Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지
DOI QR코드

DOI QR Code

A Study for establishment of soil moisture station in mountain terrain (1): the representative analysis of soil moisture for construction of Cosmic-ray verification system

산악 지형에서의 토양수분 관측소 구축을 위한 연구(1): Cosmic-ray 검증시스템 구축을 위한 토양수분량 대표성 분석 연구

  • Kim, Kiyoung (Korea Institute of Hydrological Survey, Research & Development Division) ;
  • Jung, Sungwon (Korea Institute of Hydrological Survey) ;
  • Lee, Yeongil (Korea Institute of Hydrological Survey, Research & Development Division)
  • 김기영 (한국수자원조사기술원 연구개발실) ;
  • 정성원 (한국수자원조사기술원) ;
  • 이연길 (한국수자원조사기술원 연구개발실)
  • Received : 2018.10.23
  • Accepted : 2018.11.26
  • Published : 2019.01.31
Download PDF
⟨ Previous Next ⟩

Abstract

The major purpose of this study is to construct an in-situ soil moisture verification network employing Frequency Domain Reflectometry (FDR) sensors for Cosmic-ray soil moisture observation system operation as well as long-term field-scale soil moisture monitoring. The test bed of Cosmic-ray and FDR verification network system was established at the Sulma Catchment, in connection with the existing instrumentations for integrated data provision of various hydrologic variables. This test bed includes one Cosmic-ray Neutron Probe (CRNP) and ten FDR stations with four different measurement depths (10 cm, 20 cm, 30 cm, and 40 cm) at each station, and has been operating since July 2018. Furthermore, to assess the reliability of the in-situ verification network, the volumetric water content data measured by FDR sensors were compared to those calculated through the core sampling method. The evaluation results of FDR sensors- measured soil moisture against sampling method during the study period indicated a reasonable agreement, with average values of $bias=-0.03m^3/m^3$ and RMSE $0.03m^3/m^3$, revealing that this FDR network is adequate to provide long-term reliable field-scale soil moisture monitoring at Sulmacheon basin. In addition, soil moisture time series observed at all FDR stations during the study period generally respond well to the rainfall events; and at some locations, the characteristics of rainfall water intercepted by canopy were also identified. The Temporal Stability Analysis (TSA) was performed for all FDR stations located within the CRNP footprint at each measurement depth to determine the representative locations for field-average soil moisture at different soil profiles of the verification network. The TSA results showed that superior performances were obtained at FDR 5 for 10 cm depth, FDR 8 for 20 cm depth, FDR2 for 30 cm depth, and FDR1 for 40 cm depth, respectively; demonstrating that those aforementioned stations can be regarded as temporal stable locations to represent field mean soil moisture measurements at their corresponding measurement depths. Although the limit on study duration has been presented, the analysis results of this study can provide useful knowledge on soil moisture variability and stability at the test bed, as well as supporting the utilization of the Cosmic-ray observation system for long-term field-scale soil moisture monitoring.

본 연구에서는 Cosmic-ray 토양수분량 관측시스템 구축 시 필요한 검증 네트워크 설계 기법 개발에 목적을 두고 유전율식(dielectric constant) 장비인 Frequency Domain Reflectometry (FDR)와 연계하여 Cosmic-ray 검증시스템을 구축 운영하였다. Cosmic-ray 검증시스템 평가에 필요한 시범지역은 기존 계측 장비와의 연계성과 다양한 수문자료의 활용성을 고려하여 설마천 유역에 구축하였다. 시범지역은 Cosmic-ray 장비와 FDR 센서(10개소)로 구축하였으며 2018년 7월부터 현재까지 운영되고 있다. 본 연구에서는 검증시스템의 신뢰도를 높이기 위해 코어법(soil core sampling method)을 통해 산출한 용적수분함량(volumetric water content)을 유전율식 장비와 정기적으로 검증하였다. 연구기간 중 수행한 코어법과 FDR 센서를 검증한 결과, 두 자료의 통계량이 $bias=-0.03m^3/m^3$과 $RMSE=0.03m^3/m^3$의 유의한 값을 보였다. 또한 연구기간 동안 FDR 센서의 시계열 특성은 모든 강우에 정상적으로 반응하였다. 그러나 일부 지점에서는 낙엽 및 캐노피의 차단과 상부사면의 유출 등으로 인해 상이한 특성을 보였다. Cosmic-ray 영향원(influence line) 내 FDR 센서의 대표성 분석은 시간 안정성 해석법(temporal stability analysis, TSA)을 이용하여 토심별(10 cm, 20 cm, 30 cm, 40 cm)로 분석하였다. 10개소에 대한 토심별 토양수분량의 대표성을 TSA로 분석한 결과, 토심 10 cm에서는 FDR 5, 토심 20 cm에서는 FDR 8, 토심 30 cm에서는 FDR 2, 토심 40 cm에서는 FDR 1에서 가장 우수한 대표 특성을 보였다. 본 연구의 시범지역 운영 기간이 짧다는 한계는 있지만 지금까지의 분석 결과를 토대로 하여 볼 때, Cosmic-ray 관측시스템 구축 시에는 검증 장비로는 유전율식을 활용하고, Cosmic-ray 영향원 내 토양수분량의 대표성 분석은 TSA 방법으로 수행하는 것이 바람직할 것으로 판단된다.

