The following stream flow classifications on the map are final and include input provided during the public comment period.

The State of Connecticut Stream Flow Standards and Regulations (Section 26-141b-1 to 26-141b-8 of the Regulations of Connecticut State Agencies) define four stream flow class standards:

Class 1 is described as a free flowing stream

Class 2 is described as minimally altered stream flow

Class 3 is described as moderately altered stream flow

Class 4 is described as substantially altered stream flow

The regulations include consideration of 18 factors related to the degree of alteration in stream flow when adopting river or stream system classifications. Spatial data for each of the factors was gathered from a variety of best available sources. These sources were available at varying scales. A methodology was developed to consider all 18 factors and determine the class for a particular stream segment. In addition, public comment was solicited and considered to identify the final stream flow classification.

For additional information on the classification process, see Section 26-141b-5 RCSA Adoption of river or stream system classifications, Fact Sheet for Stream Flow Classification Process under Section 26-141b-1 to 26-141b-8 of the Regulations of Connecticut State Agencies, Technical Support Document Methodology for Defining Preliminary Stream Flow Classification, and Final Stream Flow Classifications and Statement of Reasons Document. These documents can be found on the CT DEEP website at www.ct.gov/deep/streamflow.

The goal of this project was to develop a standard Northeastern Aquatic Habitat Classification (NEAHCS) and GIS map for 13 northeastern states (ME, NH, VT, MA, RI, CT, NY, PA, NJ, DE, MD, VA, WV, and DC.) that are part of the Northeast Association of Fish and Wildlife Agencies (NEAFWA). This classification and GIS dataset was designed to consistently represent the expected natural aquatic habitat types across this region in a manner deemed appropriate and useful for conservation planning by the participating states. This product is not intended to override state classifications, but is meant to complement state classifications and provide a means for looking at aquatic biodiversity patterns across the region.Background: With the creation and implementation of State Wildlife Action Plans (SWAP) by state fisheries and wildlife agencies, the need for consistent, current digital habitat maps has grown dramatically. The implementation of the SWAPs within each state and across the Northeast region will be greatly enhanced through the development of current, consistent terrestrial and aquatic habitat geographic information systems (GIS) datasets. These habitat datasets are expected to form the foundation of state and regional conservation in the Northeastern United States. Key anticipated uses include the following: Provide common definitions and mapping of aquatic habitat types across state lines. This will allow each state to identify aquatic habitats consistently across jurisdictional borders, such as large habitat patches and watersheds that cover multiple jurisdictions. This will also improve the success of state-level actions by assisting jurisdictions that have not yet developed aquatic habitat classification and mapping tools. Facilitate a new understanding of aquatic biota and populations on a regional scale by linking biological datasets to the regional aquatic habitat types for reporting and analysis. Create a new opportunity to assess the condition and prioritize habitats at a scale broader than the individual state by linking and reporting information on dams, land use, conservation lands, impaired waters, and other condition metrics by the regional aquatic habitat types Developing an Aquatic Ecosystem Classification: Unlike terrestrial communities, no national standard aquatic community classification for the U.S. currently exists. The comprehensive biological sample data necessary to develop a classification and map of aquatic ecosystems from biological data alone is also lacking across large regions, including the northeast states. The Northeast Aquatic Habitat Classification System thus used the aquatic biophysical classification approach developed by the Nature Conservancy and recommended by the National Fish Habitat Science Panel (Olivero and Anderson 2003, Higgins et al. 2005, Beard et al. 2006). This classification approach can be implemented at regional scales and emphasizes the environmental gradients of climate, elevation, landform, and geology which are known to shape aquatic ecosystems at several spatial scales and influence the physical aquatic habitat diversity (Higgins et al. 2005). The individual variables chosen to define specific aquatic habitat types can vary between regions, and regions are encouraged to refine the classification attributes to better reflect more meaningful ecological breaks and variables within their region (Higgins et al. 2005, Beard and Whelan, 2006). The Northeastern Aquatic Habitat Classification System (NAHCS) workgroup decided to use 4 primary variables to define aquatic habitat types in northeast streams and rivers. These variables include stream size, gradient, geologic buffering capacity, and natural stream temperature regime. Please see the full report for more information on why these variables were chosen and how the classification was applied.

GIS database on the Yarsha Khola watershed

    Members informations:
    Attached Vector(s):
     MemberID: 1
    Vector Name: Land use 1961
    Source Map Name: SOI toposheet
    Source Map Scale: 50000
    Source Map Date: 1905-05-14
    Projection: Nepal 87
    Feature_type: polygon
    Vector 
    digitized from topographic maps

    Members informations:
    Attached Vector(s):
     MemberID: 2
    Vector Name: Land use 1981
    Source Map Name: LRMP
    Source Map Scale: 50000
    Source Map Date: 1905-06-03
    Feature_type: polygon
    Vector 
    from Land Resources Mapping Project (LRMP)

    Members informations:
    Attached Vector(s):
     MemberID: 3
    Vector Name: Land use 1992
    Source Map Name: topo sheet
    Source Map Scale: 25000
    Source Map Date: 1905-06-14
    Projection: Nepal 87
    Feature_type: polygon
    Vector 
    from topo sheet

    Members informations:
    Attached Vector(s):
     MemberID: 4
    Vector Name: Land use 1996
    Source Map Name: air photographs
    Source Map Scale: 20000
    Source Map Date: 1905-06-18
    Projection: Nepal 87
    Feature_type: polygon
    Vector 
    from air photographs

    Members informations:
    Attached Vector(s):
     MemberID: 5
    Vector Name: VDC
    Source Map Name: toposheet
    Source Map Scale: 25000
    Source Map Date: 1905-06-14
    Feature_type: polygon
    Vector 
    VDC (Village Development Committee) boundaries

    Attached Image(s):
     Member ID: 6
    Image Name: Orthophoto Mosaic
    Image Source name: AIRCRAFT
    Image Resolution: 1m
    Image Number of Rows:
    Image Number of Columns:
    Image Number of Bits: 8
    Image 
    Mosaic of digitally produced orthophotos

