Overview
I am an environmental modeling scientist specializing in watershed hydrology, soil erosion, and hydro-climatic processes. My research integrates process-based models—including SWAT/SWAT+, WEPP, and SWMM—geospatial analysis (GIS and remote sensing), and data-driven approaches (machine learning) to understand and predict watershed responses under environmental change.
My work emphasizes:
- Mechanistic understanding of hydrologic and sediment processes
- Bridging physics-based models with data-driven methods
- Addressing real-world challenges under data-limited conditions
- Multi-scale analysis from precipitation processes to watershed responses
Research themes
Watershed Hydrology & Sediment Dynamics
Process-based modeling of streamflow, erosion, sediment transport, nonpoint-source pollution, and water quality at the watershed scale, with emphasis on critical-source-area identification and management.
- SWAT / SWAT+
- Sediment
- NPS
- Water Quality
Physics + Data Integration
Hybrid approaches that combine process-based watershed models with support vector regression, wavelets, and machine learning to improve prediction while retaining physical understanding.
- SWAT–SVR
- Wavelet
- Machine Learning
- Prediction
Hydro-climate Extremes & Downscaling
Climate variability, precipitation downscaling, storm intensification, and future-scenario analysis for runoff, soil erosion, crop yield, and watershed risk.
- WEPP
- Climate Extremes
- Downscaling
- Scenario Analysis
Selected work
- Elevated CO2, temperature, and storm-intensification effects on crop yield, runoff, and soil loss Catena · 2022
- Surface-runoff and soil-loss response to climate change under GCM ensembles and management systems Soil & Tillage Research · 2022
- Long-term precipitation variability in the Poyang Lake Basin Open Journal of Modern Hydrology · 2016
Karst Hydrology
Improved representation of losing streams, sinkhole-driven recharge, and groundwater–surface-water connectivity in SWAT+ for complex and data-limited karst watersheds.
- Karst
- Sinkholes
- Losing Streams
- SWAT+
Precipitation Microphysics & Urban Stormwater
Parsivel²-based analysis of raindrop-size distributions and storm variability, integrated with high-resolution SWMM modeling of urban runoff and contaminant transport across varied rainfall scenarios and surface conditions.
- Parsivel²
- Raindrop Size
- SWMM
- Urban Stormwater Modeling
Selected work
- Evaluating Parsivel²’s raindrop data across simulated and natural rain events Atmospheric Environment · 2025
- Coastal winter precipitation measured with a Parsivel² disdrometer Atmospheric Research · 2024
- SWMM emergency-response modeling of biological-agent transport across urban surfaces Journal of Hazardous Materials · 2023
Explore all research summaries →
Research approach
Observation
Field data
Remote sensing
Climate dataProcessUnderstanding
Hydrology
Sediment
Rainfall processesModelDevelopment
SWAT / SWAT+
WEPP
SWMMModelEnhancement
Machine learning
Calibration
UncertaintyScenarioApplication
Decisions
Management
Resilience
Across these phases, I integrate multi-source observations, calibration and uncertainty analysis, physics–data coupling, and scalable workflows for real-world environmental applications.
Scholarly contributions and impact
My publication record reflects contributions in three main areas:
- Watershed-modeling applications and improvements
- Hybrid modeling approaches combining physics and machine learning
- Hydro-climate impact assessment and environmental-change analysis
My work includes both applied studies and synthesis and review contributions, with citation impact demonstrating sustained engagement within the hydrology and environmental-modeling communities.
Research vision
My long-term research goal is to develop next-generation watershed-modeling frameworks that:
- Integrate physical processes, data-driven methods, and observational constraints
- Accurately represent hydro-climatic extremes and nonlinear system behavior
- Improve prediction under data scarcity and environmental change
- Support science-based decision-making for water-resource management
A central theme of my future work is:
Advancing physics-informed, data-integrated watershed modeling for complex systems such as karst environments under changing climate conditions.
My research positions me at the intersection of hydrology, environmental modeling, climate-impact science, and data-driven modeling. I bring a systems-level perspective that combines methodological innovation with practical application, making my work relevant to academic research, government agencies, environmental consulting, and policy.
Research narrative Full Research Statement A detailed overview of my research evolution, contributions, and future directions.
My research centers on two interconnected themes: soil-erosion modeling and watershed hydrology under climate change, with a growing focus on integrating data-driven and process-based approaches to support climate-resilient land and water management.
In early work, I developed a GIS-integrated Cellular Automata (CA) model to simulate rill erosion under varying rainfall and slope conditions, funded by the National Natural Science Foundation of China. I later conducted watershed-scale erosion-risk assessments in the Poyang Lake Basin using USLE, remote sensing, and spatial analysis, contributing to improved risk mapping in a key ecological region.
My climate-related hydrology research explored 50-year trends in runoff, sediment yield, and rainfall variability using wavelet analysis, geostatistics, and downscaled data, supported by national and postdoctoral foundations.
At the U.S. EPA’s Robert S. Kerr Environmental Research Center, I co-authored a major technical report reviewing 14 watershed models for nutrient fate and transport and published a peer-reviewed synthesis on NPS pollution modeling. I also applied SWAT to evaluate sediment loading in China’s Xinjiang River Basin under data-scarce conditions.
From 2020–2021, I advanced climate-impact modeling at USDA-ARS by applying WEPP to simulate runoff, erosion, and yield under conservation practices and projected storm intensification. I built a Python-based automation tool to batch-process WEPP simulations across climate scenarios, supporting peer-reviewed publications in Catena and Soil & Tillage Research.
From 2021 to 2025, I served as a Federal Postdoctoral Research Associate (GS-12) with the U.S. EPA Office of Research and Development in North Carolina. I led high-performance SWMM modeling of contaminant transport, such as anthrax spores, for the Homeland Security Research Program, contributing to interagency resilience planning (AnCOR) with EPA, DHS, and USCG. I incorporated IronPython scripting, GIS workflows, and Parsivel² disdrometer data to study urban-runoff behavior and precipitation microphysics.
My long-term goal is to integrate data science, hydrologic modeling, and climate-adaptation strategies to support resilient watershed planning. With broad experience across modeling platforms (SWAT, WEPP, SWMM), field-data integration, HPC environments, and interdisciplinary collaboration, I am well positioned to lead research at the intersection of environmental change and water-resource management.