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15 results for “water surface elevation”
WSC - Water surface elevation (WSE) and water table depth (WTD) from 14 points at the Wibu field site, 2012-2013 growing seasons
Observation wells were installed for the purpose of continuously monitoring the water table level during the 2012 and 2013 growing seasons at the Wibu field site. These data were then used to study the yield response of corn to water table depth, soil texture, and growing season weather conditions (Zipper et al., in prep). The Wibu field site is a commercial agricultural field, which grew corn in the 2012, 2013, and 2014 growing seasons. See Zipper and Loheide (2014) Ag. For. Met. for more information about the field site. The 2012 growing season was characterized by severe drought, and the water table fell below the bottom of most wells in late June/early July.
GRWSE-global river water surface elevation from sentinel-3
<p>This dataset includes time series of Water Surface Elevation (WSE) of large rivers at over 3000 virtual stations. The WSE time series were created using Sentinel-3A and Sentinel-3B altimetry data. </p>
Geospatial data used in "Estimation of river water surface elevation using UAV photogrammetry and machine learning"
<p>Geospatial data used in article "Estimation of river water surface elevation using UAV photogrammetry and machine learning" by Radosław Szostak, Marcin Pietroń, Przemysław Wachniew, Mirosław Zimnoch and Paweł Ćwiąkała (AGH UST).</p> <p>Each zip archive contains the following files:</p> <ul> <li>dsm.tif - raster of digital surface model,</li> <li>ortho.tif - raster of orthophoto,</li> <li>gnss_wse.json - geojson multipoint shape containing RTN GNSS measurements of water surface elevation,</li> <li>grid.json - geojson multipolygon shape containing square areas of samples used in deep learning solution.</li> <li>centerline.json - geojson multipoint shape containing values sampled from DSM along centerline,</li> <li>wateredge.json - geojson multipoint shape containing values sampled from DSM along "water-edge".</li> </ul> <p>Data in AMO18.zip archive was collected by Bandini et. al (https://doi.org/10.5281/zenodo.3519888).</p> <p>Preprocessed machine learning dataset and source codes are available in github repository at: https://github.com/radekszostak/river-wse-uav-ml</p>
Model output data to "Land surface modeling in the Himalayas: on the importance of evaporative fluxes for the water balance of a high elevation catchment"
<p>We provide i) gridded initial conditions (.tif), ii) modeled gridded monthly outputs (.tif), and iii) modeled hourly outputs at the station locations (.txt) for the hydrological year 2019. Information about the variables and units can be found in the figures (.png) associated to each dataset. Details about the datasets can be found in the original publication by Buri and others (2023).</p><p> </p><p>Buri, P., Fatichi, S., Shaw, T. E., Miles, E. S., McCarthy, M. J., Fyffe, C. L., ... & Pellicciotti, F. (2023). Land Surface Modeling in the Himalayas: On the Importance of Evaporative Fluxes for the Water Balance of a High‐Elevation Catchment. <i>Water Resources Research</i>, <i>59</i>(10), e2022WR033841. DOI: <a href="https://doi.org/10.1029/2022WR033841"><strong>10.1029/2022WR033841</strong></a></p>
Sentinel-3A and Sentinel-3B radar altimetry water surface elevation in the Zambezi catchment
<p>This dataset contains the data presented in Kittel et al. (2020): Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B, https://doi.org/10.5194/hess-2020-165</p> <p>The dataset is the full Sentinel-3A and 3B radar altimetry records for water surface elevation in the Zambezi catchment for all virtual stations containing at least 80% of the expected observations and predominantly single-peak waveforms. Not all VS have been manually checked or validated.</p> <p>Additionally the repository contains a shapefile with all Sentinel-3 virtual stations in the Zambezi.</p>
Water level elevation data for monitoring wells and surface water gages at the Colorado State University Mountain Campus, 2019 – 2023
<p>This dataset contains groundwater and surface water levels measured between 2019 and 2023 at the Colorado State University Mountain Campus. The study site is situated within a formerly glaciated valley traversed by a modern perennial stream, the South Fork Cache la Poudre River, and occurs near the subalpine-montane ecosystem transition at an approximate elevation of 2,750 meters above sea level. Water levels were measured at two transects (the upstream and downstream transects). Each transect includes a surface water gage, two shallow hand-augered monitoring wells on the valley floor within the riparian zone, and a deeper water table observation well located on the adjacent terrace. Water levels were measured at a subhourly frequency using a combination of vented and non-vented pressure transducers. All data from non-vented transducers were corrected for barometric pressure fluctuations.</p>
