Hydrograph separation through multi objective optimization: Revealing the importance of a temporally and spatially constrained baseflow solute source

Abstract Quantifying baseflow is key to a reliable understanding of water quality, supply and habitat. This is especially valid for watersheds in California, USA, where changing precipitation, evapotranspiration and snowmelt patterns coupled with a land use/land cover transition towards urban/agricultural dominance imply drastic impacts on baseflow. This study presents a new approach to stream hydrograph separation using multi objective optimization. Applying the Mixed Integer Distributed Ant Colony Optimization (MIDACO) solver, baseflow is modeled at two stream sites in California by linking daily baseflow and surface runoff simulations from a recursive digital filter (RDF) with those obtained from chemical, i.e., specific conductance (SC), mass balance. Objective functions are based on (1) a modified Nash Sutcliffe Efficiency (mNSE) index that gages how well the model can reproduce measured stream SC, and (2) a mass balance indicator that limits the occurrences of stream SC exceeding the modeled baselow SC end member. Baseflow SC time series are derived from interpolation of stream SC on consecutive baseflow days predicted by the RDF in the optimization. The associated RDF parameter k, RDF pass number (1 – 5) and surface runoff SC end member are set as adjustable parameters determined via calibration. Optimum (i.e., trade off) solutions indicate good to very good model performance in terms of mNSE statistics despite the competing nature of applied objective functions. Results furthermore indicate a high sensitivity towards (1) site location, with best results for the more remote “upstream” site, and (2) RDF pass number, with best results obtained by the 2 and 3 pass applications. Significant correlations between baseflow and baseflow SC and annual drought indices reveal an immediate response of the system to precipitation deficit that should be considered carefully in future water resource projections.