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Unconfined aquifers are often directly impacted by high irrigation demands. Therefore, accurate recharge estimates are crucial for sustainable groundwater management. It is important over time to re-examine the existing hydrologic understanding of aquifers, taking into account developments in knowledge and changing climate conditions. The last in depth study into the Assiniboine Delta Aquifer located in Manitoba, Canada, that gave a recharge estimate was conducted in the 1980s (Render, 1988). This work re-examined the Assiniboine Delta Aquifer, employing new methods and data to estimate recharge rates. Twelve one-dimensional models were created in the software HYDRUS-1D to model the soil water fluxes in the unsaturated zone to analyze the historic recharge from 1996 to 2019. Remote weather station data, measured hydraulic conductivity, soil texture distribution, soil moisture content, and soil temperature data were used to initialize and run the models. Inverse calibration used the measured moisture contents to calibrate the models, which resulted in Root Mean Square Error in the calibration and validation periods averaging 0.034 and 0.051 m3/m3, respectively, above the 0.025 m3/m3 sensor measurement error. Rough estimates of soil texture distribution across the aquifer was determined to assist in the final recharge estimate. The historical regional recharge average was estimated to be 68 mm/year, double the previous estimate for the aquifer (Render, 1988). Modelled periods were limited to less than a year due to limitations in the general HYDRUS-1D software model code under frozen soil conditions, which the Assiniboine Delta Aquifer experiences during the winter months. Assumptions on initial soil moisture contents, snowpack heights, and model start dates were best estimated for historical years. Results show these estimates can have significant impacts on the resulting recharge. Suggested future work includes implementing the HYDRUS-1D freeze-thaw code to allow for model spin-up and multi-year simulations to enhance the reliability of model results. • Inverse calibration used known soil moisture to solve for hydraulic parameters. • Moisture content RMSE averaged 0.034 m3/m3 across all sensors in calibration year. • Weather data from 1996 to 2019 resulted in 68 mm/year recharge estimate over aquifer. • Recharge estimate is double what was previously reported for the aquifer. [ABSTRACT FROM AUTHOR]