This repository contains supplementary data and technical documentation for the research article by Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F., Babu, S., Borrelli, P., Cheng, L., Crochetiere, H., Ehalt Macedo, H., Filgueiras, R., Goichot, M., Higgins, J., Hogan, Z., Lip, B., McClain, M., Meng, J., Mulligan, M., Nilsson, C., Olden, J.D., Opperman, J., Petry, P., Reidy Liermann, C., Saenz, L., Salinas-Rodríguez, S., Schelle, P., Schmitt, R.J.P., Snider, J., Tan, F., Tockner, K., Valdujo, P.H., van Soesbergen, A., Zarfl, C. (2019) Mapping the world's free-flowing rivers. Nature. https://doi.org/10.1038/s41586-019-1111-9.

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 ...

Web Map containing Statutory Main River Map, Statutory Main River Map Variations 2022 and Statutory Main River Variations pre 2021 feature layers.Created for use by Web Mapping Application: Main River Map

No comments recorded for comment period (April 17 to May 16, 2023)Currently, the Lolo National Forest is looking for public input to help inform the preliminary draft wild and scenic river inventory. The Forest is using the Talking Points Collaborative Map to facilitate this effort.The Lolo National Forest is seeking input on (Step 1) the preliminary inventory of all named, free-flowing rivers1. Are there any named, free-flowing rivers or streams missing from the inventory? Help us make sure that this comprehensive inventory is complete!2. Is there a stream included in the inventory that has impoundments, diversions, or other impediments to its natural flow? Describe the location and type of the structure that impacts the stream’s free-flowing nature.3. Is there a stream included in the inventory that has impoundments, diversions, or other impediments to its natural flow that should be excluded from moving into the eligibility evaluation? Describe the location and type of the structure that impacts the stream’s free-flowing nature.The Forest is also looking for input on the draft Evaluation Framework and Outstandingly Remarkable Criteria (Step 2).1. Are there modifications needed to specific ORV criteria currently included in the evaluation framework?2. Should the region of comparison be expanded or compressed or modified for a specific ORV category?3. Are there any additional ORV criteria that should be included in the “Other Resources” section? If so, WhyThis input will be used as the foundation for the next steps in the process.

Statutory Main Rivers Map is a spatial (polyline) dataset that defines statutory watercourses in England designated as Main Rivers by the Environment Agency.

Watercourses designated as ‘main river’ are generally the larger arterial watercourses. The Environment Agency has permissive powers, but not a duty, to carry out maintenance, improvement or construction work on designated main rivers.

All other open water courses in England are determined by statute as an ‘ordinary watercourse’. On these watercourses the Lead Local flood Authority or, if within an Internal Drainage District, the Internal Drainage Board have similar permissive powers to maintain and improve.

