Water data

The Wetlands Data Layer is the product of over 45 years of work by the National Wetlands Inventory (NWI) and its collaborators and currently contains more than 35 million wetland and deepwater features. This dataset, covering the conterminous United States, Hawaii, Puerto Rico, the Virgin Islands, Guam, the major Northern Mariana Islands and Alaska, continues to grow at a rate of 50 to 100 million acres annually as data are updated. **NOTE:** Due to the variation in use and analysis of this data by the end user, each state's wetlands data extends beyond the state boundary. Each state includes wetlands data that intersect the 1:24,000 quadrangles that contain part of that state (1:2,000,000 source data). This allows the user to clip the data to their specific analysis datasets. Beware that two adjacent states will contain some of the same data along their borders. For more information, visit the National Wetlands Inventory homepage. ## STAC Metadata In addition to the `zip` asset in every STAC item, each item has its own assets unique to its wetlands. In general, each item will have several assets, each linking to a geoparquet asset with data for the entire region or a sub-region within that state. Use the `cloud-optimized` role to select just the geoparquet assets. See the Example Notebook for more.

Census Current (2020) Physical Features Web Map Service; January 1, 2020 vintage

Polygon features representing areal hydrography such as lakes and ponds in the United States, published by the US Census Bureau. Each feature is a labeled water body, with attributes including name, area of land and water, and geographic coordinates.

There are a number of other scenic and amenity areas in Co. Monaghan that require protection from inappropriate and insensitive development. These areas are designated as Areas of Secondary Amenity Value and are generally associated with river valleys, uplands, woodlands and lakes and provide an important community, recreational and tourism resource. It is an objective to manage development in these areas to ensure that the scenic value is maintained and ensure any development proposals are sensitively designed and compatible with the overall landscape character of the area. The Areas of Secondary Amenity Value are listed in Table 6.6 of Monaghan County Council Development Plan 2025 - 2031. This data is in ITM Projection. Monaghan County Council provides this information with the understanding that it is not guaranteed to be accurate, correct or complete. Monaghan County Council accepts no liability for any loss or damage suffered by those using this data for any purpose.

This Collection provides Sentinel-3 SRAL Level-2 Land Altimetry Hydrology products, which contains surface topography estimations of lakes and rivers.

Le Conseil départemental réalise chaque année deux séries de mesures qui présentent le trafic moyen journalier enregistré sur les routes du département : l’une pour les comptages permanents et l’autre pour les comptages temporaires. Ainsi, le recueil de ces données permet au gestionnaire de la voirie départementale d’affiner ses analyses routières dans le cadre de la réalisation de projets et de l’entretien du patrimoine routier. Ces mesures peuvent également venir en appui aux autres collectivités soucieuses de l’impact de la circulation sur leur territoire ainsi qu’aux usagers particuliers (problématiques riveraines, commerciales, etc.).

The Kentucky SPARROW (SPAtially Referenced Regressions On Watershed Attributes) model estimates annual nitrogen and phosphorus loads (concentrations) for stream reaches throughout the state based on data from 40 monitored stations in Kentucky and Tennessee. Approximately 300 land use, municipal, and natural resource variables were evaluated in order to identify the significant contributing factors of nitrogen and phosphorus to our streams. The SPARROW model is a non-linear model that estimates the magnitude and significance of source and delivery variables for the downstream end of each stream segment (reach) based on measured data at monitored sites. The model then sums the nutrient load within each reach with those from the upstream reaches. The results presented here are from an adjusted model - this means that measured data for monitored reaches were included in the final model and used to adjust the model at each monitored reach and thereby improve the accuracy of the estimated nutrient concentrations. Consequently, the model is most accurate immediately downstream of a monitored reach. Conversely, the largest accumulated error is in reaches immediately upstream of a monitored reach. Data are reported with 90% lower and upper confidence bounds. For nitrogen, the sources were identified as agricultural land use (pasture plus cultivated land areas - NLCD 1992), atmospheric deposition of ammonium and nitrate (NADP), and wastewater (Hoos, 2007). Delivery of the atmospheric deposition is controlled by how water moves through the soil (soil permeability - STATSGO). In addition, there is depletion of stream nitrogen in the state's reservoirs (as estimated by the model). This nitrogen model has a yield R2 (accounting for the size of each drainage area) of 0.89. For phosphorus, the sources were identified as pasture (NLCD), soil phosphorus abundance (Karathanasis, 2006), and wastewater (Hoos, 2007). Delivery of phosphorus from pasture lands is related to a function of infiltration excess overland flow (Wolock, 2003). This phosphorus model has a yield R2 of 0.65. Questions? tnwillia@usgs.gov Download Link: https://ky.box.com/v/kymartian-nitrogen-phosporus

