Dam

"Any artificial barrier which impounds or diverts water. The dam is generally hydrologically significant if it is: 1. 25 feet or more in height from the natural bed of the stream and has a storage of at least 15 acre-feet. 2. Or has an impounding capacity of 50 acre-feet or more and is at least six feet above the natural bed of the stream." (National Oceanic and Atmospheric Administration, 2019)

Sources

National Oceanic and Atmospheric Administration (NOAA). Glossary of Hyfrologic Terms. Accessed February 28, 2019. Available at: https://www.nws.noaa.gov/om/hod/SHManual/SHMan014_glossary.htm 

Related Content

Article

Climate change, dam collapses and water-borne disease: devastation in Libya caused by Storm Daniel

On September 10th of 2023, Storm Daniel made landfall in northeastern Libya, bringing torrential levels of rain and strong winds (Figure 1). This onslaught of rain caused two big dams in the region to break – the Abu Mansour dam and the Derna dam, 75 metres and 45 metres tall respectively. It is believed that the Abu Mansour dam broke first, after its reservoir was filled beyond capacity. The dam collapsed and sent a rush of water towards the Derna dam further downstream (Figure 2).

Capacity Building and Training Material

Mekong dam monitor tutorial and FAQ

This walkthrough shows users how to use the Mekong Dam Monitor to track how dams currently impact various parts of the Mekong mainstream and its tributaries. It includes step-by-step instructions on how to track river levels, interpret the Natural Flow Model from Eyes on Earth and how it compares against gauge data from the Mekong River Commission, use the virtual gauges to explore water level and flow changes at individual sites, and more. This walkthrough also answers frequently asked questions about how to find information inside the Mekong Dam Monitor.

Event

Local Perspectives Case Studies

Software/Tool/(Web-)App

ISME-HYDRO

ISME-HYDRO is a platform that helps monitor water resources of dams, thus enabling water resources managers to better execute their duties. It employs linked data infrastructure integrating in-situ measurements, satellite data, GIS data, domain knowledge, deep learning, and provides capabilities of forecasting of water volumes, of alerting for hazardous situations, of interaction with the data through four kinds of search and GIS interactivity. The platform is easily extendable and customizable.