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18 results for “Tidal Channels”
CVPIA Predation Contact Point Study - 2022: The impact of submerged aquatic vegetation removal on fish predation in a tidal river channel
Proliferation of non-native submerged aquatic vegetation (SAV) has the potential to cause widespread ecosystem changes, and has been attributed to declines in native fish populations around the world. One pathway for these declines is non-native SAV may render ecosystems more hospitable to fish predator species by creating habitat structure, by altering lower trophic food webs, or by affecting predator-prey interactions. It is presumed that non-native vegetation removal will generally favor native fish, however, fish community responses to SAV removals are not well understood. Using a field-based Before-After-Control-Impact study design, we measured the impact of manual SAV removals on short-term changes in predator abundance, predation risk on juvenile Chinook salmon ( Oncorhynchus tshawytscha ; a native fish of management concern), and the aerobic scope of predator and prey in California’s Sacramento-San Joaquin Delta. We found that, while SAV removals decreased abundances of the most common SAV-associated predator, largemouth bass ( Micropterus salmoides ), they resulted in higher predation risk of tethered prey, likely due to the removal of refuge habitat and the immigration of an open-water predator, striped bass ( Morone saxatilis ). SAV removals also buffered against a seasonal decline in environmental oxygen supply, increasing the aerobic scope of juvenile Chinook salmon and largemouth bass; whether such gains for prey would outweigh the persistent aerobic advantage of predators is an open question. While limited in spatial and temporal scope, this study has put into question any short-term benefits of small-scale SAV removal efforts for native fish populations, especially in areas where open-water predator species are abundant.
Interagency Ecological Program: Drift invertebrate and ichthyoplankton catch and water quality from the Sacramento River channel, and Sacramento River floodplain and tidal slough, collected by the Yolo Bypass Fish Monitoring Program, 1998-2022
Largely supported by the Interagency Ecological Program (IEP), California Department of Water Resources (DWR) has operated a fish monitoring program in the Yolo Bypass, a seasonal floodplain and tidal slough, since 1998. The objectives of the Yolo Bypass Fish Monitoring Program (YBFMP) are to: 1. Collect baseline data on water quality, chlorophyll, lower trophic level biota, and fish in the Yolo Bypass to monitor spatial and temporal changes in trends and abundance. 2. Analyze and communicate Yolo Bypass data with interested parties and the scientific and management communities to address pertinent management-related questions. 3. Provide technical expertise on Yolo Bypass aquatic ecology and monitoring and sampling methods. Aquatic and terrestrial insects are an important component in the diet of juvenile and adult fishes within the San Francisco Estuary, including two important native fishes: juvenile Chinook Salmon and Sacramento Splittail. The YBFMP collects drift invertebrates year-round from two sites. Currently, samples are collected biweekly (every other week) to weekly (during floodplain inundation) using a rectangular aquatic drift net that sits at the surface of the water. Invertebrates are identified and enumerated by contractors (currently EcoAnalysts, Inc.). The goals of the monitoring program are to compare the seasonal variations in densities and species trends of aquatic and terrestrial insects/non-insects within the Sacramento River channel and the Yolo Bypass, the river’s seasonal floodplain. Drift invertebrate Key findings to date include: (1) Chinook Salmon sampled in the floodplain had diets comprised of 90% Dipterans and zooplankton, with Chironomidae being the dominant Diptera family (Sommer et al., 2001), (2) The floodplain of the Yolo Bypass contains significantly higher densities of Diptera (Diptera densities being positively associated with flow) and terrestrial invertebrates than the adjacent Sacramento River (Sommer et al. 2001b: Sommer
Supplementary Data for "Interplay of river and tidal forcings promotes loops in coastal channel networks"
<p>This dataset contains supplemental data required to reproduce the results of the paper <em>Interplay of river and tidal forcings promotes loops in coastal channel networks</em> (in review at Geophysical Research Letters). We provide raw and extracted channel network data for 19 river deltas/coastal marsh sites. For each site, the following files are provided:</p> <p><strong>XXX_base.tif</strong> : the raw binary mask of the river channel network<br> <strong>XXX_clipper.shp</strong> (and associated .dbf, .prj, .qpj, and .shx files) : polygon(s) used to clip the raw mask<br> <strong>XXX_clipped.tif</strong> : the binary mask of the river channel network after being clipped by XXX_clipper.shp<br> <strong>XXX_filled.tif</strong> : the binary mask after filling islands via the method specified in the paper<br> <strong>XXX_inlet_nodes.shp</strong> (and associated .dbf, .prj, .qpj, and .shx files) : locations of the inlet nodes; used by RivGraph<br> <strong>XXX_shoreline.shp</strong> (and associated .dbf, .prj, .qpj, and .shx files) : location of the shoreline; used by RivGraph<br> <strong>XXX_links.json</strong> : GeoJSON file containing the geometries, connectivities, and widths of each link in the network<br> <strong>XXX_nodes.json</strong> : GeoJSON file containing the locations of each node of the network<br> <strong>process_XXX.py</strong> : the python script used to generate the above files</p> <p>All files listed below (except .py files) are georeferenced (i.e. can be opened with QGIS, ArcGIS or another GIS). Exceptions to the provided files include:</p> <p><strong>Barnstable</strong>: no "base.tif" is provided. Use "filled.tif".