Environmental Modelling and Software, April, 2014, Vol.54, p.39(14)
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.envsoft.2013.12.011 Byline: Li Li, Holger R. Maier, Daniel Partington, Martin F. Lambert, Craig T. Simmons Abstract: Recursive digital filters (RDFs) are one of the most commonly used methods of baseflow separation. However, how accurately they estimate baseflow and how to select appropriate values of filter parameters is generally unknown. In this paper, the output of fully integrated surface water/groundwater (SW/GW) models is used to obtain optimal parameters for, and assess the accuracy of, three commonly used RDFs under a range of physical catchment characteristics and hydrological inputs. The results indicate that the Lyne and Hollick (LH) filter performs better than the Boughton and Eckhardt filters, over a larger range of conditions. In addition, the optimal values of the filter parameters vary considerably for all three filters, depending on catchment characteristics and hydrological inputs. The dataset of the 66 catchment characteristics and hydrological inputs, as well as the corresponding simulated total streamflow and baseflow hydrographs obtained using the SW/GW model, can be downloaded as Supplementary material. Author Affiliation: (a) School of Civil, Environmental and Mining Engineering, The University of Adelaide, Adelaide 5005, South Australia, Australia (b) National Centre for Groundwater Research and Training and School of the Environment, Flinders University, GPO Box 2100, Adelaide 5001, South Australia, Australia Article History: Received 14 August 2013; Revised 17 December 2013; Accepted 18 December 2013
Employee Performance Appraisals -- Analysis ; Hydrology -- Analysis ; Streamflow -- Analysis
Cengage Learning, Inc.