This EnviroAtlas dataset is a point feature class showing the locations of stream confluences, with attributes showing indices of ecological integrity in the upstream catchments and watersheds of stream confluences and the results of a cluster analysis of these indices. Stream confluences are important components of fluvial networks. Hydraulic forces meeting at stream confluences often produce changes in streambed morphology and sediment distribution, and these changes often increase habitat heterogeneity relative to upstream and downstream locations. Increases in habitat heterogeneity at stream confluences have led some to identify them as biological hotspots. Despite their potential ecological importance, there are relatively few empirical studies documenting ecological patterns across the upstream-confluence-downstream gradient. To facilitate more studies of the ecological value and role of stream confluences in fluvial networks, we have produced a database of stream confluences and their associated watershed attributes for the conterminous United States. The database includes 1,085,629 stream confluences and 383 attributes for each confluence that are organized into 15 database tables for both tributary and mainstem upstream catchments ("local" watersheds) and watersheds. Themes represented by the database tables include hydrology (e.g., stream order), land cover and land cover change, geology (e.g., calcium content of underlying lithosphere), physical condition (e.g., precipitation), measures of ecological integrity, and stressors (e.g., impaired streams). We use measures of ecological integrity (Thornbrugh et al. 2018) from the StreamCat database (Hill et al. 2016) to classify stream confluences using disjoint clustering and validate the cluster results using decision tree analysis. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Montana’s surface-water-use classification system bases class assignments primarily on water temperature, fish, and associated aquatic life. Each class has an associated beneficial use. A waterbody supports its beneficial uses when it meets the Water Quality Standards (WQS) established to protect those uses. A waterbody is impaired when any one of its WQS are violated. Determining whether or not a specific use is supported is independent of all other designated uses. For example, a waterbody may partially support aquatic life because of excess nutrients, not support drinking water because of arsenic, but fully support agriculture and industrial uses. Classes A, B, and C are the three most common. Class I is a temporary category assigned to three streams that were grossly impaired when the system was established. Classes A-Closed and A-1 are considered high quality, the principal beneficial use of which is public water supply. The A-Closed class may invoke watershed protection and use restrictions to protect drinking water. Classes B and C each have subsections according to whether they support coldwater or warmwater aquatic life. B-1, B-2, C-1, and C-2 support coldwater aquatic life; B-3 and C-3 support warmwater aquatic life. B and C waters have nearly identical use classifications, but B waters specify drinking water as a beneficial use whereas C waters do not. C-3 streams are suitable for warmwater aquatic life and recreation. Because these streams often contain naturally high total dissolved solids (salinity), their quality is marginal for drinking and agricultural and industrial uses. In August 2003 Montana added four additional classes: D, E, F, and G. The classes include ephemeral streams (E-1, E-2), ditches (D-1, D-2), seasonal or semi-permanent lakes and ponds (E-3, E-4, E-5), and waters with low or sporadic flow (F-1). G-1 waters must be maintained for watering wildlife and livestock and supporting secondary contact recreation and aquatic life, not including fish. These waters are marginally suitable for irrigation after treatment or with mitigation measures and includes “holding water” from coal bed methane development. Note: The classification system designated uses for waterbodies as present at the time of classification in 1955. Waterbodies may now have other realized uses that are not officially designated. In such cases, a waterbody may be reclassified to officially recognize these other uses. Conversely, designated uses cannot be removed from a waterbody without a formal Use Attainability Analysis and approval under rulemaking by the Montana Board of Environmental Review. Streams forming the boundary of Indian Reservations are coded as State of Montana (SOM) waters for practical reasons related to enforcing Federal and Montana water quality standards. In some cases meanders, canals, and ditches that transect the boundary and then reconnect with a border stream are also coded as SOM waters even when they are located in part or entirely within the Indian Reservation. As a result of this coding protocol, if you use the "select by location" procedure to identify streams that are completely within one of the reservations, the resulting selected records may include a small number of streams coded as SOM in the "Authority Entity" field. This is not a mistake and needs to be kept in mind when interpreting selection results. Streams that are not parallel to or located on a border but that cross into and are entirely within an Indian Reservation retain the use class as designated by the ARM description for the watershed they are part of but they are designated as "Not State Jurisdiction" or NSJ in the event table's "Jurisdiction" field and the name of the tribe is recorded in the "Authority Entity" field. The name of the reservation is recorded in the "Area Name" field. Streams that are not parallel to or located on a border but that cross into and are entirely within national parks, wilderness areas or primitive areas are assigned a use class of A-1 as specified by ARM Title 17 Chapter 30 Sub-Chapter 614 (https://deq.mt.gov/files/DEQAdmin/DIR/Documents/legal/Chapters/CH30-06.pdf). The name of the park, primitive area, or wilderness area is recorded in the "Area Name" field of the event table. As a consequence, a stream crossing a border will likely have different use classes on either side of the border.

