For the benefit of humanity and the planet, the scientific community must promote and protect free and open science communication, ensuring that scientific insights are shared in a way that is accessible to all.

Open Collaboration Hydrology (OCH) is an online community and platform devoted to promoting the use and development of open and collaborative water science and management tools. As part of the Voices for Science AGU program, this presentation shares OCH's story, approach, and communication channels. Moreover, this presentation will share the profound impact of open and collaborative approaches on expanding the boundaries of water systems knowledge and its management. Open Collaboration Hydrology embraces participatory/collaborative modelling principles, open science, and the Free Open Source Software standards (FOSS) to facilitate the convergence of diverse perspectives, understandings, and beliefs about water systems. This presentation also aims to inspire attendees by showcasing the transformative potential of Open Collaboration in hydrology and inviting them to engage in making water science resources equitable, accessible, and inclusive for everyone.

Using data from five long-term field sites measuring soil moisture, we show the limitations of using soil moisture observations alone to constrain modelled hydrological fluxes. We test a land surface model, MESH/CLASS, with two configurations: one where the soil hydraulic properties are determined using a pedotransfer function (the texture-based calibration) and one where they are assigned directly (the hydraulic properties-based calibration). The hydraulic properties-based calibration outperforms the texture-based calibration in terms of reproducing changes in soil moisture storage within a 1.6 m deep profile at each site, but both perform reasonably well, especially in the summer months. When the models are constrained using observations of changes in soil moisture, the predicted hydrological fluxes are subject to very large uncertainties associated with equifinality. The uncertainty is larger for the hydraulic properties-based calibration, even though the performance was better. We argue that since the pedotransfer functions constrain the model parameters in the texture-based calibrations in an unrealistic way, the texture-based calibration underestimates the uncertainty in the fluxes. We recommend that reproducing observed cumulative changes in soil moisture storage should be considered a necessary but insufficient criterion of model success. Additional sources of information are needed to reduce uncertainties, and these could include improved estimation of the soil hydraulic properties and direct observations of fluxes, particularly evapotranspiration.