LAC is the most water-rich region in the world by most metrics; however, water resource distribution throughout the region does not correspond demand. To understand water risk throughout the region, this dataset provides population and land area estimates for factors related to water risk, allowing users to explore vulnerability throughout the region to multiple dimensions of water risk. This dataset contains estimates of populations living in areas of water stress and risk in 27 countries in Latin America and the Caribbean (LAC) at the municipal level. The dataset contains categories of 18 factors related to water risk and 39 indices of water risk and population estimates within each with aggregations possible at the basin, state, country, and regional level. The population data used to generate this dataset were obtained from the WorldPop project 2020 UN-adjusted population projections, while estimates of water stress and risk come from WRI’s Aqueduct 3.0 Water Risk Framework. Municipal administrative boundaries are from the Database of Global Administrative Areas (GADM). For more information on the methodology users are invited to read IADB Technical Note IDB-TN-2411: “Scarcity in the Land of Plenty”, and WRIs “Aqueduct 3.0: Updated Decision-relevant Global Water Risk Indicators”.

Water is essential to the progress of human societies. It is required for a healthy environment and a thriving economy. Food production, electricity generation, and manufacturing, among other things, all depend on it. However, many decision-makers lack the technical expertise to fully understand hydrological information.

In response to growing concerns from the private sector and other actors about water availability, water quality, climate change, and increasing demand, WRI applied the composite index approach as a robust communication tool to translate hydrological data into intuitive indicators of water-related risks.

This dataset updates the Aqueduct™ water risk framework, in which we combine 13 water risk indicators—including quantity, quality, and reputational risks—into a composite overall water risk score.

This database and the Aqueduct tools enable comparison of water-related risks across large geographies to identify regions or assets deserving of closer attention. Aqueduct 3.0 introduces an updated water risk framework and new and improved indicators. It also features different hydrological sub-basins. We introduce indicators based on a new hydrological model that now features (1) integrated water supply and demand, (2) surface water and groundwater modelling, (3) higher spatial resolution, and (4) a monthly time series that enables the provision of monthly scores for selected indicators.

Key elements of Aqueduct, such as overall water risk, cannot be directly measured and therefore are not validated. Aqueduct remains primarily a prioritization tool and should be augmented by local and regional deep dives.

User Guide Includes column descriptors and other metadata regarding the dataset https://github.com/wri/aqueduct30_data_download/blob/master/metadata.md

Source https://www.wri.org/resources/data-sets/aqueduct-global-maps-30-data

About Aqueduct Aqueduct’s tools map water risks such as floods, droughts, and stress, using open-source, peer-reviewed data. Beyond the tools, the Aqueduct team works one-on-one with companies, governments, and research partners to help advance best practices in water resources management and enable sustainable growth in a water-constrained world.

Over the past six years, the Aqueduct tools have reached hundreds of thousands of users across the globe and informed decision-makers in and beyond the water sector. Aqueduct data and insights have been featured in major media outlets including, the Economist, the Guardian, Bloomberg Businessweek, the New York Times and Vox’s Netflix show Explained.

This iteration of Aqueduct represents our most robust look at water risks to date, including more granular data, higher resolution, new indicators, improved tool function and access to underlying hydrological models.

