Search

This study focuses on how the representation of daily precipitation probability distributions may affect the application of equidistant quantile matching (EDCDFm). Five representations, that is, two parametric distributions and three nonparametric approaches, are selected. The parametric distributions include Gamma and Weibull while the nonparametric approaches include empirical cumulative distribution function (ECDF) and kernel density estimation method (KDE) as well as an improved KDE named diffusion‐based kernel density estimation (DKDE). All five methods were applied to correct the daily precipitation of 11 stations over the Daqing River Basin, North China in 1981–2015. The results demonstrated that DKDE is closer to ECDF than the other three methods in the goodness‐of‐fit evaluation. Furthermore, nonparametric methods present advantages over parametric methods; especially, DKDE and ECDF are skilful equally and both of them display impressive comprehensive performance than other methods by multi‐index. These findings suggest that representing the precipitation probability distributions accurately is beneficial for the bias correction and selecting one or more suitable indexes is of great significance to the verification of EDCDFm. This study can provide guidance for future water resources management of the Daqing River Basin. [ABSTRACT FROM AUTHOR]

Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-stage bias correction to daily precipitation and max/min temperature data in the Daqing River Basin (DQRB) with the HadGEM3-RA climate model. Validated from 1981 to 2015, future scenarios under two emission paths covering 2031–2065 and 2066–2100 were projected to assess variations in both the amount and unevenness of precipitation. The results suggested that, overall, the two-stage bias correction could reproduce the marginal distributions of variables and the evolution process of the dependence structure. In the future, the amount of precipitation in the plains is expected to increase more than that in the mountains, while precipitation unevenness, as measured by relative entropy, shows a slight increase in the mountains and a decrease in the plains, with enhanced seasonality. Conditioned on rising temperatures, high-/low-intensity precipitation tends to intensify/weaken precipitation unevenness. Additionally, the potential application of the bias correction method used herein and the possible impacts of uneven precipitation on nonpoint source pollution are given for further analyses. This study can provide useful information for future nonpoint source pollution simulations in the DQRB. [ABSTRACT FROM AUTHOR]

• A model was proposed for flood event-related risk assessment. • Timely insight was given into the risks related to water transfer in flood season. • The security domains for flood risk and ecological risk were determined. • Flood duration played a more significant role in risks under water diversion. • Adding risk indicators in the joint probability distribution improved the accuracy. Understanding flood event-related risk in an interconnected river–lake system (IRLS) is a prerequisite for developing water resource management strategies and enhancing disaster resilience. Previous flood event-related risk assessments either hardly consider the context in which water diversion encounters flood events or hardly consider the physical process, stochastic analysis and multivariate interactions of flood event characteristics simultaneously, thereby resulting in a less reliable assessment of flood event-related risk. To resolve this limitation, a copula-coupled hydrodynamic risk assessment model (CHRAM) is proposed to characterize the physical, multivariate, and stochastic nature of risk, improving the accuracy of risk assessment. In this study, CHRAM is capable of accurately quantifying flood event-related risks (i.e., flood risk and ecological risk) of the Nansi Lake Basin in the flood season under the operation of the eastern route of the South-to-North Water Diversion Project in China. Our findings revealed that the total flood volume (R sum) and duration (T d) of flood events were significantly sensitive characteristic indexes for flood risk and ecological risk. In addition, the security domains of flood risk (R sum < 35 mm and T d < 23 d) and ecological risk (R sum < 50 mm and T d < 27 d) were determined based on the analysis of the relationship between sensitive characteristic indexes and risk indicators. The results also showed that the impact of T d on flood risk, ecological risk and flood-ecological combined risk was 3–14 times greater than the impact of R sum. The occurrence probability of flood-ecological combined risk was smaller than that of flood risk but greater than that of ecological risk, with the corresponding maximum risk probabilities of 11.2%, 36.5%, and 4.7%, respectively. This study extends the current knowledge about risk assessment in IRLS and is beneficial to instruct the management of projects for similar systems. [ABSTRACT FROM AUTHOR]

• Vegetation patches enhanced the spatial heterogeneity of pressure at the sediment–water interface. • The spatial–temporal characteristics of hyporheic exchange were associated with the scales of vegetation patch (group), with distinct ecological values. • The streamwise distance of the patches controlled the size of the hyporheic zone. • A prediction model of hyporheic exchange flux was developed. The vegetated region is known as the "hot zone" for the exchange of substances in river systems, which causes an uneven pressure distribution at the sediment–water interface (SWI) and then forms hyporheic exchange (HE). However, as a common form of plant survival, the impact of vegetation patches on HE has received little research attention. In this study, laboratory experiment and numerical simulations were conducted to explore the effects of solid volume fraction within the patch (φ), the overlying water average velocity (U), and the streamwise distance of the patches (S x) on HE. The results showed that the pressure along the SWI caused the spatial–temporal characteristics of HE at the vegetation patch (VP) scale and vegetation patch group (VG) scale. At the VP scale, the HE depth was influenced by φ , U , and S x in increasing order, and increased with the increase in these values within a certain range. At the VG scale, the HE depth was positively correlated with φ and U and negatively correlated with S x , and the spatial characteristics of HE were larger at this scale than at the VP scale. The HE flux was linearly related to φ and power functionally related to U. There was an asymptotic behavior of the effect of S x on the HE flux, which means that the rate of change of the HE flux progressively decreases with S x. The HE volume was influenced by S x , φ, and U in increasing order and was positively correlated with all of these parameters. Based on the flow blockage parameter, Reynolds number (Re), and S x , a prediction model of HE flux was developed. The results of this study provided further understanding of the role of vegetation patches in driving the HE process and may serve as a reference for vegetated river benthic habitat restoration. [ABSTRACT FROM AUTHOR]