<br> <strong>GBM</strong>: some hand-cleaning was performed on "filled.tif".<br> <strong>Mackenize</strong>: "clipper.shp" is not provided, but "clipped.tif" is.<br> <strong>Mississippi</strong>: "clipper.shp" is not provided as the mask was made from a shapefile.</p> <p>In order to run process_XXX.py, the RivGraph package will need to be installed. Instructions<br> can be found at https://github.com/jonschwenk/RivGraph.</p>
Model setup and output for 'Tidal conversion and dissipation at steep topography in a channel poleward of the critical latitude'
<p><strong>Data supplement to Hughes and Klymak 2019</strong></p> <p>Model input and output in a reduced form associated with the following paper:</p> <p><strong>Tidal conversion and dissipation at steep topography in a channel poleward of the critical latitude<br></strong><em>Journal of Physical Oceanography.</em> <a href="http://dx.doi.org/10.1175/JPO-D-18-0132.1">doi:10.1175/JPO-D-18-0132.1</a></p> <p><strong>Inputs</strong></p> <p>As described in Table 1 of the associated paper, there are three main sets of simulations. The input files for these sets are contained in their respective directories (`vary_width`, `vary_forcing`, and `vary_freq`). The python script that creates all of the necessary files is `gendata.py`. A fourth directory is titled `baroclinic_terms` and includes that simulation in which <em>u'</em> and <em>p'</em> are output at high temporal resolution.</p> <p>A key point regarding the input files is that for the vary width and vary forcing cases, a single simulation involves multiple channels. This lets me compile a single executable `mitgcmuv` with a Nx × Ny grid of 600 × 1280, which I divide up into the necessary number of channels by putting vertical walls in appropriate places. For the vary width cases, the 'narrow' simulations are all channels from 0.2 to 32 km and the 'wide' simulations are all wider channels. Once the simulation has run, I use netcdf tools (`ncks`) to extract the individual channels using the scripts in the `extract_scripts` directory.</p> <p>Most of the files in the `code` directories will be familiar to anyone that uses the MITgcm. An exception is the `energy_diagnostics_fill.F` (and `diagnostics_main_init.F` and `do_statevars_diags.F`, which have minor additions). The original, from `https://github.com/jklymak/MITgcmcode`, was modified slightly to suit this project.</p> <p><strong>Outputs</strong></p> <p>The results directory contains five subdirectories to be described in turn.</p> <p>Notes that in all cases, energy terms in the netCDF files do not include a factor of ρ. This was added in at the plotting stage.</p> <p>All simulations used Checkpoint67b and were run on Graham: https://docs.computecanada.ca/wiki/Graham.</p> <p><strong>vary_width</strong></p> <p>The majority of the files are of the form `obstacle_FFF_YY.nc` where `FFF` is $1000 ω/f$ and `YY` is the channel width in kilometres. These files contain the tidally averaged, depth-integrated energy diagnostics for the seventh tidal cycle at all points (<em>x, y</em>) within the energy control volume.</p> <p>There are also three files entitled `tophat_995_YY.nc`, which contain fields of <em>U</em>, <em>V</em>, and <em>T</em> (which gives density with α = 0.0002) at two levels. These fields are used as examples for weakly and strongly responding channels.</p> <p><br><strong>vary_forcing</strong></p> <p>These files are of the form `forcing_UU.nc` where `UU` is the deep-water tidal current amplitude <em>U_</em>0 in cm/s. They contain the same energy terms as for the vary width simulations.</p> <p><strong>vary_freq</strong></p> <p>These files are of the form `freq_FFF_fields.nc` and contain fields of <em>U</em>, <em>V</em>, and <em>T</em> at two levels. Energy terms are not included because the vary frequency simulations were only run to get estimates of the along-ridge wavelength.</p> <p><strong>baroclinic_terms</strong></p> <p>The single file within this directory contains <em>u'</em> and <em>p'</em> at a single <em>x</em> position every five minutes for four tidal cycles.</p> <p><strong>gaussian_26</strong></p> <p>This directory, named for its obstacle and width, contains <em>U</em>, <em>V</em>, and <em>T</em> at every grid point for a snapshot in time and another file with the corresponding snapshots of all energy terms.</p>
A possible formation channel for blue hook stars in globular cluster - II. Effects of metallicity, mass ratio, tidal enhancement efficiency and helium abundance
<p>MESA inlists and run_star_extras associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2016MNRAS.463.3449L">Lei et al. (2016)</a>. MESA version 7211.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/stw2242">10.1093/mnras/stw2242</a></p>
Model output: Unraveling the mechanisms that cause cyclic channel-shoal dynamics of ebb-tidal deltas: a numerical modeling study
