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Sensitivity analysis and uncertainty in hydrosedimentological models : contribution to modeling of watershed

Grant number: 13/13885-0
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): October 01, 2013
Effective date (End): June 30, 2016
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Physical Geography
Principal Investigator:SERGIO DOS ANJOS FERREIRA PINTO
Grantee:Luiz Henrique Pereira
Home Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

Attenuate uncertainties in the results of dynamic models that estimate the sediment yield and transport in the river becomes fundamental when considering the urgency of territorials policies to minimize the risk of under-or over-exploitation of natural resources as well as indicate the water availability in watersheds. The application of simulation models of environmental processes has been widely favored by the advance of geotechnologies, in particular Geographic Information Systems, which enable the extraction, processing, analysis and integration of geospatial data. However, it is noted that little attention has been given to the analysis and evaluation of the factors responsible for the discrepancy between estimates and observations, that can be realised when the applying the model is preceded by the uncertainty analysis and sensitivity of the components terms, the so that the data obtainment and calibration of parameters are consistent with the observed reality. Considering the above, this research proposal aims to evaluate the performance of models of loss soil and water (USLE, MUSLE, RUSLE, WEEP and SWAT), and analyze the variation of sensitivity and uncertainty generated by the data of the parameters involved, considering the application of different methods for obtaining at the same variable. The activities will be developed with the theoretical scope of the modeling of environmental systems, and based on GIS techniques and remote sensing. It is expected that the results obtained suggest the most appropriate set of methods for extraction of data geomorphological, hydrological and pedological for each model, according with scale adopted for mapping and the physical characteristics dominant of the scenario in analysis. (AU)