A Sensitivity Analysis of Simulated Infiltration Rates to Uncertain Discretization in the Moisture Content Domain

Lulu Liu, Han Yu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

An unconditionally mass conservative hydrologic model proposed by Talbot and Ogden provides an effective and fast technique for estimating region-scale water infiltration. It discretizes soil moisture content into a proper but uncertain number of hydraulically interacting bins such that each bin represents a collection of pore sizes. To simulate rainfall-infiltration, a two-step alternating process runs until completion; and these two steps are surface water infiltration into bins and redistribution of inter-bin flow. Therefore, a nonlinear dynamical system in time is generated based on different bin front depths. In this study, using rigorous mathematical analysis first reveals that more bins can produce larger infiltration fluxes, and the overall flux variation is nonlinear with respect to the number of bins. It significantly implies that a greater variety of pore sizes produces a larger infiltration rate. An asymptotic analysis shows a finite change in infiltration rates for an infinite number of bins, which maximizes the heterogeneity of pore sizes. A corollary proves that the difference in the predicted infiltration rates using this model can be quantitatively bounded under a specific depth ratio of the deepest to the shallowest bin fronts. The theoretical results are demonstrated using numerical experiments in coarse and fine textured soils. Further studies will extend the analysis to the general selection of a suitable number of bins.
Original languageEnglish (US)
Pages (from-to)1192
JournalWater
Volume11
Issue number6
DOIs
StatePublished - Jun 7 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Funding: This research was sponsored by the Natural Science Foundation for Young Scientists of Jiangsu Province (grant no. BK20180450), the Natural Science Foundation of Nanjing University of Posts and Telecommunications NUPTSF (grant no. NY219080) and the China Postdoctoral Science Foundation (grant no. 2018T110531).

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