Dataset used in "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques"
<p>Dataset for research paper "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques", published in Remote Sensing of Environment 2019, Elsevier Journal.</p> <p>Dataset includes:</p> <p>-MATLAB_codes.rar: zip file that contains MATLAB codes. MAIN.m is the main code, it refers to external functions that are included in the zip file. MAIN.m plots the figures of the paper in which we compare radar, LIDAR and photogrammetry and computes statistics of table 3 (table of the paper)</p> <p>-zip file WL_observations_Aomose.zip contains LIDAR, radar, and photogrammetry observations to be loaded by MATLAB code MAIN.m</p> <p>-the LIDAR Digital Surface Model (DSM_final.tif) retrieved in the stream Amose Å</p> <p>-the photogrammetry Digital Elevation Model (DEM_nov.tif) and orthomosaic (orthomosaic_nov.tif) </p> <p> </p>
Data from: Elevated [CO2] mitigates the effect of surface drought by stimulating root growth to access sub-soil water
Open the record for dataset details and reuse information.
Water level elevation data for monitoring wells and surface water gages at the Colorado State University Mountain Campus, 2019 – 2023
Open the record for dataset details and reuse information.
Water surface elevations of the base flood for the central Arizona Flood Insurance Rate Maps (FIRM)
Water surface elevations of the base flood as approved by the Federal mergency management Agency (FEMA) for the Flood Insurance Rate Maps (FIRM). The base flood elevation, in feet, is in relation to the National Geodetic Vertical Datum of 1929. Profile baselines are for the Flood Insurance Rate Maps (FIRM). The cross section data are used for the production of Flood Insurance Rate Maps. The Flood Insurance Rate Maps (FIRMs) show different floodplains with different zone designations. These are primarily for insurance rating purposes, but the zone differentiation can be very helpful for other floodplain management purposes. The differentiated floodplain zones are used for the production of Flood Insurance Rate Maps. Maricopa County has been subdivided into FIRM panels for the publication and distribution of FIRMs. Profile baselines are for the Flood Insurance Rate Maps (FIRM).
Delta-X: AirSWOT L3 Water Surface Elevations, MRD, Louisiana, 2021, Version 2
This dataset contains water surface elevations at selected point locations generated from the AirSWOT data collected during the Spring and Fall 2021 Delta-X deployments over the Atchafalaya and Terrebonne basins in Louisiana, USA. AirSWOT uses near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The Level 3 (L3) data were created by masking land areas out of the AirSWOT Level 2 products, then filtering and averaging to the AirSWOT heights to produce water surface elevations at selected points throughout the scene. The AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions. AirSWOT performance in the floodplain was limited by the presence of vegetation and the very small slope characteristic of two dimensional floodplain discharge. Therefore, the bulk of the AirSWOT data collections were targeted at the larger channels, since the channel discharge provides the necessary boundary conditions for potential overflow to islands and floodplains. The data are provided in comma-separated values (CSV) format.
Surface Water Elevation and Quality, Peace-Athabasca Delta, Canada, 2006-2007
The Peace-Athabasca Delta (PAD) is a large boreal wetland located in northeastern Alberta, Canada at the confluence of the Peace and Athabasca Rivers with Lake Athabasca (Figures 1 and 2). A Ramsar Convention wetland and UNESCO World Heritage Site, it is among the world's most ecologically significant wetlands. This data set contains four comma-delimited ASCII files, two of which contain water surface elevation site and measurement information and two contain water quality and ancillary parameter location and measurement data for 120 sites within the PAD.Data archived include water surface elevation and water quality parameters measured at points throughout the Delta during summers 2006 and 2007. These data sets were originally collected to improve understanding of hydrologic recharge processes in low-relief environments and to provide ground-based measurements to validate satellite observations of inundation and sediment transport. All work was supported by the NASA Terrestrial Hydrology Program under grant NNG06GE05G to the Department of Geography, University of California-Los Angeles, Los Angeles, California.
