Channel Dynamics Research Articles

Long-term memory and synapse-like dynamics in two-dimensional nanofluidic channels

Fine-tuned ion transport across nanoscale pores is key to many biological processes, including neurotransmission. Recent advances have enabled the confinement of water and ions to two dimensions, unveiling transport properties inaccessible at larger scales and triggering hopes of reproducing the ionic machinery of biological systems. Here we report experiments demonstrating the emergence of memory in the transport of aqueous electrolytes across (sub)nanoscale channels. We unveil two types of nanofluidic memristors depending on channel material and confinement, with memory ranging from minutes to hours. We explain how large time scales could emerge from interfacial processes such as ionic self-assembly or surface adsorption. Such behavior allowed us to implement Hebbian learning with nanofluidic systems. This result lays the foundation for biomimetic computations on aqueous electrolytic chips.

Dynamic aspects of suspended-sediment-concentration recession curves

Understanding and modeling suspended sediment concentration (C) dynamics in river channels are essential for many theoretical as well as practical purposes. The sediment rating curve approach that relates C with river discharge (Q) is among the most followed modeling approaches, mainly because of its simplicity and effectiveness. Although studies in the past have suggested the possibility of C-Q relationship for a basin not being unique, how the relationship evolves with time is not yet fully understood. In this study, we limit our analysis to recession periods when both C and Q continuously decrease with time and show that the coefficient of C-Q power-law equation changes across recession events. Furthermore, we propose to express -dC/dt as a function of C for recession periods: -dC/dt=fCe. The exponent e is assumed to be related to static catchment characteristics and the coefficient f to dynamic factors, namely catchment-water storage and sediment availability condition. Assuming the dynamic factors controlling f to evolve slowly with time, we propose that it is possible to predict f for a recession event considering only past C data. Once f is estimated, we can predict C for anytime during the recession event. The advantage of the proposed model is that it can predict future suspended sediment concentration at a river cross section during a recession event. We applied the proposed model to 35 US Geological Survey basins and found the 25th, 50th, and 75th values of NSE, respectively, to be 0.55, 0.64, and 0.78, and the corresponding values for the rating curve model - 0.05, 0.01 and 0.20. The results here essentially highlight the importance of recognizing the dynamic nature of suspended sediment concentration-discharge relationship.

A monopolistic supply chain model under price threshold government subsidy contract

Utility of efficient automobiles has compelled us to explore various aspect of its promotion. Our manuscript analyzes a monopolistic automobile manufacturer trying to produce efficient vehicles along with traditional vehicles. A utility-based dynamic production design has been studied under price-dependent subsidy (PDS) model to explore the effects of government subsidy on manufacturing of Battery-operated vehicles (BOV) and Diesel vehicles (DV). We have compared the PDS mechanism under two sustainable and green strategies namely, BOV socially responsible (BSR) strategy and DV energy reduction (DER) strategy to bring out the best possible channel dynamics that can optimize its gross profit margins. We speculated that an increase in threshold price has positive impacts under BSR and DER strategies. However we found numerically and analytically that, even under subsidized BOV's, energy efficient DV's are still in much demand. Our study compels us to explore three different cost cases and the best possible optimal variant has been numerically established. We note that BSR strategy holds good in some circumstances while DER strategy rules in other. Our findings have been illustrated graphically by using real-life scenarios to validate our models.

Quadratic Displacement Operators—Theory and Application to Millimeter-Wave Channel Tracking

