The National Hydro Network (NHN) focuses on providing a quality geometric description and a set of basic attributes describing Canada's inland surface waters. It provides geospatial digital data compliant with the NHN Standard such as lakes, reservoirs, watercourses (rivers and streams), canals, islands, drainage linear network, toponyms or geographical names, constructions and obstacles related to surface waters, etc. The best available federal and provincial data are used for its production, which is done jointly by the federal and interested provincial and territorial partners. The NHN is created from existing data at the 1:50 000 scale or better. The NHN data have a great potential for analysis, cartographic representation and display and will serve as base data in many applications. The NHN Work Unit Limits were created based on Water Survey of Canada Sub-Sub-Drainage Area.

Please note that a web service is currently under development and will be launched in the fall of 2025. Stay on the lookout! ## #Avertissement :### ### #Le broadcaster cannot guarantee the accuracy, precision, or completeness of the data nor can it be held responsible for the conclusions that arise from their use. This data has no legal value.#### The High Resolution Quebec Hydrographic Network Geobase (GRHQ-HR) offers an up-to-date and very accurate representation of the hydrographic network (scale of 1/2,000). This repository, produced from lidar data, is offered by hydrographic division unit (UDH). The deployment of this geobase is carried out progressively by levels of completeness (NC). Ultimately, it will cover the territory of southern Quebec. During the deployment phase of the repository, the Quebec Hydrographic Network Geobase (GRHQ), the GRHQ-HR as well as potential flow beds from the lidar will be simultaneously available on Data Quebec for this portion of the territory. The GRHQ-HR includes a 3D linear geometric network, which represents the continuity and direction of flow in all types of aquatic entities (streams, lakes, wetlands, etc.). This network is created by modeling potential flow beds and completed by central flow lines (simplified representation of hydrographic surfaces in central lines). This geobase is part of a strategy to update the cartographic map of Quebec's hydrography. It was carried out in partnership with the Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks (MELCCFP). # #Caractéristiques UDH completeness levels## Each level of completeness characterizes the level of work editing, validation, and descriptive content of the datasets. Thematic and toponymic data will enhance the datasets. ### #NC -1 (primary geometric network) #### * Potential and filamentary flow beds derived from hydrographic, oriented and topological surfaces. * Defined priority level (allows network analyses). * Presence of certain basic attributes (sustainability, network connection, network connection, accumulation of flows, flow accumulation, flow accumulation, Strahler and Horton orders, distance from upstream, distance from downstream). * Linear reference system (road numbers, coordinates). * Presence of certain basic attributes (sustainability, network connection, accumulation of flows, flow accumulation, flow accumulation, Strahler and Horton orders, distance from upstream, distance from downstream). * Linear reference system (road numbers, coordinates) M of the vertices). * Hydrographic surfaces of the GRHQ on a scale of 1/20,000 (2D). * Presence of certain toponyms in attribute. * Hydrocoherent numerical terrain models (GeoTIFF). * Flow accumulation matrices (GeoTIFF). * Flow direction matrices (GeoTIFF). ### #NC -2 (improved geometric network) #### * Characteristics of NC-1. * Update of hydrographic surfaces by photogrammetry. * Correction of potential flow bed path errors and update of downstream filamentaries. * Partial addition of hydrographic thematic data (dams, falls, reservoirs, reefs, islands, wetlands, rapids). * Lidar survey date index. * Topical nesting biological matrices. * Update of hydrocoherent numerical terrain models. * Update of flow direction matrices. * Update of flow accumulation matrices. ### #NC -3 (thematic improvement) #### * Characteristics of the NC-2. * Hydrographic themes completed (breakwaters, docks). * Addition of toponyms. ### #NC -4 (improvement of toponymic content) #### * Characteristics of NC-3. * Continuity of toponymic data on geometries. * Additions of named entities.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Description:

This zipfile contains linear geometries showing a channel network across the SAFE Project landscape. The network was calculated using the GRASS hydrology tool r.stream.extract from SRTM elevation data and the resulting flow accumulation predictions (see https://zenodo.org/record/3490488 and https://zenodo.org/record/3490687).

Note that these networks are derived entirely from remotely sensed data, but do form a single interconnected network across the wider SAFE landscape. Other stream network data are available () but the provenance of these are not well known and they only cover part of the SAFE network.

Details of the geoprocessing can be found here: https://www.safeproject.net/dokuwiki/safe_gis/stream_networks.

Project: This dataset was collected as part of the following SAFE research project: SAFE CORE DATA

XML metadata: GEMINI compliant metadata for this dataset is available here

Files: This dataset consists of 2 files: SAFE_SRTM_Stream_network_metadata.xlsx, SRTM_Channels_network.zip

SAFE_SRTM_Stream_network_metadata.xlsx

This file only contains metadata for the files below

SRTM_Channels_network.zip

Description: Shapefile containing 54413 calculated segments forming a channel network across the wider SAFE landscape.

This file contains 1 data tables:

1. Feature properties (described in worksheet Properties)

   Description: Field descriptions for shapefile properties

   Number of fields: 17

   Number of data rows: Unavailable (table metadata description only).

