38 datasets found

Applications of AI for Water Management

Este trabajo se llevó a cabo en Majucla, colonia ubicada en el municipio de Cuscatancingo San Salvador, e involucra a los jóvenes del Comité Juvenil Expresión Hip Hop. El objeto del trabajo es presentar a Majucla, el barrio y sus calles, como cuna de saberes emergentes de las artes urbanas o cuna de actividades artísticas hip hop y lo que implica el concepto emergente frente al saber disciplinar y la epistemología. Por contraste con el saber académico es conveniente acuñar este concepto que alude a lo menor, lo excluido, lo subordinado, en analogía con la vida que pende de un hilo en los sectores deprimidos. Saberes emergentes es llegar a ser mientras las actividades de los jóvenes se dirigen a crear e intentar comercializar sus obras. Pese a las dificultades encontradas, principalmente por la violencia imperante y las barreras de acceso a la educación, los jóvenes siguen empeñados en crear arte y fortalecer el colectivo. Aprenden en la universidad de la calle aquellos saberes que les permitan identificarse como diferentes y resistir en las condiciones en que les tocó vivir.

This study (https://doi.org/10.1007/s12517-017-3298-0) assesses the impacts of untreated wastewater discharge from Sulaimani City, Iraq, into the Tanjero River and proposes a framework for wastewater treatment planning. Nine sewer outlets representing residential, commercial, industrial, tourism, and hospital effluents were sampled over a year, and physicochemical analyses revealed elevated levels of turbidity, total dissolved solids, hardness, nitrates, and heavy metals—particularly in industrial zones. Questionnaire surveys conducted in 31 surrounding villages indicated significant health burdens, including chronic diseases, diarrhea, typhoid, skin disorders, and cancer, alongside impacts on livestock, fisheries, and agricultural productivity. Rice cultivation has nearly disappeared, and vegetable farming has declined due to water contamination. The findings highlight severe environmental and public health risks from current practices, where raw wastewater is still used for irrigation and animal watering. To mitigate these impacts, the study recommends constructing two wastewater treatment plants with stormwater retention structures, enforcing pretreatment of industrial effluents, and introducing appropriate on-site sanitation for unconnected households. Adoption of these measures would safeguard water resources, improve public health, and enable the safe reuse of treated wastewater for agriculture and industry.

This dataset represents the digitized version of the Geological Map of Somalia (scale 1:1,500,000), compiled between 1987 and 1991 and printed in 1994. The map was edited and coordinated by E. Abbate, M. Sagri, and F.P. Sassi, with contributions from the Faculty of Geology, Somali National University (Mogadishu) and the Universities of Florence and Padua, Italy, along with several Somali and international collaborators. The map provides a comprehensive overview of Somalia’s geological formations, stratigraphy, and structural features, covering the Gulf of Aden margin, central basins, and the Indian Ocean coastal belt. Lithological units range from Precambrian crystalline complexes to recent Quaternary deposits, with detailed symbology distinguishing volcanic, sedimentary, and metamorphic sequences. The original map also incorporates tectonic structures, fault systems, and stratigraphic cross-sections that are not included in the SHP file, but the original map is provided georeferenced in EPSG:32638 - WGS 84 / UTM zone 38N.

The digitization process involved georeferencing, vectorization, and attribute assignment of geological units and structures to enable spatial analysis within modern GIS environments. This dataset supports research and decision-making in natural resource management, groundwater assessment, mineral exploration, land-use planning, and academic studies. During the digitization process, the original projection of the map was not specified, requiring approximate control points for georeferencing. As a result, minor distortions may remain, and the spatial alignment is not perfectly accurate.

This map illustrates the satellite-detected water extent in Sindh, Balochistan, and Punjab Provinces, Pakistan, as observed from Sentinel-2 satellite images acquired on 31 July 2025 at 13:02 local time (08:02 UTC). Within the analyzed area of approximately 83,000 km², about 6,300 km² of land appears to be affected by floodwaters. The floodwater extent appears to have increased by approximately 1,300 km² since 11 July 2025. Based on WorldPop population data and the flood extent, approximately 2.3 million people are potentially exposed or living close to the flooded areas.

