315 datasets found

This publication reviews the current state-of-the-art of AI and Machine Learning (ML) applications within water management, introducing some of the main concepts and providing the reader with a general understanding of different technologies and concepts. Further, it features examples of the most influential applications of AI within water management and highlights the ethical challenges when streamlining AI for water resources management.

The FRIEND/Nile project, implemented in two phases (2001-2006 and 2007-2013), aimed to enhance water resources management in the Nile Basin through regional cooperation, capacity building, and applied hydrological research. Initiated under the UNESCO International Hydrological Programme (IHP) and funded by the Flemish Government of Belgium, the project engaged key institutions across five Nile Basin countries—Egypt, Sudan, Ethiopia, Kenya, and Tanzania. The project focused on improving understanding of the river's hydrological regime through collaborative research and data sharing.

Phase I (2001-2006) established technical and institutional cooperation, emphasizing four key research components: Rainfall-Runoff Modeling, Sediment Transport and Watershed Management, Flood Frequency Analysis, and Drought and Low Flow Analysis. Over 20 training workshops and technical meetings were conducted, enhancing the capacity of researchers and institutions within the region. The project facilitated data acquisition, model development, and technical publications, laying the foundation for improved transboundary water governance.

Phase II (2007-2013) expanded on these efforts by addressing new challenges such as eco-hydrology, stochastic modeling, and erosion and sediment transport. It introduced advanced hydrological models, improved performance monitoring, and evaluated climate change impacts on water availability in the Nile Basin. The project contributed to enhanced scientific cooperation, strengthened institutional frameworks, and provided policy-relevant insights to support sustainable water resource management.

Hydrodiplomacy, legal and institutional aspects of water resources governance: from the international to the domestic perspective: training manual

This layer shows NASA's Earth Observing-1 (EO-1) satellite images of Pakistan on August 11, 2010, after two weeks of flooding had devastated the country.By early August 2010, two weeks of devastating monsoon rains had transformed the landscape of Pakistan, pushing rivers over their banks, inundating villages, washing away bridges and roads, destroying crops, and killing livestock. By August 12, 2010, more than 1,600 people had perished, according to news reports, and the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) estimated that more than 14 million people had been affected in some way.For more information, visit NASA's Earth Observatory page: http://earthobservatory.nasa.gov/IOTD/view.php?id=45200

This layer shows NASA's Earth Observing-1 (EO-1) satellite images of Ayutthaya (Thailand) flood on October 23, 2011. Flooding forced the closure of manufacturing plants in Ayutthaya, according to news reports. The city is a UNESCO World Heritage site. On 12 October 2011, UNESCO Bangkok announced a planned assessment of flood damage to Ayutthaya, requested by the government of Thailand.For more information, visit NASA's Earth Observatory page: http://earthobservatory.nasa.gov/IOTD/view.php?id=76234

This 5 km resolution grid presents groundwater storage in Africa (in mm). This parameter was estimated by combining the saturated aquifer thickness and effective porosity of aquifers across Africa. For each aquifer flow/storage type an effective porosity range was assigned based on a series of studies across Africa and surrogates in other parts of the world. Groundwater storage is given in millimeters. Detailed description of the methodology, and a full list of data sources used to develop the layer can be found in the peer-reviewed paper available here: http://iopscience.iop.org/article/10.1088/1748-9326/7/2/024009/pdfThe raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/africanGroundwater/mapsDownload.html

This 1 km resolution grid shows the estimated mean annual groundwater storage change (in cm) across the aquifer based on annual groundwater-level change and specific yield. Methodology and a full list of data sources used can be found in the peer-reviewed paper: https://www.nature.com/articles/ngeo2791.epdf?author_access_token=_2Z_fJZxRkSVmgVJ7xHTVdRgN0jAjWel9jnR3ZoTv0O07GfIlzqIVm44UgFPb1r62_FUJLao4zkJSzYpv-4gIWJorRXEpgh4iarB8vlRNY_tGV_18CAf2j-_GnADYbdpThe raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/SEAsiaGroundwater/mapsDownload.html

Humedad relativa (%) en la región del Trifinio.Información extraida de la publicación: Catálogo de Objetos Geográficos, Proyecto Gobernanza de las aguas subterráneas en los acuíferos transfronterizos (GGRETA por sus siglas en ingles). UNESCO-PHI, UICN, Agencia Suiza para el Desarrollo y la Cooperación COSUDE. Publicación: Septiembre 2014Para más información visite el Geoportal del Plan Trifinio: http://www.geoportaltrifinio.net/

This 5 km resolution grid indicates what borehole yields (in l/s) can reasonably be expected in different hydrogeological units. The ranges indicate the approximate interquartile range of the yield of boreholes that have been sited and drilled using appropriate techniques. Groundwater productivity is given in liters per second.Detailed description of the methodology, and a full list of data sources used to develop the layer can be found in the peer-reviewed paper available here: http://iopscience.iop.org/article/10.1088/1748-9326/7/2/024009/pdf The raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/africanGroundwater/mapsDownload.html

These datasets and maps present the landslides observed and landslide susceptibility of the Chimanimani and Chipinge Districts of Zimbabwe. The maps provide a qualitative assessment of the likelihood of a landslide occurrence in an area depend on the terrain condition, and knowledge of prior landslides in the region. These maps have been prepared with the recording of 20 000 landslides, that have been identified in the region, particularly those as a result of the Cyclone Idai that occurred in 2019.