   Fields:

   • cat: Identity of segment (Field type: id)
   • type_cd: Segment type (see also type) (Field type: numeric)
   • ID: Identity of segment (Field type: id)
   • length: Length of network segment (Field type: numeric)
   • n_ponts: Number of points in segment (Field type: numeric)
   • sourceX: X coordinate of source point of segment (Field type: numeric)
   • sourceY: Y coordinate of source point of segment (Field type: numeric)
   • sinkX: X coordinate of sink point of segment (Field type: numeric)
   • sinkY: Y coordinate of sink point of segment (Field type: numeric)
   • type: Segment type - is the segment a source or outflow segment (connected at one end only, type_cd = 0) or internal (connected at both ends, type_cd=1) (Field type: categorical)
   • snkChnn: Identity of sink channel for this segment (Field type: id)
   • srcChnn: Identities of source channels for this segment (Field type: id)
   • nSourcs: Count of source channels (Field type: numeric)
   • sorcElv: Elevation of start point of segment (Field type: numeric)
   • sinkElv: Elevation of sink point of segment (Field type: numeric)
   • sorcFlw: Incoming flow at segment source (Field type: numeric)
   • sinkFlw: Outgoing flow at segment sink (Field type: numeric)

Date range: 2010-10-01 to 2019-10-01

Latitudinal extent: 4.0223 to 5.9761

Longitudinal extent: 116.0242 to 117.9758

This dataset is associated with a manuscript currently under review.

This dataset contains simulated daily streamflow data across Africa and South America.

Corresponding peer-reviewed publication

This dataset corresponds to all input and output files that were used in the study reported in:

Wade, J., David, C.H., Collins, E.L., Altenau, E.H., Coss, S., Cerbelaud, A., Tom, M., Durand, M., Pavelsky T.M. (In Review), Bidirectional Translations Between Observational and Topography-based Hydrographic Datasets: MERIT-Basins and the SWOT River Database (SWORD).

When making use of any of the files in this dataset, please cite both the aforementioned article and the dataset herein.

Summary

The MERIT-SWORD data product reconciles critical differences between the SWOT River Database (SWORD; Altenau et al., 2021), the hydrography dataset used to aggregate observations from the Surface Water and Ocean Topography (SWOT) Mission, and MERIT-Basins (MB; Lin et al., 2019; Yang et al., 2021), an elevation-derived vector hydrography dataset commonly used by global river routing models (Collins et al., 2024). The SWORD and MERIT-Basins river networks differ considerably in their representation of the location and extent of global river reaches, complicating potential synergistic data transfer between SWOT observations and existing hydrologic models.

MERIT-SWORD aims to:

Generate bidirectional, one-to-many links (i.e. translations) between river reaches in SWORD and MERIT-Basins (ms_translate files).

Provide a reach-specific evaluation of the quality of translations (ms_diagnostic files).

Data sources

The following sources were used to produce files in this dataset:

MERIT-Basins (version 1.0) derived from MERIT-Hydro (version 0.7) available under a CC BY-NC-SA 4.0 license. https://www.reachhydro.org/home/params/merit-basins

SWOT River Database (SWORD) (version 16) available under a CC BY 4.0. https://zenodo.org/records/10013982. DOI: 10.5281/zenodo.10013982

Mean Discharge Runoff and Storage (MeanDRS) dataset (version v0.4) available under a CC BY-NC-SA 4.0 license. https://zenodo.org/records/10013744. DOI: 10.5281/zenodo.10013744; 10.1038/s41561-024-01421-5

Software

The software that was used to produce files in this dataset are available at https://github.com/jswade/merit-sword.

Primary Data Products

The following files represent the primary data products of the MERIT-SWORD dataset. Each file class generally has 61 files, corresponding to the 61 global hydrologic regions (region ii). For typical use of this dataset, download the 3 following zip folders listed below. The ms_translate.zip and ms_diagnostic.zip NetCDF files are best suited for scripting applications, while the ms_translate_shp.zip shapefiles are best suited for GIS applications.

The MERIT-SWORD translation tables (.nc) establish links between corresponding river reaches in MERIT-Basins and SWORD in both directions. The mb_to_sword translations relate the COMID values of all MERIT-Basins reaches in region ii (as defined by MERIT-Basins) to corresponding SWORD reach_id values, which are ranked by their degree of overlap and stored in columns sword_1 – sword_40. The partial intersecting lengths (m) of SWORD reaches within related MERIT-Basins unit catchments are stored in columns part_len_1 – part_len_40 and can be used to weight data transfers from more than one SWORD reach. The sword_to_mb translations relate the reach_id values of all SWORD reaches in region ii (as defined by SWORD) to corresponding MERIT-Basins COMID values, which are ranked by their degree of overlap and stored in columns mb_1 – mb_40. The partial intersecting lengths (m) of SWORD reaches within related MERIT-Basins unit catchments are again stored in columns part_len_1 – part_len_40.

ms _translate.zip

mb_to_sword: mb_to_sword_pfaf_ii_translate.nc

sword_to_mb: sword_to_mb_pfaf_ii_translate.nc

The MERIT-SWORD diagnostic tables (.nc) contain evaluations of the quality of translations between MERIT-Basins and SWORD reaches, stored in column flag. The mb_to_sword diagnostic files contain integer quality flags for each MERIT-Basins reach translation in region ii. The sword_to_mb diagnostic files contain integer quality flags for each SWORD reach translation in region ii. The quality flags are as follows:

0 = Valid translation.

1 = Translated reaches are not topologically connected to each other.

2 = Reach does not have a corresponding reach in the other dataset (absent translation).

21 = Reach does not have a corresponding reach in the other dataset due to flow accumulation mismatches.