The Reference Observatory of Basins for INternational hydrological climate change detection (ROBIN) project established a new long-term collaboration of international experts to establish and sustain a global reference hydrological network (RHN), through common standards, protocols, indicators, and data infrastructure. ‘Reference Hydrometric Networks’ (RHNs), consist of gauging stations whose catchments are relatively undisturbed and record high quality data and little missing data. The concept of RHNs, their history and evolution are described in (Whitfield et al., 2012) previously and many countries have already established RHNs, however this is the first initiative to bring them together at a global level. The ROBIN Full Dataset consists of 3,060 stations in 30 countries, however the dataset described here is the ROBIN Public Dataset which contains metadata records for all 3,060 stations and daily streamflow data for a total of 2,386 stations. This tiered approached was due to data sharing restrictions in some countries. More information about the ROBIN Network and dataset can be found on the project website: https://www.ceh.ac.uk/our-science/projects/robin

These maps, developed by Deltares, creat the flood impact of flood hazards expected in the Chimanimani and Chipinge Districts, Zimbabwe and are evaluated at 30m resolution.

Natural disasters frequently damage or destroy school infrastructure, jeopardizing educational opportunities and putting school children's lives in danger. This was experienced by children and staff members in Zimbabwe, Chimanimani and Chipinge districts in particular during cyclone Idai which hit eastern Zimbabwe in 2019 and the cyclones that followed. More than 140 schools were affected by the floods and the land slides. The situation at St. Charles Lwanga High School, where 200 children, teachers and support staff were stranded for two days and had to face the cyclone, shows the importance of safe school infrastructure. To better prepare for such eventualities, UNESCO through the Zimbabwe Idai Recovery Project funded by World Bank and managed by UNOPS collaborated with the University of Udine and the University of Zimbabwe to implement the VISUS (Visual Inspection for Defining the Safety Upgrading Strategies), a multi-hazard school safety assessment methodology that help policymakers decide where to focus risk reduction efforts based on available resources and scientific evidence. The VISUS methodology helps assess schools using a holistic, multi-hazard approach that considers five aspects: site conditions, structural performance, local structural criticalities, non-structural components, and functional aspects. The methodology has also been improved to consider outbreak of disease such as COVID-19. The VISUS methodology was conceived as an effective decision making tool for planning risk mitigation actions. The project helped mainstream school safety components into the UNOPS’ School Rehabilitation Program and could contribute to the Civil Protection Unit’s School Disaster Education Programme. The team’s efforts also assisted in making investments decisions to strengthen the safety of schools efficiently and economically.

Reports and datasets generated as part of the Climate Risk Informed Decision Analysis (CRIDA) implemented in the Chimanimani Districts, in response to Cyclone Idai and to build resilience of local communities to climate change impacts.

Zimbabwe is exposed to multiple weather-related hazards, suffering from frequent periodic cyclones, droughts, floods, and related epidemics and landslides. On 15 March 2019, tropical Cyclone Idai hit eastern Zimbabwe, and at least 172 deaths were reported, more than 186 people were injured and 327 were missing, while over 270,000 people were affected across nine districts, particularly in Chimanimani and Chipinge. Of those affected, 20,002 households (61.5%) or 100,106 people (74.2% of the 2012 population) were in Chimanimani. Meanwhile, ecosystem damage also occurred where boulders and mud were dumped downhill, affecting wildlife habitats, water quality, tourism activities and usability of land resources. The cyclone’s aftermath has therefore increased environmental risks, which will in turn affect local adaptation. Loss of vegetation cover means the natural defense against future flood waters and landslides is no longer available. Similar events in future are therefore likely to cause even more destruction. The overall objective of the initiative is therefore to reduce the vulnerability of communities in the Chimanimani and Chipinge Districts to natural disasters, such as floods, droughts and landslides; and to enhance water resource management as well as ecosystem services in response to the uncertainty of future climate change. The project is designed to approach the water-related risk and vulnerability through an integrated strategy that targets several aspects of disaster risk reduction, and provides scalable implementation of the project through a modular pathway and the development of case studies in target flood and landslide prone areas.

