Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

<p>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 distance...

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Autores principales:	E. Lee, S. Kim
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/228250bd9a774149bbc774b95ac6f523
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spelling	oai:doaj.org-article:228250bd9a774149bbc774b95ac6f5232021-11-08T11:09:52ZCharacterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map10.5194/hess-25-5733-20211027-56061607-7938https://doaj.org/article/228250bd9a774149bbc774b95ac6f5232021-11-01T00:00:00Zhttps://hess.copernicus.org/articles/25/5733/2021/hess-25-5733-2021.pdfhttps://doaj.org/toc/1027-5606https://doaj.org/toc/1607-7938<p>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 (at 10 locations with three different depths) for 356 rainfall events on a steep, forested hillslope between 2007 and 2016. The soil moisture features for hydrologic events can be effectively represented by the antecedent soil moisture, soil moisture difference index, and standard deviation of the peak-to-peak time between rainfall and soil moisture response. Five clusters were delineated for hydrologically meaningful event classifications in the SOM representation. The two-dimensional spatial weighting patterns in the SOM provided more insights into the relationships between rainfall characteristics, antecedent wetness, and soil moisture response at different locations and depths. The distinction of the classified events could be explained by several rainfall features and antecedent soil moisture conditions that resulted in different patterns attributable to combinations of hillslope hydrological processes, vertical flow, and lateral flow along either surface or subsurface boundaries for the upslope and downslope areas.</p>E. LeeS. KimCopernicus PublicationsarticleTechnologyTEnvironmental technology. Sanitary engineeringTD1-1066Geography. Anthropology. RecreationGEnvironmental sciencesGE1-350ENHydrology and Earth System Sciences, Vol 25, Pp 5733-5748 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350
spellingShingle	Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 E. Lee S. Kim Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
description	<p>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 (at 10 locations with three different depths) for 356 rainfall events on a steep, forested hillslope between 2007 and 2016. The soil moisture features for hydrologic events can be effectively represented by the antecedent soil moisture, soil moisture difference index, and standard deviation of the peak-to-peak time between rainfall and soil moisture response. Five clusters were delineated for hydrologically meaningful event classifications in the SOM representation. The two-dimensional spatial weighting patterns in the SOM provided more insights into the relationships between rainfall characteristics, antecedent wetness, and soil moisture response at different locations and depths. The distinction of the classified events could be explained by several rainfall features and antecedent soil moisture conditions that resulted in different patterns attributable to combinations of hillslope hydrological processes, vertical flow, and lateral flow along either surface or subsurface boundaries for the upslope and downslope areas.</p>
format	article
author	E. Lee S. Kim
author_facet	E. Lee S. Kim
author_sort	E. Lee
title	Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
title_short	Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
title_full	Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
title_fullStr	Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
title_full_unstemmed	Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
title_sort	characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/228250bd9a774149bbc774b95ac6f523
work_keys_str_mv	AT elee characterizationofsoilmoistureresponsepatternsandhillslopehydrologicalprocessesthroughaselforganizingmap AT skim characterizationofsoilmoistureresponsepatternsandhillslopehydrologicalprocessesthroughaselforganizingmap
_version_	1718442313179463680

Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

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