First, a family of quadratic displacement operators based on group Fourier Transform has been proposed for joint distribution analysis. Second, considering the quadratic displacement operators, a novel millimeter-wave massive MIMO channel tracking has been proposed in Time-Angle (TA) plane. Due to a poor scattering environment, millimeter-wave communication suffers from an ill-conditioned channel matrix. Computationally effective compressed sensing has been proposed to estimate a few dominant paths. These methods rely on orthogonal pilot signals to estimate the channel reliably. However, applying compressed-sensing solutions to the continuous channel leads to significant pilot overhead. To reduce the pilot overhead, one needs to consider the channel dynamics, particularly the spectral overlap between the channel samples. Considering that channel spectral properties can be represented as a joint time-angle distribution, we propose a novel quadratic displacement operator in TA-plane. Considering group Fourier transform in TA-plane, we show that the subderivative of an angular parameter is the dual group of the original angular signal. For a group transform defined over the finite Abelian group, with respect to the finite-dimensional antenna arrays, the purposed time-angle representation matches the cover space of manifold defined in the virtual channel model recommended by A. Sayeed. In TA-plane, the quadratic displacement operator maps old time-angle coordinate onto a new coordinate by taking to account the local spectral properties of the channel samples. By applying the purposed quadratic displacement operator to the Saleh-Valenzuela channel model, the time evolution operator for directional millimeter-wave channel has been derived. Assuming independently identically distributed multipath contribution, we show that channel Wigner distribution is the direct sum of the cluster-wise Wigner distribution. Accordingly, we have shown that the continuous linear time-variant channel transfer function can be represented as the Hadamard product between Wigner distribution of the channel and Saleh-Valenzuela model. Considering the fact that the density matrix is a Weyl correspondence of Wigner distribution, a union of subspaces method has been employed to construct the density matrix for channels samples with slightly different states. Numerical results have been presented to evaluate the performance of the proposed channel tracking method.

Monitoring channel dynamics of Burhi Dihing River using multi-temporal satellite data

River channel is considered as a dynamic entity in the fluvial system. The Burhi Dihing river is an important south bank tributary of the river Brahmaputra, characterized by highly dynamic and unstable channel variations. The present study deals with the channel dynamics of river Burhi Dihing from Miau, Arunachal Pradesh to Dihingmukh, Assam using remote sensing techniques. Study of channel area, channel length, braiding index, sandbars and fill and erosion has been carried out for the period 1989-1999,1999-2008 and 2008- 2018 by dividing the study area into 6 grid at 15’ longitudinal interval. The river is witnessing more progression changes then regression changes as in last three decade the total amount of deposition done by the river is 3935.964 hectares whereas the total amount of erosion done by the river is only 1552.961 hectares. The area of the channel is decreasing from 102.78 sq km in the year 1989 to 78.949 sq km in the year 2018. During the last three decade, i.e. from 1989 to 2018 the river have has become more braided as in the year 1989 the B.I was 1.76 which have increased to 1.96 in the year 2018 as well as the total number of sandbars have also increased from 208 in the 1989 to 405 in 2018. The outcome of the study is obtained by using the Toposheet, LANDSET ETM image and Google earth images in QGIS 2.14 software.

Unveiling the capabilities of bipolar conical channels in neuromorphic iontronics.

Conical channels filled with an aqueous electrolyte have been proposed as promising candidates for iontronic neuromorphic circuits. This is facilitated by a novel analytical model for the internal channel dynamics [T. M. Kamsma, W. Q. Boon, T. ter Rele, C. Spitoni and R. van Roij, Phys. Rev. Lett., 2023, 130(26), 268401], the relative ease of fabrication of conical channels, and the wide range of achievable memory retention times by varying the channel lengths. In this work, we demonstrate that the analytical model for conical channels can be generalized to channels with an inhomogeneous surface charge distribution, which we predict to exhibit significantly stronger current rectification and more pronounced memristive properties in the case of bipolar channels, i.e. channels where the tip and base carry a surface charge of opposite sign. Additionally, we show that the use of bipolar conical channels in a previously proposed iontronic circuit features hallmarks of neuronal communication, such as all-or-none action potentials and spike train generation. Bipolar channels allow, however, for circuit parameters in the range of their biological analogues, and exhibit membrane potentials that match well with biological mammalian action potentials, further supporting their potential biocompatibility.