Keywords

SJOHCI_2019_v52n1_51_f0001.png 이미지

Fig. 1. Location of Study Area (Seolmacheon Basin)

SJOHCI_2019_v52n1_51_f0002.png 이미지

Fig. 2. Location of the CRNP and FDR stations at the study area

SJOHCI_2019_v52n1_51_f0003.png 이미지

Fig. 3. A Soil types determination according to their clay, silt, and clay composition, as used by Soil Texture Triangle diagram from the USDA

SJOHCI_2019_v52n1_51_f0004.png 이미지

Fig. 4. Comparison of volumetric soil moisture measured by FDR network against those obtained from direct sampling method

SJOHCI_2019_v52n1_51_f0005.png 이미지

Fig. 5. Time series of soil moisture and precipitation observed at all stations from July. 2018 to Oct. 2018

SJOHCI_2019_v52n1_51_f0006.png 이미지

Fig. 6. Box-plot for soil moisture variability at each FDR station for four different measurement depths: (a) 10 cm, (b) 20 cm, (c) 30 cm, and (d) 40 cm

SJOHCI_2019_v52n1_51_f0007.png 이미지

Fig. 7. Temporal stability analysis for soil moisture values obtained at four different measurement depths: (a) 10 cm, (b) 20 cm, (c) 30 cm, and (d) 40 cm

SJOHCI_2019_v52n1_51_f0008.png 이미지

Fig. 8. Comparison of temporal stable location-measured soil moisture versus areal mean soil moisture at four different measurement depths:(a) 10 cm, (b) 20 cm, (c) 30 cm, and (d) 40 cm

Table 1. Field Sites, Geographic location, elevation, and sensor depths for FDR soil moisture verification network

SJOHCI_2019_v52n1_51_t0001.png 이미지

Table 2. Average soil properties for different sectors within the verification network

SJOHCI_2019_v52n1_51_t0002.png 이미지

Table 3. Summary of evaluation statistics of FDR-measured soil moisture against gravimetric sampling-based soil moisture

SJOHCI_2019_v52n1_51_t0003.png 이미지

References

  1. Bogena, H. R., Huisman, J. A., Baatz, R., Hendricks Franssen, H. J., and Vereecken, H. (2013). "Accuracy of the cosmic-ray soil water content probe in humid forest ecosystems: The worst case scenario." Water Resources Research, Vol. 49, No. 9, pp. 5778-5791. https://doi.org/10.1002/wrcr.20463
  2. Brocca, L., Melone, F., Moramarco, T., and Morbidelli, R. (2009). "Soil moisture temporal stability over experimental areas in Central Italy." Geoderma, Vol. 148, No. 3-4, pp. 364-374. https://doi.org/10.1016/j.geoderma.2008.11.004
  3. Brocca, L., Melone, F., Moramarco, T., and Morbidelli, R. (2010). "Spatial-temporal variability of soil moisture and its estimation across scales." Water Resources Research, Vol. 46, No. 2.
  4. Choi, M., and Jacobs, J. M. (2007). "Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints." Advances in Water Resources, Vol. 30, No. 4, pp. 883-896. https://doi.org/10.1016/j.advwatres.2006.07.007
  5. Dorigo, W. A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiova, A., Sanchis-Dufau, A. D., and Drusch, M. (2013). "Global automated quality control of in situ soil moisture data from the International Soil Moisture Network." Vadose Zone Journal, Vol. 12, No. 3.
  6. Franz, T. E., Zreda, M., Rosolem, R., and Ferre, T. P. A. (2013). "A universal calibration function for determination of soil moisture with cosmic-ray neutrons." Hydrology and Earth System Sciences, Vol. 17, No. 2, pp. 453-460. https://doi.org/10.5194/hess-17-453-2013
  7. Heidbuchel, I., Guntner, A., and Blume, T. (2016). "Use of cosmic-ray neutron sensors for soil moisture monitoring in forests." Hydrology & Earth System Sciences, Vol. 20, No. 3, pp. 1269-1288. https://doi.org/10.5194/hess-20-1269-2016
  8. Jacobs, J. M., Mohanty, B. P., Hsu, E. C., and Miller, D. (2004). "SMEX02: Field scale variability, time stability and similarity of soil moisture." Remote sensing of Environment, Vol. 92, No. 4, pp. 436-446. https://doi.org/10.1016/j.rse.2004.02.017
  9. Korea Institute of Civil engineering and building Technology (KICT) (2003). "Hydrological Survey for Flood Forecasting of the Mountainous River Basin." pp. 7-12.
  10. Lee, Y., Lee, J., Choi, M., and Jung, S. (2015). "Evaluation of MODIS- derived Evapotranspiration According to the Water Budget Analysis." Journal of Korea Water Resources Association, Vol. 48, No. 10, pp. 831-843. https://doi.org/10.3741/JKWRA.2015.48.10.831
  11. Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., de Jeu, R. A., Wagner, W., McCabe, M. F., and Van Dijk, A. I. J. M. (2012). "Trendpreserving blending of passive and active microwave soil moisture retrievals." Remote Sensing of Environment, Vol. 123, pp. 280-297. https://doi.org/10.1016/j.rse.2012.03.014
  12. Paloscia, S., Macelloni, G., and Santi, E. (2006). "Soil moisture estimates from AMSR-E brightness temperatures by using a dual-frequency algorithm." IEEE Transactions on Geoscience and Remote Sensing, Vol. 44, No. 11, pp. 3135-3144. https://doi.org/10.1109/TGRS.2006.881714
  13. Sur, C., Jung, Y., and Choi, M. (2013). "Temporal stability and variability of field scale soil moisture on mountainous hillslopes in Northeast Asia." Geoderma, Vol. 207, pp. 234-243. https://doi.org/10.1016/j.geoderma.2013.05.007
  14. Vachaud, G., Passerat de Silans, A., Balabanis, P., and Vauclin, M. (1985). "Temporal stability of spatially measured soil water probability density function 1." Soil Science Society of America Journal, Vol. 49, No. 4, pp. 822-828. https://doi.org/10.2136/sssaj1985.03615995004900040006x