Water balance is measured by transpiration, which has a significant impact on the performance of geotechnical infrastructure (vegetated slopes), ecological infrastructure (wetlands), urban infrastructure (green roof, biofiltration units) and agricultural infrastructure. Past studies have formulated models using analytical modeling to evaluate the transpiration index based on energy balance and suction. In circumstance of impartial and uncertain information about the root and shoot properties and its effect on the transpiration index, the present work aims to introduce the new optimization algorithm of genetic programming (GP) to quantify and optimize the transpiration index of plant.
The GP framework, having objective function of structural risk minimization, is used for formulating the transpiration index model. The statistical metrics with 2D and 3D analyses of the models are conducted to determine its accuracy and understand the transpiration process.
The model analysis reveals that the proposed model extrapolates the transpiration index values accurately based on five inputs. 2D and 3D relationships between the transpiration index and the five inputs suggest that the total root area has the highest impact on the transpiration index followed by shoot length and root biomass. There is not much impact of the shoot mass and stem basal diameter on the transpiration index. It was also found that the transpiration index increases with an increase in total root area and root biomass.
This work is a first-of-its-kind study involving the extensive computation analysis for quantifying and optimizing the transpiration index of the soil for the complex civil systems.
