The rivers of Africa dataset is derived from the World Wildlife Fund's (WWF) HydroSHEDS drainage direction layer and a stream network layer. The source of the drainage direction layer was the 15-second Digital Elevation Model (DEM) from NASA's Shuttle Radar Topographic Mission (SRTM). The raster stream network was determined by using the HydroSHEDS flow accumulation grid, with a threshold of about 1000 km² upstream area.

The stream network dataset consists of the following information: the origin node of each arc in the network (FROM_NODE), the destination of each arc in the network (TO_NODE), the Strahler stream order of each arc in the network (STRAHLER), numerical code and name of the major basin that the arc falls within (MAJ_BAS and MAJ_NAME); - area of the major basin in square km that the arc falls within (MAJ_AREA); - numerical code and name of the sub-basin that the arc falls within (SUB_BAS and SUB_NAME); - area of the sub-basin in square km that the arc falls within (SUB_AREA); - numerical code of the sub-basin towards which the sub-basin flows that the arc falls within (TO_SUBBAS) (the codes -888 and -999 have been assigned respectively to internal sub-basins and to sub-basins draining into the sea). The attributes table now includes a field named "Regime" with tentative classification of perennial ("P") and intermittent ("I") streams.

Supplemental Information:

This dataset is developed as part of a GIS-based information system on water resources for the African continent. It has been published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations.

Contact points:

Data lineage:

The linework of the map was obtained by converting the stream network to a feature dataset with the Hydrology toolset in ESRI ArcGIS.The Flow Direction and Stream Order grids were derived from hydrologically corrected elevation data with a resolution of 15 arc-seconds.The elevation dataset was part of a mapping product, HydroSHEDS, developed by the Conservation Science Program of World Wildlife Fund.Original input data had been obtained during NASA's Shuttle Radar Topography Mission (SRTM).

Online resources:

Hydrological basins in Africa

HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) provides hydrographic information in a consistent and comprehensive format for regional and global-scale applications. HydroSHEDS offers a suite of geo-referenced data sets (vector and raster), including stream networks, watershed boundaries, drainage directions, and ancillary data layers such as flow accumulations, distances, and river topology information. HydroSHEDS is derived from elevation data of the Shuttle Radar Topography Mission (SRTM) at 3 arc-second resolution. Available HydroSHEDS resolutions range from 3 arc-second (approx. 90 meters at the equator) to 5 minute (approx. 10 km at the equator) with seamless near-global extent.

Citation:Title: HydroSHEDS (BAS) - Africa drainage basins (watershed boundaries) at 30s resolutionCredits: World Wildlife Fund (WWF)Publication Date: 2006Publisher: U.S. Geological SurveyOnline Linkages: http://hydrosheds.cr.usgs.govhttp://www.worldwildlife.org/hydroshedsOther Citation Info: Please cite HydroSHEDS as: Lehner, B., Verdin, K., Jarvis, A. (2006): HydroSHEDS Technical Documentation. World Wildlife Fund US, Washington, DC. Available at http://hydrosheds.cr.usgs.gov.

This layer package was loaded using Data Basin.Click here to go to the detail page for this layer package in Data Basin, where you can find out more information, such as full metadata, or use it to create a live web map.

This spatial rivers dataset is part of the South African Inventory of Inland Aquatic Ecosystems (SAIIAE) which was released with the National Biodiversity Assessment (NBA) 2018. In the NBA 2018 the National Freshwater Ecosystem Priority Area (NFEPA) rivers GIS layer was used to represent the diversity of rivers nationally. It used the 1:500 000 river network coverage available from the Department of Water and Sanitation (DWS) and can be downloaded from the following website: http://www.dwaf.gov.za/iwqs/gis_data/river/rivs500k.aspx. This GIS layer summarizes the river ecosystem types, river condition, Ecosystem Threat Status (ETS) and Ecosystem Protection Level (EPL) as well as the free-flowing (62 identified by the NFEPA project) and flagship river information.

Geo-referenced point database on dams in Africa.