Data DescriptionWater Quality Parameters: Ammonia, BOD, DO, Orthophosphate, pH, Temperature, Nitrogen, Nitrate.Countries/Regions: United States, Canada, Ireland, England, China.Years Covered: 1940-2023.Data Records: 2.82 million.Definition of ColumnsCountry: Name of the water-body region.Area: Name of the area in the region.Waterbody Type: Type of the water-body source.Date: Date of the sample collection (dd-mm-yyyy).Ammonia (mg/l): Ammonia concentration.Biochemical Oxygen Demand (BOD) (mg/l): Oxygen demand measurement.Dissolved Oxygen (DO) (mg/l): Concentration of dissolved oxygen.Orthophosphate (mg/l): Orthophosphate concentration.pH (pH units): pH level of water.Temperature (°C): Temperature in Celsius.Nitrogen (mg/l): Total nitrogen concentration.Nitrate (mg/l): Nitrate concentration.CCME_Values: Calculated water quality index values using the CCME WQI model.CCME_WQI: Water Quality Index classification based on CCME_Values.Data Directory Description:Category 1: DatasetCombined Data: This folder contains two CSV files: Combined_dataset.csv and Summary.xlsx. The Combined_dataset.csv file includes all eight water quality parameter readings across five countries, with additional data for initial preprocessing steps like missing value handling, outlier detection, and other operations. It also contains the CCME Water Quality Index calculation for empirical analysis and ML-based research. The Summary.xlsx provides a brief description of the datasets, including data distributions (e.g., maximum, minimum, mean, standard deviation).Combined_dataset.csvSummary.xlsxCountry-wise Data: This folder contains separate country-based datasets in CSV files. Each file includes the eight water quality parameters for regional analysis. The Summary_country.xlsx file presents country-wise dataset descriptions with data distributions (e.g., maximum, minimum, mean, standard deviation).England_dataset.csvCanada_dataset.csvUSA_dataset.csvIreland_dataset.csvChina_dataset.csvSummary_country.xlsxCategory 2: CodeData processing and harmonization code (e.g., Language Conversion, Date Conversion, Parameter Naming and Unit Conversion, Missing Value Handling, WQI Measurement and Classification).Data_Processing_Harmonnization.ipynbThe code used for Technical Validation (e.g., assessing the Data Distribution, Outlier Detection, Water Quality Trend Analysis, and Vrifying the Application of the Dataset for the ML Models).Technical_Validation.ipynbCategory 3: Data Collection SourcesThis category includes links to the selected dataset sources, which were used to create the dataset and are provided for further reconstruction or data formation. It contains links to various data collection sources.DataCollectionSources.xlsxOriginal Paper Title: A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted ResearchAbstractAssessment and monitoring of surface water quality are essential for food security, public health, and ecosystem protection. Although water quality monitoring is a known phenomenon, little effort has been made to offer a comprehensive and harmonized dataset for surface water at the global scale. This study presents a comprehensive surface water quality dataset that preserves spatio-temporal variability, integrity, consistency, and depth of the data to facilitate empirical and data-driven evaluation, prediction, and forecasting. The dataset is assembled from a range of sources, including regional and global water quality databases, water management organizations, and individual research projects from five prominent countries in the world, e.g., the USA, Canada, Ireland, England, and China. The resulting dataset consists of 2.82 million measurements of eight water quality parameters that span 1940 - 2023. This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.Note: Cite this repository and the original paper when using this dataset.

In 1991, the U.S. Geological Survey (USGS) began a study of more than 50 major river basins across the Nation as part of the National Water-Quality Assessment (NAWQA) project of the National Water-Quality Program. One of the major goals of the NAWQA project is to determine how water-quality conditions change over time. To support that goal, long-term consistent and comparable monitoring has been conducted on streams and rivers throughout the Nation. Outside of the NAWQA project, the USGS and other Federal, State, and local agencies also have collected long-term water-quality data to support their own assessments of changing water-quality conditions. Data from these multiple sources have been combined to support one of the most comprehensive assessments conducted to date of water-quality trends in the United States. Ultimately, these data will provide insight into how natural features and human activities have contributed to water-quality changes over time in Nation’s streams and rivers. This USGS data release contains all of the input and output files necessary to reproduce the results of the Seasonal Kendall trend tests described in the associated U.S. Geological Survey Scientific Investigations Report. Data preparation for input to the model is also fully described in the above-mentioned report.

Canada is a water rich country with one of the highest annual water uses per person among developed countries. This study provides a systematic, comprehensive analysis of recent data on this water use at national and subnational scales. It spatially disaggregates surveyed data from Statistics Canada (StatCan) to develop a historical dataset from 2005-2018 for Canadian water withdrawals at provincial and river basin scales for seven water use sectors: domestic use, manufacturing, irrigation, livestock, mining, oil and gas and thermal power generation. Additionally, sectoral water withdrawals are estimated for each province-river basin combination. Sectoral priorities are analyzed at the provincial and river basin scales and historical trends are identified. Water use intensity indicators are calculated and compared between different provinces, and a water stress index is used to identify regions most prone to water shortages. We find that water use decreased nationally over the study years for all sectors except irrigation, mining and oil and gas. Ontario had the highest water use of all provinces, mainly for thermal power generation. Manufacturing and domestic sectors were the dominant users in Quebec and British Columbia while the Prairies had more diversified uses. Domestic water use per capita values in Newfoundland & Labrador and Quebec are higher than the national average and all global values included in the study for comparison. Finally, the irrigation sector withdraws the most water per $GDP nationally while the oil and gas sector withdraws the least. Dataset development faced challenges related to data availability and uncertainties in downscaling assumptions. These challenges are described, and emphasize the need for a systematic and standardized approach to water data gathering and sharing in Canada.

