Frequency Analysis of the Nonstationary Annual Runoff Series Using the Mechanism-Based Reconstruction Method

Abstract

Due to climate change and human activities, the statistical characteristics of annual runoff series of many rivers around the world exhibit complex nonstationary changes, which seriously impact the frequency analysis of annual runoff and are thus becoming a hotspot of research. A variety of nonstationary frequency analysis methods has been proposed by many scholars, but their reliability and accuracy in practical application are still controversial. The recently proposed Mechanism-based Reconstruction (Me-RS) method is a method to deal with nonstationary changes in hydrological series, which solves the frequency analysis problem of the nonstationary hydrological series by transforming nonstationary series into stationary Me-RS series. Based on the Me-RS method, a calculation method of design annual runoff under the nonstationary conditions is proposed in this paper and applied to the Jialu River Basin (JRB) in northern Shaanxi, China. From the aspects of rationality and uncertainty, the calculated design value of annual runoff is analyzed and evaluated. Then, compared with the design values calculated by traditional frequency analysis method regardless of whether the sample series is stationary, the correctness of the Me-RS theory and its application reliability is demonstrated. The results show that calculation of design annual runoff based on the Me-RS method is not only scientific in theory, but also the obtained design values are relatively consistent with the characteristics of the river basin, and the uncertainty is obviously smaller. Therefore, the Me-RS provides an effective tool for annual runoff frequency analysis under nonstationary conditions.

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

“…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.…”

“…The better the stationarity, the less the uncertainty. In addition, Li et al (2021) and Li & Qin (2022) used this method to conduct the frequency analysis on the annual runoff series of WRB and the Jialu River Basin in northern Shaanxi, China. The design values were also consistent with the measured data, such as the 50%-frequency design annual runoff is close to the average annual runoff, which also proves that the de-nonstationarity method has a certain reliability.…”

The Use of GAMLSS Framework for a Non-Stationary Frequency Analysis of Annual Runoff Data over a Mediterranean Area

“…Generally, however, in a changing environment, combinations of multiple factors, such as precipitation, temperature, evapotranspiration and, for example, reservoir construction, can lead to variations in flow regimes by altering flow characteristics, i.e., the seasonality of runoff and the frequency and magnitude of floods [5]. In fact, stream runoff has shown significant changes globally due to the impact of climate change, mainly because of anthropogenic effects on climate and basin characteristics [6][7][8]. For this reason, methods that account for non-stationarity have been developed in order to replace long-established characteristic principles of estimation of distribution parameters and, consequently, water resource management and to shift to an evolutionary paradigm.…”

“…The current literature on frequency analysis of non-stationary hydrological variables focuses mainly on two issues: (i) the development of the non-stationary method and (ii) the exploration of covariates that reflect changes in hydrological variables. Many studies [7,25,26] have presented the time-varying moment method, which assumes that the hydrological variable of interest follows a certain type of probability distribution, whose moments change over time [27].…”

Nonstationary Annual Maximum Flood Frequency Analysis Using a Conceptual Hydrologic Model with Time-Varying Parameters

“…Design flood value associated with a specific return period (e.g., 100-year that is most commonly used in relevant studies) is traditionally estimated based on flood frequency analysis through statistical approaches [6]. Recently, with the concept that stationarity is dead [4], various methodologies using a probabilistic model of flood frequency considering nonstationarity have been introduced [7][8][9][10][11][12][13][14][15]. Khaliq et al [16] provide a comprehensive review of these approaches, including the incorporation of trends in distribution parameters, trends in statistical moments, etc.…”