This 1 km resolution grid shows salinity measured as total dissolved solids (TDS, in mg/l) in the groundwater across the Indo-Gangetic basin. Methodology and a full list of data sources used can be found in the peer-reviewed paper: https://www.nature.com/articles/ngeo2791.epdf?author_access_token=_2Z_fJZxRkSVmgVJ7xHTVdRgN0jAjWel9jnR3ZoTv0O07GfIlzqIVm44UgFPb1r62_FUJLao4zkJSzYpv-4gIWJorRXEpgh4iarB8vlRNY_tGV_18CAf2j-_GnADYbdpThe raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/SEAsiaGroundwater/mapsDownload.html

Groundwater pollution risk is determined both by the intrinsic vulnerability of the aquifer and the existence of potentially polluting activities at the soil surface. This raster has a resolution of 15*15 km. It was generated by combining a groundwater vulnerability model (based on the DRASTIC method) with land use/land cover (from the GlobCoverdatat set) using an additive model. For more information, visit: http://www.sciencedirect.com/science/article/pii/S0048969715311189 test

This 1 km resolution grid shows mean annual change in water-table levels across the aquifer during the period 2000 to 2010 in meters per year. Methodology and a full list of data sources used can be found in the peer-reviewed paper: https://www.nature.com/articles/ngeo2791.epdf?author_access_token=_2Z_fJZxRkSVmgVJ7xHTVdRgN0jAjWel9jnR3ZoTv0O07GfIlzqIVm44UgFPb1r62_FUJLao4zkJSzYpv-4gIWJorRXEpgh4iarB8vlRNY_tGV_18CAf2j-_GnADYbdpThe raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/SEAsiaGroundwater/mapsDownload.html

This 1 km resolution grid shows the estimated mean annual groundwater abstraction in millimeters across the Indo-Gangetic basin based on data from 2010.Methodology and a full list of data sources used can be found in the peer-reviewed paper: https://www.nature.com/articles/ngeo2791.epdf?author_access_token=_2Z_fJZxRkSVmgVJ7xHTVdRgN0jAjWel9jnR3ZoTv0O07GfIlzqIVm44UgFPb1r62_FUJLao4zkJSzYpv-4gIWJorRXEpgh4iarB8vlRNY_tGV_18CAf2j-_GnADYbdpThe raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/SEAsiaGroundwater/mapsDownload.html

Elevación de la región del Trifinio.Información extraida de la publicación: Catálogo de Objetos Geográficos, Proyecto Gobernanza de las aguas subterráneas en los acuíferos transfronterizos (GGRETA por sus siglas en ingles). UNESCO-PHI, UICN, Agencia Suiza para el Desarrollo y la Cooperación COSUDE. Publicación: Septiembre 2014Para más información visite el Geoportal del Plan Trifinio: http://www.geoportaltrifinio.net/

This layer presents an estimation of the global risk induced by flood hazard. Unit is estimated risk index from 1 (low) to 5 (extreme). For more information, visit the Global Risk Data Platform: http://preview.grid.unep.ch/index.php?preview=data&events=floods&evcat=5&lang=eng

This layer presents an estimation of the annual economical exposition to tropical cyclone surges. (Don't forget to zoom on the coast!)Unit is expected average annual GDP (2010 as the year of reference) exposed in (US $, year 2000 equivalent).For more information, visit the Global Risk Data Platform: http://preview.grid.unep.ch/index.php?preview=data&events=surges&evcat=4&lang=eng

OpenLISEM is an open-source hydrological model suited for the simulation of floods, flash floods and erosion events. The following sections provide an overview of the results from the OpenLISEM model used in the exposure mapping A 30x30m flood map (maximum flood height) for the BuPuSa region was developed for several points on the intensity-frequency-duration curve. This curve represents the extreme value analysis (EVA) for the rainfall across the BuPuSa area. Based on 50 years of historic rainfall data from TAMSAT the EVA is developed for a 1000 year period. From this different rainfall intensities area taken which are referred to at the return period. The statistical possibility of a certain rainfall intensity to happen once in X many years. Flood maps were developed for the following return periods: 1/2, 1/10, 1/50, 1/100 and 1/1000. In addition to 5 different return periods, two different scenarios were modeled. A short high intensity rainfall event that typically causes flash floods, and a longer term lower intensity rainfall event that typically causes fluvial (river) floods. These events were represented by respectively a 6h rainfall event and a 14 day rainfall event. As a result 10 different flood maps were developed.

This layer presents an estimation of the annual physical exposition to drought based on Standardized Precipitation Index. Unit is expected average annual population (2010 as the year of reference) exposed (inhabitants). For more information, visit the Global Risk Data Platform: http://preview.grid.unep.ch/index.php?preview=data&events=droughts&evcat=4&lang=eng

This layer presents an estimation of the annual physical exposition to flood. Unit is expected average annual population (2007 as the year of reference) exposed (inhabitants).For more information, visit the Global Risk Data Platform: http://preview.grid.unep.ch/index.php?preview=data&events=floods&evcat=3&lang=eng