iSnobal is an energy and mass balance snow model that has grown over the last four decades from a simple research tool into an operational basin scale system for estimating how much energy and water are stored in our mountain snowpack. Its design has always focused on efficiency, accurate physics, and flexibility in the weather forcing data it uses. Recent updates have modernized the code, improved numerical stability, and refined how the model handles radiation and turbulent energy exchanges. Importantly, for operational adoption, the user experience has also improved through easier installation, automated setup, and standalone tools for developing forcing data from weather stations or forecast models. These upgrades allow new sensitivity studies, estimation of model uncertainty, and real-time decision support applications. Ongoing work is to incorporate next generation remote sensing data and improve how the model accounts for snow darkening from light absorbing particles and interactions between vegetation and snow. Further improvements on the horizon include leveraging machine learning methods to automate parameter selection and better connect iSnobal with hydrologic routing models. All of these advancements aim to broaden operational adoption and improve the accuracy of snowpack characterization, strengthening water resource prediction for reservoir operations, flood forecasting, drought mitigation, and seasonal allocation in snow-dominated basins throughout Idaho and the West.