Improved SiC MOSFET Model Considering Channel Dynamics of Transfer Characteristics

An improved SiC MOSFET model is proposed in this article, which predicts the dynamics accurately in the wide operation range of the SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> . The temperature-sensitive effect (TSE), the short channel effect (SCE), and the interface state effect are comprehensively taken into consideration in the modeling of the transfer characteristics. A dynamic test platform of transfer characteristics is designed to extract data better than the datasheet. The turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> and turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> processes of the SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> are decoupled, and the nonlinear interterminal capacitances are also modeled thoroughly. To verify the convergence and accuracy of the proposed model, a 400 V/30 A double pulse test is fulfilled, and the complex converters are also simulated with the proposed model. The results show that the proposed model has good convergence and accuracy in predicting the switching trajectory of the SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> , which would be favorable for observing the dynamics in the high-speed switching processes of the SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> .

Uneven Grid-based Linear Parameter-Varying Controller Design for Guided Projectiles

This paper proposes a Linear Parameter-Varying (LPV) controller design for the pitch channel dynamics of a new class of Long Range Guided Projectiles (LRGP). The grid-based approach is preferred since it provides advantages in terms of performance and conservatism. Differently from standard aerospace applications that limit the scheduling vector to the variation of the altitude and the Mach number, the investigated flight envelope is parameterized through a 3D grid, which includes the variation of the angle-of-attack, crucial for range optimization purposes. Thus, an extensive investigation of the grid design is required to minimize the computational complexity of the controller synthesis. The performances of the LPV controller are assessed by employing a nonlinear reference tracking simulation scenario.

Multipartite entanglement and purity dynamics in channels influenced by fractional Gaussian noise

The dynamical map of entanglement, coherence and mixedness in four-qubit maximally entangled GHZ-class state paired with classical channels driven by fractional Gaussian noise is investigated. The qubit-channel coupling is assumed in four distinct ways: common, bipartite, tripartite, and independent local channel-qubit configurations comprising single, double, triple, or independent noisy sources. Using entanglement witness, negativity, purity and von Neumann entropy, except for the independent configuration, we show that indefinite entanglement, coherence, and purity preservation may be simulated in multipartite GHZ-like states. Quantum correlations and purity decrease exponentially in four qubits, and exact fluctuating local field behavior, as well as entanglement sudden death and birth revivals, are completely suppressed. Entanglement, coherence, and purity preservation are affected by noise and the number of independent channels utilized. The Hurst parameter of fractional Gaussian noise was discovered in the four qubits to improve entanglement, coherence and avoid mixedness.

The Effect of Gap Reduction on Fluid Dynamics and Mass Transfer in Membrane Narrow Channels Filled with Novel Spacers-A Detailed Computational Study.

The effect of gap thickness reduction 2h (i.e., the reduction h at each membrane surface) is studied on the flow field and mass transfer, in membrane channels filled with novel spacers, under conditions representative of those prevailing in RO desalination modules. The patented novel net-type spacers are comprised of regularly-spaced spherical nodes (in contact with the membranes) and interconnecting cylindrical filaments at the midplane of the channel. Advanced 3D flow simulations, performed at "unit cell" level, show the strong effect of a modest gap reduction on the flow field. Analysis of the computational results leads to new insights regarding flow development as well as to useful correlations of key process parameters (i.e., for friction losses, mass-transfer rates, wall shear stresses) accounting for the effect of gap reduction. Contrary to conventional spacers, the novel spacer geometry, under conditions of usual/modest channel-gap reduction, exhibits no stagnant flow zones and relatively high shear stresses on both the membranes and the filaments, which leads to desirable mitigation of fouling and a reduction in concentration polarization. The developed correlations can be adapted to existing advanced simulators of RO module performance for improved process design and optimization.

