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Process-based Flood Frequency Analysis
Process-based Flood Frequency Analysis
For more detailed information, please refer to our publications: Perez et al., 2024, and Perez et al., 2018.
For more detailed information, please refer to our publications: Perez et al., 2024, and Perez et al., 2018.
Estimating the extent, frequency, and magnitude of flood events presents significant challenges due to the complexity and variability of hydrological processes. Addressing this challenge requires the implementation of process-based hydrological models, which provide a detailed representation of hydrological processes. These models enable us to capture the complex dynamics of watersheds, including variations in land use, soil types, and channel characteristics. This approach is particularly valuable as it allows us to explore and understand how hydrological perturbations—such as accelerated changes in land use, wildfires, and evolving climate patterns—can impact flood magnitudes. Such changes not only alter natural ecosystems but also modify flood risks for human populations. Our research aims to deepen this understanding and provide actionable insights.
Estimating the extent, frequency, and magnitude of flood events presents significant challenges due to the complexity and variability of hydrological processes. Addressing this challenge requires the implementation of process-based hydrological models, which provide a detailed representation of hydrological processes. These models enable us to capture the complex dynamics of watersheds, including variations in land use, soil types, and channel characteristics. This approach is particularly valuable as it allows us to explore and understand how hydrological perturbations—such as accelerated changes in land use, wildfires, and evolving climate patterns—can impact flood magnitudes. Such changes not only alter natural ecosystems but also modify flood risks for human populations. Our research aims to deepen this understanding and provide actionable insights.
Resonance of hydrological systems on flood events
Resonance of hydrological systems on flood events
Advancing our understanding of hydrological conditions that lead to extraordinary flood events is crucial for improving flood protection and resilience. Fundamental science is urgently needed to narrow down the unique hydrological conditions that may produce extraordinary flood events. In this vein, we are developing numerical tools to detect such conditions, thereby strengthening engineering practices for flood protection infrastructure and enhancing flood risk resilience. A unique contribution in this area is the development of the Directional Unit Hydrograph model. This model adds new dimensions of storm direction and storm velocity to the traditional unit hydrograph model, enabling the identification of unique conditions that produce "resonance" in the hydrological system, leading to extraordinary flood events. This approach will be vital in addressing future questions on how floods will change with ongoing shifts in climate patterns and in detecting unique, extraordinary flood events.
Advancing our understanding of hydrological conditions that lead to extraordinary flood events is crucial for improving flood protection and resilience. Fundamental science is urgently needed to narrow down the unique hydrological conditions that may produce extraordinary flood events. In this vein, we are developing numerical tools to detect such conditions, thereby strengthening engineering practices for flood protection infrastructure and enhancing flood risk resilience. A unique contribution in this area is the development of the Directional Unit Hydrograph model. This model adds new dimensions of storm direction and storm velocity to the traditional unit hydrograph model, enabling the identification of unique conditions that produce "resonance" in the hydrological system, leading to extraordinary flood events. This approach will be vital in addressing future questions on how floods will change with ongoing shifts in climate patterns and in detecting unique, extraordinary flood events.
Urban Hydrology Systems
Urban Hydrology Systems
Urban systems, especially sewer systems, are constantly challenged by the ongoing changes in the conditions for which they were originally designed. Population dynamics, accelerated urban development, changes in land use, and fluctuations in groundwater tables are among the challenges that complicate the reliable design and maintenance of these critical urban infrastructures. To address these challenges, we have developed a novel parsimonious model that allows for the efficient computational modeling of sewer flow. This model enables us to explore sewage dynamics comprehensively, including the analysis of inflow-infiltration and the opportunity to explore the deterioration of the structural integrity of the system.
Urban systems, especially sewer systems, are constantly challenged by the ongoing changes in the conditions for which they were originally designed. Population dynamics, accelerated urban development, changes in land use, and fluctuations in groundwater tables are among the challenges that complicate the reliable design and maintenance of these critical urban infrastructures. To address these challenges, we have developed a novel parsimonious model that allows for the efficient computational modeling of sewer flow. This model enables us to explore sewage dynamics comprehensively, including the analysis of inflow-infiltration and the opportunity to explore the deterioration of the structural integrity of the system.
Extreme storm events under future climates
Extreme storm events under future climates
For more detailed information, please refer to our publications: Perez et al., 2024. in review
For more detailed information, please refer to our publications: Perez et al., 2024. in review
How extreme precipitation will change under different global warming scenarios remains one of the most challenging questions in climate science. There is clear agreement that the ongoing increase in greenhouse gas emissions is and will continue to drastically alter regional and global patterns of rainfall events. However, the complex spatial-temporal structure of extreme rainstorms, influenced by both local and regional drivers, makes it difficult to quantify with high confidence how extreme precipitation will change in future climates. Addressing this challenge is critical for engineering design and enhancing flood resilience in the face of these extreme events. In our research, we analyze Global Climate Models to dissect patterns and better understand projected changes in extreme rainfall. We achieve this by employing advanced techniques that integrate machine learning methods, storm tracking algorithms, and stochastic storm transposition.
How extreme precipitation will change under different global warming scenarios remains one of the most challenging questions in climate science. There is clear agreement that the ongoing increase in greenhouse gas emissions is and will continue to drastically alter regional and global patterns of rainfall events. However, the complex spatial-temporal structure of extreme rainstorms, influenced by both local and regional drivers, makes it difficult to quantify with high confidence how extreme precipitation will change in future climates. Addressing this challenge is critical for engineering design and enhancing flood resilience in the face of these extreme events. In our research, we analyze Global Climate Models to dissect patterns and better understand projected changes in extreme rainfall. We achieve this by employing advanced techniques that integrate machine learning methods, storm tracking algorithms, and stochastic storm transposition.
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