Why should space-time variability of rainfall be considered in precision agriculture for soybean in Piracicaba, São Paulo state?

Autor(es)

dos Santos, Thais Leticia ; Battisti, Rafael ; Reichardt, Klaus ; Goncalves, Ivo Zution ; do Amaral, Victor Proenca ; Pilau, Felipe Gustavo

• Tipo de documento: Artigo Científico
• Fonte: CIENTIA AGRICOL; v. 82, p. 11-pg., 2025-01-01.

Resumo

Brazil ranks among the world's largest soybean producers; however, significant gaps in crop yield still exist, primarily linked to weather conditions. This study quantifies rainfall spatial variability using two dense networks of rain gauges and examines the impact of this variability on soybean crops' attainable productivity. The study was carried out in Piracicaba, S & atilde;o Paulo state, Brazil. The first rain gauge network measuring campaign was conducted from 1993 to 1994, featuring ten gauges distributed in 1000 ha. The second rain gauge network was active from 2016 to 2018, comprising nine gauges covering 36 ha. A multi-model simulation was employed to assess the effect of rainfall spatial variability on soybean yield. The relative yield loss ({g) due to water deficiency was simulated for three different sowing dates and across each rainfall sampling point. The findings indicate that the rainfall spatial variability directly influences attainable productivity. The extent of rainfall variability does not translate directly into yield outcomes; however, temporal variability associated with different sowing times significantly impacts soybean yield. (AU)

• Processo FAPESP: 15/14497-0 - Previsão imediata de tempestades intensas e entendimento dos processos físicos no interior das nuvens: o SOS-CHUVA (Sistema de Observação e Previsão de Tempo Severo)
• Beneficiário: Luiz Augusto Toledo Machado
• Modalidade de apoio: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - Temático