310 conjuntos de datos encontrados

This dataset contains citizen science water quality measurements collected under the Be-Resilient initiative of the UNESCO Intergovernmental Hydrological Programme (IHP). Data were gathered across multiple Biosphere Reserves in South Africa as part of ongoing efforts to enhance community-based monitoring and local resilience to hydroclimatic risks.

The dataset includes in-situ observations of key water quality parameters, such as pH, electrical conductivity, turbidity, dissolved oxygen, and temperature, each accompanied by localized timestamps and contextual metadata. Measurements were obtained by trained citizen scientists and local volunteers, following standardized protocols designed to ensure comparability across sites and over time.

Individual identifiers have been removed to protect the privacy of participants. The dataset serves as an open, quality-controlled source for hydrological and environmental analyses, education, and early-warning applications. It contributes to the broader Be-Resilient programme objective of promoting citizen and open science approaches for climate adaptation, data democratization, and the co-production of water knowledge in vulnerable and data-scarce regions.

El Conjunto de Datos Global de Sandwatch consolida observaciones participativas recopiladas a través del Programa Sandwatch de la UNESCO, una iniciativa mundial de ciencia ciudadana y educación que promueve la adaptación al cambio climático y la gestión sostenible de las zonas costeras. El conjunto incluye datos estandarizados de monitoreo de 145 playas en más de 50 países, recopilados por más de 300 observadores comunitarios, escuelas y grupos ambientales.

Abarcando más de una década de observaciones, el conjunto documenta la morfología de las playas, la erosión y acreción, la composición, los desechos, las actividades humanas, la calidad del agua, las olas y corrientes, la vegetación y la fauna. Cada registro refleja la participación activa de las comunidades locales en la recopilación de datos y el cuidado ambiental, fortaleciendo la conciencia y la resiliencia de los ecosistemas costeros, especialmente en los Pequeños Estados Insulares en Desarrollo (PEID) y regiones costeras bajas.

La estructura de los datos sigue la metodología de Sandwatch (Monitorear, Analizar, Compartir y Actuar – MAST) y está alineada con los marcos de la UNESCO sobre Educación para el Desarrollo Sostenible (EDS) y adaptación al cambio climático. Este recurso interdisciplinario integra dimensiones ambientales, sociales y educativas del cambio costero, siendo de gran valor para la investigación, la educación y la formulación de políticas sobre resiliencia costera y monitoreo participativo.

This dataset contains a collection of presentations delivered by UNESCO’s Intergovernmental Hydrological Programme (IHP) to a variety of audiences—including IHP National Committees, project teams, Member States, and regional stakeholders—on the IHP-WINS (Water Information Network System) platform. The presentations aim to raise awareness of IHP-WINS as a central hub for hydrological, climatic, and contextual data, supporting evidence-based decision-making, digital transformation, and open science. Each presentation is tailored to the specific audience, highlighting relevant use cases, data management workflows, visualization tools, governance structures, and opportunities for collaboration. The dataset provides an overview of how IHP-WINS is positioned within UNESCO’s water programmes to enhance interoperability, promote data sharing, and support the implementation of IHP-IX priorities at national, regional, and project levels.

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.

The Randolph Glacier Inventory (RGI) is a global set of glacier outlines intended as a snapshot of the world’s glaciers outside of ice sheets. It provides a single outline for each glacier from approximately the year 2000, as well as a set of attributes and other relevant auxiliary information. Glacier outlines are distributed as Shapefiles. Hypsometric data and attributes (CSV files) and metadata (json) are also available. All RGI data are packaged both globally and by region (as defined by the Global Terrestrial Network for Glaciers (GTN-G) Glacier Regions). The RGI is not suitable for measuring glacier-by-glacier rates of area change. However, it can be used to estimate glacier volumes; rates of elevation change at regional and global scales; and glacier responses to climatic forcing. RGI version 7.0 was developed by the “Working Group on the Randolph Glacier Inventory (RGI) and its role in future glacier monitoring” of the International Association of Cryospheric Sciences (IACS). The glaciological community contributes glacier mapping data to the Global Land Ice Measurements from Space (GLIMS) database. A subset of the glacier outlines in GLIMS are then extracted and reprocessed to produce the RGI. See the RGI documentation under "User Guide" (below) for more information.

El visor de SIDS proporciona información relacionada con las aguas subterráneas en los Pequeños Estados Insulares en Desarrollo. En la actualidad, el sistema contiene principalmente información derivada del Programa de Evaluación de Aguas Transfronterizas (TWAP) sobre 43 SIDS. Los datos incluyen indicadores que describen las dimensiones hidrogeológicas, ambientales, socioeconómicas y de gobernanza de los sistemas de aguas subterráneas de los SIDS.

