Transit time distributions and StorAge Selection functions in a sloping soil lysimeter with time‐varying flow paths: Direct observation of internal and external transport variability

• Published in: Water resources research 2016-09, Vol.52 (9), p.7105-7129
• Main Authors: Kim, Minseok, Pangle, Luke A., Cardoso, Charléne, Lora, Marco, Volkmann, Till H. M., Wang, Yadi, Harman, Ciaran J., Troch, Peter A.
• Format: Article
• Language: English
• Subjects: Aeration zone; Data interpretation; Decomposition; Dynamical systems; Dynamics; experiment; Flow paths; Flow rates; Flow velocity; Groundwater table; hillslope; History; Hydrologic systems; Hydrology; Mathematical models; Modelling; Partitioning; Rain; Rainfall; Soil; Soils; solute transport; Storage; storage selection functions; Temporal variability; Temporal variations; Tests; Theories; Tracers; Transit time; Transport; Travel time; Variability; Water; Water table
• ISSN: 0043-1397; 1944-7973
• DOI: 10.1002/2016WR018620

Transit times through hydrologic systems vary in time, but the nature of that variability is not well understood. Transit times variability was investigated in a 1 m3 sloping lysimeter, representing a simplified model of a hillslope receiving periodic rainfall events for 28 days. Tracer tests were conducted using an experimental protocol that allows time‐variable transit time distributions (TTDs) to be calculated from data. Observed TTDs varied with the storage state of the system, and the history of inflows and outflows. We propose that the observed time variability of the TTDs can be decomposed into two parts: “internal” variability associated with changes in the arrangement of, and partitioning between, flow pathways; and “external” variability driven by fluctuations in the flow rate along all flow pathways. These concepts can be defined quantitatively in terms of rank StorAge Selection (rSAS) functions, which is a theory describing lumped transport dynamics. Internal variability is associated with temporal variability in the rSAS function, while external is not. The rSAS function variability was characterized by an “inverse storage effect,” whereby younger water is released in greater proportion under wetter conditions than drier. We hypothesize that this effect is caused by the rapid mobilization of water in the unsaturated zone by the rising water table. Common approximations used to model transport dynamics that neglect internal variability were unable to reproduce the observed breakthrough curves accurately. This suggests that internal variability can play an important role in hydrologic transport dynamics, with implications for field data interpretation and modeling. Key Points: Observations of tracer transport in a 1 m3 sloping lysimeter with a fluctuating water were used to investigate lumped transport modeling Time variability of transit times was decomposed into two components: internal (flow pathways) and external (total flow) variability Internal variability arising from the fluctuating water table can be captured by rank StorAge Selection functions