한국농림기상학회지, 제 9권 제2호(2007) (pISSN 1229-5671, eISSN 2288-1859)
Korean Journal of Agricultural and Forest Meteorology, Vol. 9, No. 2, (2007), pp. 88~99
DOI: 10.5532/KJAFM.2007.9.2.088
ⓒ Author(s) 2014. CC Attribution 3.0 License.


광릉수목원 내 산지사면에서의 토양수분 시계열 자료의 단변량 분석

손미나(1), 김상현(1), 김도훈(1), 이동호(2), 김 준(2)
(1)부산대학교 환경공학과, (2)연세대학교 대기과학과/지구환경연구소

(2007년 03월 20일 접수; 2007년 06월 11일 수락)

Univariate Analysis of Soil Moisture Time Series for a
Hillslope Located in the KoFlux Gwangneung Supersite

Mina Son(1), Sanghyun Kim(1), Dohoon Kim(1), Dongho Lee(2),, Joon Kim(2)
(1)Department of Environmental Engineering, Water resource and Environment Laboratory,
Pusan National University, Busan, 609-735, Korea
(2)Department of Atmospheric Sciences / Global Environment Laboratory,
Yonsei University, Seoul, 120-749, Korea

(Received March 20, 2007; Accepted June 11, 2007)

ABSTRACT
Soil moisture is one of the essential components in determining surface hydrological processes such as infiltration, surface runoff as well as meteorological, ecological and water quality responses at watershed scale. This paper discusses soil moisture transfer processes measured at hillslope scale in the Gwangneung forest catchment to understand and provide the basis of stochastic structures of soil moisture variation. Measured soil moisture series were modelled based upon the developed univariate model platform. The modeling consists of a series of procedures: pre-treatment of data, model structure investigation, selection of candidate models, parameter estimation and diagnostic checking. The spatial distribution of model is associated with topographic characteristics of the hillslope. The upslope area computed by the multiple flow direction algorithm and the local slope are found to be effective parameters to explain the distribution of the model structure. This study enables us to identify the key factors affecting the soil moisture distribution and to ultimately construct a realistic soil moisture map in a complex landscape such as the Gwangneung Supersite.

Keyword: Soil moisture, Time series, Univariate analysis, ARMA model

MAIN

적요

토양수분은 토양으로의 침투나 지표유출 기작에 직접적인 영향을 주며 간접적으로 유역 단위의 수문학적, 수리화학적, 기상학적, 생태학적 반응에 중요한 역할을 한다. 본 연구에서는 광릉 슈퍼사이트 내 원두부 소유역을 대상으로 사면에서의 토양수분 전이과정이 토양수분의 추계학적 모형구조와 갖는 연계성을 규명하기 위해서 일련의 유도과정이 수행되었다. 유도된 단변량추계학적 모형의 구조에 근거하여, 관측된 토양수분의 시계열을 모의하였다. 자료전처리, 모형구조의 규명, 후보 모형군의 구성, 모수추정, 검정 등의 과정을 통해서 도출된 모형들의 공간적인 분포는 대상사면의 지형학적인 특성들이 반영된 것으로 판단된다. 다방향 알고리즘에 의한 기여면적이나 습윤 지수와 함께 대상지점의 국부경사도가 중요변수로 도출되었다. 본 연구 결과는 광릉 슈퍼사이트와 같은 복잡 경관에서 토양수분의 공간분포를 결정짓는 중요한 요인들을 이해하고 이를 통해 현실성있는 토양수분 분포 지도를 작성하는데 기여하게 될 것이다.

REFERENCES

Ambroise, B., 2004: Variable ‘active’ versus ‘contributing’ area or periods: a necessary distinction. Hydrological Processes 18, 1149-1155crossref(new window)

Box, G. E. P., and G. M. Jenkins, 1976: Time Series Analysis : Forecasting and Control, (Revised ed.). Prentice Hall, Englewood Cliffs, New Jersey

Beven, K., 2002: Towards an alternative blueprint for a physically based digitally simulated hydrologic response modeling system. Hydrological Processes 16, 189-206crossref(new window)

Bras, R. L., and I. Rodriguez-Iturbe, 1985: Random Functions and Hydrology. Addison-Wesley, Reading, Mass

Chow, V. T., D. R. Maidment, and L. W. Mays, 1998: Applied Hydrology. McGraw-Hill, Inc., 201-213

Claude, D. T., and D. G. Wendy, 1993: Comparison of univariate and transfer function models of groundwater fluctuations. Water Resources Research 29(10), 3517-3533crossref(new window)

Georgakakos, K. P., 1996: Soil moisture theories and observations (Forward). Journal of Hydrology 184(1-2), 1.crossref(new window)

Hipel, K. W., A. I. McLeod, and W. C. Lennox, 1977: Advances in Box-Jenkins modeling: 1. Model construction. Water Resources Research 13(3), 567-575crossref(new window)

Liu, L. M., and G. B. Hundak, 1992: Forecasting and Time Series Analysis Using the SCA Statistical System. Scientific Computing Associates Corp., 8.1-8.84

Mullan, A. B., 1998: Southern hemisphere sea-surface temperatures and their contemporary and lag association with New Zealand temperature and precipitation. International journal of climatology 18, 817-840

O’Callaghan, J. F., and D. M. Mark, 1984: The extraction of drainage networks from digital elevation data, Computer Vision, Graphics and Image Processing 28, 323-344crossref(new window)

Ridolfi, L., P. D’Odorico, A. Porporato, and I. Rodriguez- Iturbe, 2003: Stochastic soil moisture dynamics along a hillslope. Journal of Hydrology 272(1-4), 264-275crossref(new window)

Topp, G. C., 2003: State of the art of measuring soil water content. Hydrological Processes 17, 2993-2996crossref(new window)

Tsay, R. S. and G. C. Tiao, 1984: Consistent estimates of autoregressive parameters and extended sample autocorrelation function for stationary and nonstationary ARMA models. Journal of the American Statistical Association 79, 84-96crossref(new window)

Walker, J. P., G. R. Willgoose, and J. D. Kalma, 2004: In situ measurement of soil moisture: a comparison of techniques. Journal of Hydrology 293, 85-99crossref(new window)

Wilson, D. J., A. W. Western, and R. B. Grayson, 2005: A terrain and data-based method for generating the spatial distribution of soil moisture. Advances in Water Resources 28, 43-54crossref(new window)