Los datos han sido obtenidos a partir de encuestas por cuestionario y un exhaustivo estudio documental realizado por la Universidad Simon Fraser (Canadá) y coordinado por UNESCO-IHP. La información en el sistema puede ser explorada y analizada mediante un visor basado en mapas, lo que resulta particularmente útil para realizar análisis comparativos entre múltiples SIDS. Además, también están disponibles fichas informativas de los SIDS que proporcionan resúmenes claros por cada SIDS. Se recopilarán y cargarán más datos sobre los SIDS en el visor a medida que estén disponibles.

Para cualquier consulta o comentario sobre los datos e información de los SIDS, por favor visite nuestra página del Área Focal de SIDS. (https://www.un-igrac.org/areas-expertise/small-island-developing-states-sids)

Composed of 669 biosphere reserves in 120 countries, including 16 transboundary sites, the World Network of Biosphere Reserves (WNBR) of the UNESCO Man And Biosphere (MAB) Programme consists of a dynamic and interactive network of sites of excellence. It works to foster the harmonious integration of people and nature for sustainable development through participatory dialogue, knowledge sharing, poverty reduction, human well-being improvements, respect for cultural values and by improving society’s ability to cope with climate change.For more information, visit: http://www.unesco.org/new/en/natural-sciences/environment/ecological-sciences/man-and-biosphere-programme/

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

Estos mapas, desarrollados por Deltares, representan el impacto de los peligros de inundación previstos en los distritos de Chimanimani y Chipinge, en Zimbabue, y han sido evaluados con una resolución de 30 metros.

Outcome of the 'Visual Inspection for Defining the Safety Upgrading Strategies’ (VISUS) approach to assess the school safety in the Chimanimani District after the Cyclone Idai. A VISUS survey across 15 schools in the Chimanimani district was conducted to gauge rehabilitation needs and identify key areas to build resilience.

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.

Este conjunto de datos contiene los materiales oficiales del evento de lanzamiento de la plataforma IHP-WINS (Sistema de Información sobre el Agua del Programa Hidrológico Internacional), celebrado el 28 de abril de 2023. Incluye el folleto de lanzamiento, la presentación utilizada durante el evento y la grabación completa del seminario web. Estos recursos ofrecen una visión general de los objetivos, funcionalidades y relevancia de la plataforma en el apoyo al intercambio de datos, la ciencia abierta y la gestión colaborativa de los recursos hídricos. El conjunto de datos sirve como referencia para partes interesadas, socios y colaboradores que deseen conocer la visión y las aplicaciones prácticas de IHP-WINS.

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 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.

El proyecto FRIEND/Nile, implementado en dos fases (2001-2006 y 2007-2013), tuvo como objetivo mejorar la gestión de los recursos hídricos en la cuenca del Nilo a través de la cooperación regional, el desarrollo de capacidades y la investigación hidrológica aplicada. Iniciado bajo el Programa Hidrológico Internacional (PHI) de la UNESCO y financiado por el Gobierno de Flandes en Bélgica, el proyecto involucró a instituciones clave de cinco países de la cuenca del Nilo: Egipto, Sudán, Etiopía, Kenia y Tanzania. El proyecto se centró en mejorar la comprensión del régimen hidrológico del río mediante la cooperación en la investigación y el intercambio de datos.

La Fase I (2001-2006) estableció la cooperación técnica e institucional, enfatizando cuatro componentes de investigación clave: modelado lluvia-escorrentía, transporte de sedimentos y gestión de cuencas, análisis de frecuencia de inundaciones y análisis de sequías y caudales bajos. Se llevaron a cabo más de 20 talleres de capacitación y reuniones técnicas, mejorando la capacidad de los investigadores y las instituciones de la región. El proyecto facilitó la adquisición de datos, el desarrollo de modelos y la publicación de documentos técnicos, sentando las bases para una mejor gobernanza del agua transfronteriza.

La Fase II (2007-2013) amplió estos esfuerzos abordando nuevos desafíos como la ecohidrología, el modelado estocástico y la erosión y transporte de sedimentos. Se introdujeron modelos hidrológicos avanzados, se mejoró el monitoreo del rendimiento y se evaluaron los impactos del cambio climático en la disponibilidad de agua en la cuenca del Nilo. El proyecto contribuyó a una mayor cooperación científica, fortaleció los marcos institucionales y proporcionó información relevante para la formulación de políticas de gestión sostenible del agua.

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