Recent environmental changes have significantly impacted rice cultivation in Ben Tre province, the Vietnamese Mekong Delta (VMD) coastal province. This research employed the Mann-Kendall (MK) non-parametric method and Sen’s slope (SS) technique to detect trends in the rice yield of the winter-spring crop (WSC) in Ben Tre province and environmental parameters from 2009 to 2020. These environmental parameters include the meteorological drought index and key water resource metrics, potentially affecting the region’s rice yield. Furthermore, it established the relationship between these environmental parameters and rice yield using multiple linear regression. The results indicated an average decrease of 0.13 ton/ha/year in the WSC’s rice yield, with a severe reduction to 2.86 ton/ha in 2016. This decline in rice yield is likely attributed to environmental shifts, particularly during years with extreme hydrological events. The study found that during the months of dry season, from January to April, there was a decrease of 0.14 per year in the minimum Standardized Precipitation Evapotranspiration Index (SPEI-4min) at the Ben Tre meteorological station; an increase in the minimum daily discharge at the Tan Chau station (QTCmin) by 81 m3/s/year; a decrease in the mean daily water level at the My Thuan station (QMTmean) by 0.22 cm/year; and an increase in the maximum daily water level at the Ben Trai station (HBTmax) by 0.67 cm/year. However, the maximum daily salinity concentration at the Tra Vinh station (STVmax) showed no significant trend, oscillating between 6.5 and 15 g/l, potentially because the three-hourly monitoring intervals might not have fully captured peak salinity levels. The regression model identified SPEI-4min (with a Correlation Index (CI) of 0.450) and STVmax (CI = 0.372) as the primary factors influencing rice yield. Additionally, QTCmin and HBTmax were also significant, though to a lesser extent, with correlation indices of 0.310 and 0.303, respectively. Conversely, QMTmean had a relatively minor influence, with a correlation index of 0.136. These findings are crucial to developing adaptive strategies and policies for improving the resilience of rice production in the study province and throughout the VMD.