For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/2cd0c5e9-83b2-49a9-8c3e-79675ffd18bfSIS SOIL:The new Irish Soil Information System concludes a 5 year programme, supported by the Irish Environmental Protection Agency (STRIVE Research Programme 2007-2013) and Teagasc, to develop a new 1:250,000 scale national soil map (https://soils.teagasc.ie). The Irish Soil Information System adopted a unique methodology combining digital soil mapping techniques with traditional soil survey application. Developing earlier work conducted by An Foras Talúntais, the project generated soil-landscape models for previously surveyed counties. These soil-landscape (‘soilscape’) models formed the basis for training statistical ‘inference engines’ for predicting soil mapping units, checked during field survey. 213 soil series are identified, each with differing characteristics, having contrasting environmental and agronomic responses. Properties were recorded in a database able to satisfy national and EU policy requirements. The Irish soil map and related soil property data will also serve public interest, providing the means to learn online about Irish soil resources. Use the Symbology layer file 'SOIL_SISNationalSoil.lyr' based on Value Field 'Association_Unit'. SIS SOIL DRAINAGE:In Ireland, soil drainage category is considered to have a predominant influence on soil processes (Schulte et al., 2012). The maritime climate of Ireland drives wet soil conditions, such that excess soil moisture in combination with heavy textured soils is considered a key constraint in relation to achieving productivity and environmental targets. Both soil moisture content and the rate at which water drains from the soil are critical indicators of soil physical quality and the overall functional capacity of soil. Therefore, a natural extension to the Irish Soil Information System included the development of an indicative soil drainage map for Ireland. The soil subgroup map was used to develop the indicative drainage map, based on diagnostic criteria relating to the subgroup categorization. Use the Symbology layer file 'SOIL_SISSoilDrainage.lyr' based on Value Field 'Drainage'. SIS SOIL DEPTH: Soil depth is a measure of the thickness of the soil cover and reflects the relationship between parent material and length of soil forming processes. Soil depth determines the potential rooting depth of plants and any restrictions within the soil that may hinder rooting depth. Plants derive nearly 80 per cent of their water needs from the upper part of the soil solum, i.e. where the root system is denser. The rooting depths depend on plant physiology, type of soil and water availability. Generally, vegetables (beans, tomatoes, potatoes, parsnip, carrots, leek, broccoli, etc.) are shallow rooted, about 50–60 cm; fruit trees and some other plants have medium rooting depths, 70–120 cm and other crops such as barley, wheat, oats, and maize may have deeper roots. Furthermore, rooting depths vary according to the age of the plants. The exact soil depth is difficult to define accurately due to its high variability across the landscape. The effective soil depth can be reduced by the presence of bedrock or impermeable layers. Use the Symbology layer file 'SOIL_SISSoilDepth.lyr' based on Valued Field 'Depth'. SIS SOIL TEXTURE:Soil texture is an important soil characteristic that influences processes such as water infiltration rates, rootability, gas exchanges, leaching, chemical activity, susceptibility to erosion and water holding capacity. The soil textural class is determined by the percentage of sand, silt, and clay. Soil texture also influences how much water is available to the plant; clay soils have a greater water holding capacity than sandy soils. Use the Symbology layer file 'SOIL_SISSoilTexture.lyr' based on Value Field 'Texture'. SIS SOIL SOC:In the previous national soil survey conducted by An Foras Taluntais, 14 counties were described in detail with soil profile descriptions provided for the representative soil series found within a county. Soil samples were taken at each soil horizon to a depth of 1 meter and analyses performed for a range of measurements, including soil organic carbon, texture, cation exchange capacity, pH; however in most cases no bulk density measurements were taken. This meant that while soil organic carbon concentrations were available this could not be related to a stock for a given soil series. In 2012/2013, 246 profile pits were sampled and analysed as part of the Irish Soil Information System project to fill in gaps in the description of representative profile data for Ireland. Use the Symbology layer file 'SOIL_SISSoilSOC.lyr' based on Value Field 'SOC'.

The North Carolina Department of Environment, Health, and Natural Resources, Division of Environmental Management, in cooperation with the NC Center for Geographic Information and Analysis, developed the digital Water Supply Watersheds data to enhance planning, siting and impact analysis in areas directly affecting water supply intakes. This file outlines the extent of protected and critical areas and stream classifications for areas around water supply watersheds in which development directly affects a water supply intake. This file enables users to identify the areas which have special restrictions for building and development based on water supply intakes. This file is updated as changes occur.

This data was created to assist governmental agencies and others in making resource management decisions through use of a Geographic Information System (GIS).

system filename: wsw Revisions and updates to this layer include:

18.) filename: wsw496 The April 1, 1996 update: A) The Upper Frech Broad River (Asheville) water supply watershed was moved from the proposed coverage to the adopted coverage. B) The Mills River (Asheville) water supply watershed was moved from the proposed coverage to the adopted coverage. C) The French Broad River water supply watershed was moved from the adopted coverage into the proposed coverage. These edits affect Buncombe and Henderson Counties. 17.) filename: wsw396 The March 6, 1996 update: A) The Reedy Fork critical area was changed to 'WS-III NSW' to match the protected area. This affected the Greensboro 100k tile area. B) The Belews Creek protected area was changed to 'WS-IV' to match the critical area. This affected the Winston-Salem 100k tile area. 16.) filename: wsw196 The January 25, 1996 update: A) Protected boundary was altered in the Long Creek (Little Tennessee) watershed. The watershed name was renamed to be Rock Creek (Little Tennessee). This affected the Robbinsville 24k quad. B) Protected boundary was altered in the South Fork Catawba River watershed. This affected the Banoke 24k quad. C) Addition of protected boundary for the Belews Creek watershed. This affected the Belews Creek 24k quad. D) Watersheds were deleted by request of DEM-Tranters Creek which was on the Rocky Mount & Plymouth 100k quads and Stokely Hollow which was on the Asheville 100k quad. E) Extensive changes to the actual boundaries of the watersheds throughout the state in an effort to have them coincident with the Hydrologic Units adopted earlier by EHNR-DEM and USDA-NRCS. Boundaries coincident in both coverages were deleted from the watershed file and copied back from the hydrologic units file. PREVIOUS TO THE 1/25/96 FILE, THIS FILE WAS NAMED: NC.WSW 15.) filname: nc.wsw695 The June 30, 1995 update: A) Protected and critical boundaries were altered in the Hiawassee River watershed. This affected the Mocksville, Peachtree, Marble, and Andrews 24k quads. B) The protected boundary was altered in the South Fork Catawba River watershed in Catawbaw and Lincoln Counties. The Banoak, Reepsville, and Maiden 24k quads were affected. C) The entire WSW area in Bear Creek was deleted in Davie County, affecting the Mocksville and Calahan 24k quads. D) Protected and critical boundaries were altered in the North Toe watershed in Avery and Mitchell counties. This affects the Carvers Gap, Newland, Spruce Pine, and Linville Falls 24k quads. 14.) filename: nc.wsw595 The May 4, 1995 update: an arc was deleted which divided the South Yadkin River-Cooleemee protected area. The change affects the area within the Cool Springs, Cooleemee, Calahan, and Mocksville 24k quads. 13.) filename: nc.wsw195 The January 13, 1995 update: A) A new boundary was added to the Hiawassee River (Murphy) in the Hiawassee River Basin. This addition split the existing watershed, and the western half was deleted. The change affects the Hayesville, Peachtree, and Murphy 24k quads. 12.) filename: nc.wsw1194 The November 4, 1994 update: A) The Smith River WSW, in the Roanoke river basin, had one of its boundaries altered. The change affects the Northeastern Eden 24k quad. 11.) filename: nc.wsw994 The September 13, 1994 update: A) The Lands Creek in the Little Tennessee River Basin in Swain County on the Fontana Lake 100k quad had the PAT attributes added. 10.) filename: nc.wsw894 The August 26, 1994 update consisted of the following watershed adoptions (additions). A) The Deep River in Lee County, in the Cape Fear River Basin. B) The Deep Creek in Swain County, in the Little Tennessee River Basin. C) The Yadkin River in Davie County, in the Yadkin River Basin. D.) The Yadkin River in King County, in the Yadkin River Basin, E) The South Yadkin River in Cooleemee City, in the Yadkin River Basin. 9.) filename: nc.wsw594 The May 18, 1994 update: A) The Tar River WSW within the Tar-Pamlico river basin was deleted. 8.) filename: nc.wsw494 The April 28, 1994 update: A) All proposed areas were removed from the data and are managed separately. Only amended areas are now reflected in this data. 7.) filename: nc.wsw194 The January 12, 1994 update: A) The Campbell Creek watershed in the French Broad river basin had the northern boundary moved. The edits affected the Dellwood 24k quad. B) The South Fork Catawba in the Catawba Watershed had its classification modified from WS-IV CA to WS-IV. C)The South Fork Catawba in the Catawba Watershed had its protected area reduced in size. The change affects the Banoak and Reepsville 24k quads. 6.) filename: nc.wsw102893 The October 28, 1993 update: A) The South Fork Catawba had previously had the protected area deleted. An additional portion of the boundary had been deleted, which was supposed to remain. The boundary was added back into the coverage. The affected maps were the 24k Maiden, Reepsville, Lincolnton West, Hickory, and Banoak, 100k quads were Hickory and Gastonia. 5.) filename: nc.wsw101593 The October 15, 1993 update: A) The northern protected area boundary for Clark Creek was deleted and the east and west critical area buffers were redigitized. Affected maps are the 24k Reepsville and Maiden and the Hickory 100k quad. 4.) filename: The September 8, 1993 update: A) The Little Tennessee River (Fontana Lake) protected area had the southeastern radius line removed, and had a northern ridgeline added. Affected maps are the 24k Fontana Dam and Tuskeegee quads, and the Fontana Lake 100k quad. 3.) filename: wsw193 The January 22, 1993 update: A) Cold Water Creek (Lake Fisher) in the Yadkin River Basin was changed from WS-III to WS-IV. 2.) filename: The November 17, 1992 update: A) Stokely Hollow, 100k Asheboro quad changed from WS-I to WS-II. B) Corrected location of Reddies River intake for the Yadkin river basin, Wilkesboro 24k, Boone 100k. C) Changed location of watershed boundary, intake, and critical area for the South Fork New River, New River Basin, Jefferson 24k, West Jefferson 24k Boone 100k. 1.) filename: nc.pcarv.old (protected/critical area with the same state lake as the .coe coverage, but this version was interpreted from USGS maps) filename: nc.pcarv.coe (protected/critical area with the Army Corp of Engineers version of a state lake) filename: nc.pcarv Previous to August 1992, this file was called Public Water Supply watersheds and only included WS-I, WS-II, WS-III classifications. filename: nc.pca filename: nc.pca2