22 = Reach does not have a corresponding reach in the other dataset because it is located in what the other dataset defines as the ocean.

ms_diagnostic.zip

mb_to_sword: mb_to_sword_pfaf_ii_diagnostic.nc

sword_to_mb: sword_to_mb_pfaf_ii_diagnostic.nc

For GIS applications, the translations and diagnostic tables are also available in shapefile format, joined to their respective MERIT-Basins and SWORD river vector shapefiles. The MERIT-Basins and SWORD shapefiles retain their original attribute tables, in additional to the added translation and diagnostic columns.

ms _translate_shp.zip

mb: riv_pfaf_ii_MERIT_Hydro_v07_Basins_v01_translate.shp

sword: jj_sword_reaches_hbii_v16_translate.shp

Example Applications Data Products

The following files are example use cases of transferring data between MERIT-Basins and SWORD. They are not required for typical use of the MERIT-SWORD dataset.

The MeanDRS-to-SWORD application example files demonstrate how the MERIT-SWORD translation tables can be used to transfer discharge simulations along MERIT-Basins reaches (i.e. MeanDRS; https://zenodo.org/records/8264511) to corresponding SWORD reaches in region ii and continent xx. MeanDRS discharge simulations (m3 s-1) are transferred to SWORD reaches based on a weighted average translation of corresponding reaches and stored in the column meanDRS_Q.

app_meandrs_to_sword.zip: xx_sword_reaches_hbii_v16_meandrs.shp

The SWORD-to-MERIT-Basins application example files demonstrate how the MERIT-SWORD translation tables can be used to transfer variables of interest (in this case, river width) from SWORD reaches to corresponding MERIT-Basins reaches in region ii. SWORD width estimates (m) are transferred to MERIT-Basins reaches based on a weighted average translation of corresponding reaches and stored in the column sword_wid.

app_sword_to_mb.zip: riv_pfaf_ii_MERIT_Hydro_v07_Basins_v01_sword.shp

Intermediate Data Products

The following files are intermediates used in generating the primary data. They are not required for typical use of the MERIT-SWORD dataset.

The MERIT-SWORD river trace files represent our first approximation of MERIT-Basins reaches that correspond to SWORD reaches in region ii, prior to the manual removal of mistakenly included reaches. The river trace files are only used to generate the final river network files and are not used elsewhere in the dataset.

ms_riv_trace.zip: meritsword_pfaf_ii_trace.shp

The MERIT-SWORD river network shapefiles contain the MERIT-Basins reaches that in aggregate best correspond to the location and extent of the SWORD river network for each of the Pfafstetter level 2 regions as defined by SWORD v16 (i.e. the 61 values of ii). The MERIT-SWORD river networks serve as an intermediary data product to enable reliable translations.

ms_riv_network.zip: meritsword_pfaf_ii_network.shp

The MERIT-SWORD transpose files are used to confirm that the translation tables in one direction can recreated in their entirety using only data from the translation tables in the other direction, ensuring ~3,500 less data transfer. These files are exact copies of the files contained in ms_translate.zip.

ms _transpose.zip

mb_transposed: mb_to_sword_pfaf_ii_transpose.nc

sword_transposed: sword_to_mb_pfaf_ii_transpose.nc

The MERIT-SWORD translation catchment files contain the MERIT-Basins unit catchments corresponding to each reach used in generating the mb_to_sword and sword_to_mb translations for each region ii. The files are used internally during the translation process and not required for typical dataset use.

ms_translate_cat.zip

mb_to_sword: mb_to_sword_pfaf_ii_translate_cat.nc

sword_to_mb: sword_to_mb_pfaf_ii_translate.cat.nc

The hydrologic regions as defined by MERIT-Basins and SWORD are not identical and overlap in many cases, complicating translations. The region overlap files provide bidirectional mappings between region identifiers in both datasets. The files are used in most dataset scripts to determine the regional files from each dataset that need to be loaded.

ms_region_overlap.zip: sword_to_mb_reg_overlap.csv, sword_to_mb_reg_overlap.csv

The MERIT-SWORD river edit files contain ~3,500 MERIT-Basins river reaches that were mistakenly included during river network generation and do not correspond to any SWORD reaches. These reaches are removed from the river trace files to generate the final MERIT-SWORD river network data product.

ms_riv_edit.zip: meritsword_edits.csv

Near the antimeridian, MERIT-Basins and SWORD shapefiles differ in their longitude convention. Additionally, the SWORD dataset lacks a shapefile for region 54, which does not have any SWORD reaches. The SWORD edit files contain copies of SWORD files, altered to match the longitude convention of MERIT-Basins and including a dummy shapefile for region 54.

sword_edit.zip: xx_sword_reaches_hbii_v16.shp

Known bugs in this dataset or the associated manuscript

No bugs have been identified at this time.

References

Altenau, E. H., Pavelsky, T. M., Durand, M. T., Yang, X., Frasson, R. P. de M., & Bendezu, L. (2021). The Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD): A Global River Network for Satellite Data Products. Water Resources Research, 57(7), e2021WR030054. https://doi.org/10.1029/2021WR030054

Collins, E. L., David, C. H., Riggs, R., Allen, G. H., Pavelsky, T. M., Lin, P., Pan, M., Yamazaki,

Supplementary files for Extraction of connected river networks from multi-temporal remote sensing imagery using a path tracking technique. Precise delineation of river networks is important for accurate hydrological and flood modelling. Whilst remote sensing (RS) has showed great potential in monitoring hydrological changes over space and time, the existing RS-based methods extract river networks based on local morphologies and seldom take into account the overall hydrological connectivity of the rivers. The existing methods also commonly neglect the effect of seasonal variation of water surfaces and the existence of temporary water bodies, which deteriorate the precision of positioning river networks. To address these challenges, a new two-stage method is developed to Extract spatiotemporal variation of water surfaces based on Multi-temporal remote sensing Imagery and Delineate connected river networks with improved accuracy (EMID method for short) using a path tracking technique. The EMID method delineates connected river networks using (a) multi-temporal imagery and a Random Forest model to synoptically map the location and extent of water surfaces under different hydrological conditions, and (b) an optimization algorithm to find the best river paths based on water-occurrence frequency. Four drainage basins with various river morphologies are considered to validate EMID. Comparing with alternative methods, the EMID method consistently produces river network results with improved accuracy in terms of stream location, river coverage and network connectivity.