Glacier polygons representing glacier areas. Each row is a polygon with attributes for name, area, and centroid coordinates. Published by the US Census Bureau for the United States.

Base topografica digitale realizzata dalla Regione Umbria  utilizzando i tipi foto incisi separati in edizione originale della Carta Topografica Regionale 1:100.000 di proprietà  della Regione Umbria, elaborata sulla base dei tipi della carta 1:100.000 dell'Istituto Geografico Militare.   Aggiornamento topografico delle infrastrutture varie principali eseguito sulla base dei dati relativi al DBPrior 10k e successivi aggiornamenti della Regione Umbria anno 2010.  Aggiornamento espansione urbana sulla base dei dati della carta GEOBOTANICA della Regione Umbria anno 1992-1994.

Census Current (2020) Physical Features Web Map Service; January 1, 2020 vintage

Dates of Images: 4/30/2024, 5/7/2024, 5/12/2024 Date of Next Image: Varies by region, typically 12 days since previous pass. Summary: The Alaska Satellite Facility has developed surface water extent products of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument. These images can be used to see where water is located at the time of the satellite overpass. This product shows all water detected and does not differentiate between normal water and flood water. To determine where flooding may have occurred, combine this layer with a reference water layer. The water extent difference maps shown here were created by subtracting the water extent of the first date from the water extent of the second date to show what changes, if any, occurred in the water extent. Suggested Use: Water extent difference: Light Blue: Water Present in the Second Date Only Dark Blue: Water Present in Both Dates Orange: Water Present in the First Date Only Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A satellite Resolution: 30 meters Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=b112fbd0d5904b229c4e1f7df11484f8 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_TX/2408_sentinel1_water/ImageServer/WMSServer

Dates of Images: 5/2/2024, 5/4/2024 Date of Next Image: Varies by region, typically 12 days since previous pass. Set time slider to most recent interval and click on area of interest to identify date of last pass. Summary: The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composites and surface water extent products of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the flooding event. Sentinel-1 RGB Decomposition of RTC VV and VH imagery over United States coastlines. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). To identify the date of an image either set the time slider to a 1 day interval or zoom in to AOI, set time slider to desired range and click on the imagery. The name may contain a full date and time in a format like this example: S1A_IW_20210705T231453_DVR_RTC30_G_gpufed_27F4 The date and time would be 07/05/2021 at 23:14:53 UTC. Suggested Use: In this image, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas. Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A/B satellite NOTE: Sentinel-1B is no longer acquiring data and is only available into December 2021 Resolution: 30 meters Esri REST Endpoint: See direct subsetted information on the link the to the right with WMS options. RGB Product: https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RGB/ImageServer RTC Product: VV - https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RTC_VV/ImageServer VH - https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RTC_VH/ImageServer Surface Water Extent Product: https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_WM/ImageServer WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_BRAZIL/2407_sentinel1/ImageServer/WMSServer Data Download: Data can be downloaded via the Pop-Ups in the Web Map or through each service's attribute table.

Date of Images: 5/24/2022 Date of Next Image: Unknown Summary: Scientists at NASA's Marshall Space Flight Center created these water extents using Landsat imagery. These images can be used to see where open water is visible at the time of the satellite overpass. This product shows all water detected and differentiates between normal water areas and some flooded areas. This product was classified using the ESA Worldview. It's important to note that all flooded areas may not be captured do to the sensors limitations of not being able to "see" through vegetation and buildings. To determine where additional flooding may have occurred, combine this layer with other data sets. Suggested Use: This product shows water that is detected by the sensor with different colors indicating different land cover/land use classifications from CDL that appear to have water and are potentially flooded. Blue (1): Known Water Red (2): Flooded Developed Green (3): Flooded Vegetation Orange (4): Flooded Cropland/Grassland Gray (5): Clouds/Cloud Shadow (0): No Data Satellite/Sensor: Landsat Resolution: 30 meters Credits: NASA Disasters Program, Includes copyrighted material of Planet Labs PBC. All rights reserved. Esri REST Endpoint: See URL section on the right side of page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_landsat_WaterExtent/MapServer/WMSServer

