Information on water depth in river channels is important for a number of applications in water resource management but can be difficult to obtain via conventional field methods, particularly over large spatial extents and with the kind of frequency and regularity required to support monitoring programs. Remote sensing methods could provide a viable alternative means of mapping river bathymetry (i.e., water depth). The purpose of this study was to develop and test new, spectrally based techniques for estimating water depth from satellite image data. More specifically, a neural network-based temporal ensembling approach was evaluated in comparison to several other neural network depth retrieval (NNDR) algorithms. These methods are described in a manuscript titled "Neural Network-Based Temporal Ensembling of Water Depth Estimates Derived from SuperDove Images" and the purpose of this data release is to make available the depth maps produced using these techniques. The images used as input were acquired by the SuperDove cubesats comprising the PlanetScope constellation, but the original images cannot be redistributed due to licensing restrictions; the end products derived from these images are provided instead. The large number of cubesats in the PlanetScope constellation allows for frequent temporal coverage and the neural network-based approach takes advantage of this high density time series of information by estimating depth via one of four NNDR methods described in the manuscript: 1. Mean-spec: the images are averaged over time and the resulting mean image is used as input to the NNDR. 2. Mean-depth: a separate NNDR is applied independently to each image in the time series and the resulting time series of depth estimates is averaged to obtain the final depth map. 3. NN-depth: a separate NNDR is applied independently to each image in the time series and the resulting time series of depth estimates is then used as input to a second, ensembling neural network that essentially weights the depth estimates from the individual images so as to optimize the agreement between the image-derived depth estimates and field measurements of water depth used for training; the output from the ensembling neural network serves as the final depth map. 4. Optimal single image: a separate NNDR is applied independently to each image in the time series and only the image that yields the strongest agreement between the image-derived depth estimates and the field measurements of water depth used for training is used as the final depth map. MATLAB (Version 24.1, including the Deep Learning Toolbox) source code for performing this analysis is provided in the function NN_depth_ensembling.m available on the main landing page for the data release of which this is a child item, along with a flow chart illustrating the four different neural network-based depth retrieval methods. To develop and test this new NNDR approach, the method was applied to satellite images from the Colorado River near Lees Ferry, AZ, acquired in March and April of 2021. Field measurements of water depth available through another data release (Legleiter, C.J., Debenedetto, G.P., and Forbes, B.T., 2022, Field measurements of water depth from the Colorado River near Lees Ferry, AZ, March 16-18, 2021: U.S. Geological Survey data release, https://doi.org/10.5066/P9HZL7BZ) were used for training and validation. The depth maps produced via each of the four methods described above are provided as GeoTIFF files, with file name suffixes that indicate the method employed: Colorado_mean-spec.tif, Colorado_mean-depth.tif, Colorado_NN-depth.tif, and Colorado-single-image.tif. In addition, to assess the robustness of the Mean-spec and NN-depth methods to the introduction of a large pulse of sediment by a flood event that occurred partway through the image time series, depth maps from before and after the flood are provided in the files Colorado_Mean-spec_after_flood.tif, Colorado_Mean-spec_before_flood.tif, Colorado_NN-depth_after_flood.tif, and Colorado_NN-depth_before_flood.tif. The spatial resolution of the depth maps is 3 meters and the pixel values within each map are water depth estimates in units of meters.

Information on water depth in river channels is important for a number of applications in water resource management but can be difficult to obtain via conventional field methods, particularly over large spatial extents and with the kind of frequency and regularity required to support monitoring programs. Remote sensing methods could provide a viable alternative means of mapping river bathymetry (i.e., water depth). The purpose of this study was to develop and test new, spectrally based techniques for estimating water depth from satellite image data. More specifically, a neural network-based temporal ensembling approach was evaluated in comparison to several other neural network depth retrieval (NNDR) algorithms. These methods are described in a manuscript titled "Neural Network-Based Temporal Ensembling of Water Depth Estimates Derived from SuperDove Images" and the purpose of this data release is to make available the depth maps produced using these techniques. The images used as ...

The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 104 degrees west longitude. The aquifer underlies about 175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. The Republican River Basin is about 25,000 square miles and is located in northeast Colorado, northern Kansas, and southwest Nebraska. The Republican River Basin overlies the High Plains aquifer for 87 percent of the basin area. This dataset consists of a raster of water-level changes for the High Plains aquifer, in the Republican River Basin, 2002 to 2015. This digital dataset was created using water-level measurements from (1) 977 wells, which are located in the Republican River Basin, and (2) 546 wells, which are located within 20 miles outside the boundary of the Republican River Basin. These 1,523 wells were measured in both 2002 and in 2015. The map was reviewed for consistency with the relevant data at a scale of 1:1,000,000.