The data set provides global river networks and corresponding water resources zones at three arc-seconds resolution and seven level. It provides river networks with good accuracy and precision and water resource zones with clearer topological relationships to ensure the efficiency of hydrological simulation and the accuracy of water resources evaluation.

'A data set of global river networks and corresponding water resources zones divisions V2.0'

The hydrographic features of the CanVec series include watercourses, water linear flow segments, hydrographic obstacles (falls, rapids, etc.), waterbodies (lakes, watercourses, etc.), permanent snow and ice features, water wells and springs. The Hydrographic features theme provides quality vector geospatial data (current, accurate, and consistent) of Canadian hydrographic phenomena. It aims to offer a geometric description and a set of basic attributes on hydrographic features that comply with international geomatics standards, seamlessly across Canada. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Related Products: Topographic Data of Canada - CanVec Series

This metadata record documents a geospatial dataset for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) used to drive the National Hydrologic Model (NHM). The Alaska Geospatial Fabric v1 is the spatial representation of the hydrologic response units (HRUs) used for the PRMS NHM Alaska domain. These HRUs were generated using the twelve-digit Hydrologic Unit Code (HUC12) watershed from the U.S. Geological Survey's Watershed Boundary Dataset (USGS, 2019), the Natural Resources Canada National Hydrographic Network (NHN) Work Units (NHN, 2019), similar to USGS eight-digit HUC watersheds, and stream gage locations from the U.S. Geological Survey (USGS, 2019) and Natural Resources Canada (NHN, 2019). Watershed-to-watershed routing was added to all Canadian Work Units and updated in twelve-digit HUCs from topographic map examination to ensure connectivity from the headwaters of the domain to the ocean. Watersheds containing one or more stream gages were bisected using standard watershed delineation techniques to ensure accurate contributing area for each gage. Gages near watershed boundaries were not used to bisect the watershed. Following these processing steps, these watersheds became the HRUs used for the initial version of the National Hydrologic Model Alaska Domain. Overlapping watershed vector lines were not unified. The stream gages used for this exercise became the points of interest (POIs) for use in the Alaska Domain. Stream segments used to route water from HRUs to stream outlets were generated using the routing information in the HRUs and the centroids of the HRUs. Please refer to the lineage elements of this metadata record for the above citations.

**Note that topographic maps at a scale of 1/100,000 are no longer updated. For the latest update date, see the metadata. The reference cartographic data is now constituted according to a continuous information layer approach: ** * AQRéseau+ * Geobase of the Quebec Hydrographic Network (GRHQ) * Administrative divisions at the scale of 1/20,000 (SDA)] (https://www.donneesquebec.ca/recherche/fr/dataset/decoupages-administratifs) * Geobase of the hydrographic terrain network of Quebec (GRHQ) * Administrative divisions at the scale of 1/20,000 (SDA) _ Topographic maps at a scale of 1/100,000 offer an overview of the occupation of Quebec territory at a scale of 1/100,000. A series in the south (266 sheets) and a series in the north (151 sheets) of the 53rd parallel cover the majority of Quebec. The data is less than 10 meters accurate and each file covers an area of approximately 4,000 km2, equivalent to 16 sheets at a scale of 1/20,000. Main components: * Hydrography (lakes of more than three hectares, permanent watercourses, swamps, etc.). * Vegetation (wooded areas and peatlands of more than 13 hectares). * Human constructions: * transport infrastructures (motorable roads, bridges, airports, etc.); * buildings larger than 12,500 m2; * buildings larger than 12,500 m2; * equipment and designated areas. * The relief (level curves at an equidistance). of 20 meters and elevation points). ##### Special features of the series south of the 53rd parallel * The data are obtained by a generalization of map data on a scale of 1/20,000. Between the 51st and the 53rd parallel, they are extracted from SPOT satellite imagery at 10 meters of resolution. * The data formats available for this series are: * Cover ArcInfo (vector); * GeoTIFF, CCL projection (matrix); * GeoTIFF, MTM projection (matrix); * GeoTIFF, MTM projection (matrix); * PDF (matrix); * PDF (matrix). ##### Special features of the series north of the 53rd parallel * The data is obtained by a generalization of map data from Natural Resources Canada (CanVec product) at a scale of 1:50,000. Multi-source data, namely data from Adresses Québec, data on airports and hydrobases from the Ministère des Transports du Québec, and data on reservoirs from Hydro-Québec, increase the quality of this cartographic product on a scale of 1/100,000. * The data format available for this series is: * FGDB (vector).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Abstract: The Hydrology Reference Network is a group of OPW hydrometric gauging stations that have been specially selected to provide a nationwide snapshot of the status of flood or drought events. These gauges were selected on the basis that they provide good quality estimates of fluvial high flows and have a suitable geographical spread across the country. The hydrological reference is used in two possible ways. This first is for reporting on large scale flood incidents after the fact. The second is for tracking changing water levels during a flood event for the purposes of rapid reporting. As the quality of measurements at these stations are of a sufficiently high quality, it has been possible to derive certain thresholds that describe the current or previously observed status of water levels at these sites. Current water levels at these gauges can be compared to the thresholds to describe the degree of severity of flood or drought conditions at any particular time. Lineage: Data is pulled from the selected OPW Hydrometric Gauges hourly. It should be noted that the configuration of gauges may change over time subject to new gauges becoming available that meet the acceptance criteria for the network.

