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Review of Remote Sensing Studies on Groundwater Resources

원격탐사의 지하수 수자원 적용 사례 고찰

  • Lee, Jeongho (Division of Natural Resources Conservation, Korea Environment Institute)
  • 이정호 (한국환경정책.평가연구원 국토자연연구실)
  • Received : 2017.08.03
  • Accepted : 2017.10.16
  • Published : 2017.10.30

Abstract

Several research cases using remote sensing methods to analyze changes of storage and dynamics of groundwater aquifer were reviewed in this paper. The status of groundwater storage, in an area with regional scale, could be qualitatively inferred from geological feature, surface water altimetry and topography, distribution of vegetation, and difference between precipitation and evapotranspiration. These qualitative indicators could be measured by geological lineament analysis, airborne magnetic survey, DEM analysis, LAI and NDVI calculation, and surface energy balance modeling. It is certain that GRACE and InSAR have received remarkable attentions as direct utilization from satellite data for quantification of groundwater storage and dynamics. GRACE, composed of twin satellites having acceleration sensors, could detect global or regional microgravity changes and transform them into mass changes of water on surface and inside of the Earth. Numerous studies in terms of groundwater storage using GRACE sensor data were performed with several merits such that (1) there is no requirement of sensor data, (2) auxiliary data for quantification of groundwater can be entirely obtained from another satellite sensors, and (3) algorithms for processing measured data have continuously progressed from designated data management center. The limitations of GRACE for groundwater storage measurement could be defined as follows: (1) In an area with small scale, mass change quantification of groundwater might be inaccurate due to detection limit of the acceleration sensor, and (2) the results would be overestimated in case of combination between sensor and field survey data. InSAR can quantify the dynamic characteristics of aquifer by measuring vertical micro displacement, using linear proportional relation between groundwater head and vertical surface movement. However, InSAR data might now constrain their application to arid or semi-arid area whose land cover appear to be simple, and are hard to apply to the area with the anticipation of loss of coherence with surface. Development of GRACE and InSAR sensor data preprocessing algorithms optimized to topography, geology, and natural conditions of Korea should be prioritized to regionally quantify the mass change and dynamics of the groundwater resources of Korea.

본 논문에서는 지하수 수자원의 부존 및 대수층의 역학적 변화를 원격 탐사 방법으로 해석한 연구사례를 고찰하였다. 지질 분포, 지표수 및 지형 고도차, 식생 분포, 강수량과 증발산량의 변화를 측정하는 기법에는 항공 자력 탐사 분석에 의한 지질 선구조 해석, DEM, 엽면적지수, 정규 식생 지수 및 지표면 에너지 밸런스 계산 등이 있으며, 모두 원격 탐사로 수득된 자료에 기반하며, 광역적 차원에서의 지하수 수자원 부존 여부를 정성적으로 분석할 수 있다. 위성 센서 자료의 직접 이용을 통한 지하수 부존 및 동력학의 정량적 해석은 현재까지 GRACE와 InSAR가 가장 각광받는 탐사 방법임을 알 수 있었다. GRACE는 미소 중력장 변화를 지구 표면 및 내부 수체의 질량 변화로 전환할 수 있는 센서 보유 위성으로서, 센서 자료의 보정이 필요 없고, 지하수 부존 정량 분석을 위한 보조 자료를 모두 다른 위성 센서 자료에서 수득할 수 있으며, 자료처리 알고리즘의 지속적인 개선이 진행되고 있어서, 전세계적으로 수많은 연구가 수행되었다. 그러나, 위성센서의 검출 한계로 인해 협소한 지역에서의 지하수 질량 변화 정량이 부정확할 수 있고, 현장 조사 자료와 연동할 경우 과대 추정된 결과가 도출될 수 있다. InSAR는 특정 대수층에서 지표의 수직 변위가 지하수위와 비례한다는 원리를 이용, mm 단위의 지표 수직 변위를 측정하여 대수층 및 대수층 내 지하수의 물리적 특징을 정량화할 수 있다. 그러나, 지표의 토지 피복이 단순한 건조-반건조 기후 지역에 한정되어 적용되고 있으며, 지표면과의 긴밀도 값 손실이 우려되는 지역에서는 적용이 힘들다. 상기 두 위성을 이용하여 우리나라 지하수 수자원의 질량 변화 및 흐름 특징을 광역적으로 정량화하기 위해서는 우리나라의 지형 및 지질, 자연 조건에 알맞은 자료 전처리 알고리즘 개발 및 적용이 선행되어야 할 것이다.

