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

TY - JOUR

T1 - Inverse modelling with a genetic algorithm to derive hydraulic properties of a multi-layered forest soil

AU - Schneider, Sébastien

AU - Jacques, Diederik

AU - Mallants, Dirk

N1 - Score = 10

PY - 2013/9

Y1 - 2013/9

N2 - 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.

AB - 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.

KW - inverse optimistion

KW - genetic algorithm

KW - soil water balance

UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/ezp_131116

UR - http://knowledgecentre.sckcen.be/so2/bibref/10552

U2 - 10.1071/SR13144

DO - 10.1071/SR13144

M3 - Article

VL - 51

SP - 372

EP - 389

JO - Soil Research

JF - Soil Research

SN - 1838-675X

IS - 5

ER -