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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(1)
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Assessment of native radar reflectivity and radar rainfall estimates for discharge forecasting in mountain catchments with a random forest model
ArticleAbstract: Discharge forecasting is a key component for early warning systems and extremely useful for decisionPalabras claves:Andes, Discharge forecasting, Machine learning, Mountain region, Native radar data, Radar rainfall, Radar reflectivity, X-bandAutores:Bendix J., Contreras P., Johanna Orellana-Alvear, Paul Muñoz, Rolando Enrique Célleri Alvear, Rollenbeck R.Fuentes:googlescopusFrom local to regional compound flood mapping with deep learning and data fusion techniques
ArticleAbstract: Compound flooding (CF), as a result of oceanic, hydrological, meteorological and anthropogenic drivePalabras claves:Compound flood mapping, convolutional neural networks, data fusion, deep learning, hurricanesAutores:Moftakhari H., Moradkhani H., Muñoz D.F., Paul MuñozFuentes:googlescopusFusing Multisource Data to Estimate the Effects of Urbanization, Sea Level Rise, and Hurricane Impacts on Long-Term Wetland Change Dynamics
ArticleAbstract: Wetlands are endangered ecosystems that provide vital habitats for flora and fauna worldwide. They sPalabras claves:data fusion, deep learning, hurricane impacts, mobile bay, Sea level rise, urban development, wetland lossAutores:Alipour A., Moftakhari H., Moradkhani H., Mortazavi B., Muñoz D.F., Paul MuñozFuentes:googlescopusFlash-flood forecasting in an andean mountain catchment-development of a step-wise methodology based on the random forest algorithm
ArticleAbstract: Flash-flood forecasting has emerged worldwide due to the catastrophic socio-economic impacts this haPalabras claves:Flash-flood, forecasting, Lag analysis, Machine learning, Precipitation-runoff, random forestAutores:Johanna Orellana-Alvear, Patrick Willems, Paul Muñoz, Rolando Enrique Célleri AlvearFuentes:googlescopusFlood early warning systems using machine learning techniques: The case of the tomebamba catchment at the southern Andes of Ecuador
ArticleAbstract: Worldwide, machine learning (ML) is increasingly being used for developing flood early warning systePalabras claves:Andes, Flood early warning, forecasting, hydrological extremes, Machine learningAutores:Bendix J., Jan Jozef Albert Feyen, Johanna Orellana-Alvear, Paul Muñoz, Rolando Enrique Célleri AlvearFuentes:googlescopusEffect of the resolution of tipping-bucket rain gauge and calculation method on rainfall intensities in an andean mountain gradient
ArticleAbstract: A laser-optical disdrometer served as reference to assess the absolute percent bias of calculated raPalabras claves:Altitudinal gradient, ECUADOR, Páramo ecoregion, Percent absolute bias, Precipitation sensor, Rainfall intensityAutores:Jan Jozef Albert Feyen, P Muñoz, Paul Muñoz, Rolando Enrique Célleri AlvearFuentes:googlerraaescopusNear-real-time satellite precipitation data ingestion into peak runoff forecasting models
ArticleAbstract: Extreme peak runoff forecasting is still a challenge in hydrology. In fact, the use of traditional pPalabras claves:Baseflow separation, Extreme runoff, Feature engineering, forecasting, IMERG, PERSIANN, Tropical AndesAutores:Corzo G., Jan Jozef Albert Feyen, Paul Muñoz, Rolando Enrique Célleri Alvear, Solomatine D.Fuentes:googlescopusInfluence of random forest hyperparameterization on short-term runoff forecasting in an andean mountain catchment
ArticleAbstract: The Random Forest (RF) algorithm, a decision-tree-based technique, has become a promising approach fPalabras claves:Machine learning, Optimal hyperparameters, random forest, Runoff forecasting, Tropical AndesAutores:Bendix J., Contreras P., Johanna Orellana-Alvear, Paul Muñoz, Rolando Enrique Célleri AlvearFuentes:googlescopus