A quantitative basis for comparing, analyzing, and understanding environmental performance for 180 countries. We score and rank these countries on their environmental performance using the most recent year of data available and calculate how these scores have changed over the previous decade. Data provided by country, and can be filtered by regions. Relavent metrics scored on the EPI include: Access to sanitation and drinking water, Unsafe sanitation, unsafe drinking water, water resources impact (based on wastewater discharge), Wastewater Treatment

Nonstationary streamflow due to environmental and human-induced causes can affect water quality over time, yet these effects are poorly accounted for in water-quality trend models. This data release provides instream water-quality trends and estimates of two components of change, for sites across the Nation previously presented in Oelsner et al. (2017). We used previously calibrated Weighted Regressions on Time, Discharge, and Season (WRTDS) models published in De Cicco et al. (2017) to estimate instream water-quality trends and associated uncertainties with the generalized flow normalization procedure available in EGRET version 3.0 (Hirsch et al., 2018a) and EGRETci version 2.0 (Hirsch et al., 2018b). The procedure allows for nonstationarity in the flow regime, whereas previous versions of EGRET assumed streamflow stationarity. Water-quality trends of annual mean concentrations and loads (also referred to as fluxes) are provided as an annual series and the change between the start and end year for four trend periods (1972-2012, 1982-2012, 1992-2012, and 2002-2012). Information about the sites, including the collecting agency and associated streamflow gage, and information about site selection and the data screening process can be found in Oelsner et al. (2017). This data release includes results for 19 water-quality parameters including nutrients (ammonia, nitrate, filtered and unfiltered orthophosphate, total nitrogen, total phosphorus), major ions (calcium, chloride, magnesium, potassium, sodium, sulfate), salinity indicators (specific conductance, total dissolved solids), carbon (alkalinity, dissolved organic carbon, total organic carbon), and sediment (total suspended solids, suspended-sediment concentration) at over 1,200 sites. Note, the number of parameters with data varies by site with most sites having data for 1-4 parameters. Each water-quality trend was parsed into two components of change: (1) the streamflow trend component (QTC) and (2) the watershed management trend component (MTC). The QTC is an indicator of the amount of change in the water-quality trend attributed to changes in the streamflow regime, and the MTC is an indicator of the amount of change in the water-quality trend that may be attributed to human actions and changes in point and non-point sources in a watershed. Note, the MTC is referred to as the concentration-discharge trend component (CQTC) in the EGRET version 3.0 software. For our work, we chose to refer to this trend component as the MTC because it provides a more conceptual description (Murphy and Sprague, 2019). The trend results presented here expand upon the results in De Cicco et al. (2017) and Oelsner et al. (2017), which were analyzed using flow-normalization under the stationary streamflow assumption. The results presented in this data release are intended to complement these previously published results and support investigations into natural and human effects on water-quality trends across the United States. Data preparation information and WRTDS model specifications are described in Oelsner et al. (2017) and Murphy and Sprague (2019). This work was completed as part of the National Water-Quality Assessment (NAWQA) project of the National Water-Quality Program. De Cicco, L.A., Sprague, L.A., Murphy, J.C., Riskin, M.L., Falcone, J.A., Stets, E.G., Oelsner, G.P., and Johnson, H.M., 2017, Water-quality and streamflow datasets used in the Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2012 (ver. 1.1 July 7, 2017): U.S. Geological Survey data release, https://doi.org/10.5066/F7KW5D4H. Hirsch, R., De Cicco, L., Watkins, D., Carr, L., and Murphy, J., 2018a, EGRET: Exploration and Graphics for RivEr Trends, version 3.0, https://CRAN.R-project.org/package=EGRET. Hirsch, R., De Cicco, L., and Murphy, J., 2018b, EGRETci: Exploration and Graphics for RivEr Trends (EGRET) Confidence Intervals, version 2.0. https://CRAN.R-project.org/package=EGRETci. Murphy, J.C., and Sprague, L.A., 2019, Water-quality trends in US rivers: Exploring effects from streamflow trends and changes in watershed management: The Science of the total environment, ISSN: 1879-1026, Vol: 656, Page: 645-658, https://doi.org/10.1016/j.scitotenv.2018.11.255. Oelsner, G.P., Sprague, L.A., Murphy, J.C., Zuellig, R.E., Johnson, H.M., Ryberg, K.R., Falcone, J.A., Stets, E.G., Vecchia, A.V., Riskin, M.L., De Cicco, L.A., Mills, T.J., and Farmer, W.H., 2017, Water-quality trends in the Nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results (ver. 2.0, October 2017): U.S. Geological Survey Scientific Investigations Report 2017–5006, 136 p., https://doi.org/10.3133/sir20175006.