Click here to downloadClick for metadataService URL: https://gis.dnr.wa.gov/site2/rest/services/Public_Forest_Practices/WADNR_PUBLIC_FP_Rule/MapServer/7This feature class was developed as a cooperative project between the Department of Natural Resources Forest Practices Division, the Department of Ecology, and the Olympic National Forest. The data set was designed as a polygon coverage, delineated on 1:250,000- scale map overlays and digitized in 1991. It was plotted and proofed, but not completed at that time. Beginning in August, 1994 the coverage STRMTEMP was edited, corrected, and proofed. The data set is now a polygon feature class and shows only Class AA, A, and B polygons. It does not address Lake Class completely (some lakes are delineated, some not); see notes below for explanation. Specific conditions of certain stream segments are also not addressed by the feature class. The WAC MUST be referred to whenever this data set is used. The 1991 MPL coverage was used in delineating the extent of AA polygons. Changes through time in Federal land boundaries may affect the classification of waters in those lands. SUMMARY OF TEMPERATURE CLASSIFICATIONS DESIGNATED IN CHAPTER 173-201A WAC WATERQUALITY STANDARDS FOR SURFACE WATERS OF THE STATE OF WASHINGTON WAC 173-201A-030 General water use and criteria classes (1) Class AA (extraordinary) Temperature shall not exceed 16.0 degrees C (freshwater) or 13.0 degrees C (marine water) due to human activities. (2) Class A (excellent) Temperature shall not exceed 18.0 degrees C (freshwater) or 16.0 degrees C (marine water) due to human activities. (3) Class B (good) Temperature shall not exceed 21.0 degrees C (freshwater) or 19.0 degrees C (marine water) due to human activities. (4) Class C (fair) Temperature shall not exceed 22.0 degrees C due to human activities. For all of the above classes, when natural conditions exceed the listed temperature, no temperature increases will be allowed which will raise the receiving water temperature by greater than 0.3 degrees C. (5) Lake Class Temperature - no measurable change from natural conditions. *** Notes regarding WAC 173-201A sections 130 and 140 - Specific classifications for fresh and marine waters: All lakes and their feeder streams are classified as Lake Class. In this data set some large lakes and their feeder streams have had polygons created around them. These are shown as Class AA. Many lakes too small to be separately delineated may be contained within Class B, A, or AA polygons. Some stream segments have special conditions applied to their temperature standards. These conditions are listed in the WAC but are not delineated in the polygon coverage. These include the Columbia River, Duwamish River, Grande Ronde River, Hoquiam River, Lake Washington Ship Canal, Mill Creek (near Walla Walla), Palouse River, Pend Oreille River, Puyallup River, Skagit River, Snake River, Spokane River, Walla Walla River, Wishkah River, Yakima River, and Tacoma city waterway in Commencement Bay. These Special temperature designations are for the stream waters in the listed segment only. Temperature standards for all waters feeding that segment are as shown in the polygon coverage. This data set is a polygon coverage, and does not contain information on all surface waters listed in the WAC. All questions pertaining to temperature classification of surface waters in Washington must be clarified by referring to the WAC.