The collection of water quality data has been an integral part of the International Boundary and Water Commission's mission and goal since the signing of the 1944 Water Treaty. The IBWC collects water quality data for several transboundary rivers, the Rio Grande, Colorado River, New River, Alamo River, and the Tijuana River, along with stations in the Pacific Ocean known as the South Bay Ocean Outfall Water Quality Monitoring Program (Pacific Ocean). The data is collected and exchanged between the United States and Mexico as agreed to under the IBWC 1944 Water Treaty and the subsequent agreements made by the IBWC to implement the various water quality monitoring programs along the border. Water quality goals for each program are either specified in an IBWC Minute (such as Minute No. 264 for New River), or compared to water quality standards using United States or Mexican standards for rivers and streams.

Data layers in this map are based on georeferenced data from the EPA Community Water System Survey (2006) and various data from US Census Bureau.

The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 104 degrees west longitude. The aquifer underlies about 175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This dataset consists of a raster of water-level changes for the High Plains aquifer, predevelopment (about 1950) to 2011. This digital dataset was created using water-level measurements from 3,322 wells measured in both the predevelopment period (about 1950) and in 2011 and using other published information on water-level change in areas with few water-level measurements. The map was reviewed for consistency with the relevant data at a scale of 1:1,000,000.

Aggregated from thousands of local jurisdictions by the Colorado Department of Local Affairs (DOLA) Demography office. Many of the district boundaries were created from scanned drawings or digitized PDFs, and therefore no guarantee of accuracy can be made for the data.

This United States Geological Survey (USGS) web map displays the National Watershed Boundary Dataset (WBD). It defines the perimeter of drainage areas formed by the terrain and other landscape characteristics. The drainage areas are nested within each other so that a large drainage area (Upper Mississippi River), will be composed of multiple smaller drainage areas like the Wisconsin River. Each of these smaller areas can be further subdivided into subsequently smaller drainage areas.The intent of defining hydrologic units (HU) for the WBD is to establish a base-line drainage boundary framework, accounting for all land and surface areas. The WBD is a comprehensive aggregated collection of HU data consistent with the national criteria for delineation and resolution. Each HU is identified by a unique hydrologic unit code (HUC). This service includes HU boundaries for HUC2 (Hydrologic unit boundary), HUC4 (Region), HUC6 (Subregion), HUC8 (Basin), HUC10 (Sub-basin) and HUC12 (Watershed). Pop-ups include HUC name, HUC code and the states that are included in each HU.More information about the WBD can be found at the WBD information site.Click here for information on the Federal Standards and Procedures for the National Watershed Boundary Dataset.Data for this service can be found here._Other Federal User Community federally focused content that may interest youDepartment of the Interior U.S Geological Survey

The Babbitt Center for Land and Water Policy, a center of the Lincoln Institute of Land Policy, has released a comprehensive, peer-reviewed map of the Colorado River Basin that showcases the area’s geography and hydrography while addressing inconsistencies found among current maps of the region. The map also includes a narrative history of the basin, and it highlights crucial concerns facing the region. It will provide an updated resource to stakeholders in the Colorado River Basin as they chart a sustainable path forward for the Colorado River, which supports over 40 million people across the United States and Mexico and irrigates 4.5 million acres of agriculture.The Babbitt Center produced the printed map in partnership with the Lincoln Institute’s newly launched Center for Geospatial Solutions, which harnesses data to inform decision making related to land and water management. The full-color, double-sided map highlights specific regions and issues of note in one of the fastest-growing areas in the United States. Features include:A physical and political map of the entire Colorado River Basin, including the location of the 30 federally recognized tribal nations in the basin; structures such as dams, reservoirs, transbasin diversions, and canals; protected areas; and indications of whether streams are perennial or intermittent.Inset maps spotlighting wildfire risk, the Colorado River Delta in Mexico, the shrinking Salton Sea, and the relationship between urban development, irrigated agriculture, and water management in major cities.Stunning photographs of the Colorado River headwaters and Delta, Lake Powell, the Imperial Valley, and other significant landmarks of the region.Narrative explorations of key issues in the Colorado River Basin, including climate change, tribal water rights, wildfire, development, agriculture, and biodiversity.Historical information on the division of water among the U.S. states and Mexico and the drought contingency negotiations that have occurred during the first two decades of the 21st century as climate change threatens significant streamflow losses."Click here to learn more at the Lincoln Data Website"

The USGS compiles online access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands.

