A new approach to use of wavelet transform for baseflow separation of Karst springs (case study: Gamasiyab spring)

Abstract Today, groundwater is the essential resource whole water sector demands. The spring baseflow discharge analysis can significantly help us better manage resources. This study was focused on separation of Gamasiyab karstic (western Iran) using wavelet transform (WT). recursive digital filter (RDF) method with different algorithms has been used to compare approach performance. Forty-nine years (1968–2018) recorded springs’ daily data were for this aim. isotopic content (IC) determine best RDF algorithm and WT separation. IC monthly samples taken in 2017–2018 measured. results showed that had adjusted coefficient determination ( $$R_{{{\text{adjusted}}}}^{2}$$ R adjusted 2 ) 0.95 root mean square error (RMSE) 0.552 (m 3 /s) compared index method. related Eckhardt 0.97 RMSE 0.670 /s), which performance Results most samples, values separated by are closer values. Also, based criterion, a lower than known as study. accurately could split rivers.