This data layer is part of a collection of GIS data created for the Okanagan Mainstem Floodplain Mapping Project. Notes below apply to the entire project data set.***Download Size is 12.5 GBGeneral Notes1. Please refer to the Disclaimer further below.2. Please review the associated project reports before using the floodplain maps: Northwest Hydraulic Consultants Ltd. (NHC). 2020. ‘Okanagan Mainstem Floodplain Mapping Project’. Report prepared for the Okanagan Basin Water Board (OBWB). 31 March 2020. NHC project number 3004430. Northwest Hydraulic Consultants Ltd. (NHC). 2021. ‘Okanagan Mainstem Floodplain Mapping Project – Development of CGVD1928 Floodplain Mapping’. Letter report prepared for the Okanagan Basin Water Board (OBWB). 30 March 2021. NHC project number 3006034.Northwest Hydraulic Consultants Ltd. (NHC). 2022. ‘Supplemental to the Okanagan Mainstem Floodplain Mapping Project – Current Operations Flood Construction Levels for Okanagan and Wood-Kalamalka Lakes’. Report prepared for the Okanagan Basin Water Board (OBWB). Final. 16 August 2022. NHC project number 3006613.3. These floodplain mapping layers delineate flood inundation extents under the specific flood events. Tributaries are not included in mapping.4. The mapped inundation is based on the calculated water level. Freeboard, wind effects, and wave effects have been added to the calculated water level where noted.5. Where noted, a freeboard allowance of 0.6 m has been added to the calculated flood water level. It has been added to account for local variations in water level and uncertainty in the underlying data and modelling.6. Where noted, the FCL (or COFCL) included in lake mapping layers includes an allowance for wind setup and wave runup based on co-occurrence of the seasonal 200-year wind event. The wind and wave effects extend 40 m shoreward to delineate the expected limit of wave effects. Beyond this limit the FCL (or COFCL) is based on inundation of the flood event without wave effects. Wave effects have been calculated based on generalized shoreline profile and roughness for each shoreline reach. Site specific runup analysis by a Qualified Registrant may be warranted to refine the generalized wave effects shown, which could increase or decrease the FCL (or COFCL) by as much as a metre.7. Underlying hydraulic analysis assumes channel and shoreline geometry is stationary. Erosion, deposition, degradation, and aggradation are expected to occur and may alter actual observed flood levels and extents. Obstructions, such as log-jams, local storm water inflows or other land drainage, groundwater, or tributary flows may cause flood levels to exceed those indicated on the maps.8. The Okanagan floodplain is subject to persistent ponding due to poor drainage. Persistent ponding is not covered by the flood inundation mapping.9. For flood level maps (water level and inundation extents):a. Layers for each flood scenario describe inundation extents, water surface elevations, and depths.b. The calculated water level has been extended perpendicular to flow across the floodplain; thus mapping inundation of isolated areas regardless of likelihood of inundation; whether it be from dike failure, seepage, or local inflows. Distant isolated areas may be conservatively mapped as inundated. Site specific judgement by a Qualified Professional is required to determine validity of isolated inundation.c. Filtering was used to remove isolated areas smaller than 100 m2. Holes in the inundation extent with areas less than 100 m2 were also removed. Isolated areas larger than 100 m2 are included in GIS data layers and are shown on maps if they are within 40 metres of direct inundation or within 40 metres of other retained polygons.d. Okanagan Dam breach, dam overtopping, or overtopping and breaching of Penticton Beach were not modelled. Inundation downstream of the Okanagan Dam on the left bank floodplain is based on river modelling with the assumption that Okanagan Lake levels will not overtop Lakeshore Drive and adjacent high ground. For the design flood scenarios, inundation mapping on the right bank of the Okanagan River from the Okanagan Dam downstream to the Highway 97 bridge and Burnaby Avenue is based on additional lake and river modelling. For other flood scenarios, river and lake inundation has been mapped separately and has not been integrated on the right bank. Inundation mapping on the right bank is based on river modelling as far as the most upstream modelled river cross section.10. For flood hazard maps (depth and velocity):a. Layers describe flood water depths and velocities. Depths and velocities are based on the maximum values from three modelled scenarios: all dikes removed, left bank dikes removed, and right bank dikes removed. Depths do not include freeboard.b. All hazard layers were modelled with the same parameters and boundary conditions as the design flood.11. Flood