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The identification of haplotypes influencing traits of agronomic interest, with well-defined effects across environments, is of key importance to develop varieties adapted to their context of use. It requires advanced crossing schemes, multi-environment characterization and relevant statistical tools. Here we present a sorghum multi-reference back-cross nested association mapping (BCNAM) population composed of 3901 lines produced by crossing 24 diverse parents to three elite parents from West and Central Africa (WCA-BCNAM). The population was characterized in environments contrasting for photoperiod, rainfall, temperature, and soil fertility. To analyse this multi-parental and multi-environment design, we developed a new methodology for QTL detection and parental effect estimation. In addition, envirotyping data were mobilized to determine the influence of specific environmental covariables on the genetic effects, which allowed spatial projections of the QTL effects. We mobilized this strategy to analyse the genetic architecture of flowering time and plant height, which represent key adaptation mechanisms in environments like West Africa. Our results allowed a better characterisation of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod sensitive and candidate gene Elf3 being insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the WCA-BCNAM constitutes a key genetic resource to feed breeding programs in relevant elite parental lines and develop climate-smart varieties.