Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas
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Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas Yang Peng 1
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& Xianliang Yu & Hongxiang Yan & Jipeng Zhang
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Received: 24 November 2019 / Accepted: 18 August 2020 / Published online: 25 August 2020 # Springer Nature B.V. 2020
Abstract
An estimation of daily suspended sediment concentration (SSC) is required for water resource and environmental management. The traditional methods for simulating daily SSC focus on modeling the SSCs themselves, whereas the cross-correlation structure between SSC and streamflow has received only minor attention. To address this issue, we propose a stochastic method to generate long-term daily SSC using multivariate copula functions that account for temporal and cross dependences in daily SSCs. We use the conditional copula method to construct daily multivariate distributions to alleviate the complications and workload of parameter estimations using high-dimensional copulas. The observed daily streamflow and SSC data are normalized using the normal quantile transform method to relax the computationally intensive model of building daily marginal distributions. Daily SSCs can thus be simulated through the multivariate conditional distribution using previous daily SSC and concurrent daily streamflow values. The proposed method is rigorously examined by application to a case study at the Pingshan station in the Jinsha River Basin, China, and compared with the bivariate copula method. The results show that the proposed method has a high degree of accuracy, in preserving the statistics and temporal correlation of daily SSC observations, and better preserves the lag-0 cross correlation compared with the bivariate copula method. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resource and environmental management, which play a critical role in accurately estimating the frequency and magnitude of extreme SSC events. Keywords Daily suspended sediment concentration . Stochastic simulation . Multivariate copulas . Joint distribution . Temporal correlation . Cross correlation
* Yang Peng [email protected] Extended author information available on the last page of the article
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Peng Y. et al.
1 Introduction Suspended sediments in rivers play an important role in water resource and environmental management because they are responsible for the transport of nutrients and contaminants (Ryan 1991; Cigizoglu 2004), reservoir sedimentation, channel and harbor silting, and soil erosion and loss (Yang 1996; Jansson 2002; Pelletier 2012). Suspended sediment concentration (SSC) is a key variable for water quality and sediment transport. The need for SSC simulations has received increasing attention in recent years because daily SSC data are required for the design and operation of water resource facilities (e.g., reservoirs, dams, stable channels, assessment of water quality and water resource management, estimation of sediment yield and erosion rates) (Cigizoglu 2004; Kisi 20
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