modelling and mapping is based on a digital elevation model (DEM) with the following coordinate system and datum specifications: Universal Transverse Mercator Zone 11-N (UTM Zone 11-N), North American Datum 1983 Canadian Spatial Reference System epoch 2002.0 (NAD83 CSRS (2002.0)), Canadian Geodetic Vertical Datum 2013 (CGVD2013), Canadian Gravimetric Geoid model of 2013 (CGG2013). FCL values are presented on the maps in both CGVD2013 and CGVD1928 vertical datums. CGVD1928 values are based on the following specifications: NAD83 CSRS (2002.0), CGVD1928, Height Transformation version 2.0 epoch 1997 (HTv2.0 (1997)). COFCL and COFCL values are presented only in CGVD2013.12. The accuracy of simulated flood levels is limited by the reliability and extent of water level, flow, and climatic data. The accuracy of the floodplain extents is limited by the accuracy of the design flood flow, the hydraulic model, and the digital surface representation of local topography. Localized areas above or below the mapped inundation maybe generalized. Therefore, floodplain maps should be considered an administrative tool that indicates flood elevations and floodplain boundaries for a designated flood. A qualified professional is to be consulted for site-specific engineering analysis.13. Industry best practices were followed to generate the floodplain maps. However, actual flood levels and extents may vary from those shown. OBWB and NHC do not assume any liability for variations of flood levels and extents from that shown.Data Sources Design flood events are based on hydrologic modelling of the Okanagan River watershed. The hydraulic response is based on a combination of 1D and 2D numerical models developed by NHC using HEC-RAS software, and NHC SWAN models. The hydraulic models are calibrated to the 2017 flood event and validated to the 2018 flood event; due to limits on data availability the hydrologic model is calibrated using data from 1980-2010. The digital elevation model (DEM) used to develop the model and mapping is based on Lidar data collected from March to November 2018 and provided by Emergency Management BC (EMBC), channel survey conducted by WSP in March, April, and June 2019, and additional survey data. See accompanying report for details NHC (2020).DisclaimerThis document has been prepared by Northwest Hydraulic Consultants Ltd. for the benefit of Okanagan Basin Water Board, Regional District of North Okanagan, Regional District of Central Okanagan, Regional District of Okanagan-Similkameen, Okanagan Nation Alliance for specific application to the Okanagan Mainstem Floodplain Mapping Project, Okanagan Valley, British Columbia, Canada (Ellison, Wood, Kalamalka, Okanagan, Skaha, Vaseux, and Osoyoos lakes and Okanagan River from Okanagan Lake to Osoyoos Lake). The information and data contained herein represent Northwest Hydraulic Consultants Ltd. best professional judgment in light of the knowledge and information available to Northwest Hydraulic Consultants Ltd. at the time of preparation, and was prepared in accordance with generally accepted engineering practices.Except as required by law, this document and the information and data contained herein are to be treated as confidential and may be used and relied upon only by Okanagan Basin Water Board, Regional District of North Okanagan, Regional District of Central Okanagan, Regional District of Okanagan-Similkameen, Okanagan Nation Alliance, its officers and employees. Northwest Hydraulic Consultants Ltd. denies any liability whatsoever to other parties who may obtain access to this document for any injury, loss or damage suffered by such parties arising from their use of, or reliance upon, this report or any of its contents.Data Layer List and Descriptions<!--· River / Lake Model Boundary -River / Lake Model Boundary (NHC): Boundary between Okanagan River and Okanagan Lake modelling and mapping areas for design and flood mapping.Recommended Design Flood (gates open): Ellison, Skaha, Vaseux, and Osoyoos lakeso Lake Shoreline Flood Construction Level (FCL) Zone – Recommended Design Flood with Freeboard and Wave Effect (NHC): Zone defined based on approximate shoreline and the wave breaking boundary plus a buffer; FCLs defined by zone along shoreline; shoreline FCLs take precedence over lake inundation FCLs.o Lake Flood Construction Level (FCL) Zone (Inundation Extent) – Recommended Design Flood with Freeboard (NHC): Design flood inundation extent with freeboard. Design event varies by lake, plus wind setup, plus mid-century climate change; plus freeboard 0.6m.o Lake Inundation Extent – Recommended Design Flood without Freeboard (NHC): Design flood inundation extent without freeboard. Design event varies by lake, plus wind setup, plus mid-century climate change.o Depth Grids§ Ellison Lake Depth – Recommended Design without Freeboard (NHC): ELLISON LAKE: 200-YEAR MID-CENTURY. Design flood depth

