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Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. 

Abstract Groundwater recharge moves downward from the land surface and reaches the groundwater to replenish aquifers. Despite its importance, methods to directly measure recharge remain cost and time‐intensive. Recharge is usually estimated using indirect methods, such as the widely used water‐table fluctuation (WTF) method, which is based on the premise that rises in groundwater levels are due to recharge. In the WTF method, recharge is calculated as the difference between the observed groundwater hydrograph and the hydrograph obtained in the absence of water input. The hydrograph in the absence of rise‐producing input is estimated based on a characteristic master recession curve (MRC), which describes an average behavior for a declining water‐table. Previous studies derive MRC using recession data from all seasons. We hypothesize that for sites where groundwater table is shallow, using recession data from periods with high groundwater‐influenced evapotranspiration (ET) rates versus all periods will yield significantly different MRC, and consequently different estimates of recharge. We test this hypothesis and show that groundwater recession rates are significantly greater in warm months when the groundwater‐influenced ET rates are higher. Since obtaining seasonal recession rates is challenging for locations with a limited amount of data and is prohibitive if it is to be obtained for any given season of a particular year, we propose two novel parsimonious methods to obtain recession time constants for distinct seasons. The proposed methods show the potential to significantly improve the estimates of seasonal recession time constants and provide a better understanding of seasonal variations in recharge estimates.