As per Cognitive Market Research's latest published report, the Global Hydraulics and Hydrology Software market size will be $940.56 Million by 2028. Hydraulics and Hydrology Software Industry's Compound Annual Growth Rate will be 7.48% from 2023 to 2030.

The North America Hydraulics and Hydrology Software market size will be USD 306.25 Million by 2028.

What is Driving Hydraulics and Hydrology Software Industry Growth?

Need for water distribution

Living organisms need water to survive. Water is present in abundant quantities on and under Earth’s surface, but less than 1 percent of it is liquid fresh water. Although approximately 98 percent of liquid fresh water exists as groundwater, much of it occurs very deep. Thus to execute uniform supply of water, it is necessary to store, treat and distribute. It is extremely necessary to treat water as it has a strong tendency to dissolve other substances, so it is rarely found in its pure form.

People wholly depends on water for drinking, cooking, washing, carrying away wastes, and other domestic needs. Water supply systems must also meet requirements for public, commercial, and industrial activities. In all cases, the water must fulfil both quality and quantity requirements. Further, development of infrastructure due to rise in urbanization and population, requirement for water distribution is increasing.

According to the latest joint report of the WHO and UNICEF, over 884 million people have no access to improved drinking water. Delivering domestic water to the point of consumption requires some degree of engineering. Hydraulics and hydrology software provides comprehensive and easy decision-support tool for water distribution networks. The software helps in generating master plans, support land development projects, and optimize the operations of water distribution, wastewater, and storm water systems.

Thus, need for water distribution drives the growth of hydraulics and hydrology software market.

Restraints for Hydraulics and Hydrology Software Market

High initial cost associated with the installation.(Access Detailed Analysis in the Full Report Version)

Opportunities for Hydraulics and Hydrology Software Market

Rising concerns regarding waste-water treatment.(Access Detailed Analysis in the Full Report Version)

Introduction of Hydraulics and Hydrology Software

Hydrology and Hydraulics Software is used to create master plans, assist land development projects, and improve water distribution, wastewater, and storm water system operations. The programme helps any water utility to achieve its operational and managerial objectives, such as energy efficiency, design cost, and resource management.

Hydraulic and hydrological modelling are essential tools for analyzing network behavior, planning and designing changes to water infrastructure systems, and predicting water cycle activities. The programme includes tools for automating numerous delineations, computations, and modelling operations, both simple and complicated. It assists in increasing capacity to provide appropriate service levels while also allowing for additional flexibility.

Furthermore, the software is used by water professionals at utilities and engineering firms to plan intelligently and deliver clean water safely, accurately model water system operations, make reliable renewal decisions, reduce emergency response time, deliver high-quality design projects with minimal capital investments, and improve team productivity with sustainable GIS and CAD-integrated hydraulic models.

Hydraulic and hydrological software is used in water, storm water, wastewater, and other applications and is accessible on premise and in the cloud. Hydraulic and hydrological software is commonly used in sectors such as water and wastewater treatment, water distribution systems, oil and gas, building and architecture, and many more.

Many nations are currently seeing an increase in storms and floods, necessitating the development of effective hydraulics and hydrological models. Henceforth, industry participants are implementing technologies like Artificial Intelligence to make the process easier. As a result, the market for hydraulics and hydrology software is growing.

Abstract

This data and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The DNRM Water Measurement Information System Extract contains data collected from the State's Stream Gauging Station Network. This also includes an extract of water quality information. Refer to WMDP_UG_102014.pdf for the list of stream gauging stations managed by the Department of Natural Resources and Mines.

Dataset History

The department operates the Stream Gauging Station Network primarily to fulfil legislative requirements under Part 3, s35 of the Water Act 2000 (Qld) to regularly measure and keep publicly available records of volume and quality of water in Queensland.

The network assesses the state's water resource availability by providing data for hydrologic analysis, operation and management activities to ensure the productive and responsible use of natural resources. The network also provides real time information to the Bureau of Meteorology to assist with flood forecasting services which are used by local authorities across Queensland to prepare for potential flood inundation.

The Stream Gauging Station Network consists of around 400 stream gauging stations across Queensland that collect height and flow information. In addition, around 170 of these sites also collect time series water quality information. The network is operated by departmental Hydrographic staff within an ISO 9001:2008 accredited quality management system. Stream flow measurements are an integral part of the production of volumetric data for stream gauging stations throughout Queensland. Hydrographic staff take measurements throughout the full range of low and flood flow conditions.

Gaps in data records

Gaps in data records are more to occur likely during extreme events, particularly for TSWQ stations, where the data is automatically audited and potentially erroneous data is prevented from being displayed (Unreported data).

Data validation

DNRM is endeavouring to validate data as quickly as possible. Our performance indicator aims for data to be validated is within 160 days. You may wish to request updated information periodically to be supplied with the current validated data.

With respect to use of data:

Unvalidated data (Quality Code 130) has not been rigorously assessed and the data is quality coded to indentify this. These data should by used with care as they may change after validation. These data should only be used by persons who are familiar with the characteristics of streamflow information.

Validated data are data that has been assessed and is the best available quality at the time, however the data should always be interpreted taking into account the quality codes that have been applied.

Hydrologic advice should be sought to assist with any interpretation.

Water monitoring sites

Please see How water is monitored for further information on the departments water quality and quantity monitoring networks.

