Drought is a complex natural hazard that has been recurrently occurred in many regions across the globe. Therefore, precise drought characterization and its regional monitoring are key challenges for advanced water management and hydrological research. In this research, we provided a novel method to improve annual average time series data for the Standardized Drought Index (SDI)-type drought monitoring tools. We proposed multi-auxiliary information-based estimation strategy that improves annual moving average/total precipitation time series records. Therefore, we incorporated a minimum and maximum temperature as auxiliary variables under multi-auxiliary regression estimator. In summary, this study propagates a new drought index named: the Precision-Weighted Standardized Precipitation Index (PWSDI). We evaluated the performance of PWSDI for 10 meteorological stations in Pakistan. We found that improved estimates of temporal precipitation time series are good candidates for modelling and monitoring hydrological drought at the regional settings under SDI procedure.