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Uncertainty assessment of soil hydraulic parameterization by inverse modelling of evaporation experiments

Grant number: 21/10520-8
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): December 15, 2021
Effective date (End): December 14, 2022
Field of knowledge:Agronomical Sciences - Agronomy - Soil Science
Principal researcher:Quirijn de Jong van Lier
Grantee:Leonardo Inforsato
Supervisor abroad: Wolfgang Durner
Home Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Research place: University of Technology Braunschweig, Germany  
Associated to the scholarship:20/00145-2 - Development of methodology to obtain soil hydraulic properties assisted by evaporation experiment in laboratory, BP.DR

Abstract

Soil hydraulic properties, the retention function (RF) and the conductivity function (CF) are required for understanding and predicting water movement through soils, and therefore fundamental in hydrological studies and modelling. These properties are commonly expressed in semi-empirical mathematical models, and a correct determination of the respective model parameters is a prerequisite for the accurate prediction of soil water dynamics and water balance components in hydrological models. Among the methods to calibrate the models for a specific soil, sample evaporation experiments followed by Inverse Modelling (IM) is an efficient way to acquire both RF and CF simultaneously. The estimated parameters which define the soil hydraulic properties carry uncertainties which can only be reliably quantified if experimental data are of sufficient quantity and quality. This application for a grant abroad (BEPE-Fapesp) contains a proposal to conduct part of the ongoing PhD project under the supervision of an external advisor. The proposal is directly linked to the PhD project, focusing on the improvement of IM methods, specifically aiming at advances in the estimation of parameter uncertainties in scenarios with data with a relatively high bias or noise, for which currently used IM methods are inaccurate. The results will be expressed in an improved software to realize IM from evaporation experiments providing better parameter uncertainty estimation, and the proposed methodology and software will be evaluated and tested. With this internship, it is expected that the student extends his analytical skills working under supervision of a specialized external advisor and, simultaneously, improves the quality of the results of his PhD study, resulting in the publication of publications in peer-reviewed journals of high impact. (AU)

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