Gerald Corzo
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View article: Diagnosing Spatiotemporal Urban Flood Responses Under Shift Rainfall Variabilities
Diagnosing Spatiotemporal Urban Flood Responses Under Shift Rainfall Variabilities Open
View article: Spatial and temporal analysis of changes in hydrological fluxes and their relation to deforestation in the Madeira River basin
Spatial and temporal analysis of changes in hydrological fluxes and their relation to deforestation in the Madeira River basin Open
View article: Comprehensive performance evaluation of satellite-based and reanalysis rainfall estimate products in Ethiopia: For drought, flood, and water resources applications.
Comprehensive performance evaluation of satellite-based and reanalysis rainfall estimate products in Ethiopia: For drought, flood, and water resources applications. Open
Study Region Ethiopia: This study assessed the accuracy of ten satellite-based and reanalysis rainfall estimation products across Ethiopia via direct comparisons with 430 in-situ datasets from 2001 to 2020. The performance of these rainfal…
View article: Spatial and Temporal Analysis of Changes in Hydrological Fluxes and Their Relation to Deforestation in the Madeira River Basin
Spatial and Temporal Analysis of Changes in Hydrological Fluxes and Their Relation to Deforestation in the Madeira River Basin Open
View article: Spatiotemporal Non-Linear Dynamics Assessment (SNLDA) of ERA5-Land Precipitation in the Magdalena River Basin
Spatiotemporal Non-Linear Dynamics Assessment (SNLDA) of ERA5-Land Precipitation in the Magdalena River Basin Open
View article: Machine Learning Analysis of Precipitation as Trigger for Shallow Landslides: Ometepe Island, Nicaragua
Machine Learning Analysis of Precipitation as Trigger for Shallow Landslides: Ometepe Island, Nicaragua Open
In this study, we address the need for improved landslide forecasting by exploring innovative machine learning approaches to classify shallow landslide events. Focusing on Ometepe Island, Nicaragua, known for its susceptibility to hydromet…
View article: Sub-seasonal soil moisture anomaly forecasting using combinations of deep learning, based on the reanalysis soil moisture records
Sub-seasonal soil moisture anomaly forecasting using combinations of deep learning, based on the reanalysis soil moisture records Open
Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persist…
View article: Spatial-temporal analysis of the impact of deforestation on the hydrological variability of the Amazon basin.
Spatial-temporal analysis of the impact of deforestation on the hydrological variability of the Amazon basin. Open
In recent years, there has been growing concern about deforestation in the Amazon River basin, particularly in relation to its impact on regional water resources. This study performs a spatial and temporal analysis of deforestation variati…
View article: Understanding the Amazon's Atmospheric Hydrology: Insights from ERA5 Data and Directional Transport Analysis 
Understanding the Amazon's Atmospheric Hydrology: Insights from ERA5 Data and Directional Transport Analysis  Open
The atmospheric dynamics of the Amazon, critical for global environmental stability, have faced increasing influence from numerous El Niño and La Niña events in recent decades. While reanalysis data has incorporated these events …
View article: Enhancing Reservoir Management for Sustainable Hydropower Generation: A Machine Learning-Driven Approach in Response to Increasing Extreme Events in Ecuador
Enhancing Reservoir Management for Sustainable Hydropower Generation: A Machine Learning-Driven Approach in Response to Increasing Extreme Events in Ecuador Open
In recent years, frequent climate extreme events have significantly impacted various sectors, especially critical ones like hydropower generation. In Latin America and the Caribbean, hydropower constitutes a pivotal element, contributing 4…
View article: Coupling Deep Learning and Physically Based Hydrological Models for Monthly Streamflow Predictions
Coupling Deep Learning and Physically Based Hydrological Models for Monthly Streamflow Predictions Open
This study proposes a new hybrid model for monthly streamflow predictions by coupling a physically based distributed hydrological model with a deep learning (DL) model. Specifically, a simplified hydrological model is first developed by op…
View article: Development of a hazard risk map for assessing pedestrian risk in urban flash floods: A case study in Cúcuta, Colombia
Development of a hazard risk map for assessing pedestrian risk in urban flash floods: A case study in Cúcuta, Colombia Open
The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities, leading to severe flooding and significant economic losses for civilians. This trend highlights the urgent need for …
View article: Improved drought forecasting in Kazakhstan using machine and deep learning: a non-contiguous drought analysis approach
Improved drought forecasting in Kazakhstan using machine and deep learning: a non-contiguous drought analysis approach Open
Kazakhstan is recently experiencing an increase in drought trends. However, low-capacity probabilistic drought forecasts and poor dissemination have led to a drought crisis in 2021 that resulted in the loss of thousands of livestock. To im…
View article: Spatiotemporal Non-Linear Dynamics Assessment (Snlda) of Era5-Land Precipitation in the Magdalena River Basin
Spatiotemporal Non-Linear Dynamics Assessment (Snlda) of Era5-Land Precipitation in the Magdalena River Basin Open
View article: Coupling deep learning and physically-based hydrological models for monthly streamflow predictions