The WaDE Program is committed to assisting WSWC member states in publicly sharing water rights, allocation, supply, and use data through a common streamlined and standardized service that enables regional analyses to inform water resources planning and policies.

How much water is there? What is its quality? How is it currently being used? Improving our water data infrastructure, quality, and availability is one of the country’s most pressing challenges, but it is one that will enable us to more sustainably manage our most precious resource. To address this challenge, the Western States Water Council (WSWC) aimed to formulate a strategy and to develop a framework for its member states to begin to share important water supply, water use, and water administration datasets with each other, with federal partners, and with the public, called the Water Data Exchange.

Property Description

Hylak_id Unique lake identifier. Values range from 1 to 1,427,688.

**Lake_name ** Name of lake or reservoir. This field is currently only populated for lakes with an area of at least 500 km2; for large reservoirs where a name was available in the GRanD database; and for smaller lakes where a name was available in the GLWD database.

Country Country that the lake (or reservoir) is located in. International or transboundary lakes are assigned to the country in which its corresponding lake pour point is located and may be arbitrary for pour points that fall on country boundaries.

Continent Continent that the lake (or reservoir) is located in. Geographic continent: Africa, Asia, Europe, North America, South America, or Oceania (Australia and Pacific Islands)

Poly_src The name of datasets that were used in the column. Source of original lake polygon: CanVec; SWBD; MODIS; NHD; ECRINS; GLWD; GRanD; or Other More information on these data sources can be found in Table 1.

Lake_type Indicator for lake type: 1: Lake 2: Reservoir 3: Lake control (i.e. natural lake with regulation structure) Note that the default value for all water bodies is 1, and only those water bodies explicitly identified as other types (mostly based on information from the GRanD database) have other values; hence the type ‘Lake’ also includes all unidentified smaller human-made reservoirs and regulated lakes.

Grand_id ID of the corresponding reservoir in the GRanD database, or value 0 for no corresponding GRanD record. This field can be used to join additional attributes from the GRanD database.

Lake_area Lake surface area (i.e. polygon area), in square kilometers.

Shore_len Length of shoreline (i.e. polygon outline), in kilometers.

Shore_dev Shoreline development, measured as the ratio between shoreline length and the circumference of a circle with the same area. A lake with the shape of a perfect circle has a shoreline development of 1, while higher values indicate increasing shoreline complexity.

Vol_total Total lake or reservoir volume, in million cubic meters (1 mcm = 0.001 km3). For most polygons, this value represents the total lake volume as estimated using the geostatistical modeling approach by Messager et al. (2016). However, where either a reported lake volume (for lakes ≥ 500 km2) or a reported reservoir volume (from GRanD database) existed, the total volume represents this reported value. In cases of regulated lakes, the total volume represents the larger value between reported reservoir and modeled or reported lake volume. Column ‘Vol_src’ provides additional information regarding these distinctions.

Vol_res Reported reservoir volume, or storage volume of added lake regulation, in million cubic meters (1 mcm = 0.001 km3). 0: no reservoir volume

Vol_src 1: ‘Vol_total’ is the reported total lake volume from literature 2: ‘Vol_total’ is the reported total reservoir volume from GRanD or literature 3: ‘Vol_total’ is the estimated total lake volume using the geostatistical modeling approach by Messager et al. (2016)

Depth_avg Average lake depth, in meters. Average lake depth is defined as the ratio between total lake volume (‘Vol_total’) and lake area (‘Lake_area’).

Dis_avg Average long-term discharge flowing through the lake, in cubic meters per second. This value is derived from modeled runoff and discharge estimates provided by the global hydrological model WaterGAP, downscaled to the 15 arc-second resolution of HydroSHEDS (see section 2.2 for more details) and is extracted at the location of the lake pour point. Note that these model estimates contain considerable uncertainty, in particular for very low flows. -9999: no data as lake pour point is not on HydroSHEDS landmask

Res_time Average residence time of the lake water, in days. The average residence time is calculated as the ratio between total lake volume (‘Vol_total’) and average long-term discharge (‘Dis_avg’). Values below 0.1 are rounded up to 0.1 as shorter residence times seem implausible (and likely indicate model errors). -1: cannot be calculated as ‘Dis_avg’ is 0 -9999: no data as lake pour point is not on HydroSHEDS landmask

Elevation Elevation of lake surface, in meters above sea level. This value was primarily derived from the EarthEnv-DEM90 digital elevation model at 90 m pixel resolution by calculating the majority pixel elevation found within the lake boundaries. To remove some artefacts inherent in this DEM for northern latitudes, all lake values that showed negative elevation for the area north of 60°N were substituted with results using the coarser GTOPO30 DEM of USGS at 1 km pixel resolution, which ensures land surfaces ≥0 in this region. Note that due to the remaining uncertainties in the EarthEnv-DEM90 some small negative values occur along the global oce...

