Effective Energy and Mass Transfer (EEMT)¶

Overview¶

Effective Energy and Mass Transfer (EEMT) is a framework for quantifying energy and mass flux in Earth's Critical Zone. EEMT provides a common energy currency for understanding landscape evolution, soil formation, and biogeochemical processes across spatiotemporal scales.

Where:

• E_BIO = Energy from net primary production (biological energy)
• E_PPT = Energy from effective precipitation (thermal energy)

Units: MJ m⁻² yr⁻¹ (megajoules per square meter per year)

Architecture¶

The EEMT workflow integrates topographic analysis with climate data to produce energy flux maps:

flowchart LR
    subgraph inputs[" Input Data "]
        DEM[("DEM<br/>Elevation")]
        DAYMET[("DAYMET<br/>Climate")]
    end

    subgraph processing[" Processing "]
        SOL["Solar Radiation<br/>(r.sun)"]
        TOPO["Topographic Analysis<br/>(slope, aspect, TWI)"]
        CLIMATE["Climate Processing<br/>(tmin, tmax, prcp)"]
    end

    subgraph output[" Output "]
        EEMT["EEMT Calculation"]
        OUT[("Energy Maps<br/>MJ/m²/yr")]
    end

    DEM --> SOL
    DEM --> TOPO
    DAYMET --> CLIMATE
    SOL --> EEMT
    TOPO --> EEMT
    CLIMATE --> EEMT
    EEMT --> OUT

    style inputs fill:#e8f5e9,stroke:#2e7d32
    style processing fill:#fff3e0,stroke:#ff9800
    style output fill:#e3f2fd,stroke:#1976d2

Key Features¶

Quick Start¶

Web Interface (Recommended)¶

The fastest way to get started with EEMT is through our containerized web interface:

# 1. Build Docker container (one-time setup)
cd docker/ubuntu/24.04/
./build.sh

# 2. Start web interface  
cd ../../web-interface/
pip install -r requirements.txt
python app.py

# 3. Open browser to http://127.0.0.1:5000

Features: - 🌐 Web-based Interface: Upload DEMs and configure workflows through browser - 🐳 Containerized Execution: All dependencies included, no complex setup - 📊 Real-time Monitoring: Track progress with live updates - 💾 Easy Results: Download processed data as ZIP archives

Command Line Interface¶

For advanced users, EEMT can be run directly:

# 1. Install Dependencies
conda install -c conda-forge grass gdal rasterio xarray dask

# 2. Run Solar Radiation Workflow
cd sol/sol/
python run-workflow --step 15 --num_threads 4 your_dem.tif

# 3. Run Full EEMT Analysis  
cd ../../eemt/eemt/
python run-workflow --start-year 2020 --end-year 2020 your_dem.tif

Scientific Foundation¶

EEMT calculations are based on peer-reviewed methodologies:

Typical EEMT Values by Climate Zone¶

Applications¶

Research Applications¶

• Soil formation modeling: Predict pedogenesis rates across landscapes
• Critical Zone evolution: Understand long-term landscape development
• Biogeochemical cycling: Quantify carbon and nutrient fluxes
• Climate change impacts: Assess ecosystem sensitivity to warming

Operational Applications¶

• Land management: Optimize restoration and conservation strategies
• Agricultural planning: Site-specific productivity assessments
• Urban planning: Heat island mitigation and green infrastructure
• Risk assessment: Drought, fire, and erosion hazard mapping

Getting Started¶

Community¶

Contributing¶

We welcome contributions to improve EEMT methods, add new examples, and extend functionality. See our Development Guide.

Support¶

• GitHub Issues: Report bugs and request features
• Discussions: Ask scientific methodology questions
• Examples: Share use cases and workflows

Citation¶

If you use EEMT in your research, please cite:

For high-performance computing implementations: