Glaciares de Chile
- Glaciares del Volcán Melimoyu
- Glaciares del Nevado de Queulat
- Glaciares del Volcán Mentolat
- Glaciares del Volcán Cay
- Glaciares del Volcán Macá
- Glaciares del Volcán Hudson
- Glaciar Erasmo
- Glaciar San Rafael
- Glaciar San Quintín
- Campo de Hielo Norte
- Glaciar Nef
- Glaciar Colonia
- Lago Cachet II
- Glaciar Steffen
- Glaciares del Monte San Lorenzo
- Glaciar Jorge Montt
- Glaciar Lucía
- Glaciar Los Moscos
- Glaciar Bernardo
- Glaciar O’Higgins
- Glaciar Chico
- Campo de Hielo Sur
- Campo de Hielo Sur
- Glaciar Témpanos
- Glaciar Pío XI
- Glaciar Viedma
- Glaciar Perito Moreno
- Glaciar Dickson
- Glaciar Olvidado
- Glaciar Grey
- Glaciar Amalia
- Glaciar Pingo
- Glaciar Tyndall
- Glaciar Balmaceda
- Isla Desolación
- Glaciares de la Isla Santa Inés
- Seno Gabriel
- Glaciar Schiaparelli
- Glaciar Marinelli
- Fiordo Parry
- Cordillera Darwin
- Glaciar Garibaldi
- Glaciar Roncagli
- Glaciares Isla Hoste
Antártica
Development of an early warning system to reduce the impact of floods related to glacial lake outburst floods (SAGAZ)
Rada, C., A. Rivera & S. Alfaro (2024): International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives), XLVIII-2/W6-2024, 45–50.
Abstract.
The retreat of glaciers has led to increasing in natural hazards due, for example, by emptying of lakes dammed by unconsolidated glacial deposits (moraines) or ice, which are susceptible to catastrophic erosion, generating rapid floods, phenomena known as “Glacial Lake Outburst Floods” (GLOFs). Current systems that warn of the occurrence of a GLOF are activated when the emptying begins, which leaves little time to act, so they should be considered early alarm systems. The challenge is to predict the onset of the flood allowing the generation of an early warning system. To address this problem, SAGAZ ultimately aims to develop a system capable of identifying periods of increased GLOF risk using a predictive model fed by weather forecasts and monitoring station data. This system identifies a period of higher risk, which allows informing authorities several days in advance. This paper presents the results of the first phase of SAGAZ implementation, which aimed to (1) develop and validate a prototype monitoring station and deploy a network of stations on glacial lakes across southern Patagonia, (2) collect the necessary data for the development, training and validation of predictive models and (3) begin the implementation and testing of the predictive model. As a result, a network of 10 monitoring stations was installed in the Aysén and Magallanes regions of Chile and 1 in the Province of Santa Cruz in Argentina, of which 6 are currently operational and transmitting data in real time. The rest went off due to power failures and icebergs damaging sensors. The measures we have taken to avoid station’s failures are described, as well as some characteristics of the implemented prototype, the installed networks and the data obtained so far.