Application of a machine learning technique for developing short-term flood and drought forecasting models in tropical mountainous catchments

Abstract:

Floods and droughts are among the most common natural hazards worldwide. They produce major impacts on society, economy, and ecosystems. Even worst, the frequency and severity of hydrological extremes are expected to increase with climate change and land-use alteration. As a countermeasure, during last decades, implementation of flood and drought forecasting models have globally become an emerging field of research for water management and risk assessment. In mountainous areas, hydrological extremes forecasting is unfortunately more challenging considering that information other than precipitation and runoff is not commonly available due to budget constraints, remoteness of the study areas and extreme spatio-temporal variability of additional driving forces. This is especially true for the tropical Andes in South America, which is the longest and widest cool region in the tropics. Recent …

Año de publicación:

2021

Keywords:

Fuente:

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