Reservoirs regulate hydrologic and land-atmospheric regimes across scales. Through impounding water on the land-surface, reservoirs perturb streamflow magnitude and timing, and change water and energy exchanges between land and atmosphere. Due to the extent and severity of these effects, there is a need for representing reservoir in Land Surface Models (LSMs) so that the effects of reservoir on water and energy fluxes and the resulting impacts on local and regional climate can be quantified. Till now, few algorithms are proposed to represent the impacts of reservoirs on streamflow. These algorithms often have simple prognostic structures that are identified with a global parametric set. These global parameterizations, however, can have large errors at the catchment scale and/or regionally, which hinder their applications for local and regional impact assessments. Here we aim at improving the regional representation of reservoirs through reparametrizing a global reservoir algorithm across a range of reservoirs in the world including 20 reservoirs in western Canada. We evaluate reparametrized models in terms of accuracy, quantified as well as parametric identifiability and trade-off between representations of discharge and storage. To validate our findings, we further intercompare the reparametrized model with an algorithm developed by Yassin et al. (2019) and applied in western Canada too. We also report the value of calibration information, and quantify identifiability and trade-offs between describing reservoir storage and discharge. Our finding provides new insights for representing reservoirs in LSMs and can contribute into improved hydrology and land-surface modeling capability at local and regional scales.