4 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.

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

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.