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) 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 American River near Fair Oaks, CA, acquired in October 2020. Field measurements of water depth available through another data release (Legleiter, C.J., and Harrison, L.R., 2022, Field measurements of water depth from the American River near Fair Oaks, CA, October 19-21, 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P92PNWE5) 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: American_mean-spec.tif, American_mean-depth.tif, American_NN-depth.tif, and American-single-image.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.

Mapping of rivers and non-stream water points in Puy-de-Dôme prepared in accordance with the Government Instruction of 3 June 2015 on the mapping and identification of rivers and their maintenance and the Ministerial Orders of 04/05/2017 and Prefectural of 05/07/2017 on untreated areas.

Based on the definition of the watercourse (constitutes a stream, a flow of running water in a natural bed originally fed by a source and having a sufficient flow of much of the year) and the definition of water points (spray, beef and water body), a mapping project is proposed in the interactive map classifying the hydrographic sections and water surfaces of the IGN TOPO BD into four categories: — watercourses for the application of Articles L214-1 to L214-6 of the Environmental Code — the sections that need to be examined to determine whether they meet the definition of watercourse — non-stream water points for which an untreated area is to be set up — non-stream sections that need to be examined to determine whether they meet the definition of a water point within the meaning of the untreated area

Based on the definition of the watercourse (constitutes a stream, a flow of running water in a natural bed originally fed by a source and having a sufficient flow of much of the year) and the definition of water points (spray, beef and water body), a mapping project is proposed in the interactive map classifying the hydrographic sections and water surfaces of the IGN TOPO BD into four categories: — watercourses for the application of Articles L214-1 to L214-6 of the Environmental Code — the sections that need to be examined to determine whether they meet the definition of watercourse — non-stream water points for which an untreated area is to be set up — non-stream sections that need to be examined to determine whether they meet the definition of a water point within the meaning of the untreated area

National Hydrologic Dataset downloaded from USGS on 2/4/2022. This data is also available from the USGS as a service at https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServerAbstract: The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee. Use the metadata link, http://nhdgeo.usgs.gov/metadata/nhd_high.htm, for additional information. Purpose: The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.

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.

Use this map to explore spatial data in the American River watershed. To add additional data: (1) click Modify Map; (2) then click Add; (3) then click Search for Layers; and (4) in the Sierra Nevada Conservancy search box, type American River Watershed to find extra data.

This dataset comprises river centrelines, digitised from OS 1:50,000 mapping. It consists of four components: rivers; canals; surface pipes (man-made channels for transporting water such as aqueducts and leats); and miscellaneous channels (including estuary and lake centre-lines and some underground channels). This dataset is a representation of the river network in Great Britain as a set of line segments, i.e. it does not comprise a geometric network.

These maps have been produced to meet SEPA’s duty to publish flood hazard maps as set out in the Flood Risk Management (Scotland) Act 2009. The maps show where there is a risk of flooding from the sea, from rivers and from surface water.The following probabilities are available for river flooding: - High - 10 year return period - Medium - 200 year return period - Low - 1000 year return period and 200 year return period plus climate change using the UKCP09 high emissions scenario for the 2080s.The river hazard maps show (where available): - Flood extent - Flood depth - Flood velocities where appropriate. The climate change scenario has been defined by United Kingdom Climate Projection 2009 (UKCP09) predictions for 2080 high emissions 95%ile predictions. Velocity is presented, where appropriate; this is determined by considering the confidence in input data, modelling method and impact. It is currently represented as one of four bandsMedium and low probability flood events were selected for consistency with return periods used in Scottish Planning Policy, whereas the high probability was chosen as it is reflective of observed events experienced over the last few decades.

Mosaic of old river maps in ECW made from old river maps that have been scanned. After this, the leaf edges are removed and the images are georeferenced in RD. After this, a mosaic was made in ECW format for each print, series or revision. In a corresponding index file (shape) you can find out which year each individual card is.