Current TS and water quality data Quality Codes

The Quality Codes the department currently uses are listed in the table below. These may be seen when viewing recent data.

Description Print Quality Code Quality Code Height (m) Flow Rain (mm) EC (S/cm) Temp (C) PH DO (mg/L)

Good 10

Water level below threshold (no flow) B 15

Fair 20

Poor 30

Estimate E 60

Interim 130

applies to time series data type

Print Quality Code reflects the numerical Quality Code on pre-computed outputs

All current and historic data Quality Codes

The complete list of all current and historical Quality Codes are shown in the table below. Historical codes are indicated in italics and may be seen when viewing historical data, DNRM does not employ them in routine operations.

Description Print Quality Code Quality Code

Good (Actual reading) 1

Historical data code 9

Good 10

Water level below threshold (no flow) B 15

Fair 20

Good daily records (BoM data) 26

Poor 30

Gauging temp - Good 31

Gauging temp - Fair 32

Gauging temp - Poor 33

Gauging temp - Composite 34

Gauging temp - Suspect instrument 35

Gauging temp - Derived measurement 36

Gauging temp - Discharge correlated 37

Gauging temp - Data of no value 39

Derived height (CITEC data) * 59

Estimate E 60

Derived discharge * 69

Back water affected (CITEC data) 79

Accumulated rainfall (BoM data) 80

Wet days within period 81

Rainfall (non-standard) 83

Gauge height > instrument threshold 119

Historic water quality data, Fair 125

Not coded (unvalidated data) * 130

Interim I 140

Unknown quality U 150

Unreported data Blank value field 151

160

170

180

200

201

255

Italics applies to historically used data QualityCodes

Print Quality Code reflects the numerical Quality Code on pre-computed outputs

Dataset Citation

Queensland Department of Natural Resources and Mines (2015) Maranoa-Balonne-Condamine surfacewater EC sites. Bioregional Assessment Source Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/4e7f862a-573c-440d-9974-7b83afc50db9.

The World HydroBasemap service is designed to be used as a base map by scientists, professionals, and researchers in the fields of Hydrology, Geography, Climate, Soils, and other natural sciences. The map features a hydro-centric design based on the amount of water flowing within the drainage network such that symbols of the same size and color represent roughly the same amount of water. This map shows surface water flow as a linear phenomenon even over and through bodies of water. Using the best available data we show relative flow accurately, so that if one river carries more water downstream than another river, the result will be that the river will have a thicker symbol on the map. This map is a mashup oftheWorld Hydro Reference overlay, and the WorldTerrain base, which allows you to sandwich in content such as thematic serviceslike soil units, vegetation, or ecoregions. This basemap provides a frame of reference for showing regional, national, and continental hydrologic phenomena such as drought, runoff, river level monitoring and flood forecasting.River names are collected in the UTF8 character set, so river names are collected in their original language, but are written in the Roman alphabet. Sources for all river names are from the open source geonames.org project so they are international by nature.The map is compiled from several sources. The global scales (very small scales through 1:2,300,000) include content from: HydroSHEDS, GTOPO30 Global Topographic Data, SRTM, GLWD, WorldClim, GRDC, and WWF Global 200 Terrestrial Eco Regions, with the latter three providing the inputs and basis for calculating flow. At medium scales (1:36,000 to 1:2,000,000) this service currently contains only U.S. data from the NHDPlusV2 that was jointly produced by the USGS and EPA. This work is licensed under the Web Services and API Terms of Use. View Summary |View Terms of Use HydroSHEDSThis product, the World Hydro Basemap, incorporates data from the HydroSHEDS database which is World Wildlife Fund, Inc. (2006-2012) and has been used herein under license. WWF has not evaluated the data as altered and incorporated within the World Hydro Basemap, and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose. Portions of the HydroSHEDS database incorporate data which are the intellectual property rights of USGS (2006-2008) (data available from U.S. Geological Survey, EROS Data Center, SD), NASA (2000-2005), ESRI (1992-1998), CIAT (2004-2006), UNEP-WCMC (1993), WWF (2004), Commonwealth of Australia (2007), and Her Royal Majesty and the British Crown and are used under license. The scientific citation for the HydroSHEDS database is: Lehner, B., Verdin, K., Jarvis, A. (2008): New global hydrography derived from spaceborne elevation data. Eos, Transactions, AGU, 89(10): 93-94.

These digital terrain models (DTM) offer a regional numerical representation of Quebec's relief based on altimetric (altitude) and planimetric (rectangular or geographic) data. They are the result of a collaboration between the Ministry of Natural Resources and Forests (MRNF) and Natural Resources Canada (NRCan) within the framework of the Agreement to produce an up-to-date digital map of northern Quebec and the creation of the product “National Hydro Network (RHN)” for the territory of Quebec. When integrated into a geographic information system, these models allow the implementation of multiple types of spatial analyses such as natural risks, landscape analysis, infrastructure implementation, etc. NCDs are obtained as a result of hypsometric and hydrographic data processing that uses the concept of hydro-coherence that uses the concept of hydro-coherence consisting in interpolating altimetric values by ensuring a connected drainage network and an accurate representation of crests and river courses. water. The oriented RHN filament makes it possible to grade lakes and to control the altimeter descent of watercourses. The final product is a quality portrait of relief on a scale of 1/50,000. DNTs provide altitude values that are based on a grid with a resolution of 0.324 arcseconds in geographic coordinates, which corresponds to a resolution of about 10 meters in the field.This third party metadata element was translated using an automated translation tool (Amazon Translate).