Cold water habitat was determined using available fish and water temperature data collected by the Connecticut Department of Energy and Environmental Protection (CT DEEP) Monitoring and Assessment, Inland Fisheries and Volunteer Stream Temperature Programs. The analysis to date includes years 1988 - 2023. The mapping application will be updated with new or updated information as it is collected, quality assured and analyzed. CT DEEP has a robust data set of stream fish community and temperature logger data dating back to the late 1980's. In previous work (Beauchene et al., 2014) these data were used to develop cold water temperature metrics and fish species that were indicators of cold-water habitat. With the knowledge gained from the compilation of recent Connecticut based studies, identification and subsequent classification of cold-water habitat can be made with data from either fish or stream water temperature. To catalog cold water habitat CT DEEP analyzed all available fish and water temperature data collected in accordance to standard operating procedures to identify cold water rivers and streams. The analysis to date includes years 1988 – 2023 and identified 1,716 samples and 792 sites indicating cold water habitat from both fish community and temperature logger data. If a site was measured to have cold water habitat with either fish community or water temperature using the June-August metric at any time during our surveys, it was considered cold water stream habitat. Additional information regarding the data and project can be found on: https://portal.ct.gov/DEEP/Water/Inland-Water-Monitoring/Cold-Water-Stream-Habitat-Map.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: County Soil Survey Data with Attributes

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

Additionally, almost 450 ha of the surrounding area consists of bogs and other wetlands. Generally, the soils throughout the forest are glacial tills, acid in reaction, with low fertility and high organic composition. These soils are classified primarily within three suborders: orthods, orchrepts, and aquepts. The climate is chiefly cold, humid, and continental and the region exhibits a snowpack of up to 2 m from December through March.

The original soil polygons were obtained by digitizing a 1963 USDA General Soil Map of Penobscot County, Maine. All of the soil symbols used were taken directly off of the county soil map. Data from the State Soil Geographic Database (STATSGO) were cross-matched. The county symbol was chosen as the identifier, and a STATGO identifier that best "fits" the county soil identifier was selected. The original maps used for the digitization came in 6 map sheets. All of the sheets were digitized, corrected, edge-matched, and appended. Once this was finished, topology was built, new items and attributes were added.

The data in its current form can be used to delineate basic soil groups. However, because the STATSGO map unit identifier is located in each polygon the user can link any of the other STATSGO data sets depending on the desired information. The identifier is the key for creating a very detailed and thorough soils data set. Once linked the data can be used for ecological modeling, resource management, and many other applications.

Changes to instream flow are known to be one of the major factors that affect the health of biological communities. Flow alteration can degrade physical habitat and alter water quality, reducing the ability of a stream to support aquatic life. Understanding the relationship between changes in flow and changes in benthic invertebrate communities (a key indicator of stream health) is critical to informing decisions about ecosystem vulnerability, identifying causes of stream and watershed degradation, and setting priorities for future watershed management.

Among the range of approaches available for setting flow targets that support biological integrity, a recently completed project in southern California evaluated the Ecological Limits of Hydrologic Alteration (ELOHA) framework to assess the effect of flow alteration on the condition of benthic macroinvertebrate (BMI) communities across the region. The ELOHA framework establishes recommended targets using a process that includes estimation of flow alteration and development of flow-ecology relationships based on the response of biological communities to changes in flow. This project applied to the ELOHA framework to develop regional flow-ecology relationships and targets based on responses in the benthic macroinvertebrate community. The objectives of this project were: 1) Develop a recommended set of flow targets for southern California streams that would maximize the likelihood of maintaining healthy biological communities as indicated by the California Stream Condition Index (CSCI) for benthic invertebrates. 2) Produce a set of tools that can be readily applied to future sites to estimate hydrologic alteration relative to biologically-define targets.

This project was led by the Southern California Coastal Water Research Project (SCCWRP) and developed flow-ecology relationships using data from nearly 600 bioassessment sites sampled over the past eight years. The California Stream Condition Index (CSCI), a measure of biological condition based on benthic macroinvertebrate communities, was calculated at each of these sites (for more information on the CSCI, refer to the CSCI Fact Sheet and the Bioassessment scores map that shows statewide CSCI scores and stream hydrologic classifications). The degree of hydrologic alteration at each of these sites was assessed by comparing estimates of present-day and historical flows using a set of regionally calibrated hydrologic models. Differences from historic flow conditions were compared to CSCI scores to estimate the probability of good biological conditions along gradients of increasing hydrologic alteration.

The datasets presented here provide the biological and flow metrics calculated for each site to develop recommended flow targets and management priorities at those sites. For more information, please refer the final report for this project, available here.

Differential Map Streaming for SDV Market Outlook

According to our latest research, the global Differential Map Streaming for SDV (Software-Defined Vehicles) market size in 2024 stands at USD 1.54 billion, with a robust compound annual growth rate (CAGR) of 18.7% projected from 2025 to 2033. By 2033, the market is forecasted to reach a significant value of USD 7.55 billion. This remarkable growth is primarily driven by the increasing integration of real-time, high-definition mapping solutions in connected and autonomous vehicles, which is revolutionizing the automotive industry’s approach to navigation, safety, and operational efficiency.

A key growth factor for the Differential Map Streaming for SDV market is the rapid advancement of autonomous vehicle technologies and the increasing demand for real-time, highly accurate mapping data. As automotive manufacturers and technology providers race to develop safer, more reliable autonomous driving systems, the need for dynamic, frequently updated maps has become paramount. Differential map streaming enables vehicles to access the most current information about road conditions, traffic, obstacles, and infrastructure changes, which is essential for safe navigation and advanced driver assistance systems (ADAS). The proliferation of connected vehicle ecosystems, coupled with the exponential growth in data generation from sensors and IoT devices, further amplifies the demand for scalable, cloud-based map streaming solutions that can deliver rich, context-aware content to SDVs in real-time.

Another major driver is the increasing adoption of software-defined architectures in modern vehicles, enabling over-the-air (OTA) updates and modular software enhancements. This shift is transforming the automotive landscape, allowing OEMs and fleet operators to continuously improve vehicle performance, safety, and user experience through seamless software updates. Differential map streaming plays a pivotal role in this transformation by providing the infrastructure necessary for delivering incremental map changes, reducing bandwidth consumption, and ensuring that vehicles are always equipped with the latest geospatial data. This not only supports the development of more sophisticated ADAS and autonomous functionalities but also enhances operational efficiency for commercial fleets, which rely on up-to-date mapping for route optimization and regulatory compliance.

