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Research Article

Spatial-temporal variaility analysis of in-situ soil moisture data in the Cheongmicheon and Seolmacheon basins

청미천, 설마천 유역의 지점 토양수분 자료 시ㆍ공간 변동성 분석

Yinji Lia
,
Seongkeun Chob
,
Minha Choicd*
이 은희a
,
조 성근b
,
최 민하cd*
aMaster Student, Department of Global Smart City, Sungkyunkwan University, Suwon, Korea
bPh.D Student, Department of Water Resources, Graduate School of Water Resources, Sungkyunkwan University, Suwon, Korea
cProfessor, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
dProfessor, School of Civil, Architectural Engineering & Landscape Architecture, Sungkyunkwan University, Suwon, Korea
a성균관대학교 글로벌스마트시티융합전공 석사과정
b성균관대학교 수자원전문대학원 수자원공학과 박사과정
c성균관대학교 수자원전문대학원 수자원학과 교수
d성균관대학교 건설환경공학부 교수
*Corresponding Author
28 February 2025. pp. 155-167
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Abstract

Soil moisture is an important factor in the analysis of the water cycle and natural disasters with a catchment area. With the spatio-temporal variability analysis of in-situ soil moisture datasets, robust soil moisture monitoring for the validation of satellite dataset could be conducted. The optimal and minimum necessary sampling size (NSS) using the in-situ soil moisture data at a depth of 10 cm, as measured by time domain reflectometry (TDR) was investigated in the Chengmicheon (CMC) and Seolmacheon (SMC) basins from 21 August 2018 to 20 August 2019 (excluding winter). Specifically, the in-situ soil moisture data that comprising 18 and 19 points were used to detect the spatio-temporal variation pattern of soil moisture in the CMC and SMC demonstration areas. The representing spatial mean value points in the CMC and SMC demonstration areas were identified based on the Temporal Stability of Index (TSI). The mean soil moisture coefficient of variation in the CMC and SMC demonstration areas were 0.20 and 0.37, respectively. In two study areas, the representative points were able to capture the spatial and temporal mean soil moisture with high accuracy (R2 value of greater than 0.88), and the two representative points in the two demonstration areas were both located in areas with soil moisture that was drier than the mean values. In addition, the number of soil moisture points based on the Random Combination Method (RCM) were examined utilising the Coefficient of Determination (R2) and Root Mean Square Error (RMSE) accuracy indicators, with a focus on the time series variation of spatial mean soil moisture. The precision of the time series estimates of spatial mean soil moisture has been improved as the number of soil moisture observations increases, and the requisite minimum number of soil moisture points in the CMC and SMC demonstration areas were 4 with an RMSE of less than 2% and an R2 accuracy of greater than 0.95. In addition, a statistical sampling analysis based on the spatial mean soil moisture was conducted to determine the requisite number of points, indicating that the number of requisite soil moisture points has been increased in proportion to the reduction in absolute error at a given confidence level. The minimum number of soil moisture points required at the 95% confidence level with an absolute error of 4% was determined to be 4 and 28 in the CMC and SMC demonstration areas, respectively, due to the high spatial variability of soil moisture in the SMC demonstration area.

Keywords
Soil moisture
Temporal stability analysis
Necessary sampling size
Chengmicheon
Seolmacheon

토양수분은 유역 내에서의 물순환 해석 및 자연 재난 발생 분석에 있어 중요한 요소이다. 효과적인 토양수분 모니터링을 위해서는 보편적으로 위성 영상의 검증 자료 역할을 수행하는 지점 토양수분에 대한 시공간 변동성 분석이 요구된다. 본 연구에서는 2018년 8월 21일부터 2019년 8월 20일(동절기 제외)까지 청미천과 설마천 유역 내에서 Time Domain Reflectometry (TDR) 방식으로 측정한 심도 10 cm의 지점 토양수분 데이터를 활용하여 신뢰성 있는 시공간 토양수분량을 산정하기 위한 최적 및 최소 필요 지점 개수(Necessary Sampling Size, NSS)를 분석하였다. 구체적으로, 청미천과 설마천 시범지역에서 각각 18개, 19개 지점을 대상으로 토양수분의 시공간적인 변화 패턴을 분석하였으며, 공간 평균 토양수분과의 상대적 차이를 기반으로 하는 Temporal Stability of Index (TSI)의 수치를 바탕으로 대표성을 나타내는 지점을 선별하였다. 그 결과, 청미천과 설마천 시범지역의 평균 공간 변동계수(Coefficient of Variation)는 각각 0.20과 0.37로 나타났으며, 두 시범지역에서 모두 높은 정확도(R2 값 0.88 이상)로 각 관측망 내 평균 토양수분을 시공간적으로 반영하는 대표 지점을 선별할 수 있었으며, 시범지역 내 대표 지점은 모두 평균값보다 건조한 위치에서 나타났다. 공간 평균 토양수분의 시계열 변화를 기반으로, Coefficient of Determination (R2)와 Root Mean Square Error (RMSE) 정확도 지표를 활용하여 랜덤 조합 샘플링 기반의 토양수분 지점 개수를 분석하였다. 그 결과, 토양수분의 지점 개수가 많아짐에 따라 공간 평균 토양수분의 시계열 추정값의 정확도는 높아지는 것을 확인할 수 있었으며, 2% 이하의 RMSE, 0.95 이상의 R2 정확도에서 청미천과 설마천 시범지역을 대상으로 요구되는 토양수분의 최소 지점 개수는 모두 4개로 나타났다. 반면 공간 평균 토양수분 기반의 통계 샘플링 분석을 수행하여 적절한 지점 개수를 산정한 결과, 동일한 신뢰도 수준에서 절대 오차가 작아 짐에 따라 요구되는 토양수분 지점 개수는 많아지는 것으로 나타났다. 95% 신뢰 수준, 4%의 절대 오차 범위에서 청미천과 설마천 시범지역을 대상으로 요구되는 최대 지점 개수는 각각 4개, 28개로 확인되었으며, 설마천 시범지역에서 토양수분의 공간 변동성이 크기 때문에 이러한 결과가 나타난 것으로 판단된다.

키워드
토양수분
시간 안정성
필요 지점 개수
청미천
설마천
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Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 58
  • No :2
  • Pages :155-167
  • Received Date : 2024-09-12
  • Revised Date : 2024-12-20
  • Accepted Date : 2024-12-31
  • DOI :https://doi.org/10.3741/JKWRA.2025.58.2.155
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