Delta-X: In-situ Water Surface Elevation, MRD, Louisiana, USA, 2021
This dataset contains in situ water level measurements collected at 49 different locations across the Atchafalaya and Terrebonne basins in the Mississippi River Delta (MRD) floodplain, and 49 files with the in situ measurements from raw water level converted to absolute water surface elevation with respect to NAVD88 (GEOID12B). There were 65 sites included in the study, however, data from 16 of the sites were corrupted, unretrievable from the instrument or the instrument was lost during deployment. Additionally, it contains water surface elevations collected by GNSS mounted to a boat while underway, and a summary file with site information for all 65 sites. Relative water level measurements were recorded every 15-20 minutes using commercial pressure transducers (Levelogger, Solinst) to measure water depth. Water surface elevation was determined by measuring an absolute height conversion at each sensor location using AirSWOT or a survey-grade global navigation satellite system (GNSS). These water level measurements calibrate and validate the Delta-X campaign's remote sensing observations and hydrodynamic models. The data are provided in comma separated values (CSV) and JPEG image formats.
Delta-X: AirSWOT L2 Geocoded Water Surface Elevation, MRD, LA, 2021, V3
This dataset contains Level 2 (L2) AirSWOT geocoded products, including estimated water surface elevation. The AirSWOT instrument is a Ka-band interferometer and for this study is flown on the King Air B200 platform. Data were collected during the DeltaX airborne campaign over the Atchafalaya and Terrebonne basins of the Mississippi River Delta, Louisiana, USA. Flights occurred during the Delta-X Spring 2021 deployment from 2021-03-26 to 2021-04-18 and the Delta-X Fall 2021 deployment from 2021-08-21 to 2021-09-12. AirSWOT is capable of producing high resolution (3.6 m) digital elevation models over land and water bodies using near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The instrument includes six antennas that form multiple baseline pairs for along-track and across-track interferometry. AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions and is an airborne calibration and validation instrument for the Surface Water and Ocean Topography (SWOT) satellite. This Version 3 dataset provides updated data files due to an updated Calumet survey that changed the water level by 0.138 m. This resulted in all the AirSWOT water levels changing by that same amount. For these L2 products, only the estimated water surface elevation in respect to the WGS84 ellipsoid surface, and estimated height above the NAVD88 (GEOID12B) vertical datum files changed. Note that data acquired on September 1 and September 5, 2021 do not meet the expected MAE in-situ comparison and should be used with caution. This dataset contains cloud optimized GeoTIFF rasters in UTM map coordinates for each flight line. In addition, a text file provides basic metadata, including flight line ID, start and end UTC times of data acquisition, processor version number, and the date and time of different processing stages.
Pre-Delta-X: L2 AirSWOT Water Surface Elevations, Atchafalaya Basin, LA, USA, 2016
This dataset provides water surface elevations over the Wax Lake Delta in the Atchafalaya Basin in coastal Louisiana, USA, in May 2015. These Level 2 (L2) data were collected by AirSWOT, an airborne instrument employing near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data at 3.6 m resolution. Along with elevation estimates, the dataset includes measures of estimation errors, sensitivity, incidence angle, backscatter, and interferometric correlation. For this application, in situ water level data were added into the AirSWOT phase calibration procedure. These L2 data consist of a set of rasters in Universal Transverse Mercator (UTM) map coordinates for each of the 39 AirSWOT flight lines. These elevation data were later used for calculating elevation and slopes along the main channels in this wetland system, as well as tying observations to ocean tidal conditions.
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