Using Particle Tracking to Understand Flow Paths, Age Distributions, and the Paradoxical Origins of the Inverse Storage Effect in an Experimental Catchment. Issue 4 (22nd April 2020)

• Record Type: Journal Article
• Authors: Wilusz, D. C.; Harman, C. J.; Ball, W. P.; Maxwell, R. M.; Buda, A. R.
• Is Part Of: Water resources research. Volume 56:Issue 4(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-22
• Subjects: integrated hydrology model -- transit time model -- runoff generation mechanisms -- particle tracking -- storage selection functions; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2019WR025140
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Many catchment studies use estimates of stream age distributions, including transit time distributions and StorAge Selection (SAS) functions, to make inferences about hydrologic processes and dominant flow paths. To improve the basis for such inferences, this study examined how different hydrologic flow paths contribute to the age distribution of discharge and evapotranspiration (ET) at the U.S. Department of Agriculture's Mahantango Creek experimental catchment in PA, USA, using the integrated surface‐subsurface hydrology model Parallel Flow‐Common Land Model with SLIM‐FAST particle tracking. The model tracked ET and five flow paths: direct runoff, overland flow, interflow, and shallow and deep groundwater. Over a 1‐year simulation, we found that individual flow paths release generally older age‐rank storage under wetting conditions (a direct storage effect). Paradoxically, total discharge originated from younger age‐rank storage under wetting conditions (an inverse storage effect). This inverse storage effect was caused by the disproportionate increase in contributions from younger flow paths, particularly overland flow. This result suggests that where direct storage effects have been observed for individual sources of discharge (such as shallow groundwater), the same may not necessarily hold for total discharge and could in fact be reversed. Other findings include (1) a highly nonunique mapping between water age and flow path, (2) a "middle‐aged depression" in stream ages that cannot be fit by unimodal distributions (e.g., gamma and beta), (3) a taxonomy of transit time distribution shapes that occur during a typical storm, and (4) relatively young ET age distributions with a time‐invariant SAS function shape that reflects the parameterized depth distribution of root‐water uptake. Plain Language Summary: How does rainfall and the pollution it carries get into streams? How much travels overland, through soils, or deep underground? Hydrologists have used a variety of methods to understand the flow pathways of water, including studies of the age of the water, which is defined as the amount of time that has passed since water in the environment fell as rain. In this study, we use site measurements and a detailed computer model in a well‐studied farmland to simulate the movement and ages of water along five different flow paths that feed into a stream. To make our results more relevant to other research, we describe water ages in the stream relative to water ages in the ground. As has been found in other locations, we find that stream water tends to become younger after heavy rain. One might therefore expect that flow paths feeding the stream would also become younger after heavy rain. In fact, they generally become older. This apparent contradiction is explained by the fact that one of the youngest flow paths, overland flow, not only gets older under wet conditions but also gets larger and drives down the average age of the entire stream. Key Points: Integrated watershed model tracked flux and age of seven hydrologic flow paths contributing to Q and E T Flow paths have overlapping ages, which confounds mechanistic interpretation of transit times Inverse storage effect caused by shifting proportion—not shifting age—of each flow path