This layer presents water abstraction in Cubic Meters per capita per year for 32 countries (23 in Europe and North America, 5 in Asia and the Pacific, 4 in Latin America and the Caribbean) at the most recent date between 2008 and 2012. However, data are available from 1975 to 2014 for 39 countries. Water abstractions or water withdrawals, are defined as freshwater taken from ground or surface water sources, either permanently or temporarily, and conveyed to a place of use. The data include abstractions for public water supply, irrigation, industrial processes, cooling of electric power plants, mine water and drainage water. For more information, visit the OECD database: https://data.oecd.org/water/water-withdrawals.htm#indicator-chart

The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 1st River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the abovementioned surface water bodies and groundwater bodies.

The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations.

The dataset compiles the available spatial data related to the 1st RBMPs which were due in 2010 (hereafter WFD2010). See http://rod.eionet.europa.eu/obligations/521 for further information on the WFD2010 reporting.

It was prepared to support the reporting of the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting.

The data reported in WFD2010 were updated using data reported in WFD2016, whenever the spatial objects are identical in 2010 and 2016. For WFD2010 objects, some information may be missing, if the objects no longer exist in the 2nd River Basin Management Plans, and were not reported in WFD2016.

Relevant concepts:

River basin district (RBD): The area of land and sea, made up of one or more neighbouring river basins together with their associated groundwaters and coastal waters, which is the main unit for management of river basins.

River basin: The area of land from which all surface run-off flows through a sequence of streams, rivers and, possibly, lakes into the sea at a single river mouth, estuary or delta.

Sub-basin: The area of land from which all surface run-off flows through a series of streams, rivers and, possibly, lakes to a particular point in a water course (normally a lake or a river confluence).

Sub-unit [Operational definition. Not in the WFD]: Reporting unit. River basin districts larger than 50000 square kilometre should be divided into comparable sub-units with an area between 5000 and 50000 square kilometre. The sub-units should be created using river basins (if more than one river basin exists in the RBD), set of contiguous river basins, or sub-basins, for example. If the RBD area is less than 50000 square kilometre, the RBD itself should be used as a sub-unit.

Surface water body: Body of surface water means a discrete and significant element of surface water such as a lake, a reservoir, a stream, river or canal, part of a stream, river or canal, a transitional water or a stretch of coastal water.

Surface water: Inland waters, except groundwater; transitional waters and coastal waters, except in respect of chemical status for which it shall also include territorial waters.

Inland water: All standing or flowing water on the surface of the land, and all groundwater on the landward side of the baseline from which the breadth of territorial waters is measured.

River: Body of inland water flowing for the most part on the surface of the land but which may flow underground for part of its course.

Lake: Body of standing inland surface water.

Transitional waters: Bodies of surface water in the vicinity of river mouths which are partly saline in character as a result of their proximity to coastal waters but which are substantially influenced by freshwater flows.

Coastal water: Surface water on the landward side of a line, every point of which is at a distance of one nautical mile on the seaward side from the nearest point of the baseline from which the breadth of territorial waters is measured, extending where appropriate up to the outer limit of transitional waters.

Territorial sea: The territorial waters, or territorial sea as defined by the 1982 United Nations Convention on the Law of the Sea, extend up to a limit not exceeding 12 nautical miles (22.2 km), measured from the baseline. The normal baseline is the low-water line along the coast.

Territorial waters [Operational definition. Not in WFD.]: Reporting unit. The zone between the limit of the coastal water bodies and the limit of the territorial sea, geometrically subdivided in Thiessen polygons according to the adjacent coastal sub-unit (or using any alternative delineation provided by the national competent authorities), and assigned to an adjacent sub-unit for the purpose of reporting the chemical status of the territorial waters under the Water Framework Directive.

Groundwater body: 'Body of groundwater' means a distinct volume of groundwater within an aquifer or aquifers.

Groundwater: All water which is below the surface of the ground in the saturation zone and in direct contact with the ground or subsoil. Aquifer: Subsurface layer or layers of rock or other geological strata of sufficient porosity and permeability to allow either a significant flow of groundwater or the abstraction of significant quantities of groundwater.

Monitoring site: [Operational definition. Not in the WFD] Monitoring point included in a WFD surveillance, operational or investigative monitoring programme.