<p>Output from model runs for Lenstra et al., “Unraveling the mechanisms that cause cyclic channel-shoal dynamics of ebb-tidal deltas: a modeling study”. The dataset contains two types of model output, namely (1) the default model runs and (2) the sensitity runs with waves+tides, waves only, and tides only.</p> <p>The files covering the default model runs contain:</p> <p>ModeledDays - time vector for the depth series [days]</p> <p>XT - east-west location of grid points high resolution domains [m]</p> <p>YT - north-south location of grid points high resolution domains [m]</p> <p>depth - depth series for the high resolution domains [m]</p> <p>XSea - east-west location of grid points outer sea domain [m]</p> <p>YSea - north-south location of grid points outer sea domain [m]</p> <p>depthSea - depth series for the outer sea domain [m]</p> <p>XBasin - east-west location of grid points basin domain [m]</p> <p>YBasin - north-south location of grid points basin domain [m]</p> <p>depthBasin - depth series for the basin domain [m]</p> <p>ST_Days - time vector for the sediment transport series [days]</p> <p>ST_Inlet - tidally-averaged total sediment transport through the inlet (positive seaward) [10<sup>6</sup> m<sup>3</sup>/year]</p> <p>ST_Up - tidally-averaged total sediment transport through the cross-section at the updrift coast (positive eastward) [10<sup>6</sup> m<sup>3</sup>/year]</p> <p>ST_Down - tidally-averaged total sediment transport through the cross-section at the downdrif coast (positive eastward) [10<sup>6</sup> m<sup>3</sup>/year]</p> <p>The files covering the sensitivity runs contain for the high resolution domains:</p> <p>XT - east-west location of grid points [m]</p> <p>YT - north-south location of grid points [m]</p> <p>TA_STX - east-west component of the tidally-averaged total sediment transport [m<sup>3</sup>/s/m]</p> <p>TA_STY - north-south component of the tidally-averaged total sediment transport [m<sup>3</sup>/s/m]</p> <p>TA_U - east-west component of the tidally-averaged flow velocities [m/s]</p> <p>TA_V - north-south component of the tidally-averagedf low velocities [m/s]</p> <p>M2 - amplitude of the semi-diurnal tidal flow velocities (not for wave only runs) [m/s] </p>
Data & Code for Peak water levels rise less than mean sea level in tidal channels subject to depth convergence by deepening
<p>Data & Code for the article: "Peak water levels rise less than mean sea level in tidal channels subject to depth convergence by deepening"</p> <p>- Input-files used to run the models</p> <p>- Scripts used for the figures</p> <p>- Excel-based tool to calculate tidal response to channel deepening with system-specific parameters</p> <p>- ...</p>
Dataset from Rummel et al.: "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 1
<p>Model data from the numerical setup of the Weser River Estuary used in Rummel et al. (submitted to JGR:Oceans): "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 1.</p> <p>The dates in the file names are connected to specific model runs and do not explain the modelled time period.</p> <p>Explanation of datasets:</p> <ul> <li>2D_elev* - 2D model output for the entire year 2016 for validation at one location each (associated station name included in file name), original topography.</li> <li>3D_stat* - 3D model output for the entire year 2016 for validation at one location each (associated station name included in file name), original topography.</li> <li>3D_cross_30_80* - 3D model output for one month of 2016 for the model domain from Weser km 30 to 80 including variables needed for the salt transport decomposition. <ul> <li>2024-05-23 - March 2016, original topography</li> <li>2024-06-07 - March 2016, dredged topography</li> <li>2024-06-06 - September 2016, original topography (different temporal resolution)</li> <li>2024-06-10 - September 2016, dredged topography</li> </ul> </li> <li>3D_channel* - 3D model output for the navigational channel in the entire model domain for the entire year 2016. <ul> <li>2024-04-02 - original topography</li> <li>2024-05-16 - dredged topography</li> </ul> </li> <li>3D_cross_55/65_2024-09-02* - 3D model output for September 2016, original topography for crosssections at Weser km 55 and 65 including variables needed for the salt transport decomposition.</li> </ul>
Dataset from Rummel et al.: "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 2
<p>Model data from the numerical setup of the Weser River Estuary used in Rummel et al. (submitted to JGR: Oceans): "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 2.</p> <p>The dates in the file names are connected to specific model runs and do not explain the modelled time period.</p> <p>This dataset contains daily averaged 3D model output for the entire year 2016 of the whole model domain with the original, not dredged topography.</p> <p> </p>
Dataset from Rummel et al.: "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 3
<p>Model data from the numerical setup of the Weser River Estuary used in Rummel et al. (submitted to JGR: Oceans): "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 3.</p> <p>The dates in the file names are connected to specific model runs and do not explain the modelled time period.</p> <p>This dataset contains daily averaged 3D model output for the entire year 2016 of the whole model domain with the dredged topography.</p>
Data used in paper "The sensitivity of tidal channel systems under the influences of initial bed conditions, vegetation, and tidal asymmetry".
