Redirigiendo al acceso original de articulo en 22 segundos...
Inicio  /  Water  /  Vol: 9 Par: 8 (2017)  /  Artículo
ARTÍCULO
TITULO

Decision-Making Methodology for Risk Management Applied to Imja Lake in Nepal

Amanda D. Cuellar and Daene C. McKinney    

Resumen

Glacial retreat causes the formation of glacier lakes with the potential of producing glacial lake outburst floods (GLOFs). Imja Lake in Nepal is considered at risk for a GLOF. Communities in the path of a potential Imja GLOF are implementing adaptation projects, yet no quantitative data or guidance is available to understand the benefits of these projects or how to weigh benefits against the cost of implementation. We develop and demonstrate a decision-making methodology for GLOF risk management, incorporating available scientific information and uncertainty. The methodology consists of (1) identifying flooding scenarios, (2) evaluating scenario consequences, and (3) performing an economic analysis of proposed adaptation projects. The methodology is applied to assess benefits in Dingboche of lowering Imja Lake by 3, 10 and 20 m. The results show that the baseline case (no lake lowering) has the lowest expected cost because of low valuation of agricultural land and homes in the literature. Nonetheless, the result is sensitive to changes in the analysis variables. We also found that lowering the lake by 10 or 20 m is efficient according only to the methodology used here; however, considering only direct economic damages and literature cost estimates, the costs outweigh the benefits for these projects.

 Artículos similares

       
 
Seyed Ali Alavi, Saeed Esfandi, Amir Reza Khavarian-Garmsir, Safiyeh Tayebi, Aliakbar Shamsipour and Ayyoob Sharifi    
This research aims to analyze the relationship between environmental justice and urban green space connectivity in Tehran, Iran. The evaluation of green space connectivity in this study is conducted through two distinct cost layers: one aimed at enhancin... ver más
Revista: Urban Science

 
Maryam Badar and Marco Fisichella    
Fairness-aware mining of data streams is a challenging concern in the contemporary domain of machine learning. Many stream learning algorithms are used to replace humans in critical decision-making processes, e.g., hiring staff, assessing credit risk, et... ver más

 
Eduard Angelats, Alban Gorreja, Pedro F. Espín-López, M. Eulàlia Parés, Eva Savina Malinverni and Roberto Pierdicca    
The seamless integration of indoor and outdoor positioning has gained considerable attention due to its practical implications in various fields. This paper presents an innovative approach aimed at detecting and delineating outdoor, indoor, and transitio... ver más

 
Paolo Bellavista and Giuseppe Di Modica    
A Digital Twin (DT) refers to a virtual representation or digital replica of a physical object, system, process, or entity. This concept involves creating a detailed, real-time digital counterpart that mimics the behavior, characteristics, and attributes... ver más
Revista: Future Internet

 
Abdullah F. Al-Aboosi, Aldo Jonathan Muñoz Vazquez, Fadhil Y. Al-Aboosi, Mahmoud El-Halwagi and Wei Zhan    
Accurate prediction of renewable energy output is essential for integrating sustainable energy sources into the grid, facilitating a transition towards a more resilient energy infrastructure. Novel applications of machine learning and artificial intellig... ver más