Water Quality Dataset

The basis of this dataset is taken from WaterBase water quality data shared on EAA. After most of the columns there were dropped, new data was created with the help of Worldbank, OSM, Foursquare, SEDAC. After removing the country and city information from the available location information, socioeconomic features of that country were added. However, the distance of certain road types close to those coordinates was also added with OSM. It is thought that such information plays an important role in the pollution of waters.

Features:

parameterWaterBodyCategory: Water body category code, as defined in the codelist. (Taken from EAA) observedPropertyDeterminandCode: Unique code of the determinand monitored, as defined in the codelist. (Taken from EAA) procedureAnalysedFraction: Specification of which fraction of the sample was analysed. (Taken from EAA) procedureAnalysedMedia: Type of media monitored. (Taken from EAA) resultUom: Unit of measure for the reported values. (Taken from EAA) phenomenonTimeReferenceYear: Year during which the data were sampled. (Taken from EAA) parameterSamplingPeriod: The period of the year during which the data used for the aggregation were sampled. (Taken from EAA) resultMeanValue: Mean value of the data used for aggregation. (Taken from EAA) waterBodyIdentifier: Unique international identifier of the water body in which the data were obtained. (Taken from EAA) Country: Country info generated by using coordinates. PopulationDensity: Population density of Country TerraMarineProtected_2016_2018: Mean of protected Terra Marine areas of Country Between 2016-2018 TouristMean_1990_2020: Mean of Tourist count of Country between 1990-2020 VenueCount: Venue count in near of given coordinates. netMigration_2011_2018: Mean of migration of given Country between 2011-2018 literacyRate_2010_2018: Literacy rate of Country between 2010-2018 combustibleRenewables_2009_2014: Compustible Renewable count in Country between 2009-2014 droughts_floods_temperature: gdp composition_food_organic_waste_percent composition_glass_percent composition_metal_percent composition_other_percent composition_paper_cardboard_percent composition_plastic_percent composition_rubber_leather_percent composition_wood_percent composition_yard_garden_green_waste_percent waste_treatment_recycling_percent

Sources: https://www.eea.europa.eu/data-and-maps/data/waterbase-water-quality-2 https://datacatalog.worldbank.org/dataset/what-waste-global-database

The AQUASTAT core database provides the platform for organizing and presenting over 180 variables and indicators on water resources and their use which include water withdrawal, wastewater, pressure on water resources, irrigation and drainage, and few components on environment and health. They can be searched and extracted, along with their metadata, for 200+ countries and for different regions over an extensive time period (from 1960 to 2017). The current database regroups data per 5-year period and shows for each variable the value for the most recent year during that period, if available. It can be queried in three languages (English, French and Spanish) on the following main categories: land use: total area, arable land and permanent crops population: total, urban and rural conventional water resources: surface water and groundwater non-conventional sources of water: wastewater, desalinated water and fossil water water withdrawal by sector: agricultural, domestic and industrial water withdrawal by source: surface water, groundwater and non-conventional water irrigation potential area under irrigation or agricultural water management irrigation techniques: surface, sprinkler and localized drained areas irrigated crops: area and yield The update frequency of the AQUASTAT core database varies by category and sub-category, as follows: Geography and population category: Every year (through FAOSTAT for land use and population and undernourishment, World Bank for GDP, UNDP for HDI and GII). Water resources category: These are long-term average annual values and therefore remain the same over the years. A comprehensive review had been undertaken in 2014. Water use category and irrigation and drainage development category: Depending on the country’s compilation of the AQUASTAT annual questionnaire. Updates of data for some specific sub-categories are being done in collaboration with others, as and when data become available, such as: Wastewater sub-category in collaboration with IWMI; access to improved drinking water source sub-category data are provided by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation. Some of the variables are updated during major review exercises.

Water is vital for life and local water pollution can damage the environment and affect human health. Governments and private institutions monitor and regulate water quality to protect the environment and populations. The consequences of pollution can reach far and wide, costing companies significant amounts in cleanup costs and loss of reputation. Most countries have official accredited laboratories and sampling teams that use varied technology, global expertise and local knowledge to provide water quality monitoring for different types of water and different and varied sampling locations. However, one of the main problems associated with monitoring and assessing water quality and meeting minimum standards of potability or usability is the analysis of samples based on local data. The problem lies in the fact that in many cases the data, due to the methodology or technique used or the expertise of the human resource that handles the samples, ends up configured in sets that have a large amount of missing information or data without information. This implies a problem depending on the analysis to be carried out. If you want to estimate a water quality index based on the samples, then you may have biased calculations due to the loss of information.

