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Comprehensive assessments of hydrological components are crucial for enhancing operational water supply simulations. However, hydrological models are often evaluated based on their surface flow simulations, while the validation of subsurface and groundwater components tends to be overlooked or not well documented. In this study, we evaluated the outputs of two hydrological models, the Large Basin Runoff Model (LBRM) and the Weather Research and Forecasting – Hydrological modeling extension package (WRF-Hydro), for potential implementation in operational water balance forecasting in the Great Lakes region. We examined the simulated hydrological variables including surface (e.g. snow water equivalent, evapotranspiration, and streamflow), subsurface (e.g. soil moisture at different layers), and groundwater components with observed or reference data from ground-based stations and remotely sensed images. The findings of this study provide valuable insights into the capabilities and limitations of each model. These findings contribute to more informed water management strategies for the Great Lakes region. 

Abstract Biodiversity collections are experiencing a renaissance fueled by the intersection of informatics, emerging technologies, and the extended use and interpretation of specimens and archived databases. In this article, we explore the potential for transformative research in ecology integrating biodiversity collections, stable isotope analysis (SIA), and environmental informatics. Like genomic DNA, SIA provides a common currency interpreted in the context of biogeochemical principles. Integration of SIA data across collections allows for evaluation of long-term ecological change at local to continental scales. Challenges including the analysis of sparse samples, a lack of information about baseline isotopic composition, and the effects of preservation remain, but none of these challenges is insurmountable. The proposed research framework interfaces with existing databases and observatories to provide benchmarks for retrospective studies and ecological forecasting. Collections and SIA add historical context to fundamental questions in freshwater ecological research, reference points for ecosystem monitoring, and a means of quantitative assessment for ecosystem restoration.