Map of the rivers the Upper Rhine, the Waal, the Merwede, the Oude and part of the Nieuwe Maas from Lobith to Brielle: in twenty sheets in addition to two supplementary sheets for the Dordtsche Kil / manufactured by order of his Excellency the Minister of the Interior, under the direction of the Chief Engineer at the General Service of the Water Management B.H. Goudriaan. - Scale 1:10,000. - [Delft]: General Department of Water Management, 1830-1835. ([Delft] : the Office and the printing works of the Directorate of Military Reconnaissance). - 1 map series, in 27 sheets: lithography; various formats. A number of sheets of the first series of the river map of the Upper Rhine exist with "Normal Lines Gelderland" in handwriting. On these sheets the results of the bank measurements in 1850-1851 and 1872-1873 are written in manuscript. Three additional map sheets are kept with the depositor of this river map, produced in 1863, on which the river positions and emergency levels along the Dutch main rivers are indicated.

This is a view service of the CEH 1:50k rivers dataset. This is a river centreline network, based originally on OS 1:50,000 mapping. There are four layer: rivers; canals; surface pipes (man-made channels such as aqueducts and leats) and miscellaneous channels (including estuary and lake centre-lines and some underground channels).The dataset was produced within a long-term project of the Institute of Hydrology (now CEH) between the mid-1970s and the late 1990s. The project digitised, (either manually or using 'laser scanners') the "blue line" layer of the Ordnance Survey's 1:50,000 2nd series (Landranger) maps. The dataset consists of all the single blue lines from the source maps, plus centre-lines from double sided rivers, lakes and estuaries. All gaps in the source material have been closed, using local knowledge where necessary, to give a river network that is continuous from source to mouth

U.S. Geological Survey (USGS) and Virginia Institute of Marine Science (VIMS) scientists conducted field data collection efforts during June 11th - 16th, 2020, using a combination of remote sensing technologies to map riverbank and wetland topography and vegetation at five sites in the Chesapeake Bay Region of Virginia. The five sites are located along the James, Severn, and York Rivers. The work was initiated to evaluate the utility of different remote sensing technologies in mapping river bluff and wetland topography and vegetation for change detection and sediment transport modeling. The USGS team collected Global Navigation Satellite System (GNSS), total station, and ground based lidar (GBL) data while the VIMS team collected aerial imagery using an Unmanned Aerial System (UAS). This data release contains shapefiles of the processed GNSS and total station data, point clouds in the form of lidar data exchange (las) files from the ground lidar data and aerial imagery produced via Structure from Motion (SfM).

This data is the reference for all planning actors and farmers (government instruction of 3 June 2015). It is the backstop of the State services for the investigation of cases under the Environmental Code and in particular for the Water Act. It is also the case for all agricultural regulations as well as the CAP aid cross-compliance rules (GAEC). The layer is called N_COURS_EAU_LOIEAU_L_044.

The data relating to the mapping of rivers in the Loire-Atlantique subject to the law on water and agricultural regulations is a composite data formed in part and initially by the resumption of the river inventories conducted by the SAGEs “Estuaire de la Loire” and “Vilaine”. 75 % of the departmental territory is concerned.

Of the remaining 25 %, the mapping was carried out under the control of DDTM 44 in partnership with the actors in the territory: Chamber of Agriculture, AFB, SAGE-bearing structures, river unions, managers, communities.

Please note: — The data includes the tertiary marshes networks which are subject to all regulations except headings 3110, 3120, 3130, 3140 and 3210 of the Water Act; — inconsistencies may exist at the boundaries of departments.

This water flow network dataset is a route feature class rather than a simple polyline. The geometry is generated by merging the river lines of individual geometric network datasets. This layer contains an integrated flow network that includes known flow connections through rivers, lakes and groundwater aquifers. In places where the network is depicted flowing through lakes or through underground channels, the flow channels are schematic only, and do not represent the precise location of these flow channels. The appropriate Geological Survey Ireland data sets should be consulted where underground flows or connections are known or suspected.For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/c4043e19-38ec-4120-a588-8cd01ac94a9c

