Variability of soil hydraulic parameters and its impact on agro-hydrological model predictions

• Grant number: 15/04430-5
• Support type: Scholarships in Brazil - Doctorate
• Effective date (Start): June 01, 2015
• Effective date (End): November 30, 2018
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Quirijn de Jong van Lier
• Grantee: Thalita Campos Oliveira
• Home Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Associated scholarship(s): 17/21109-1 - Variability of soil hydraulic parameters and its impact on predictions of an agro hydrological model., BE.EP.DR

Abstract

The soil plays an important role in the hydrological cycle, especially in the water flows in the soil-plant-atmosphere system. Many hydrological models have been developed to increase understanding of these relations and improve predictions. One of these models is the SWAP model (Soil-Water-Atmosphere-Plant), enabling simulation of transport of water, solutes and heat in saturated and unsaturated soil zone in interaction with plant development. SWAP is soil physically based on soil hydraulic properties (retention and conduction) employing the Richards equation, It has a high input data requirement, especially for the parameters that define soil hydraulic properties. These parameters are subject to variations due to natural soil variability. In this study we aimed to analyze the impact of the variability of soil hydraulic parameters on the prediction of water balance components through a stochastic process using SWAP. Hydraulic properties (soil water retention and hydraulic conductivity) will be determined in undisturbed soil samples (metal rings of 5 cm diameter and 3 cm height) with a large number of repetitions and Van Genuchten model parameters, residual water content, saturated water content, alpha, n and saturated hydraulic conductivity will be determined. Then, using a statistical resampling method (bootstrap), the frequency distribution of these parameters will be defined and three representative population sizes will be chosen. Using the three population sizes, the frequency distribution of accumulated evapotranspiration, deep drainage and surface runoff will be determined by a stochastic procedure with the SWAP model, running the model for a great number of stochastic realizations of parameter values (order of 10.000 times). The results of the stochastic analysis will reflect the sensitivity of the model to input parameters variability. The obtained information will contribute with a better understanding of the impact of hydraulic parameters variability on water balance components estimated by hydrological models. (AU)