daily baseflow separation using recursive digital filters (case study of anzali’s wetland)

Baseflow separation (bfs) from streamflow is necessary for hydrological modeling of direct runoff, ground-surface water contribution, and water supply reliability, especially during a dry period. recursive digital filters are automated and easy-to-use bfs techniques developed during three recent decades. in this study, three prevailing recursive digital filters including chapman, chapman & maxwell, and boughton methods are performed in nine rivers located in anzali’s wetland watershed, in northern iran. the long-term daily streamflow dataset (1987-2017) in the hydrometric stations ends to the wetland is considered for analysis. results indicated that the baseflow plays a crucial role in the nine studied rivers to feed the anzali’s wetland (on average 41% to 49% of the streamflow). the chapman and maxwell method overestimates the bf in comparison to the other methods. the findings of this study yield insight into the functionality of the adopted digital filters in bfs and can help scientists easily access or enhance their functionality and evaluate the meaningfulness of the incorporated parameters concerning the base flow estimation