Transpiration and subsurface controls of streamflow recession characteristics

Abstract

In headwater catchments, streamflow recedes between periods of rainfall at a predictable rate generally defined by a power–law relationship relating streamflow decay to streamflow. Research over the last four decades has applied this relationship to predictions of water resource availability as well as estimations of basin‐wide physiographic characteristics and ecohydrologic conditions. However, the interaction of biophysical processes giving rise to the form of these power–law relationships remains poorly understood, and recent investigations into the variability of streamflow recession characteristics between discrete events have alternatively suggested evapotranspiration, water table elevation, and stream network contraction as dominant factors, without consensus. To assess potential temporal variability and interactions in the mechanism(s) driving streamflow recession, we combine long‐term observational data from a headwater stream in the southern Appalachian Mountains with state and flux conditions from a process‐based ecohydrologic model. Streamflow recession characteristics are nonunique and vary systematically with seasonal fluctuations in both rates of transpiration and watershed wetness conditions, such that transpiration dominates recession signals in the early growing season and diminishes in effect as the water table elevation progressively drops below and decouples with the root zone with topographic position. As a result of this decoupling, there exists a seasonal hysteretic relationship between streamflow decay and both evapotranspiration and watershed wetness conditions. Results indicate that for portions of the year, forest transpiration may actively compete with subsurface drainage for the same water resource that supplies streamflow, though for extended time periods, these processes exploit distinct water stores. Our analysis raises concerns about the efficacy of assessing humid headwater systems using traditional recession analysis, with recession curve parameters treated as static features of the watershed, and we provide novel alternatives for evaluating interacting biological and geophysical drivers of streamflow recession.

An Empirical Reevaluation of Streamflow Recession Analysis at the Continental Scale

“…Shaw and Riha () proposed that the point clouds of several glacially impacted watersheds in New York were composed of a series of relatively steep individual recession events that were shifted up/left (higher −d Q /d t for value of Q ) as rates of evapotranspiration increased. In a humid headwater catchment with high transmissivity soils at Coweeta, North Carolina, Tashie et al () further developed this model, noting seasonal hysteretic loops in the relationship between the recession characteristics of individual events and both rates of evapotranspiration and water table elevation, indicating a seasonal switching between dominant controls on recession behavior. They proposed that b is variable and governed by the relative contribution of shallow unsaturated zone storage and deep saturated zone storage, and that a values are governed by rates of evapotranspiration for part of the year and storage conditions for the remainder of the year.…”

“…For observed recession events in natural watersheds, however, evidence of concavity is absent in the literature. On the contrary, the convexity of individual recession events has been noted in several studies, in direct contradiction of hydraulic aquifer theory illustrated in Figure , though this discrepancy has not been thoroughly investigated (Ghosh et al, ; Shaw & Riha, ; Tashie et al, ; McMillan et al, ).…”

“…Previous studies have noted that convexity of the recession curve indicates recession behavior in violation of the Boussinesq assumptions, due to the existence of multiple reservoirs , ongoing groundwater recharge (Li et al, 2017), transition from active drainage network contraction to q decay as the primary mechanism of decreasing −dQ/dt (Ghosh et al, 2016), deep subsurface groundwater Figure 11. The percent of convex recession events of each watershed organized according to hydrologic landscape regions (HLRs): (1) subhumid plains with permeable soils and bedrock, (2) humid plains with permeable soils and bedrock, (3) subhumid plains with impermeable soils and permeable bedrock, (4) humid plains with permeable soils and bedrock, (Wang & Cai, 2010), or substantial unsaturated zone contribution to streamflow (Tashie et al, 2019). Our results indicate that for the overwhelming majority of watersheds in the continental United States, observed recession curves are not only more nonlinear than previously indicated, but that their nonlinearity also tends to increase with length of recession.…”

Spatial and Temporal Patterns in Baseflow Recession in the Continental United States

“…To accommodate this variability, researchers have developed a new paradigm in which a is not a static metric that integrates the hydraulic properties of a representative Boussinesq hillslope aquifer (i.e., Brutsaert & Nieber, 1977), but instead is a variable indicator of watershed state and flux conditions. For example, when a and b are effectively decorrelated, an increase in the relative value of a between events indicates a relative decay in the stability of streamflow, though it is still debated whether this decay is due to direct competition between transpiration and streamflow for water resources, a decline in the water table, a contraction of the stream network, or some seasonally transient combination of factors (Biswal & Kumar, 2014;Biswal & Marani, 2014;Li et al, 2017;Patnaik et al, 2015;Sánchez-Murillo et al, 2015;Tashie et al, 2019). The nonlinearity of recession also varies among individual events (e.g., Jachens et al, 2019;Mutzner et al, 2013, Sánchez-Murillo et al, 2015, often according to a distinct seasonal pattern (Karlsen et al, 2019;Tashie et al, 2019) governed by mechanisms that are not yet agreed upon.…”

“…Previous studies have investigated the effects of geomorphologic, soil hydraulic, and climatologic properties on basin-average recession characteristic values at the regional scale (Mutzner et al, 2013;Patnaik et al, 2015Patnaik et al, , 2018Sánchez-Murillo et al, 2015;Tashie et al, 2020;Ye et al, 2014) and of temporally variable drivers like ET, PPT, soil moisture, or groundwater at the local scale (Karlsen et al, 2019;Shaw & Riha, 2012;Tashie et al, 2019). However, potential regional patterns and trends in the seasonal dynamics of recession characteristics (and their physical drivers) remain poorly understood.…”