The ECMWF catalog of real-time products offers real-time meterological and oceanographic productions from the ECMWF forecast system. Users should consult the ECMWF Forecast User Guide for detailed information on each of the products. ## Overview of products The following diagram shows the publishing schedule of the various products. The vertical axis shows the various products, defined below, which are grouped by combinations of `stream`, `forecast type`, and `reference time`. The horizontal axis shows *forecast times* in 3-hour intervals out from the reference time. A black square over a particular forecast time, or step, indicates that a forecast is made for that forecast time, for that particular `stream`, `forecast type`, `reference time` combination. * **stream** is the forecasting system that produced the data. The values are available in the `ecmwf:stream` summary of the STAC collection. They are: * `enfo`: ensemble forecast, atmospheric fields * `mmsf`: multi-model seasonal forecasts fields from the ECMWF model only. * `oper`: high-resolution forecast, atmospheric fields * `scda`: short cut-off high-resolution forecast, atmospheric fields (also known as "high-frequency products") * `scwv`: short cut-off high-resolution forecast, ocean wave fields (also known as "high-frequency products") and * `waef`: ensemble forecast, ocean wave fields, * `wave`: wave model * **type** is the forecast type. The values are available in the `ecmwf:type` summary of the STAC collection. They are: * `fc`: forecast * `ef`: ensemble forecast * `pf`: ensemble probabilities * `tf`: trajectory forecast for tropical cyclone tracks * **reference time** is the hours after midnight when the model was run. Each stream / type will produce assets for different forecast times (steps from the reference datetime) depending on the reference time. Visit the ECMWF's User Guide for more details on each of the various products. Assets are available for the previous 30 days. ## Asset overview The data are provided as GRIB2 files. Additionally, index files are provided, which can be used to read subsets of the data from Azure Blob Storage. Within each `stream`, `forecast type`, `reference time`, the structure of the data are mostly consistent. Each GRIB2 file will have the same data variables, coordinates (aside from `time` as the *reference time* changes and `step` as the *forecast time* changes). The exception is the `enfo-ep` and `waef-ep` products, which have more `step`s in the 240-hour forecast than in the 360-hour forecast. See the example notebook for more on how to access the data. ## STAC metadata The Planetary Computer provides a single STAC item per GRIB2 file. Each GRIB2 file is global in extent, so every item has the same `bbox` and `geometry`. A few custom properties are available on each STAC item, which can be used in searches to narrow down the data to items of interest: * `ecmwf:stream`: The forecasting system (see above for definitions). The full set of values is available in the Collection's summaries. * `ecmwf:type`: The forecast type (see above for definitions). The full set of values is available in the Collection's summaries. * `ecmwf:step`: The offset from the reference datetime, expressed as ``, for example `"3h"` means "3 hours from the reference datetime". * `ecmwf:reference_datetime`: The datetime when the model was run. This indicates when the forecast *was made*, rather than when it's valid for. * `ecmwf:forecast_datetime`: The datetime for which the forecast is valid. This is also set as the item's `datetime`. See the example notebook for more on how to use the STAC metadata to query for particular data. ## Attribution The products listed and described on this page are available to the public and their use is governed by the Creative Commons CC-4.0-BY license and the ECMWF Terms of Use. This means that the data may be redistributed and used commercially, subject to appropriate attribution. The following wording should be attached to the use of this ECMWF dataset: 1. Copyright statement: Copyright "© [year] European Centre for Medium-Range Weather Forecasts (ECMWF)". 2. Source www.ecmwf.int 3. License Statement: This data is published under a Creative Commons Attribution 4.0 International (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/ 4. Disclaimer: ECMWF does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use. 5. Where applicable, an indication if the material has been modified and an indication of previous modifications. The following wording shall be attached to services created with this ECMWF dataset: 1. Copyright statement: Copyright "This service is based on data and products of the European Centre for Medium-Range Weather Forecasts (ECMWF)". 2. Source www.ecmwf.int 3. License Statement: This ECMWF data is published under a Creative Commons Attribution 4.0 International (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/ 4. Disclaimer: ECMWF does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use. 5. Where applicable, an indication if the material has been modified and an indication of previous modifications ## More information For more, see the ECMWF's User Guide and example notebooks.