This digital data set consists of contours for predevelopment water-level elevations for the High Plains aquifer in the central United States. The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 106 degrees west longitude. The outcrop area covers 174,000 square miles and is present in Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital data set was created by digitizing the contours for predevelopment water-level elevations from a 1:1,000,000-scale base map created by the U.S. Geological Survey High Plains Regional Aquifer-System Analysis (RASA) project (Gutentag, E.D., Heimes, F.J., Krothe, N.C., Luckey, R.R., and Weeks, J.B., 1984, Geohydrology of the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming: U.S. Geological Survey Professional Paper 1400-B, 63 p.) The data are not intended for use at scales larger than 1:1,000,000.

The dataset consists of a shapefile of measurements of surface velocity magnitude and direction at the Colorado River at Compact Point near Lees Ferry, AZ, on March 18, 2021. The dataset contains approximately 1.2 km of river length. The surface velocity measurements were made by applying Large-Scale Particle Image Velocimetry (LSPIV) techniques, using overlapping videos collected by small Unmanned Aircraft Systems (sUAS). Total time to capture all videos was less than one hour, and all frames (except frame 1, see Process Steps below) from all videos were used. Additional attributes, including divergence, curl, shear, and strain, were calculated from the surface velocity measurements and are included in the dataset.

This catalog visualizes locations of streamgages and precipitation measurements around the Colorado River Basin states located the Southwest United States. The goal of this catalog is to provide information to stakeholders, increase effective management of resources, and help establish protocols for future data collection.

This map is interactive so you can scroll over each point and view metadata about the gage. You can use the filters on the bar to the right of the map to search for specific agencies, types of gages, and whether they are currently operating or inactive. To access the links associated with gages, click on "view data" and copy link from table that is shown.

This catalog is not an exhaustive list of all gages. Some private organizations were not able to share gages that they operate and tribal communities that may operate gages were not contacted to respect the privacy of their local government operations and information.

This is an on-going project, additional updates will be made to this map as new gages are obtained and cataloged. We are currently working on collecting and adding data for California.

Please reach out to us with an questions, comments, or feedback at AZStreamCat@list.arizona.edu

Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt. Dataset SummaryThe GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available.This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

As part of a High Flow Event protocol, the Bureau of Reclamation conducts periodic, and relatively high, water releases. This map highlights modeled flows created by the U.S. Geological Survey (Magirl and others, 2008) to help visualize the stage-discharge relationship in conjunction with other map layers such as river miles and river campsites.Modeling Water-Surface Elevations and Virtual Shorelines for the Colorado River in Grand Canyon, ArizonaScientific Investigations Report 2008-5075Citation:Magirl. Christopher, F.N., Webb Robert, Griffiths Peter, 2008, Modeling Water-Surface Elevations and Virtual Shorelines for the Colorado River in Grand Canyon, Arizona, U.S.Geological Survey Scientific Investigations Report 2008-5075, 32p

A Bell 407 helicopter with a gyro-stabilized gimbal was used to collect aerial videos of Upper Colorado River Water Science Basin (IWS) riverine study sites in 2022. Videos were collected using both natural color and thermal infrared cameras. These videos were used to determine the feasibility of estimating river surface velocity using aerial imagery. Photogrammetry techniques were used with the natural color video images to produce an orthomosaic map of the study reach.

This data set was developed for salinity yield modeling in the Upper Colorado River Basin in preparation of the paper "Salinity yield modeling of the Upper Colorado River Basin using 30-meter resolution soil maps and machine learning" that is to be submitted to Water Resources Research. A github repository was also prepared to document the use of this data in the paper, and is available at https://github.com/naumi421/UCRB_Salinity.

Please see the included file "README_SalinityYieldModel_documentation_initial_table_ReviewData.docx" for detailed descriptions of all included files.

These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.

Data provided by Joel Sholtes – Colorado Mesa University.Polygon river margins traced from Mesa County air photos between 1937 and 2020. Margins are a snapshot in time and are representative only of the date that the air photo was taken.

No Publication Abstract is Available

Division of Water Resources (DWR) Current Surface Water Conditions. This is a list of all remote monitored stream, diversion, and reservoir gages within the state of Colorado.