6 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 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.

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.