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Predictive Modelling and Optimisation

Submitted by Ananda Rohn on
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The analytical backbone of OPTAIN is formed by process-based predictive models operating at both field and catchment scale.

Predictive Modelling Framework

Models such as SWAT+ (Soil and Water Assessment Tool Plus) and SWAP (Soil–Water–Atmosphere–Plant model)are applied to simulate:

  • Water balance components (surface runoff, infiltration, evapotranspiration, groundwater recharge)

  • Nutrient transport dynamics (primarily nitrogen and phosphorus fluxes)

  • Crop production responses under varying management conditions

  • Effects of climate variability and projected climate scenarios

Field-scale simulations capture detailed soil–water–plant interactions, while catchment-scale simulations integrate spatial heterogeneity and hydrological connectivity. This hierarchical modelling structure ensures that field-level decisions can be translated into catchment-scale performance indicators.

The models are calibrated and validated using available hydrological and nutrient datasets, ensuring internal consistency within each case study environment.

 
Multi-Objective Optimisation Framework

The optimisation component builds upon model outputs by exploring combinations and spatial allocations of NSWRM across catchments.

The optimisation protocol:

  • Defines decision variables at field scale (type and location of NSWRM)

  • Evaluates system performance at catchment scale

  • Applies multi-objective evolutionary algorithms

  • Generates Pareto fronts representing efficient trade-offs

The optimisation does not identify a single best solution. Instead, it maps the decision space and reveals how objective trade-offs evolve under different configurations.

This modelling–optimisation coupling allows systematic exploration of:

  • Objective weighting sensitivity

  • Spatial targeting strategies

  • Climate robustness of portfolios

  • Cost–performance relationships