Area of research
Global and Planetary Change · Water Science and Technology
Research interest
Research interests include Hydrology and Watershed Management Studies, Flood Risk Assessment and Management, Hydrology and Drought Analysis, and Climate variability and models.
Four Decades of Baseflow Drought Analysis Reveals Varying Contributions of Climatic Drivers and Physical Controls
Synergistic Integration of Flood Inundation Modeling Methods: A Review of Computational, Data‐Driven, Observational and Experimental, and Conceptual Models
An Effective Monitoring of Evolving Groundwater Drought via Multivariate Data Assimilation and Machine Learning
Synergistic impact of marine heat waves and rapid intensification exacerbates tropical cyclone destructive power worldwide
Convergent and Transdisciplinary Integration: On the Future of Integrated Modeling of Human‐Water Systems
A surrogate machine learning modeling approach for enhancing the efficiency of urban flood modeling at metropolitan scales
A data-driven framework for an efficient block-level coastal flood risk assessment
The Needs, Challenges, and Priorities for Advancing Global Flood Research
Inequality in human exposure to future climate extremes
DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States
Enhancing compound flood simulation accuracy and efficiency in urbanized coastal areas using hybrid meshes and modified digital elevation model
Harnessing Generative Deep Learning for Enhanced Ensemble Data Assimilation
Analyzing Compound Flooding Drivers Across the US Gulf Coast States
Coping with data scarcity in extreme flood forecasting: A deep generative modeling approach
Harnessing Twitter (X) with AI-enhanced natural language processing for disaster management: Insights from California wildfire
A multi-source remote sensing-based geocommunication tool for global flood monitoring and management
A cluster-based temporal attention approach for predicting cyclone-induced compound flood dynamics
Toward an integrated sustainability assessment of Water-Energy-Food nexus indicators
Spatial delineation of the compound flood transition zone using deep learning
Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting
Snow drought to hydrologic drought progression using machine learning and probabilistic analysis
A Block‐Level Categorical Flood Risk Mapping to Aid Shelter Location
FLDSensing: Remote Sensing Flood Inundation Mapping with FLDPLN
Rapid intensification of tropical cyclones in the Gulf of Mexico is more likely during marine heatwaves
Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models
Urban flood susceptibility mapping using frequency ratio and multiple decision tree-based machine learning models
Generative Adversarial Network for Real‐Time Flash Drought Monitoring: A Deep Learning Study
Hydrological Research Evolution: A Large Language Model‐Based Analysis of 310,000 Studies Published Globally Between 1980 and 2023
Assimilation of Sentinel‐Based Leaf Area Index for Modeling Surface‐Ground Water Interactions in Irrigation Districts
Nonlinear Interactions of Sea‐Level Rise and Storm Tide Alter Extreme Coastal Water Levels: How and Why?