This item is deprecated.  Please refer to https://hub.arcgis.com/maps/NBDNR::nbhn-named-features-nbhn-0000-nf-0-nbhn-0000-nf-2-and-nbhn-0000-names/about?locale=en for updated data Cet article est obsolète. Veuillez consulter https://hub.arcgis.com/maps/NBDNR::nbhn-named-features-nbhn-0000-nf-0-nbhn-0000-nf-2-and-nbhn-0000-names/about?locale=fr pour des données à jour Layers and table represent features with a known name identified as part of the creation of the NBHN. Point Layer - NBHN_0000_NF_0Polygon Layer - NBHN_0000_NF_2Typonomic Names - NBHN_0000_Names   The metadata document can be downloaded from https://nbdnr.maps.arcgis.com/sharing/rest/content/items/d5f765b86027426c90c97c820c1a3309/data Ces couches et le tableau représentent les entités possédant un nom connu, identifiés dans le cadre de la création du RHNB. Point Layer - NBHN_0000_NF_0Polygon Layer - NBHN_0000_NF_2Typonomic Names - NBHN_0000_Names   Le document de métadonnées peut être téléchargé à partir de https://nbdnr.maps.arcgis.com/sharing/rest/content/items/d5f765b86027426c90c97c820c1a3309/data

Date of Images: 2/4/2023, 2/5/2023, 2/9/2023, 2/10/2023, 2/16/2023, 2/21/2023 Date of Next Image: None Expected Summary: The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composites of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the hurricane. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). Additional SAR Information Suggested Use: In this image, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A satellite Resolution: 30 meters Credits: Sentinel data used in this derived product, contains modified Copernicus Sentinel data (2023), processed by ESA, Alaska Satellite Facility, NASA MSFC Service URL:  https://gis.earthdata.nasa.gov/portal/home/item.html?id=7a7c0584e53d4cad84af5cdde9b29eb0 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202302_EARTHQUAKE_TURKIYE/2302_sentinel1/ImageServer/WMSServer

There are a number of other scenic and amenity areas in Co. Monaghan that require protection from inappropriate and insensitive development. These areas are designated as Areas of Secondary Amenity Value and are generally associated with river valleys, uplands, woodlands and lakes and provide an important community, recreational and tourism resource. It is an objective to manage development in these areas to ensure that the scenic value is maintained and ensure any development proposals are sensitively designed and compatible with the overall landscape character of the area. The Areas of Secondary Amenity Value are listed in Table 6.6 of Monaghan County Council Development Plan 2025 - 2031. This data is in ITM Projection. Monaghan County Council provides this information with the understanding that it is not guaranteed to be accurate, correct or complete. Monaghan County Council accepts no liability for any loss or damage suffered by those using this data for any purpose.

Vector data set consisting of lines representing streams in Kentucky. Each line segment is attributed with the number of square miles of drainage area, and the peak flow values for 2, 5, 10, 25, 50, 100, 200, and 500 year intervals at that point on the stream. Peak flow values were calculated using the equations in the USGS Water-Resources Investigations Report 03-4180 "Estimating the Magnitude of Peak Flows for Streams in Kentucky for Selected Recurrence Intervals." The data also has attributes indicating when the peak flow values should not be used because the drainage area is out of the size range for the equation, the drainage area is greater than 10 percent impervious, or the stream segment is in a lake or pond.