This dataset has been used for the generation of the manuscript: Efficient improvement for water quality analysis with large amount of missing data. D. Sierra-Porta,M. Tobón-Ospino. This manuscript is being submitted to Sustainable Production and Consumption (2022 Elsevier), Publication of the Institution of Chemical Engineers.

Beurteilung der Wasserqualität im eigenen Land. Themen: Selbsteinschätzung der Informiertheit über Gewässerprobleme; Einschätzung der Wasserqualität und der Wassermenge im Lande (Knappheit oder Überfluss); Veränderung der Wasserqualität in Flüssen, Seen und Küstengewässern in den letzten fünf Jahren; Einfluss auf die Wasserqualität durch: Wasserverbrauch und Abwasser im Haushalt, Benutzung sowie Verunreinigung von Wasser in der Landwirtschaft und der Industrie (durch Einsatz von Düngemitteln und Pestiziden), Energieerzeugung, Tourismus, Schifffahrt; wichtigste Bedrohungen für Gewässer; wichtigste Auswirkung des Klimawandels auf die Gewässer; eigener Beitrag zur Entschärfung von Wasserproblemen: Verringerung des Wasserverbrauchs, Verwendung umweltfreundlicher Chemikalien im Haushalt, Vermeidung von Pestiziden und Düngemitteln im Garten; Kenntnis der Anhörung zum Flussgebietsbewirtschaftungsplan. Demographie: Alter; Geschlecht; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Urbanisierungsgrad. Zusätzlich verkodet wurde: Befragten-ID; Interviewer-ID; Interviewsprache; Land; Länder mit Küsten vs. Länder ohne Küsten; Länder am Meer; Länder am Mittelmeer vs. Länder am Schwarzen Meer; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Anzahl der Kontaktversuche; Region; Gewichtungsfaktor. Attitudes towards water-related issues. Topics: self-rated knowledge about problems facing lakes, rivers, and coastal waters (only in member states with coasts) in the own country; assessment of each of the following issues as a serious problem in the own country: water quality, water quantity; assessment of the quality of lakes, rivers, and coastal waters (only in member states with coasts) in the own country over the last five years; impact of each of the following on the status of water in the own country: household water consumption and waste water, agricultural water use as well as the use of pesticides and fertilizers, industrial water use and pollution, energy production, tourism, shipping; main threats to water environment in the own country; most important impact of climate change on water in the own country; personal measures taken to reduce water problems; awareness of the ´River Basin Management Plans´; participation in consultations by national authorities on the ´River Basin Management Plans´. Demography: age; sex; age at end of education; occupation; professional position; type of community. Additionally coded was: respondent ID; interviewer ID; language of the interview; country; costal vs. landlocked countries; sea countries; Mediterranean vs. Black sea countries; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; call history; region; weighting factor.

The AQUASTAT core database provides the platform for organizing and presenting over 180 variables and indicators on water resources and their use which include water withdrawal, wastewater, pressure on water resources, irrigation and drainage, and few components on environment and health. They can be searched and extracted, along with their metadata, for 200+ countries and for different regions over an extensive time period (from 1960 to 2017). The current database regroups data per 5-year period and shows for each variable the value for the most recent year during that period, if available. It can be queried in three languages (English, French and Spanish) on the following main categories: land use: total area, arable land and permanent crops population: total, urban and rural conventional water resources: surface water and groundwater non-conventional sources of water: wastewater, desalinated water and fossil water water withdrawal by sector: agricultural, domestic and industrial water withdrawal by source: surface water, groundwater and non-conventional water irrigation potential area under irrigation or agricultural water management irrigation techniques: surface, sprinkler and localized drained areas irrigated crops: area and yield The update frequency of the AQUASTAT core database varies by category and sub-category, as follows: Geography and population category: Every year (through FAOSTAT for land use and population and undernourishment, World Bank for GDP, UNDP for HDI and GII). Water resources category: These are long-term average annual values and therefore remain the same over the years. A comprehensive review had been undertaken in 2014. Water use category and irrigation and drainage development category: Depending on the country’s compilation of the AQUASTAT annual questionnaire. Updates of data for some specific sub-categories are being done in collaboration with others, as and when data become available, such as: Wastewater sub-category in collaboration with IWMI; access to improved drinking water source sub-category data are provided by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation. Some of the variables are updated during major review exercises.

