the main influencing factors and the relationship between these factors and the hydrological variable, this method can remove the nonstationary influences of these factors, so as to obtain a new stationary de-nonstationarity series.…”

“…The new stationary series can be used as sample series for hydrological frequency analysis or any other cases where a stationary series is required. Li et al (2020) used this method to remove the nonstationary influence of check dam projects on the flood peak discharge in Mahuyu River Basin in northern Shaanxi, China, and obtained more reasonable design values under nonstationary conditions. Furthermore, by using the de-nonstationarity method, Li & Qin (2022) have analyzed the annual runoff series of the Jialu River Basin in Shaanxi Province, China, and the calculated design annual runoff was more consistent with the measured data.…”

Probabilistic interval estimation of design floods under non-stationary conditions by an integrated approach

“…Numerous lessons have been learnt about the failure of hydraulic structures related to changing environments or changing characteristics of annual maximum streamflow series (Hui et al 2018;Ragno et al 2019). The flood frequency analysis results have been widely applied in the planning and design of a dam/reservoir and other civil engineering applications (Li et al 2020). Conventional flood frequency analysis methods are based on the assumption of temporal stationarity that the return period (or occurrence probability) of extreme floods will not alter significantly with time.…”