Preprints
https://doi.org/10.5194/hess-2021-107
https://doi.org/10.5194/hess-2021-107

  13 Apr 2021

13 Apr 2021

Review status: this preprint is currently under review for the journal HESS.

Characterization of Hillslope Hydrologic Events through a Self-Organizing Map

Eunhyung Lee and Sanghyun Kim Eunhyung Lee and Sanghyun Kim
  • Department of Environmental Engineering, College of Engineering, Pusan National University, Busan, South Korea

Abstract. Hydrologic events can be characterized as particular combinations of hydrological processes on a hillslope scale. To configure hydrological mechanisms, we analyzed a dataset using an unsupervised machine learning algorithm to cluster the hydrologic events based on the dissimilarity distances between the weighting components of a self-organizing map (SOM). The time series of soil moisture was measured at 30 points (in 10 locations with 3 varying depths) for 356 rainfall events on a steep, forested hillslope between 2007 and 2016. Soil moisture features for hydrologic events can be effectively represented by the antecedent soil moisture, maximum variation, and standard deviation of peak-to-peak time between rainfall and soil moisture response. Five clusters were delineated for hydrologically meaningful event classification in the SOM representation. The two-dimensional spatial weighting patterns in the SOM provided greater insight on relationships between rainfall characteristics, antecedent wetness, and soil moisture response at different locations and depths. The distinction of the classified events can be explained by several rainfall features and antecedent soil moisture conditions that resulted in different patterns made by combinations of hillslope hydrological processes, vertical flow, and lateral flow along either surface or subsurface boundaries for the upslope and downslope areas.

Eunhyung Lee and Sanghyun Kim

Status: open (until 08 Jun 2021)

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Eunhyung Lee and Sanghyun Kim

Eunhyung Lee and Sanghyun Kim

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Short summary
In order to understand hillslope hydrological processes during rainfall runoff event, rainfall characteristics and responses of soil moisture at the hillslope scale were explored by applying self-organizing map(SOM) to a dataset. Combinations of upslope and downslope spatial patterns of hillslope hydrological processes, vertical flow, and lateral flow along surface or subsurface boundaries were responsible for the distinctions between the event clusters.