An estuarine turbidity maximum (ETM) results from various subtidal sediment transport mechanisms related to, e.g., river, tides, and density gradients, which have been extensively analysed in single-channel estuaries. However, ETMs have also been found in estuaries composed of multiple interconnected tidal channels, where the water and suspended fine sediments are exchanged at the junctions with possible occurrence of sediment overspill. The overall aim of this study is to understand the processes that determine the ETM dynamics in such channel networks. Specifically, focusing on the ETMs formation due to sediment transport by river flow and density-driven flow, the dependence of ETM locations in an idealised three-channel network on fluvial sediment input and the local deepening and narrowing of a seaward channel is investigated. It is found that the ETM dynamics in channels of a network is coupled, and hence, changes in one channel affect the ETM pattern in all channels. Sensitivity results show that, keeping river discharge fixed, a larger fluvial sediment input leads to the upstream shift of ETMs and an increase in the overall sediment concentration. Both deepening or narrowing of a seaward channel may influence the ETMs in the entire network. Furthermore, the effect of either deepening or narrowing of a seaward channel on the ETM locations in the network depends on the system geometry and the dominant hydrodynamic conditions. Therefore, the response of the ETM location to local geometric changes is explained by analysing the dominant sediment transport mechanisms. In addition to the convergence of sediment transport mechanisms in single-estuarine channels, ETM dynamics in networks is found to be strongly affected by net exchange of sediment between the branches of a network. We find that considering the sensitivity of net sediment transport to geometric changes is needed to understand the changing ETM dynamics observed in a real estuarine network.

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Net water transport (NWT) in estuaries is important for, for example, salt intrusion and sediment dynamics. While NWT is only determined by river runoff in single channels, in estuarine networks, it results from a complex interplay between tides and residual flows. This study aims to disentangle the various contributions of these physical drivers to NWT in estuarine networks and investigate the sensitivities of NWT to variable forcing conditions, interventions, and sea level rise (SLR). To this end, a processes-based perturbative network model is developed, which accounts for the vertical flow structure to resolve density-driven flow driven by a vertically uniform along-channel salinity gradient. Other identified drivers are river discharge and three tidal rectification processes: Stokes transport and its return flow, momentum advection, and velocity-depth asymmetry. The model is applied to the Yangtze Estuary. NWT due to tidal rectifications and density-driven flow can be comparable to river discharge. Specifically in the North Branch, the direction of NWT may differ from the direction of river discharge. Varying river discharge mainly affects NWT as tide-river interaction is weak and density-driven flow is shown to be insensitive to salt intrusion. Conversely, variations in tidal amplitude strongly affect NWT related to tidal rectification and density-driven flow. The deepening (narrowing) of one channel (Deep Waterway Project), affected the NWT mostly through the density-driven flow (advection). Furthermore, NWT distribution in the Yangtze is insensitive to SLR up to 2 m because the effects of SLR on transport due to different drivers compensate each other.

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The rate reduction models have been widely used to model the recurrent failure data for their capabilities in quantifying the repair effects. Despite the widespread popularity, there have been limited studies on statistical inference of most failure rate reduction models. In view of this fact, this study proposes a semiparametric estimation framework for a general class of such models, called extended geometric failure rate reduction (EGFRR) models. Covariates are considered in our analysis and their effects are modeled as a log-linear factor on the baseline failure rate. Unlike the existing inference methods for the EGFRR models that assume the failure data are censored at a fixed number of failures, our study considers covariates and time-censoring, which are more common in practice. The semiparametric maximum likelihood (ML) estimators are obtained by carefully constructing the likelihood function. Asymptotic properties including consistency and weak convergence of the ML estimators are established by using the properties of the martingale process. In addition, we show that the semiparametric estimators are asymptotically efficient. A real example from the automobile industry illustrates the usefulness of the proposed framework and extensive simulations show its outstanding performance when comparing with the existing methods.@en

Estuaries are often characterised by a complex network of branching channels, in which the water motion is primarily driven by tides and fresh water discharge. For both scientific reasons and management purposes, it is important to gain more fundamental knowledge about the hydrodynamics in such networks, as well as their implications for turbidity and ecological functioning. A generic 2DV estuarine network model is developed to study tides and river water transport and to understand the dependence of their along-channel and vertical structure on forcings, geometry characteristics and sea level changes. The model is subsequently applied to the Yangtze Estuary to investigate tides and the distribution of river water over channels during dry and wet season, spring tide, as well as prior to and after the formation of Hengsha Passage and the construction of the Deep Waterway Project and sea level rise. Increasing river discharge enhances the friction for tides by increasing both internal and bottom stresses. Changes in tidal forcing are correlated with the friction for both tide and river. A shortcut channel reduces the water level difference in adjacent channels, as well as tidal amplitudes difference. Sea level rise results in larger friction parameters and faster propagation of tides. The distribution of river water transport is hardly affected by above mentioned changes. Model results and current vertical structure are consistent with observations.

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