Research progress in parameterizing irrigation and fertilization in land surface model

Area of Science:

• Earth and Environmental Sciences
• Agricultural Science

Background:

• Global climate change and population growth necessitate advanced agricultural techniques like irrigation and fertilization to ensure food security.
• These practices significantly influence terrestrial ecosystem processes, including water cycling, energy flow, and material cycling.
• Accurate representation in land surface models (LSMs) is vital for understanding land-atmosphere interactions and their impact on food production.

Approach:

• Reviewed parameterization methods for irrigation and nitrogen fertilizer application within LSMs.
• Focused on three key parameters: application method, usage, and timing.
• Identified discrepancies between modeled and actual agricultural practices due to data resolution limitations.

Key Points:

• Current LSMs often simplify irrigation and fertilization, deviating from real-world agricultural operations.
• This simplification hinders accurate assessment of the impacts of these practices on crop yield, environment, and local climate.
• High-resolution spatio-temporal data limitations are a major challenge in improving model accuracy.

Conclusions:

• Future LSM development should incorporate crop-specific water demands and differentiated irrigation thresholds.
• Integrating field records and regional grid data can create more realistic parameterization schemes for agricultural operations.
• Developing advanced fertilization diagnosis schemes considering crop type, phenology, and soil fertility will enhance LSM applicability and simulation accuracy, especially in data-scarce regions.