Reconstructing backwater hydrodynamics from fluvial-deltaic deposits using stratigraphic inversion: An example from the Tullig Sandstone, Western Irish Namurian Basin, County Clare, Ireland

Fluvial-deltaic systems are subject to non-uniform backwater flow where rivers approach receiving basins. This hydrodynamic condition results in sediment aggradation on the channel bed and enhanced downstream fining. In turn, this impacts river channel dynamics, including lateral migration rates and the propensity for avulsion. The imprint of non-uniform flow on stratigraphy has been reported from field, numerical modeling, and experimental studies. This work provides key observations for evaluating the impact of non-uniform flow spanning length scales from those of sediment grains to delta lobes. However, reconstructing paleohydraulic conditions of non-uniform flow from fluvial-deltaic settings remains a challenge. Non-uniform flow is a defining characteristic of fluvial-deltaic environments, but most existing relations linking hydrology and the depositional record rely on the assumption of steady and uniform flow. Herein, we present a novel stratigraphic inversion technique, combining it with morphodynamic modeling and statistical analyses, to evaluate how backwater conditions manifest in the stratigraphy of the Tullig Sandstone, an ancient fluvial-deltaic deposit of the Western Irish Namurian Basin. Our analyses refine estimates of channel properties, including flow depth and bed slope, and are validated by field measurements of sandstone-facies properties, including grain size and stratal architecture. For example, bed sediment fines down-dip, commensurate with increasing cross set and bed thicknesses. These patterns indicate bed aggradation and are consistent with reconstructed morphodynamic conditions. This study pinpoints the extent of non-uniform flow and its influence on fluvial-deltaic stratigraphy and provides a framework for improving reconstruction techniques used to interpret the paleohydrology of ancient fluvial-deltaic systems.

Bidirectional Transport Phenomenon of Ions in Electric Fields Due to the Cluster Formation in Two-Dimensional Graphene Channels

In aqueous solution, cations and anions are known to be moving oppositely and unidirectionally in electric fields. In this work, we observe an abnormal bidirectional ion transport phenomenon in electric fields because of the formation of ion clusters in two-dimensional graphene channels. A series of molecular dynamic simulations reveal that the separated ions within two-dimensional graphene channels will rapidly assemble into individual clusters under the electric field, originating from the confinement-induced effective ionic interactions as well as the strongly compressed hydration shells of ions. Notably, owing to the competition between ionic interaction and electric field, the structure of ion clusters changes from a square-unit pattern to chain-like with the increase in electric field, and the cluster size displays a maximum behavior. As a result, the motion of cations and anions in these clusters will be strongly coupled to each other, leading to the bidirectional transport phenomenon. Furthermore, these ion clusters will disappear abruptly with the increase in graphene layer distance, and thus the ion transport becomes unidirectional as normal. Our findings shed light on the unusual ion dynamics in two-dimensional channels and provide a potential avenue for the design of novel nanofluidic devices.

Multiple aspects of heat generation/absorption on the hydromagnetic flow of Carreau nanofluids via nonuniform channels

The use of nanofluid technology as a working fluid in specific channels has significantly improved heat exchange rate in thermal engineering applications. In fact, nonuniform channels with converging or diverging nature offer special characteristics that encourage the most favorable usage, such as flow via nozzles, diffusers, and reducers in polymer processing and flow through canals and rivers. Therefore, we present a theoretical and mathematical insight into nanofluid heat transfer and flow dynamics in nonuniform channels utilizing non-Newtonian nanofluids. The impacts of heat absorption/generation and Joule heating in a magnetohydrodynamics (MHD) flow of Carreau nanofluids with viscous dissipation are addressed in this research. Brownian and thermophoresis diffusion are deliberated to investigate heat and mass transport mechanisms. The modeled flow equations are numerically handled using a built-in MATLAB code based on the finite difference approach (bvp4c) for velocity, temperature, and concentration fields. The consequences of the variable magnetic field, heat absorption/generation, and numerous physical parameters on the temperature and concentration field are surveyed. The results indicate that the increasing values of heat generation/absorption parameter and Eckert number significantly enhances the temperature profiles in convergent channel. In addition, a similar behavior is observed for higher Prandtl number. An assessment of solutions achieved in this article is made with existing data in the literature.