Abstract Waterbodies are bodies of fresh water with potential significance for water balance and water reporting purposes. Composited from AusHydro V2, waterbodies comprise three major categories -

Lakes: A naturally occurring body of mainly static water surrounded by land. Reservoirs: A body of water collected and stored behind a constructed barrier for some specific use (with the exception of Flood Irrigation Storage). Swamp (subset of AusHydro feature class "Flats"): Land which is so saturated with water that it is not suitable for agricultural or pastoral use and presents a barrier to free passage or Low lying land usually adjacent to lakes or watercourses, which is regularly covered with flood water for short periods.

These features represent waterbodies that are related to the stream networks by storing the HydroID of the most downstream outlet JunctionNode. These features will also contain MappedArtificialFlowSegment. A subset of the water bodies within the AHGFWaterBody Feature Class are associated with the Bureau’s Water Storage Product and are attributed by SLAKE_Name, SLAKE_Syst and SLAKE_URN. For further information on how to link the Water Storage features in the Geofabric to the Bureau’s Water Storage Website, refer to the tutorial Access Water Storage information. Currency Date modified: 28 November 2022 Modification frequency: None Data extent Spatial extent North: -10.134630° South: -43.602680° East: 153.612750° West: 113.017480° Source information This dataset is derived from the Bureau of Meteorology's Geofabric dataset, in partnership with:

Geoscience Australia, The Australian National University Fenner School of Environment and Society and CSIRO Land and Water Flagship.

More information can be found at the Geofabric Documentation page. Lineage statement The Geofabric is an ongoing project which is the result of considerable effort and consultation by several agencies, both within Australia and internationally. The project is being led by the Bureau of Meteorology, in partnership with Geoscience Australia (GA), the Australian National University Fenner School of Environment and Society (ANU) and CSIRO Land and Water Flagship (CSIRO). The dataset presented here is a subset extracted from the national Geofabric Version 3.3 dataset. This dataset has been re-projected from GDA94 to Web Mercator as part of the Digital Atlas of Austalia project. Minor changes to symbology have been performed only as neccessary to meet the requirements of this project. Data dictionary All layers

Attribute name Description

Hydro ID Geofabric feature identifier, unique across all geodatabases within an AHGF release

AHGF Feature Type Feature type within the AHGF Data Model (e.g. Reservoir, Swamp)

Name The commonly used descriptor for the water body

Perenniality Either Perennial or Non-Perennial

Network Node ID Feature identifer: descriptor of water network

Water Store Use If the water body is used for public storage: type of usage/storage

Water Storage Name If the water body is used for public storage: name of water storage

Water Storage System If the water body is used for public storage: name of storage network

Water Storage URL If the water body is used for public storage: webpage for storage dashboard

Source Feature Class Name Feature class name from the input data source (e.g. Reservoirs)

Source Feature Type Feature type from the input data source (e.g. TownRuralStorage)

Source Type Feature subtype (numeric code) from the input data source (e.g. 2)

Source ID Unique identifier for individual feature in the input data source (e.g. 3023726)

Feature Reliability Reliability date of spatial object. Adjusted during spatial change/verification

Feature Source Name of agency that originally captured the spatial object

Attribute Reliability Reliability date of attribute object. Adjusted during attribute change/verification

Attribute Source Name of agency that originally captured the attribute object

Planimetric Accuracy Standard deviation of the horizontal positional accuracy in metres (e.g. 100)

Symbol No longer provided in Phase 3 input data. Was the symbol number for feature used in GA’s GEODATA product

Text Note Text note to accompany the feature

Contracted Catchment ID The HydroID for a contracted catchment

Contact Bureau of Meteorology, ahgf@bom.gov.au

Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This is a virtual dataset. It is too large to supply directly to this data register and is available via the Victorian government data repository - https://www.data.vic.gov.au/data/ This contains line features delineating hydrological features. Includes; Watercourses (ie channels, rivers & streams) & Connectors. Attributed for name. Arcs run downstream. A brief description of this dataset is also contained within a readme.txt within the dataset ## Purpose Vicmap Hydro provides an accurate representation of natural and man made Hydrographic features across Victoria, at a capture scale of 1:25,000. It is used in a variety of applications, particularly in emergency services, natural resource management, planning and development, and digital map publication. ## Dataset History Detail copied from the data.vic.gov.au Metadata record for Watercourse Network 1:25,000 - Vicmap Hydro (ANZVI0803002490). The line work and points were generated from the Vicmap Digital Topographic (VDT) map base coordinated by LIG. VDT evolved from Victoria's printed 1:25,000 Topographic Map Series program together with the need to supply a control framework for the creation of the rural Digital Cadastral Mapbase. The capture scale is 1:25,000 Statewide and the coverage, except for minor border issues is also statewide. The planimetric accuracy attainable will be the sum of errors from three sources:the positional accuracy of the source material, errors due to the conversion process, errors due to the manipulation process. For topographic base derived data this represents an error of 8.3m on the ground for 1:25,000 data. A conservative estimate of 10m for the standard deviation will be used in any data quality information. Alternate and equal ways of expressing this error are: not more than 10% of well-defined points will be in error by more than 16 m. The worst case error for the data is +/- 30 m. For vertical positional accuracy of points determined from contours there is an expectation that the elevation accuracy (standard deviation) will be half the value of the contour interval. ## Dataset Citation Victorian Department of Environment, Land, Water and Planning (2016) Vicmap Hydro. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/158f64d6-26cf-458b-80f4-f27161be2c55.