This dataset shows water bodies in Africa including lakes, reservoir, and lagoon. Data is curated from RCMRD Geoportal at http://geoportal.rcmrd.org/layers/servir%3Aafrica_water_bodies#license-m... The Regional Centre for Mapping of Resources for Development (RCMRD) was established in Nairobi – Kenya in 1975 under the auspices of the United Nations Economic Commission for Africa (UNECA) and the then Organization of African Unity (OAU), today African Union (AU). RCMRD is an inter-governmental organization and currently has 20 Contracting Member States in the Eastern and Southern Africa Regions; Botswana, Burundi, Comoros, Ethiopia, Kenya, Lesotho, Malawi, Mauritius, Namibia, Rwanda, Seychelles, Somali, South Africa, South Sudan, Sudan, Swaziland, Tanzania, Uganda, Zambia and Zimbabwe. To learn more about RCMRD, please visit http://www.rcmrd.org/

Time series data for the statistic Annual freshwater withdrawals, total (billion cubic meters) and country United States. Indicator Definition:Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.The indicator "Annual freshwater withdrawals, total (billion cubic meters)" stands at 444.29 as of 12/31/2022. Regarding the One-Year-Change of the series, the current value is equal to the value the year prior.The 1 year change in percent is 0.0.The 3 year change in percent is 0.0.The 5 year change in percent is 0.0.The 10 year change in percent is 3.57.The Serie's long term average value is 464.64. It's latest available value, on 12/31/2022, is 4.38 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2010, to it's latest available value, on 12/31/2022, is +6.09%.The Serie's change in percent from it's maximum value, on 12/31/1980, to it's latest available value, on 12/31/2022, is -14.16%.

Time series data for the statistic Annual freshwater withdrawals, total (billion cubic meters) and country Poland. Indicator Definition:Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.The indicator "Annual freshwater withdrawals, total (billion cubic meters)" stands at 9.38 as of 12/31/2022, the highest value since 12/31/2019. Regarding the One-Year-Change of the series, the current value constitutes an increase of 1.27 percent compared to the value the year prior.The 1 year change in percent is 1.27.The 3 year change in percent is 4.46.The 5 year change in percent is -6.89.The 10 year change in percent is -18.16.The Serie's long term average value is 12.64. It's latest available value, on 12/31/2022, is 25.75 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2020, to it's latest available value, on 12/31/2022, is +8.28%.The Serie's change in percent from it's maximum value, on 12/31/1985, to it's latest available value, on 12/31/2022, is -42.82%.

The dataset contains information on European groundwater bodies, monitoring sites, river basin districts, river basin districts sub-units and surface bodies reported to the European Environment Agency between 2001-11-29 and 2019-02-19.

The information was reported to the European Environment Agency under the State of Environment reporting obligations. For the EU28 countries and Norway, the EIONET spatial data was consolidated with the spatial data reported under the Water Framework Directive reporting obligations. For these countries, the reference spatial data set is the "WISE WFD Reference Spatial Datasets reported under Water Framework Directive".

Relevant concepts:

Groundwater body: 'Body of groundwater' means a distinct volume of groundwater within an aquifer or aquifers. Groundwater: All water which is below the surface of the ground in the saturation zone and in direct contact with the ground or subsoil. Aquifer: Subsurface layer or layers of rock or other geological strata of sufficient porosity and permeability to allow either a significant flow of groundwater or the abstraction of significant quantities of groundwater. Surface water body: Body of surface water means a discrete and significant element of surface water such as a lake, a reservoir, a stream, river or canal, part of a stream, river or canal, a transitional water or a stretch of coastal water. Surface water: Inland waters, except groundwater; transitional waters and coastal waters, except in respect of chemical status for which it shall also include territorial waters. Inland water: All standing or flowing water on the surface of the land, and all groundwater on the landward side of the baseline from which the breadth of territorial waters is measured. River: Body of inland water flowing for the most part on the surface of the land but which may flow underground for part of its course. Lake: Body of standing inland surface water. River basin district: The area of land and sea, made up of one or more neighbouring river basins together with their associated groundwaters and coastal waters, which is the main unit for management of river basins. River basin: The area of land from which all surface run-off flows through a sequence of streams, rivers and, possibly, lakes into the sea at a single river mouth, estuary or delta. Sub-basin: The area of land from which all surface run-off flows through a series of streams, rivers and, possibly, lakes to a particular point in a water course (normally a lake or a river confluence). Sub-unit [Operational definition. Not in the WFD]: Reporting unit. River basin districts larger than 50000 square kilometre should be divided into comparable sub-units with an area between 5000 and 50000 square kilometre. The sub-units should be created using river basins (if more than one river basin exists in the RBD), set of contiguous river basins, or sub-basins, for example. If the RBD area is less than 50000 square kilometre, the RBD itself should be used as a sub-unit.