River channel response to invasive plant treatment across the American Southwest

AbstractInvasive riparian plants were introduced to the American Southwest in the early 19th century and contributed to regional trends of decreasing river channel width and migration rate in the 20th century. More recently, efforts to remove invasive riparian vegetation (IRV) have been widespread, especially since 1990. To what extent has IRV treatment reversed the earlier trend of channel narrowing and reduced dynamism? In this study, paired treated and untreated reaches at 15 sites along 13 rivers were compared before and after IRV treatment using repeat aerial imagery to assess long‐term (~10‐year) channel change due to treatment on a regional scale across the Southwest USA. We found that IRV treatment significantly increased channel width and floodplain destruction. Treated reaches had higher floodplain destruction than untreated reaches at 14 of 15 sites, and IRV treatment increased the rate of floodplain destruction by a median factor of 1.9. The effect of treatment increased with the stream power of the largest flow over the study period. Resolving observations of channel change into separate measures of floodplain destruction and formation provided more information on underlying processes than simple measurements of channel width and centerline migration rate. Restoration practitioners who perform IRV treatment projects often focus on wildlife or vegetation response; however, geomorphic processes should be considered in restoration planning because they drive aquatic habitat and vegetation dynamics, and because of the potential for damage to downstream infrastructure. Depending on the restoration goal, management practices can be used to enhance or minimize the increase in channel dynamism caused by IRV treatment.

Universal Learning Waveform Selection Strategies for Adaptive Target Tracking

Online selection of optimal waveforms for target tracking with active sensors has long been a problem of interest. Many conventional solutions utilize an estimation-theoretic interpretation, in which a waveform-specific Cramér–Rao lower bound on measurement error is used to select the optimal waveform for each tracking step. However, this approach is only valid in the high SNR regime, and requires a rather restrictive set of assumptions regarding the target motion and measurement models. Furthermore, due to computational concerns, many traditional approaches are limited to near-term, or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">myopic</i> , optimization, even though radar scenes exhibit strong temporal correlation. More recently, reinforcement learning has been proposed for waveform selection, in which the problem is framed as a Markov decision process, allowing for long-term planning. However, a major limitation of reinforcement learning is that the memory length of the underlying Markov process is often unknown for realistic target and channel dynamics, and a more general framework is desirable. This work develops a universal sequential waveform selection scheme which asymptotically achieves Bellman optimality in any radar scene, which can be modeled as a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$U{\text{th}}$</tex-math></inline-formula> -order Markov process for a finite, but unknown, integer <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$U$</tex-math></inline-formula> . Our approach is based on well-established tools from the field of universal source coding, where a stationary source is parsed into variable length phrases in order to build a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">context-tree</i> , which is used as a probabilistic model for the scene’s behavior. We show that an algorithm based on a multialphabet version of the context-tree weighting method can be used to optimally solve a broad class of waveform-agile tracking problems while making minimal assumptions about the environment’s behavior.

Channel Responses for the Molecule Release From Spherical Homogeneous Matrix Carriers

Molecular communications is a promising framework for the design of controlled-release drug delivery systems. Under this framework, drug carriers, diseased cells, and the channel in between are modeled as transmitters, absorbing receivers, and diffusive channel, respectively. However, existing works on drug delivery systems consider only simple drug carrier models, which limits their practical applicability. In this paper, we investigate diffusion-based spherical matrix-type drug carriers, which are employed in medical applications. In a matrix carrier, the drug molecules are dispersed in the matrix core and diffuse from the inner to the outer layers of the carrier once immersed in a dissolution medium. We derive the channel response of the matrix carrier transmitter for an absorbing receiver. The results are validated by particle-based simulations and compared with commonly used point and transparent spherical transmitters to highlight the necessity of considering practical models. Moreover, we show that a transparent spherical transmitter, with the drug molecules uniformly distributed over the entire volume, is a special case of the considered matrix system. For this case, we provide an analytical expression for the channel response. Furthermore, we derive a criterion for evaluating whether the release process or the channel dynamics are more important for the overall characteristics of the channel response of a drug delivery system. For the limiting regimes, where only the release process or only the channel determine the behavior of the end-to-end system, we propose closed-form approximations for the channel response. Finally, as a scenario of practical relevance, we investigate the channel responses for the release of common therapeutic drugs, e.g., doxorubicin, from a diblock copolymer micelle acting as drug carrier.