Furthermore, the growing emphasis on smart mobility, urbanization, and sustainability is fueling investments in intelligent transportation systems and digital infrastructure. Governments and city planners are increasingly collaborating with automotive OEMs and technology providers to deploy advanced mapping and localization solutions that support safer, more efficient transportation networks. Differential map streaming is a cornerstone of these initiatives, enabling real-time data sharing and situational awareness across connected vehicles, infrastructure, and mobility services. As regulatory frameworks evolve to accommodate autonomous driving and digital mobility, the adoption of differential map streaming is expected to accelerate, unlocking new opportunities for innovation and market expansion.

From a regional perspective, North America and Europe currently lead the Differential Map Streaming for SDV market, driven by robust investments in autonomous vehicle research, favorable regulatory environments, and the presence of leading technology and automotive companies. Asia Pacific is rapidly emerging as a high-growth region, fueled by the expansion of smart city projects, increasing vehicle electrification, and the rise of domestic automotive giants investing in next-generation mobility solutions. Latin America and the Middle East & Africa are witnessing gradual adoption, primarily driven by commercial fleet modernization and digital transformation initiatives. As global automotive and technology ecosystems continue to converge, regional dynamics will play a critical role in shaping the future trajectory of the Differential Map Streaming for SDV market.

The new management plan for migratory fish in the Seine-Normandie Basin for the period 2016-2021 was adopted by the Basin Coordinating Prefect on 21 June 2016.

Drawing up by the Management Committee for Migratory Fishes, it shall, in consultation with the main water users, issue guidelines and recommendations to enable the management of habitats and human activities compatible with the conservation of migratory fish. The development and monitoring of the plan is possible, in particular through the Migratory Association SEINORMIGR, which drives the migratory component throughout the basin and monitors PLAGEPOMI indicators.

This layer reflects the stream line colonised by Sea Trout as of 2014:

• “colonised linear”: colonised lines accumulating accessible and partially colonised areas;

• “linear accessible without biological data”: accessible linears on which there is no biological data attesting to the presence of the species even though they are physically productive vis-à-vis it;

• “insufficient data on attendance and accessibility”: lines for which data are insufficient to decide on the attendance and accessibility of a particular species;

• “non-accessible line”: non-accessible lines for physical works classified as impassable which delimit them downstream;

• “biological limit of the species”: biological boundaries representing areas considered not conducive to breeding and/or development of juveniles.

Abstract

The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived

Shapefile defining landscape classes across the whole Clarence-Moreton preliminary assessment extent (PAE), as created for the Bioregional Assessments program. This landscape classification was developed to characterise the nature of water dependency among the diverse range of assets, based on key landscape properties related to patterns in geology, geomorphology, hydrology and ecology (both natural and modified ecosystems).

CLM Product 2.3 (Section 2.3.3) provides the methodology used to derive the classification.

Dataset History

Methodology is provided in Product 2.3, Ecosystems chapter, as copied below.

There are many different classification and landscape class methodologies which have been developed to provide consistent and functionally relevant representations of ecosystems (e.g. Australian National Aquatic Ecosystem (ANAE) classification framework). Where appropriate, the approach used to derive the 'Land classification for the Clarence-moreton preliinary assessment extent' built on, and integrated these existing classification systems.

The process of devising and implementing a landscape classification for the Clarence-Moreton PAE predominately involved combining existing classes within data associated with aquatic and groundwater-dependent ecosystems, vegetation and land use mapping. The landscape classification was derived from data layers consisting of polygons (e.g. vegetation, terrestrial/surface GDEs or wetlands), lines (stream network) and points (springs, economic groundwater assets) and produced an output polygon dataset.

1. Classification of polygon features:

The approach taken was formulated in close collaboration with several experts that had extensive experience with the landscapes of the PAE and had input into developing similar classification systems such as the ANAE classification framework (Aquatic Ecosystems Task Group, 2012). The input datasets and rule sets used for analysis of the polygon layers for this component of the classification are given in Table 1 of Product 2.3, Ecosystems chapter.

Geology is the main landscape-forming driver with four types characterising the bioregion:

* Fractured (volcanic) rock

* Consolidated sedimentary rock

* Unconsolidated sedimentary sediments - alluvium

* Unconsolidated sedimentary sediments - estuarine

The fractured rock is represented by the steep escarpment mainly along the Queensland-NSW border within the bioregion. The consolidated sedimentary rock covers the rest of the bioregion except where it is covered by the alluvium associated with hydrological features and floodplains or the estuarine sediments along the coast. The broad geological classification divides the PAE according to Queensland pre-clearing remnant vegetation mapping (9b7bcebf-8b7f-4fb4-bc91-d39f1bd960cb) with the associated landzone classes and NSW Mitchell landscapes (e64597db-453c-46be-a352-360b775d2852). Both datasets were reclassified by a geologist to conform to the four geological types.

1. Classification of lines (watercourses)

The approach to classifying watercourses in the PAE broadly focused on whether or not they were streams or rivers. The watercourses were primarily based on the Bureau of Meteorology's Geofabric cartographic mapping of river channels derived from 1:250,000 topographic maps (ed3acf9b-888c-4d53-b376-ecab89781651). The Geofabric is a purpose-built GIS that maps Australian rivers and streams and identifies how stream features are connected hydrologically. Detailed descriptions of the Geofabric can be found in the Geofabric product guide (Bureau of Meteorology 2012). The water regime of the Geofabric watercourses was defined according to their hierarchy - either 'river' (hierarchy 'major') or 'stream' (hierarchy 'minor').

Rivers were further classed as 'tidal river' where upstream tidal limits could be determined from published information.

The Geofabric watercourse mapping is a line dataset. As part of processing to derive the output landscape classes, all Geofabric watercourses were buffered 0.5m (total 1m both sides of the watercourse). This did not adequately represent the true extent of some watercourses - particularly estuaries and wide rivers. Accordingly, watercourses were broadened to reflect real extent, where NVIS4_1 dataset (57c8ee5c-43e5-4e9c-9e41-fd5012536374>) classes were 'sea and estuaries' and 'inland aquatic - freshwater, salt lakes, lagoons' and where these waterbodies were not already captured in the aquatic classes defined in Table 1 f Product 2.3, Ecosystems chapter.

Freshwater rivers were differentiated from freshwater streams according to the available Geofabric data and in part this served to acknowledge hierarchical differences in geomorphological and ecological processes within main channel depositional zones as opposed to smaller tributary systems. These rivers and streams were further differentiated from estuarine watercourses, to reflect major functional differences in hydrological processes and ecological function (Table 2 of Product 2.3, Ecosystems chapter).

