Inverse modelling with a genetic algorithm to derive hydraulic properties of a multi-layered forest soil

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Abstract

This study investigates conceptual models with contrasting complexityto quantify accurately the water balance in a soil–vegetation–atmosphere system: (i) the mechanistic HYDRUS-1D model; and (ii) a compartment model. Soil hydraulic properties were derived from field-based soil water content data collected at multiple depths installed in a forest soil for nearly one full hydrological year. Parameter optimisation was based on a genetic algorithm including elitism for improving the search for optimal solutions. Four scenarios were developed to investigate (i) the impact of the type of conceptual flow model (mechanistic or compartment), and (ii) the effect of the degree of detail or granularity used to describe the soil profile, on the accuracy of inverse modelling. Results showed that for models with the same number of material layers as the number of pedogenic horizons in the soil profile, both conceptual models reasonably match the observed water contents at all depths. A functional evaluation of model performance using the cumulative annual drainage revealed overall good performance of the simplified models; drainage values calculated with the five-layer compartment model and the one- and two-layer mechanistic model were never more than 36% larger than their reference value.

Details

Original languageEnglish
Pages (from-to)372-389
JournalSoil Research
Volume51
Issue number5
DOIs
Publication statusPublished - Sep 2013

Keywords

  • inverse optimistion, genetic algorithm, soil water balance

ID: 244623