Comparison, validation and improvement of empirical soil moisture models for conditions in Colombia

Author:

Rincón Alejandro12,Hoyos Fredy E.3,Candelo-Becerra John E.3

Affiliation:

1. Grupo de Investigación en Desarrollos Tecnológicos y Ambientales (GIDTA), Facultad de Ingeniería y Arquitectura, Universidad Católica de Manizales, Carrera 23 N. 60–63, Manizales 170002, Colombia

2. Grupo de Investigación en Microbiología y Biotecnología Agroindustrial (GIMIBAG), Instituto de Investigación en Microbiología y Biotecnología Agroindustrial, Universidad Católica de Manizales, Carrera 23 N. 60–63, Manizales 170002, Colombia

3. Departamento de Energía Eléctrica y Automática, Facultad de Minas, Universidad Nacional de Colombia, Sede Medellín, Carrera 80 No. 65–223, Campus Robledo, Medellín 050041, Colombia

Abstract

<abstract> <p>Modeling soil moisture as a function of meteorological data is necessary for agricultural applications, including irrigation scheduling. In this study, empirical water balance models and empirical compartment models are assessed for estimating soil moisture, for three locations in Colombia. The daily precipitation and average, maximum and minimum air temperatures are the input variables. In the water balance type models, the evapotranspiration term is based on the Hargreaves model, whereas the runoff and percolation terms are functions of precipitation and soil moisture. The models are calibrated using field data from each location. The main contributions compared to closely related studies are: i) the proposal of three models, formulated by combining an empirical water balance model with modifications in the precipitation, runoff, percolation and evapotranspiration terms, using functions recently proposed in the current literature and incorporating new modifications to these terms; ii) the assessment of the effect of model parameters on the fitting quality and determination of the parameters with higher effects; iii) the comparison of the proposed empirical models with recent empirical models from the literature in terms of the combination of fitting accuracy and number of parameters through the Akaike Information Criterion (AIC), and also the Nash-Sutcliffe (NS) coefficient and the root mean square error. The best models described soil moisture with an NS efficiency higher than 0.8. No single model achieved the highest performance for the three locations.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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