<p>Data used in paper "The sensitivity of tidal channel systems under the influences of initial bed conditions, vegetation, and tidal asymmetry".</p>
How does landscape vegetation configuration regulate local channel initiation in a rapidly expanding micro-tidal marsh?
<p>This study revealed the relationship between channel initiation and vegetation configuration in micro-tidal system.</p>
Tidal channel meanders serve as stepping-stones to facilitate cordgrass landward spread by creating invasion windows
<p>Understanding the mechanisms by which geomorphic structures affect habitat invasibility by mediating various abiotic and biotic factors is essential for predicting whether these geomorphic structures may provide spatial windows of opportunity to facilitate range-expansion of invasive species in salt marshes. Many studies have linked geomorphic landscape features such as tidal channels to invasion by exotic plants, but the role of tidal channel meanders (i.e., convex and concave sides) in regulating the <em>Spartina</em> invasion remains unclear. Here, we examined the combined effects of tidal channel meander-mediated hydrodynamic variables, soil abiotic stresses and propagule pressure on the colonization of <em>Spartina</em> in the Yellow River Delta, China, by conducting field observations and experiments. The results showed that lower hydrodynamic disturbance, bed shear stress, and higher propagule pressure triggered by eddies due to the convex structure of channel meanders facilitated <em>Spartina</em> seedling establishment and growth, whereas the concave side considerably inhibited the <em>Spartina</em> invasion. Lower soil abiotic stresses also significantly promoted the invasibility of the channel meanders by <em>Spartina</em>. Based on these findings, we propose a conceptual framework to illustrate the effects of the meandering geomorphology of tidal channels on the mechanisms that might allow the landward spread of <em>Spartina</em> and related processes. Our results demonstrate that the meandering geomorphic structures of tidal channels could act as stepping-stones to significantly facilitate the landward invasion of <em>Spartina</em> along tidal channels. This implies that geomorphic characteristics of tidal channels should be integrated into invasive species control and salt marsh management strategies.</p>
Tidal channel formation in a rapidly invaded micro-tidal marsh: the role of dynamic vegetation pattern and concurrent channel deepening
<p>The channel formation during the spartina alterniflora invasion influenced by vegetation pattern dynamic and concurrent channel deepening.</p>
Data from: Multi-scale temporal patterns in fish presence in a high-velocity tidal channel
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Tidal channel meanders serve as stepping-stones to facilitate cordgrass landward spread by creating invasion windows
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Straight Tidal Channel Model data
<p>This repository contains the data analyzed in the paper "Effects of vegetation, sediment supply and sea level rise<br> on the morphodynamic evolution of tidal channels" (submitted to Water Research Resources)</p> <ul> <li>Directory 'Field data' contains the data from real tidal channels (Venice Lagoon, Western Scheldt).</li> <li>Directory 'Hydrodyanmics' contains the data computed by the fully fledged 2D model 2DEF and the simplified 1D model developed by the authors over three test bathymetry.</li> <li>Directory 'Straight_Channel_long_term_configuration' contains the data about the evolution and the final configuration of the channel in all the runs.</li> </ul>
Tidal Channels in the Yellow River Estuary
<p>Coastal tidal channels in 2022 extracted from GF-3 and planetscope in the Yellow River Estuary</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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