Discharge at river Oriartorfik (m3/s) River hydrology:River hydrology ClimateBasis Nuuk:The ClimateBasis programme monitors climate and hydrology in Zackenberg, Kobbefjord and Disko (Qeqertarsuaq) and is run by Asiaq - Greenland Survey. The collected data build base-line information on climate variability and trends for all the other sub-programmes within GEM and serve as a trustworthy foundation for adaptation strategies for the Greenlandic society. The stations are embedded in Asiaq’s extensive climate and hydrology monitoring network. Furthermore, the run-off data is delivered to the World Hydrological Cycle Observing System (WHYCOS) and the Global Runoff Data Centre (GRDC) networks.

Abstract The Australian Hydrological Geospatial Fabric (Geofabric) identifies and registers the spatial relationships between important hydrological features such as watercourses, water bodies, canals, aquifers, monitoring points and catchments. Geofabric Hydrology Reporting Regions are derived from aggregations of contracted catchments from Geofabric Hydrology Reporting Catchments. This product contains two candidate reporting regions, namely AWRA Drainage Division for national scale reporting purposes and River Region for regional scale reporting purposes. More reporting regions may be added in future releases based on user requirements. The River Regions were based on a specification developed by Bureau hydrologists involved in water resources assessment in consultation with the Geofabric team and scientists from CSIRO and ANU. These boundaries were developed for use in regional scale reporting and hydrological modelling. The River Region boundaries were not used in the Australian Water Resources Assessment 2010 and 2012 but may be considered in the future as the resolution of reporting increases. Produced as part of the Australian Hydrological Geospatial Fabric (Geofabric). These regions align with, and are nested within, the revised drainage divisions. Australian Rivers, Lakes and water storages are all connected. The complex nature of our water system means that understanding these connections is vital for the effective management of water resources. The Geofabric is a specialised Geographic Information System. It is like a digital street directory of australia's important water features. It lets you map how water is moved, used and stored throughout the landscape. It is an authoritative information source that works seamlessly across australia. The Geofabric is made up of six datasets for use in hydrological visualisation, analysis and reporting. First up, the Hydrology reporting regions define australia's drainage divisions and river regions. This is used for reporting by government and other organisations. Hydrology Reporting Catchments are the building blocks of reporting regions. They provide finer detail for smaller rivers. Surface Cartography lets you visualise surface water features such as canals and bridges. This context is great for water managers and emergency services, for example to anticipate downstream communities affected by floods. This is achieved in combination with the Surface Network which links streamflows that can connect when there are high water flows. Visualising these full networks helps with streamflow forecasting. You can trace these connected and directed stream networks, and link them to Surface Catchments. This lets you identify the upstream contributing catchment area for a selected stream segment. Hydrologists use this to define networks and related catchments, and to inform environmental management and reporting. Groundwater Cartography shows groundwater resources and their features such as salinity as well as the rocks and sediments at different levels below the surface. This adds to the Geofabric’s detailed map of how our water system is connected. All information has been standardised across the country. This is why the Geofabric is widely used for streamflow analysis and the creation of customised catchments. Tutorials and a sample toolkit are available to help you perform common tasks. The Geofabric is continually being improved. Currency Date modified: 28 November 2022 Modification frequency: None Data extent Spatial extent North: -10.015416° South: -43.861528° East: 153.639028° West: 113.000139° Source information This dataset is derived from the Bureau of Meteorology's Geofabric dataset, in partnership with:

Geoscience Australia, The Australian National University Fenner School of Environment and Society and CSIRO Land and Water Flagship.

More information can be found at the Geofabric Documentation page. Lineage statement The Geofabric is an ongoing project which is the result of considerable effort and consultation by several agencies, both within Australia and internationally. The project is being led by the Bureau of Meteorology, in partnership with Geoscience Australia (GA), the Australian National University Fenner School of Environment and Society (ANU) and CSIRO Land and Water Flagship (CSIRO). The dataset presented here is a subset extracted from the national Geofabric Version 3.3 dataset. This dataset has been re-projected from GDA94 to Web Mercator as part of the Digital Atlas of Austalia project. Minor changes to symbology have been performed only as neccessary to meet the requirements of this project. Data dictionary All layers

Attribute name Description

Hydro ID Geofabric feature identifier, unique across all geodatabases within an AHGF release

Division 1 second DEM Drainage Division Name

River Region Name The name assigned to the RiverRegion

Source Feature Class Name Feature class name from the input data source (e.g. Reservoirs)

Source Feature Type Feature type from the input data source (e.g. TownRuralStorage)

Source Type Feature subtype (numeric code) from the input data source (e.g. 2)

Source ID Unique identifier for individual feature in the input data source (e.g. 3023726)

Feature Reliability Reliability date of spatial object. Adjusted during spatial change/verification

Feature Source Name of agency that originally captured the spatial object

Attribute Reliability Reliability date of attribute object. Adjusted during attribute change/verification

Attribute Source Name of agency that originally captured the attribute object

Planimetric Accuracy Standard deviation of the horizontal positional accuracy in metres (e.g. 100)

Symbol No longer provided in Phase 3 input data. Was the symbol number for feature used in GA’s GEODATA product

Text Note Text note to accompany the feature

Contact Bureau of Meteorology, ahgf@bom.gov.au

This dataset contains the flux measurements from the Yakou station eddy covariance system (EC) in the upper reaches of the Heihe integrated observatory network from January 1 to December 31 in 2020. The site (100.2421° E, 38.0142° N) was located in the Qilian County in Qinghai Province. The elevation is 4148 m. The EC was installed at a height of 3.2 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500A) was 0.15 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. The power loss occurs occasionally at this site. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references. For more information, please refer to Liu et al. (2018) and Che et al. (2019) (for sites information), Liu et al. (2011) for data processing) in the Citation section.