Coupling deep learning and physically-based hydrological models for monthly streamflow predictions Open
Revision in journal Water Resources Research, Manuscript number: 2023WR035618R Abstract: This study proposes a new hybrid model for monthly streamflow predictions by coupling …
View article: Coupling deep learning and physically-based hydrological models for monthly streamflow predictions
Coupling deep learning and physically-based hydrological models for monthly streamflow predictions Open
Revision in journal Water Resources Research, Manuscript number: 2023WR035618R Abstract: This study proposes a new hybrid model for monthly streamflow predictions by coupling a physically-based distributed hydrological model with a deep le…
View article: Coupling deep learning and physically-based hydrological models for monthly streamflow predictions
Coupling deep learning and physically-based hydrological models for monthly streamflow predictions Open
Revision in journal Water Resources Research, Paper # 2023WR035618R
View article: Coupling deep learning and physically-based hydrological models for monthly streamflow predictions
Coupling deep learning and physically-based hydrological models for monthly streamflow predictions Open
Revision in journal Water Resources Research, Paper # 2023WR035618R
View article: Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin
Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin Open
The typical drivers of drought events are lower than normal precipitation and/or higher than normal evaporation. The region's characteristics may enhance or alleviate the severity of these events. Evaluating the combined effect of the mult…
View article: Assessing Cavitation Erosion on Solid Surfaces Using a Cavitation Jet Apparatus
Assessing Cavitation Erosion on Solid Surfaces Using a Cavitation Jet Apparatus Open
This study is dedicated to the examination of cavitation-induced erosion, a critical factor in optimizing the efficiency of hydraulic systems, including hydropower plants and pumping systems. To accomplish this, we conducted a sensitivity …
View article: Fuzzy Committees of Conceptual Distributed Model
Fuzzy Committees of Conceptual Distributed Model Open
View article: An integrated approach to decision-making variables on urban water systems using an urban water use (UWU) decision-support tool
An integrated approach to decision-making variables on urban water systems using an urban water use (UWU) decision-support tool Open
In response to pressing global challenges like climate change, rapid population growth, and an urgent need for sustainable infrastructure, cities face an immediate and crucial necessity to transition swiftly toward an integrated approach t…
View article: Retracted: Spatiotemporal convolutional long short-term memory for regional streamflow predictions
Retracted: Spatiotemporal convolutional long short-term memory for regional streamflow predictions Open
Rainfall-runoff (RR) modelling is a challenging task in hydrology, especially at the regional scale. This work presents an approach to simultaneously predict daily streamflow in 86 catchments across the US using a sequential CNN-LSTM deep …
View article: Effect of climate change on the water quality of Mediterranean rivers and alternatives to improve its status
Effect of climate change on the water quality of Mediterranean rivers and alternatives to improve its status Open
View article: Integrating geographic data and the SCS-CN method with LSTM networks for enhanced runoff forecasting in a complex mountain basin
Integrating geographic data and the SCS-CN method with LSTM networks for enhanced runoff forecasting in a complex mountain basin Open
Introduction In complex mountain basins, hydrological forecasting poses a formidable challenge due to the intricacies of runoff generation processes and the limitations of available data. This study explores the enhancement of short-term r…
View article: Locating Multiple Leaks in Water Distribution Networks Combining Physically Based and Data-Driven Models and High-Performance Computing
Locating Multiple Leaks in Water Distribution Networks Combining Physically Based and Data-Driven Models and High-Performance Computing Open
Water utilities are urged to decrease their real water losses, not only to reduce costs but also to assure long-term sustainability. Hardware- and software-based techniques have been broadly used to locate leaks; within the latter, previou…
View article: Evaluating the impact of ponds on flood and drought mitigation in the Bagmati River Basin, Nepal
Evaluating the impact of ponds on flood and drought mitigation in the Bagmati River Basin, Nepal Open
This study investigates the effectiveness of ponds as a nature-based solution (NBS) to concurrently ameliorate flood and drought impacts, emphasizing the need for an integrated response to multi-extreme hydrological events. We incorporate …
View article: Comment on hess-2023-98
Comment on hess-2023-98 Open
Abstract. The European Centre for Medium-Range Weather Forecasts (ECMWF) provides subseasonal to seasonal (S2S) precipitation forecasts; S2S forecasts extend from two weeks to two months ahead; however, the accuracy of S2S…
View article: Comment on hess-2023-98
Comment on hess-2023-98 Open
Abstract. The European Centre for Medium-Range Weather Forecasts (ECMWF) provides subseasonal to seasonal (S2S) precipitation forecasts; S2S forecasts extend from two weeks to two months ahead; however, the accuracy of S2S…
View article: Comment on hess-2023-98
Comment on hess-2023-98 Open
Abstract. The European Centre for Medium-Range Weather Forecasts (ECMWF) provides subseasonal to seasonal (S2S) precipitation forecasts; S2S forecasts extend from two weeks to two months ahead; however, the accuracy of S2S…