This dataset contains the official materials from the launch event of the IHP-WINS (International Hydrological Programme – Water Information Network System) platform, held on 28 April 2023. It includes the launch brochure, the presentation delivered during the event, and the full recording of the webinar. These resources provide an overview of the platform’s objectives, functionalities, and relevance in supporting data sharing, open science, and collaborative water resources management. The dataset serves as a reference for stakeholders, partners, and contributors interested in learning about the vision and practical applications of IHP-WINS.

The global crises of biodiversity and cultural diversity are interdependent, especially so in rivers. While we know that 84% of the freshwater fauna has disappeared between 1970 and 2014, the loss in cultural diversity connected to the river and its floodplain (e.g., spiritual linkages, traditional use forms, adapted architecture, etc.) is as yet un-known. This book makes a first attempt to deal with biological and cultural diversities altogether, depicting the bio-cul-tural diversities, historical human-river relation-ships, threats, and practical examples of how to mitigate the crisis in riverscapes. More than 120 authors present interdisciplinary studies from river systems all over the world, and explore overarching issues on river ma-nagement in the Anthropocene.

Overview of the IHP Phase VIII Achievements

National Report - IHP-ROK activities undertaken in the period April 2022 - February 2024

The CRIDA approach provides a crucial framework to enable water managers and policy makers to assess the impact of climate uncertainty and change on their water resources and work towards effective adaptation strategies. This multi-step process embraces a participatory, bottom-up approach to identify water security hazards, and is sensitive to indigenous and gender-related water vulnerabilities. By engaging local communities in the design of the analysis, the information provided by scientific modeling and climate analysis can be tailored and thus provide more useful answers to the challenges they are facing. They are also providing a more informed starting point to assess the different options for adaptation, and design robust adaptation pathways, in line with the local needs.

This publication aims to bridge the gap between climate and disasters, in the face of the uncertainties that climate change poses to water managers and policymakers. Composed of a compilation of worldwide case studies, it provides examples of innovative water management and climate risk assessment approaches. The publication also highlights the National Determined Contributions (NDCs) and National Adaptation Plans (NAPs) with the aim of identifying links between these high-level frameworks, DRR and water issues, and describing how the policy-practice linkages can be turned into action.

This publication has laid out a strategic framework to integrate Open Science into hydrology, illustrating its true potential to enhance research transparency, collaboration, and accessibility within water management practices. The six pillars — open data, open source, open publishing, open infrastructure, open education, and open participation — constitute the structure of the Open Hydrology framework designed to promote transparency and reproducibility.

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 dataset covers the Counties of Turkana and Marsabit in northern Kenya. It includes borehole records with some geological and water quality measurements. It is part of the project "HYDROGEOLOGICAL MAPPING OF TURKANA and MARSABIT AQUIFERS" that was carried out by Rural Focus and SWAS WATER SURVEYS. A significant portion of the data that was required for these datasets was collected from various organizations including Oxfam, the Catholic Diocese of Lodwar, JICA, and the WRA of Kenya. The dataset has undergone improvements in accuracy and consistency while being normalized to align with UNESCO's groundwater data collection template.

The SWOT Level 2 River Single-Pass Vector Node Data Product from the Surface Water Ocean Topography (SWOT) mission provides water surface elevation, slope, width, and discharge derived from the high rate (HR) data stream from the Ka-band Radar Interferometer (KaRIn). SWOT launched on December 16, 2022 from Vandenberg Air Force Base in California into a 1-day repeat orbit for the "calibration" or "fast-sampling" phase of the mission, which completed in early July 2023. After the calibration phase, SWOT entered a 21-day repeat orbit in August 2023 to start the "science" phase of the mission, which is expected to continue through 2025.

Water surface elevation, slope, width, and discharge are provided for river reaches (approximately 10 km long) and nodes (approximately 200 m spacing) identified in the prior river database, and distributed as feature datasets covering the full swath for each continent-pass. These data are generally produced for inland and coastal hydrology surfaces, as controlled by the reloadable KaRIn HR mask. The dataset is distributed in ESRI Shapefile format. Please note that this collection contains SWOT Version C science data products.

This collection is a sub-collection of its parent: https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_RiverSP_2.0 It contains only river nodes.