Can storage-discharge characteristics of karst matrix system quantified through recession analysis be reliable?

Abstract

Storage and subsequent release of water in matrix system is a key function of karst catchments that controlling baseflow variation. Hydrograph recession analysis is currently the economic way to assess storage-discharge characteristics broadly at the catchment scale. However, there is large uncertainty in the related quantification due to recession data extraction. This study, by combining recursive digital filters with different automatic extraction methods, slow flow recession segments were extracted for hydrograph recession analysis and the further dynamic matrix storage (DMS) and related recession time (RT) assessment. The diversity and consistence among DMS and RT derived from different recession extraction methods (REMs) were analyzed, using hydrometric data in 20 catchments in the Wujiang river Basin in southwest China. Results indicate that the estimates of DMS and RT remarkedly varied between different REMs, however the order in which they ranked was mostly consistent. Moreover, the relationships between the derived DMS and RT with catchment physical features that potentially control storage and release processes are mostly consistent. Larger DMS are strongly associated with catchments featured as lower soil saturated hydraulic conductivity and smoother hydrographs. Longer RT are mostly related with drier catchments characterized as less variation of elevation and lower soil saturated hydraulic conductivity. This study highlights not only the uncertainty in quantifying storage and accompanied release characteristics, but also the reliability of storage-discharge characteristics quantified through recession analysis in terms of catchment comparison. Considering the diversity among catchments, ensemble of multi-method estimates of DMS and RT can enhance our understanding of the storage-discharge processes in the karst matrix system.