1. Classification of points (springs, waterholes, waterfalls and point-based economic receptors)

In the absence of adequate spatial datasets defining location of springs, waterholes and waterfalls, these were classified based on their occurrence in the Assets register (Table 3 of Product 2.3, Ecosystems chapter).

1. Landscape classification

Landscape classification allows geographical areas to be delineated into classes that are similar in physical and/or biological and hydrological character. Forty-four landscape classes were defined for the Clarence-Moreton PAE (Table 4 of Product 2.3, Ecosystems chapter). For the water regime classes (other than 'springs and waterholes; waterfalls'), these landscape classes are a function of the four geological and four terrain 'types' defined in Table 1 of Product 2.3, Ecosystems chapter, and resulted in 24 landscape classes. The importance of geology as the main landscape-forming driver is discussed in the geology section (within Product 2.3) and Section 2.3.3.1. Terrain exerts a strong influence on morphology, flow patterns and associated biota. The slope thresholds from the Australian National Aquatic Ecosystems (ANAE) classification framework for the Murray-Darling Basin, based on the Stein Index (Brooks et al., 2014), were used to determine the four terrain types- lowland, low energy upland, high energy upland, and transitional environments.

Hydrological features were classified according to their position in the terrain and whether they were a moving or still body of water as well as their permanency.

Modified landscapes are mostly cleared of natural vegetation and are used for agricultural or other human-intended purposes. These were classified into "dryland agriculture" or "irrigated agriculture" (BRS 2009; DSITIA 2014 ). They were acquired from the latest land use data (BRS 2009; DSITISA 2014). Natural vegetation areas were delineated into major vegetation classes based on structure (especially height and cover), growth form and floristic composition (vascular plant species) in the dominant stratum of each vegetation type (Department of the Environment and Water Resources, 2007). It was also delineated between wet and dry sclerophyll forest. Groundwater-dependent ecosystems (GDEs) are vegetation communities that access groundwater on a permanent or intermittent basis (DSITIA 2015). They occur within the main vegetation classes, where groundwater is close to the surface and accessible. Groundwater-dependency was specifically considered through the spatial intersection of GDEs in the Assets register with the vegetation landscape classes, thus resulting in an associated GDE landscape class for each vegetation landscape class.

Derivation of landscape classes was essentially a process of joining different input datasets to create an output polygon dataset representing all landscape classes. Decisions were made at different points during the process about simplification of data (eg. elimination of small polygons), prioritisation of landscape classes when there was overlap of two or more landscape classes, and improvement of data. How to proceed in these instances was based on an understanding of the quality of the input data (spatial accuracy, spatial resolution, attribute accuracy, currency) combined with an understanding both of the requirements of the output land classification for subsequent receptor analysis and of the CLM PAE landscape. Improvement of data (eg. to code missing areas or re-code existing attributes) relied on the use of supplementary contextual data - maps, satellite imagery, reports or other 'contextual' datasets. Improvement was necessary particularly when defining the polygon water regime classes, where it was found that features and/or attributes within the dataset: 9ff7ab58-2e30-4268-bdf3-bc8aa72aa940 did not adequately cover all relevant aquatic features.

While areal representation across the landscape is 'true' for most landscape classes, the area of landscape classes derived from line and point input datasets (stream, river, tidal river, 'waterfalls', and 'springs and waterholes' landscape classes) does not represent real width of these features in most cases, due to the treatment of these during processing - see section 2.3.3.1 of Product 2.3, Ecosystems chapter, for further details.

Dataset Citation

Bioregional Assessment Programme (2015) Land classification for the Clarence-Moreton preliminary assessment extent. Bioregional Assessment Derived Dataset. Viewed 10 July 2017,

This layer contains the EPA approved final overall Integrated Report or 305(b) list category for all named streams in North Carolina. This data was originally developed by Cam McNutt and uploaded 2/12/2015. The purpose of this layer is to show the overall IR category and basic stream information as related to Assessment Units. Individual parameter categories can be found in the DWR 2014 IR Parameter Cat layer.Attributes:AU_Number (assessment unit)AU Name (stream name)AU Descrip (stream segment description)NC Basin (river basin acronym)AU Lengtha (segment length)AU Units (units of length)AU Type (C - Creek, S - Stream, R - River)BIMS Index (Index number)BIMS Class (fresh water stream classification)Mainstem_N (Drains to this mainstem)OIRC (Overall Integrated Report Category)Subbasin (8-Digit Subbasin Name)Data Contact: Cam McNuttLayer Contact: Melanie WilliamsThis feature layer can be found in the NC Surface Water Classification map application.

This publication consists of the online version of a CD-ROM publication, U.S. Geological Survey Digital Data Series DDS-43. The data for this publication total 175 MB on the CD-ROM and 167 MB for this online version. This online version does not include the Acrobat Search index files. It also has a link rather than files for the Adobe Acrobat Reader installer mentioned below.

The Sierra Nevada Ecosystem Project was requested by Congress in the Conference Report for Interior and Related Agencies 1993 Appropriation Act (H.R. 5503), which authorized funds for a "scientific review of the remaining old growth in the national forests of the Sierra Nevada in California, and for a study of the entire Sierra Nevada ecosystem by an independent panel of scientists, with expertise in diverse areas related to this issue."

This publication is a digital version of the set of reports titled Sierra Nevada Ecosystem Project, Final Report to Congress published in paper form by the Centers for Water and Wildland Resources of the University of California, Davis. The reports consist of Wildland Resources Center Report No. 39 (Summary), No. 36 (Vol. I - Assessment summaries and management strategies), No. 37 (Vol. II - Assessments and scientific basis for management options), No. 38 (Vol. III - Assessments, commissioned reports, and background information), and No. 40 (Addendum). Vol. IV is a computer-based catalogue of all public databases, maps, and other digitally stored information used in the project. Vol. IV materials are listed under the SNEP name and available on the Internet from the Alexandria Project at the University of California at Santa Barbara and the California Environmental Resource Evaluation System (CERES) project of the Resources Agency of the state of California (see links below).

[Summary provided by the USGS.]