Multi-Cell Multi-Beam Prediction Using Auto-Encoder LSTM for mmWave Systems

Millimeter wave (mmWave) systems rely on communication in narrow beams for directional and spatial multiplexing gains. A key challenge in realizing these systems is beam tracking, particularly in environments with high mobility and blockage. Additionally, in wide-area mmWave cellular systems, user equipment (UE) devices must often simultaneously track signals from multiple cells, since links to individual cells can be unreliable. Models of the channel dynamics across multiple cells and multiple beams are difficult to derive from first principles. In this work, we propose a fully data-driven approach based on a novel auto-encoder integrated long short term memory (LSTM) network, which predicts multiple beams from multiple cells, one time step in the future. The key innovation is to use an auto-encoder pre-processing step, which reduces the dimensionality of the input– the main challenge in multi-cell, multi-beam tracking. The prediction capability of the proposed network is verified and compared to common baseline predictors as well as popular machine learning (ML) based neural network predictors in realistic system-level simulations using a commercial ray-tracer. We observe that predictions from the proposed network, which utilizes auto-encoders for dimensionality reduction, offers significantly better best beam accuracy and lower beam misalignment loss than common baseline approaches. We also discuss outage prediction and proactive beam switching as applications of the multi-cell multi-beam prediction.

Cognitive Learning-Aided Multi-Antenna Communications

Cognitive communications have emerged as a promising solution to enhance, adapt, and invent new tools and capabilities that transcend conventional wireless networks. Deep learning (DL) is critical in enabling essential features of cognitive systems because of its fast prediction performance, adaptive behavior, and model-free structure. These features are especially significant for multi-antenna wireless communications systems, which generate and handle massive data. Multiple antennas may provide multiplexing, diversity, or antenna gains that improve the capacity, bit error rate, or the signal-to-interference-plus-noise ratio, respectively. In practice, multi-antenna cognitive communications encounter challenges in terms of data complexity and diversity, hardware complexity, and wireless channel dynamics. DL solutions such as federated learning, transfer learning, and online learning tackle these problems at various stages of communications processing, including multi-channel estimation, hybrid beamforming, user localization, and sparse array design. This article provides a synopsis of various DL-based methods to impart cognitive behavior to multi-antenna wireless communications for improved robustness and adaptation to the environmental changes while providing satisfactory spectral efficiency and computation times. We discuss DL design challenges from the perspective of data, learning and transceiver architectures. In particular, we suggest quantized learning models, data/model parallelization, and distributed learning methods to address the aforementioned challenges.

Turbidity maxima in estuarine networks: Dependence on fluvial sediment input and local deepening/narrowing with an exploratory model

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.

Corrigendum: Assessment of the oceanic channel dynamics responsible for the IOD-ENSO precursory teleconnection in CMIP5 climate models

• please read through all the templates before choosing• pick the most relevant text template(s) from the following page and delete all others.• edit the text as necessary, ensuring that the original incorrect text is included for the record, please see the below.• please do not use any extra formatting when editing the templates, and only modify the red text unless absolutely necessary• submit to Frontiers following the instructions on this page.When the original text contained incorrect information, to preserve the scientific record, please include that text when editing the below templates.There was a mistake in the Funding statement, an incorrect number was used. The correct number is "2015C03Bd051.". The publisher apologizes for this mistake.The original version of this article has been updated.Corrigendum on: Xu T, Yuan D and Wang J (2022) Assessment of the oceanic channel dynamics responsible for the IOD-ENSO precursory teleconnection in CMIP5 climate models. Front. Clim. 4:996343. doi: 10.3389/fclim.2022.996343 In the published article, there was an error regarding the affiliations for Dongliang Yuan. As well as having affiliations, they should have Affiliation as follows:Tengfei Xu 1,2,3 , Dongliang Yuan 4,1,2,3* and Jing Wang 4Template continues on the next page