Two genetic linkage maps, constructed by DH and RILs populations derived from the same parents, were carried out for the identification and comparison of QTLs controlling yield traits across different years in rice (Oryza sativa L.). A total of 194 SSR and STS markers were used in two maps, of which 114 markers were same. The distribution of Samgang allele was higher in RILs population than it in DH population. Comparing with DH population, RILs population has more lines with higher yield and wider phenotypic transgressive segression for yield traits. Although most of QTLs for the same trait were different in two populations across different years, 8 QTLs (including gwp11.1, spp5.1, spp10.1, spp11.2, ssr1.1, ssr11.1, tgw9.1 and tgw11.1) were detected over 2 yr. It is important to note that ppp10.1, spp10.1 and tgw9.1 were identified in two populations, while spp10.1 and tgw9.1 were simultaneity observed across different years. Epistatic effects were more important than additive effects for PPP, SPP, yield in DH population and TGW, yield in RILs population. Epistatic effects of DH and RILs populations were different on the same genetic background in the present study, which illuminated the QE interaction played an important role on epistatic effect. Identification and comparison of QTLs for yield traits in DH and RILs populations should provide various and more precise information. The QTLs identified in present study would be valuable in marker-assisted selection program for improving rice yield. Two genetic linkage maps, constructed by DH and RILs populations derived from the same parents, were carried out for the identification and comparison of QTLs controlling yield traits across different years in rice (Oryza sativa L.). A total of 194 SSR and STS markers were used in two maps, of which 114 markers were same. The distribution of Samgang allele was higher in RILs population than it in DH population. Comparing with DH population, RILs population has more lines with higher yield and wider phenotypic transgressive segression for yield traits Although most of the QTLs for the same trait were different in two populations across different years, 8 QTLs (including gwp11.1, spp5.1, spp10.1, spp11.2, ssr1.1, ssr11.1, tgw9.1 and tgw11.1) were detected over 2 yr. It is important to note that ppp10.1, spp10.1 and tgw9.1 were identified in two populations, while spp10.1 and tgw9.1 were simultaneously observed across different years. Epistatic effects were more important than additive effects for PPP, SPP, yield in DH population and TGW, yield in RILs population. Epistatic effects of DH and RILs populations were different on the same genetic background in the present study, which illuminated the QE interaction played an important role on epistatic effect. Identification and comparison of QTLs for yield traits in DH and RILs populations should provide various and more precise information. The QTLs identified in present study would be valuable in marker-assisted selection program for improving rice yield.