Overview This layer shows different wetland types, as well as lakes and rivers, across North America. The map was made using the Global Lakes and Wetlands Database (GLWD) Level 3, which was created using a variety of the best available sources for lakes and wetlands on a global scale. Level 3 of the Global Lakes and Wetlands Database (GLWD) comprises lakes, reservoirs, rivers, and different wetland types in the form of a global raster map. GLWD-3 may serve as an estimate of wetland extents for global hydrology and climatology models, or to identify large-scale wetland distributions and important wetland complexes. Source: Lehner, B., and P. Döll. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296/1-4: 1–22. Geographic Coverage This layer covers all of North America, including Canada, Mexico, and the United States. Data Sources and Licensing This dataset integrates the Global Lakes and Wetlands Database, Level 3 (World Wildlife Fund US). This material is licensed under CC BY 4.0, allowing non-exclusive rights to distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, so long as attribution is given to the creator. Update frequency: Irregular Limitations of use: None. Acknowledgement of the Commission for Environmental Cooperation and the World Wildlife Fund US would be appreciated in products derived from these data. Vintage: 2004 Applications (Intended Use) Global hydrology and climatology modeling. Identification of large-scale wetland distributions and important wetland complexes. Water resource assessment and monitoring. Integration with other thematic layers in the North American Environmental Atlas for comprehensive continental analysis. Supporting cross-border environmental cooperation and policy-making among North American nations. Files Download

This Collection provides Sentinel-3 SRAL Level-2 Land Altimetry Hydrology products, which contains surface topography estimations of lakes and rivers.

There are a number of other scenic and amenity areas in Co. Monaghan that require protection from inappropriate and insensitive development. These areas are designated as Areas of Secondary Amenity Value and are generally associated with river valleys, uplands, woodlands and lakes and provide an important community, recreational and tourism resource. It is an objective to manage development in these areas to ensure that the scenic value is maintained and ensure any development proposals are sensitively designed and compatible with the overall landscape character of the area. The Areas of Secondary Amenity Value are listed in Table 6.6 of Monaghan County Council Development Plan 2025 - 2031. This data is in ITM Projection. Monaghan County Council provides this information with the understanding that it is not guaranteed to be accurate, correct or complete. Monaghan County Council accepts no liability for any loss or damage suffered by those using this data for any purpose.

This dataset contains data about water points in Fakara and Ngonga District in Niger. The field data was collected as part of the open map grant to support mapping water infrastructure and functionality in the Sahel Region. The data contains information about water usage, location of water points, types of water points, cost of accessing water (with a fee or not), operational status and operator. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] = 'drinking_water' Features may have these attributes: - access - addr:city - addr:district - addr:place - amenity - description - fee - man_made - opening_hours - operational_status - operator:type - ownership - seasonal - source - usage - water:condition This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Lake Victoria Macrophytes on the Kenyan side

Lake Victoria Macrophytes on the Kenyan side

Lake Victoria Macrophytes on the Kenyan side

Lake Victoria Macrophytes on the Kenyan side

OpenStreetMap and Overture Maps vector layers for the full Bhote Koshi and Trishuli river corridor in Bagmati and Gandaki Provinces, Nepal, for the 2026 flood response. The area of interest is a 1 km buffer around the river centrelines, running from Rasuwagadhi on the China border to the Narayani confluence at Devghat in Chitawan, across Rasuwa, Nuwakot, Dhading, Gorkha, Tanahu and Chitawan. It merges the original partner shapefile for the upper reach with OCHA's HPCS corridor downstream. This is the wide planning view, the whole corridor under assessment rather than the ground that flooded. For data limited to the flooded area, use Nepal Flood 2026 Flood Affected Area, which clips every layer to the observed inundation footprint of 27 August 2026 and a 200 m margin around it. Every layer holds what is standing and what has been lost, so buildings and roads do not vanish from a download once mappers record them as destroyed. `status` says Standing, Damaged or Destroyed, and the Destroyed and Damaged Features layer gathers everything marked destroyed or damaged in one place. Layers are rebuilt straight from OpenStreetMap each day, so they carry volunteer work as it lands. Buildings, schools, health facilities and points of interest also come in an Overture version, which fuses Microsoft, Google and OpenStreetMap and reaches ground volunteers have not mapped yet. Overture follows its own release cycle and will not show mapping done during this response, so for damage work prefer the OpenStreetMap layers and use Overture where their coverage is thin. Subscribe to the dataset for updates as mapping progresses. - Source: OpenStreetMap, Overture Maps - Part of HOT disaster response exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT