Research Profile

I am an environmental modeling scientist specializing in watershed hydrology, soil erosion, and hydro-climatic processes. My research integrates process-based models (e.g., SWAT/SWAT+, WEPP, SWMM), geospatial analysis (GIS/remote sensing), and data-driven approaches (machine learning) to understand and predict watershed responses under environmental change.

My work is characterized by a strong emphasis on:

• 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

1. Watershed Hydrology and Sediment Dynamics

My core research focuses on modeling hydrologic and sediment processes at the watershed scale, with particular attention to:

• Streamflow generation mechanisms

• Soil erosion and sediment transport

• Nonpoint source pollution and water quality

Using the SWAT/SWAT+, WEPP, and SWMM modeling framework, I have applied physically-based approaches to quantify watershed responses and identify critical source areas for management.

2. Physics–Data Integration for Hydrologic Prediction

A major component of my work involves improving hydrologic model performance through integration with machine learning techniques.

Key contributions include:

• Development of hybrid SWAT–SVR and SWAT–Wavelet–SVR models

• Enhancement of streamflow prediction accuracy under nonlinear and nonstationary conditions

• Demonstration of how data-driven methods can complement process-based models without replacing physical understanding

This line of research contributes to the emerging field of physics-informed environmental modeling.

3. Hydro-Climate Extremes and Downscaling

My research extends to understanding how climate variability and extreme precipitation affect watershed processes.

Key areas include:

• Evaluation of downscaling techniques for precipitation

• Analysis of storm intensification impacts on runoff and soil erosion

• Integration of climate scenarios into watershed models for risk assessment

This work supports improved prediction of hydrologic responses under future climate conditions. 

4. Karst Hydrology and Groundwater–Surface Water Interaction

My research has focused on karst-dominated watersheds, where traditional models often fail to represent subsurface connectivity.

Efforts include:

• Improving representation of losing streams and sinkhole-driven recharge

• Investigating groundwater–surface water connectivity

• Developing enhanced SWAT+ frameworks to better simulate karst hydrologic processes

This work aims to bridge the gap between lumped watershed models and complex subsurface systems. 

5. Precipitation Microphysics and Observational Constraints

I have also expanded into observational research using Parsivel² disdrometer data to analyze precipitation structure.

This work focuses on:

• Raindrop size distribution (DSD) characteristics

• Variability across storm types

• Implications for hydrologic modeling and erosion processes

This observational component strengthens model realism by linking rainfall microphysics to watershed response.

Research Approach

My research follows an integrative framework:

Observation → Process Understanding → Model Development → Model Enhancement → Scenario Application

Key methodological strengths include:

• Multi-source data integration (USGS, remote sensing, climate datasets, and field observations)

• Model calibration and uncertainty analysis

• Coupling of physical models with machine learning

• Development of scalable modeling approaches for real-world applications

Scholarly Contributions and Impact

My publication record reflects contributions in three main areas:

1. Watershed modeling applications and improvements

2. Hybrid modeling approaches combining physics and machine learning

3. Hydro-climate impact assessment and environmental change analysis

My work includes both applied studies and synthesis/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.

 Positioning Statement: 

My research positions me at the intersection of:

• Hydrology

• Environmental modeling

• Climate impact science

• Data-driven modeling

I bring a systems-level perspective, combining methodological innovation with practical application, making my work relevant to:

• Academic research

• Government agencies

• Environmental consulting and policy