HGS RESEARCH HIGHLIGHT – Evaluation of baseflow separation methods with real and synthetic streamflow data from a watershed
Cheng, S., Tong, X., & Illman, W. A. (2022). Evaluation of baseflow separation methods with real and synthetic streamflow data from a watershed. In Journal of Hydrology (p. 128279). Elsevier BV. https://doi.org/10.1016/j.jhydrol.2022.128279
Figure 1: Components of the HydroGeoSphere (HGS) model constructed for the ACW by Tong et al. (2021) and utilized to generate synthetic streamflow and baseflow hydrographs, comprising of four components: land cover, 3D mesh, soil type, and geological model.
A new article by our friends at the University of Waterloo provides yet another example of using HydroGeoSphere in conjunction with other hydrologic evaluation/modelling methods. In this case the authors have used a fully integrated HydroGeoSphere model of the Alder Creek Watershed as the surest method of quantifying baseflow at 10 locations along Alder Creek. The Alder Creek Watershed is a sub-catchment of the Grand River Watershed which happens to be in Aquanty’s own backyard here in Southern ON (see Figure 1)!
Baseflow represents the portion of sustained streamflow which occurs between precipitation events, or in other words is not attributed directly to overland runoff. The baseflow contribution to streamflow can be largely associated with groundwater flow into streams, but in general consists of any form of delayed flow into streams, including flows routed through surface water features such as wetlands and lakes. As the authors note, baseflow is critical in many aquatic systems as it maintains a minimum level of flow during dry periods.
Given the varied sources contributing to baseflow, the spatial variability in baseflow, and the logistical difficulties in making physical baseflow measurements (especially the groundwater contributions in large rivers), baseflow is inherently difficult to accurately estimate.
Fortunately, due to the fully integrated nature of HydroGeoSphere and the fact that HGS was created with a strong emphasis on physics (and minimal use of empirical equations), HydroGeoSphere represents a very powerful tool for baseflow estimation, especially in lightly studies watersheds!
In this study, the synthetic baseflow estimates produced by HydroGeoSphere (Figure 2) for the Alder Creek Watershed are compared against four graphical baseflow separation techniques and six digital baseflow separation techniques to determine the most optimal approaches in different reaches of the creek. Results of the study indicate that the ‘best’ baseflow separation technique varies spatially and temporally through the Alder Creek Watershed, but in general the FUKIH approach may have been ‘best’ at the majority of sites.
Figure 2: Comparison between actual and synthetic streamflow from HGS for the ACW from May 1, 2013 to April 30, 2016.
Abstract:
Baseflow originating primarily from groundwater is a critical streamflow component, although its accurate estimation is fraught with significant difficulties. This study estimates baseflow through existing graphical and digital filter methods, using actual streamflow data from a gauging station at the Alder Creek Watershed (ACW) and synthetic streamflow data at ten study locations within the same watershed simulated with HydroGeoSphere (HGS) (Aquanty Inc., 2018). There are four widely used graphical (Institute for Hydrology, 1980; Sloto and Crouse, 1996, Aksoy et al., 2008) and six digital filtering (Lyne and Hollick, 1979, Chapman and Maxwell, 1996, Furey and Gupta, 2001, Eckhardt, 2005, Tularam and Ilahee, 2008, Aksoy et al., 2009) baseflow separation approaches compared in this study. To determine the most optimal approach, baseflow estimates from real data are assessed based on the subjective concept of hydrologic plausibility, while baseflow estimates obtained from a HGS streamflow record with graphical and digital filtering methods are compared to those computed directly by HGS. Overall, results from this study indicate that baseflow hydrographs reveal a seasonal pattern at the ACW. During wintertime, streamflow is composed almost entirely of baseflow, whereas during summertime, baseflow only consists approximately 20% to 60% of streamflow. After comparing baseflow estimates with those computed by HGS, the most optimal approaches at the ten study locations are assessed. Results show that the best approach at six study locations is the FUKIH (Aksoy et al., 2009) approach, while at three locations, the Chapman and Maxwell (1996) approach and for one location, the Eckhardt (2005) approach performed the best. In conclusion, it is inferred that the most optimal approach within the ACW varies spatially.