Supplemental Information:

This dataset is described extensively on the website https://www.fao.org/aquastat/en/databases/dams. On this website, the dataset is also published in Excel to facilitate the publication of information on dams without geographical co-ordinates. It is accompanied by an explanatory document that provides specific information about the references used, and brief notes on the more complicated dams. The shapefile consists of the following information: a) GIS generated codes (FID); b) coordinates in decimal degrees (DDLONG, DDLAT); c) 'coordinates' broken down into eight codes (LATDIR with an N or an S for North or South, LATDEG, LATMIN and LATSEC for degrees, minutes and seconds latitude and LONGDIR with an W or E for West or East and LONGDEG, LONGMIN and LONGSEC for degrees minutes and seconds longitude); d) items described in details on the website, such as river basin and administrative unit; e) completion date; f) height; g)surface area; h) main purpose.

This dataset served also as a basis for the Global reservoirs and dams (GRanD) database, which resulted in the article: Lehner, B., Reidy Liermann, C., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J., Rödel, R., Sindorf, N., Wisser, D. 2011. High resolution mapping of the world’s reservoirs and dams for sustainable river flow management. Published in the Journal Frontiers in Ecology and the Environment.

For a wider distribution and to support other projects at FAO this map is also distributed in a DVD as part of a publication entitled: Jenness, J., Dooley, J., Aguilar-Manjarrez, J., Riva, C. African Water Resource Database. GIS-based tools for inland aquatic resource management. 2. Technical manual and workbook. CIFA Technical Paper. No. 33, Part 2. Rome, FAO. 2007. 308 p.

Contact points:

Metadata contact: AQUASTAT FAO-UN Land and Water Division

Online resources:

Download - Database of dams in Africa (Excel file)

Geo-referenced dam databases on AQUASTAT website

The data set contains grain size distributions, organic matter (OM) content and trace metal distribution (including Fe, Zn, Cu, Cr and Pb) of 37 shallow cores of sediments sampled from dams across the Limpopo River Basin. The dams include: Gaborone, Lotsane and Shashe dams in Botswana; Houtrivier, Nwanedi and Mutshedzi dams in South Africa; Ripple Creek and Zhovhe dams in Zimbabwe; and Massingir Dam in Mozambique. Data from two cores sampled from an oxbow lake in Mozambique are also included. The cores were collected with a gravity corer using PVC pipes of 5 cm diameter by a team from Botswana International University of Science and Technology (BIUST) led by Dr. Franchi between July 2018 and April 2021.

This dataset contains the digitized treatments in Plazi based on the original journal article Crouch, Neil R., Smith, Gideon F. (2023): Cotyledon mckayi (Crassulaceae subfam. Kalanchooideae), a new cremnophytic species from the central Tugela River Basin of KwaZulu-Natal, South Africa. Phytotaxa 632 (2): 184-192, DOI: 10.11646/phytotaxa.632.2.8, URL: https://phytotaxa.mapress.com/pt/article/download/phytotaxa.632.2.8/51402

The 2018 South African Inventory of Inland Aquatic Ecosystems (SAIIAE) geodatabase is a collection of data layers pertaining to ecosystem types and pressures for both rivers and inland wetlands. These data layers were developed and used for the 2018 National Biodiversity Assessment (NBA 2018).

The South African National Diatom Collection (SANDC) contains many thousands of records pertaining to the distribution and abundance of the diatom species of southern Africa. These records carry intrinsic value as they describe the occurrence and distribution of endemic southern African species as well as proving valuable for the hind-casting of water quality in rivers and streams around South Africa.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South River. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In South River, the median household income for the households where the householder is White increased by $10,776(12.79%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $84,221 in 2011 and $94,997 in 2021.
• Black or African American: In South River, the median household income for Black or African American households was $153,452 in 2011(2022 inflation-adjusted dollars). However there is no reported data for 2021, indicating a lack of information for this specific year.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/south-river-nj-median-household-income-by-race-trends.jpeg" alt="South River, NJ median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in South River.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-inflation-adjusted dollars.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for South River median household income by race. You can refer the same here

new detailed series of surveys of the freshwater macro-invertebrate fauna of selected rivers within the Kruger National Park is planned. We aim to compare results from these new surveys (species richness and distribution) with historical records, and look at what external factors are impacting the populations in sections of rivers where there is a notable reduction in diversity and water quality.