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Despite the importance of mountainous catchments for providing freshwater resources, especially in semi‐arid regions, little is known about key hydrological processes such as mountain block recharge (MBR). Here we implement a data‐based method informed by isotopic data to quantify MBR rates using recession flow analysis. We applied our hybrid method in a semi‐arid sky island catchment in southern Arizona, United States. Sabino Creek is a 91 km 2 catchment with its sources near the summit of the Santa Catalina Mountains northeast of Tucson. Southern Arizona's climate has two distinct wet seasons separated by prolonged dry periods. Winter frontal storms (November–March) provide about 50% of annual precipitation, and summers are dominated by monsoon convective storms from July to September. Isotope analyses of springs and surface water in the Sabino Creek catchment indicate that streamflow during dry periods is derived from groundwater storage in fractured bedrock. Storage‐discharge relationships are derived from recession flow analysis to estimate changes in storage during wet periods. To provide reliable estimates, several corrections and improvements to classic base flow recession analysis are considered. These corrections and improvements include adaptive time stepping, data binning, and the choice of storage‐discharge functions. Our analysis shows that (1) incorporating adaptive time steps to correct for streamflow measurement errors improves the coefficient of determination, (2) the quantile method is best for streamflow data binning, (3) the choice of the regression model is critical when the stage‐discharge function is used to predict changes in bedrock storage beyond the maximum observed flow in the catchment, and (4) the use of daily or night‐time hourly streamflow does not affect the form of the storage‐discharge relationship but will impact MBR estimates because of differences in the observed range of streamflow in each series.
Ajami et al. (Fri,) studied this question.