Banca de QUALIFICAÇÃO: GABRIELA DA ROCHA SALDANHA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : GABRIELA DA ROCHA SALDANHA
DATE: 18/09/2025
TIME: 09:30
LOCAL: VIDEOCONFERÊNCIA
TITLE:

Digital Mapping of Soil Attributes and Classes in the Alto Taquari River Basin based on Legacy Data and Prediction Models

KEY WORDS:

Digital Mapping, Attributes, Soil.

PAGES: 40
BIG AREA: Ciências Agrárias
AREA: Agronomia
SUMMARY:

The Taquari River (MT/MS) is one of the main drainage channels of the Pantanal region into the Paraguay River. However, since 1970, the lower course of the river has been suffering from siltation processes due to the intensification of production systems in the upper part of the basin. This environmental imbalance has reverberated the occupation and increased production in the area belonging to the Upper Taquari Hydrographic Basin (BHAT), which occurred without paying attention to the geomorphological peculiarities of the region, disregarding the environmental and socioeconomic consequences that could occur, such as the permanent flooding of several areas (Galdino; Vieira; Pellegrin, 2005). Work carried out by Risso et al. (1997) for the Upper Paraguay Basin Conservation Plan (PCBAP) and by Galdino et al. (2004) estimated losses of 315.6 t ha-1 year-1 and 555.6 t ha-1 year-1, respectively, indicating an increase in erosion potential over the years, reflecting that soil limitations continued to be continually neglected, even with considerable losses. In this context, given the neglect of the soils of the Taquari River Basin plateau, the use of tools that provide information to guide the management of these areas is of great value, given that a large volume of soil is being lost, increasing river siltation and reducing the potential of the ecosystem services they provide. The hypothesis is that through the use of technologies focused on digital soil mapping (DSM), it is possible to obtain quantitative cartographic products to represent strategic soil classes and attributes, which can aid decision-making related to the use and management of soils in the BHAT. The study aims to identify the spatial distribution of attributes (sand, clay, and organic carbon) and soil classes using machine learning models. Based on this information, the goal is to propose management zones aimed at the sustainable use of natural resources and to assess soil susceptibility to erosion in the basin.

COMMITTEE MEMBERS:
Presidente - 2223668 - HELENA SARAIVA KOENOW PINHEIRO
Externo ao Programa - 3720511 - LEONARDO DURVAL DUARTE GUIMARAES - nullInterno - 1060711 - MARCOS GERVASIO PEREIRA
Externo à Instituição - SÍLVIO BARGE BHERING - EMBRAPA