HR: 0800h
AN: H51C-0650    [Abstracts]
TI: Soil Moisture Time Series Analysis for a Hillslope located Gwangneung National Arboretum
AU: * Kim, S
EM: kimsangh@pusan.ac.kr
AF: Pusan national university, San 30 Jangjundong Kumjunggu, Busan, 609-735, Korea, Republic of
AU: Son, M
EM: gily4501@hanmail.net
AF: Pusan national university, San 30 Jangjundong Kumjunggu, Busan, 609-735, Korea, Republic of
AU: Kim, J
EM: joon-kim@yonsei.ac.kr
AF: Yonsei Univsreity, Sinchon-dong 134, Seodaemun-gu, Seoul, 120-749, Korea, Republic of
AU: Lee, D
EM: dlee@ieg.or.kr
AF: Yonsei Univsreity, Sinchon-dong 134, Seodaemun-gu, Seoul, 120-749, Korea, Republic of
AU: Kim, S
EM: sujin@koflux.yonsei.ac.kr
AF: Yonsei Univsreity, Sinchon-dong 134, Seodaemun-gu, Seoul, 120-749, Korea, Republic of
AU: Moon, S
EM: skmun2@gmail.com
AF: Yonsei Univsreity, Sinchon-dong 134, Seodaemun-gu, Seoul, 120-749, Korea, Republic of
AB: Understanding the hydrological processes at a hillslope scale can be achieved through intensive in situ monitoring of an intermediate hydrologic variable, soil moisture, during rainfall events. A soil monitoring system was installed to efficiently represent the spatial and temporal features of soil moisture for a hillslope located Gwangneung national Arboretum in South Korea. The soil moisture responses to sequential rainfall events were obtained as multiple time series. This paper attempts to explore an issue about how digital terrain analysis of many topologically based hydrology models can be addressed in terms of measured soil moisture histories. Time series analysis provides a systematic method of evaluating the stochastic characteristics of hydrologic variable. A derivation of the soil moisture transfer mechanism can be used as the physical basis of soil moisture time series analysis. After recording the soil moisture response patterns for a few consecutive rainfall events, a time series modeling procedure was applied to configure the characteristics of soil moisture. Characterizations of the variation in soil moisture variation were discussed through the interpretation of the time series models that were selected based on their terrain attributes.
DE: 1847 Modeling
DE: 1866 Soil moisture
DE: 1872 Time series analysis (3270, 4277, 4475)
SC: Hydrology [H]
MN: 2007 Fall Meeting