[From The Landmap Project: Introduction, "http://www.landmap.ac.uk/background/intro.html"]

 A joint project to provide orthorectified satellite image mosaics of Landsat,
 SPOT and ERS radar data and a high resolution Digital Elevation Model for the
 whole of the UK. These data will be in a form which can easily be merged with
 other data, such as road networks, so that any user can quickly produce a
 precise map of their area of interest.

 Predominately aimed at the UK academic and educational sectors these data and
 software are held online at the Manchester University super computer facility
 where users can either process the data remotely or download it to their local
 network.

 Please follow the links to the left for more information about the project or
 how to obtain data or access to the radar processing system at MIMAS. Please
 also refer to the MIMAS spatial-side website,
 "http://www.mimas.ac.uk/spatial/", for related remote sensing materials.

The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Program (NWQP). The NWQN represents the consolidation of four historical national networks: the USGS National Water-Quality Assessment (NAWQA) Project, the USGS National Stream Quality Accounting Network (NASQAN), the National Monitoring Network (NMN), and the Hydrologic Benchmark Network (HBN). The NWQN includes 22 large river coastal sites, 41 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Matching Funds (Co-op) program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release contains geo-referenced digital data and associated attributes of watershed boundaries for 113 NWQN and 3 Co-op sites. Two sites, "Wax Lake Outlet at Calumet, LA"; 07381590, and "Lower Atchafalaya River at Morgan City, LA"; 07381600, are outflow distributaries into the Gulf of Mexico. Watershed boundaries were delineated for the portion of the watersheds between "Red River near Alexandria, LA"; 07355500 and "Atchafalaya River at Melville, LA"; 07381495 to the two distributary sites respectively. Drainage area was undetermined for these two distributary sites because the main stream channel outflows into many smaller channels so that streamflow is no longer relative to the watershed area. NWQN watershed boundaries were derived from the Watershed Boundary Dataset-12-digit hydrologic units (WBD-12). The development of the WBD-12 was a coordinated effort between the United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS), the USGS, and the Environmental Protection Agency (EPA) (U.S. Department of Agriculture-Natural Resources Conservation Service, 2012). A hydrologic unit is a drainage area delineated to nest in a multi-level, hierarchical drainage system. Its boundaries are defined by hydrographic and topographic criteria that delineate an area of land upstream from a specific point on a river, stream or similar surface waters. The United States is divided and sub-divided into successively smaller hydrologic units identified by a unique hydrologic unit code (HUC) consisting of two to 12 digits based on the six levels of classification in the hydrologic unit system: regions, sub-regions, accounting units, cataloging units, watersheds, and sub-watersheds. NWQN watershed boundaries were delineated by selecting all sub-watershed polygons that flow into the most downstream WBD-12 polygon in which the NWQN site is located. The WBD-12 attribute table contains 8-digit, 10-digit, and 12-digit HUCs which were used to identify which sub-watersheds flow into the watershed pour point at the NWQN site location. When the NWQN site was located above the pour point of the most downstream sub-watershed, the sub-watershed was edited to make the NWQN site the pour point of that sub-watershed. To aid editing, USGS 1:24,000 digital topographic maps were used to determine the hydrologic divide from the sub-watershed boundary to the NWQN pour point. The number of sub-watersheds which are contained within the NWQN watersheds ranged from less than one to nearly 32,000 internal sub-watersheds. Internal sub-watershed boundaries were dissolved so that a single watershed boundary was generated for each NWQN watershed. Data from this release are presented at the USGS Tracking Water Quality page: http://cida.usgs.gov/quality/rivers/home (Deacon and others, 2015). Watershed boundaries delineated for this release do not take into account non-contributing area, diversions out of the watershed, or return flows into the watershed. Delineations are based solely on contributing WBD-12 polygons with modifications done only to the watershed boundary at the NWQN site location pour point. For this reason calculated drainage areas for these delineated watersheds may not match National Water Information System (MWIS) published drainage areas (http://dx.doi.org/10.5066/F7P55KJN). Deacon, J.R., Lee, C.J., Toccalino, P.L., Warren, M.P., Baker, N.T., Crawford, C.G., Gilliom, R.G., and Woodside, M.D., 2015, Tracking water-quality of the Nation’s rivers and streams, U.S. Geological Survey Web page: http://cida.usgs.gov/quality/rivers, https://dx.doi.org/doi:10.5066/F70G3H51. U.S. Department of Agriculture-Natural Resources Conservation Service, 2012, Watershed Boundary Dataset-12-digit hydrologic units: NRCS National Cartography and Geospatial Center, Fort Worth, Tex., WBDHU12_10May2012_9.3 version, accessed June 2012 at http://datagateway.nrcs.usda.gov.

The New Zealand River Environment Classification (REC) organises information about the physical characteristics of New Zealand's rivers. Individual river sections are mapped according to physical factors such as climate, source of flow for the river water, topography, and geology, and catchment land cover eg, forest, pasture or urban. Sections of river that have similar ecological characteristics can then be grouped together, no matter where they are.

This information is mapped for New Zealand's entire river network - over 425,000 kilometres of river. Different types of rivers respond differently to the pressures placed on them - the REC can be used to highlight the most appropriate management tools and approaches to reduce these pressures for each river type. Information from the classification is used to develop policy, assess the environment, and report on the quality of river water.

Stream order is the numerical position of a tributary or section of a river within the entire network. Headwater streams are assigned a stream order of 1. When two tributaries of the same stream order meet, the order increments by one for the next section downstream. However, if two sections meet where one section has higher order than the other, the next section downstream has the same order as the highest upstream section.

The User Guide can be found at https://data.mfe.govt.nz/document/123-river-environment-classification-user-guide-2010/

One purpose of the USGS National Assessment of Coastal Change Project is to provide accurate representations of pre-storm ground conditions for areas that are designated high-priority because they have dense populations or valuable resources that are at risk from storm waves. Another purpose of the project is to develop a broad geomorphic coastal classification that, with only minor modification, can be applied to most coastal regions in the United States.

A Coastal Classification Map describing local geomorphic features is the first step toward determining the hazard vulnerability of an area. The Coastal Classification Maps of the National Assessment of Coastal Change Project present ground conditions such as beach width, dune elevations, overwash potential, and density of development. In order to complete a hazard vulnerability assessment, that information must be integrated with other information, such as prior storm impacts and beach stability. The Coastal Classification Maps provide much of the basic information for such an assessment and represent a critical component of a storm-impact forecasting capability.

[Summary provided by the USGS.]