Nutrient modeling for a semi-intensive IMC pond: an MS-Excel approach

Area of Science:

• Aquaculture
• Environmental Science
• Computational Modeling

Background:

• Semi-intensive Indian Major Carp (IMC) culture is vital for aquaculture.
• Maintaining optimal water quality, particularly Total Ammonia Nitrogen (TAN), is crucial for fish health and growth.
• Existing models may not fully capture TAN dynamics in IMC pond ecosystems.

Purpose of the Study:

• To develop and validate a predictive model for Total Ammonia Nitrogen (TAN) in Indian Major Carp (IMC) culture systems.
• To assess the impact of different stocking densities on TAN levels.
• To provide a tool for optimizing water management in IMC aquaculture.

Main Methods:

• A semi-intensive IMC culture experiment was conducted over three years at varying stocking densities (20,000, 35,000, and 50,000 fingerlings/ha).
• Water quality parameters, including TAN, were monitored daily.
• A previously developed nutrient dynamics model was adapted and calibrated using MS-Excel and the forward finite difference method.

Main Results:

• The developed spreadsheet model demonstrated over 90% efficiency in estimating TAN levels.
• Model calibration and validation were performed using two and three years of observed data, respectively.
• Thirteen model parameters were standardized based on observed data from ponds with different stocking densities.

Conclusions:

• The validated spreadsheet model is a reliable tool for predicting TAN in IMC culture ponds.
• Effective water management, guided by accurate TAN prediction, can enhance fish growth and pond productivity.
• This modeling approach can be applied to optimize aquaculture practices and ensure sustainable fish farming.