Four digital water-surface profile maps for a 14-mile reach of the Mississippi River near Prairie Island in Welch, Minnesota from the confluence of the St. Croix River at Prescott, Wisconsin to upstream of the United States Army Corps of Engineers (USACE) Lock and Dam No. 3 in Welch, Minnesota, were created by the U.S. Geological Survey (USGS) in cooperation with the Prairie Island Indian Community. The water-surface profile maps depict estimates of the areal extent and depth of inundation corresponding to selected water levels (stages) at the USGS streamgage Mississippi River at Prescott, Wisconsin (USGS station number 05344500). Current conditions for estimating near-real-time areas of water inundation by use of USGS streamgage information may be obtained on the internet at http://waterdata.usgs.gov/. Water-surface profiles were computed for the stream reach using HEC-GeoRAS software by means of a one-dimensional step-backwater HEC-RAS hydraulic model using the steady-state flow computation option. The hydraulic model used in this study was previously created by the USACE . The original hydraulic model previously created extended beyond the 14-mile reach used in this study. After obtaining the hydraulic model from USACE, the HEC-RAS model was calibrated by using the most current stage-discharge relations at the USGS streamgage Mississippi River at Prescott, Wisconsin (USGS station number 05344500). The hydraulic model was then used to determine four water-surface profiles for flood stages referenced to 37.00, 39.00, 40.00, and 41.00-feet of stage at the USGS streamgage on the Mississippi River at Prescott, Wisconsin (USGS station number 05344500). The simulated water-surface profiles were then combined with a digital elevation model (DEM, derived from light detection and ranging (LiDAR) in Geographic Information System (GIS) data having a 0.35-foot vertical and 1.97-foot root mean square error horizontal resolution) in order to delineate the area inundated at each stage. The calibrated hydraulic model used to produce digital water-surface profile maps near Prairie Island, as part of the associated report, is documented in the U.S. Geological Survey Scientific Investigations Report 2021-5018 (https://doi.org/10.3133/ sir20215018). The data provided in this data release contains three zip files: 1) MissRiverPI_DepthGrids.zip, 2) MissRiverPI_InundationLayers.zip, and 3) ModelArchive.zip. The MissRiverPI_DepthGrids.zip and MissRiverPI_InundationLayers.zip files contain model output water-surface profile maps as shapefiles (.shp) and Keyhole Markup Language files (.kmz) that can be opened using Esri GIS systems (.shp files) or Google Earth (.kmz files), while the ModelArchive.zip contains model inputs, outputs, and calibration data used in creating the water-surface profiles maps.

A slow-moving area of low pressure and a high amount of atmospheric moisture produced heavy rainfall across Louisiana and southwest Mississippi in August 2016. Over 31 inches of rain was reported in Watson, 30 miles northeast of Baton Rouge, over the duration of the event. The result was major flooding that occurred in the southern portions of Louisiana and included areas surrounding Baton Rouge and Lafayette along rivers such as the Amite, Comite, Tangipahoa, Tickfaw, Vermilion, and Mermentau. The U.S. Geological Survey (USGS) Lower Mississippi-Gulf Water Science Center operates many continuous, streamflow-gaging stations in the impacted area. Peak streamflows of record were measured at 10 locations, and seven other locations experienced peak streamflows ranking in the top 5 for the duration of the period of record. In August 2016, USGS personnel made fifty streamflow measurements at 21 locations on streams in Louisiana. Many of those streamflow measurements were made for the purpose of verifying the accuracy of the stage-streamflow relation at the associated gaging station. USGS personnel also recovered and documented 590 high-water marks after the storm event by noting the location and height of the water above land surface. Many of these high water marks were used to create twelve flood-inundation maps for selected communities of Louisiana that experienced flooding in August 2016. This data release provides the actual flood-depth measurements made in selected river basins of Louisiana that were used to produce the flood-inundation maps published in the companion product (Watson and others, 2017). Reference Watson, K.M., Storm, J.B., Breaker, B.K., and Rose, C.E., 2017, Characterization of peak streamflows and flood inundation of selected areas in Louisiana from the August 2016 flood: U.S. Geological Survey Scientific Investigations Report 2017–5005, 26 p., https://doi.org/10.3133/sir20175005.