Keywords

References

  1. Abiy, A. Z. and A. M. Melesse, 2017. Evaluation of watershed scale changes in groundwater and soil moisture storage with the application of GRACE satellite imagery data, Catena, 153: 50-60. https://doi.org/10.1016/j.catena.2017.01.036
  2. Bastiaanssen, W. G. M., M. Menenti, R. A. Feddes, and A. A. M. Holtslag, 1998a. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation, Journal of Hydrology, 213: 198-212.
  3. Bastiaanssen, W. G. M., H. Pelgrum, J. Wang, Y. Ma, J. F. Moreno, G. J. Roerink, and T. van der Wal, 1998b. A remote sensing surface energy balance algorithm for land (SEBAL). 2. Validation, Journal of Hydrology, 213: 213-229.
  4. Bear, J., 1979. Hydraulics of Groundwater, McGrow-Hill, New York, USA
  5. Becker, M. W., 2006. Potential for Satellite Remote Sensing of Ground Water, Groundwater, 44: 306-318. https://doi.org/10.1111/j.1745-6584.2005.00123.x
  6. Bhanja, S. N., A. Mukherjee, D. Saha, I. Velicogna, and J. S. Famiglietti, 2016. Validation of GRACE based groundwater storage anomaly using in-situ groundwater level measurements in India, Journal of Hydrology, 543: 729-738. https://doi.org/10.1016/j.jhydrol.2016.10.042
  7. Brunner, P., H. J. Hendricks Franssen, L. Kgothang, P. Bauer-Gottwein, and W. Kinzelbach, 2007. How can remote sensing contribute in groundwater modeling, Hydrogeology Journal, 15: 5-18. https://doi.org/10.1007/s10040-006-0127-z
  8. Castellazzi, P., R. Marten, D. L. Galloway, L. Longuevergne, and A. Rivera, 2016a. Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations, Groundwater, 54(6): 768-780. https://doi.org/10.1111/gwat.12453
  9. Castellazzi, P., R. Marten, D. L. Galloway, A. Rivera, J. Huang, G. Pavlic, A. I. Calderhead, E. Chaussard, J. Garfias, and J. Salas, 2016b. Groundwater depletion in Central Mexico: Use of GRACE and InSAR to support water resources management, Water Resources Research, 52: 5985-6003. https://doi.org/10.1002/2015WR018211
  10. Chao, N,. Z Wang, W jiang, and D. Chao, 2016. A quantitative approach for hydrological drought characterization in southwestern China using GRACE, Hydrogeology Journal, 24: 893-903. https://doi.org/10.1007/s10040-015-1362-y
  11. Chaussard, E., R. Burgmann, M. Shirzaei, E. J. Fielding, and B. Baker, 2014. Predictability of hydraulic head changes and characterization of aquifersystem and fault properties from InSAR-derived ground deformation, Journal of Geophysical Research Solid Earth, 119: 6572-6590. https://doi.org/10.1002/2014JB011266
  12. Chen, J., R. Knight, H. A. Zebker, and W. A. Schreuder, 2016. confined aquifer head measurements and storage properties in the San Luis Valley, Colorado, from spaceborne InSAR observations, Water Resources Research, 52: 3623-3636. https://doi.org/10.1002/2015WR018466
  13. Eamus, D., S. Zolfaghar, R. Villalobos-Vega, J. Cleverly, and A. Huete, 2015. Groundwater-dependent ecosystems: recent insights from satellite and field-based studies, Hydrology and Earth System Sciences, 19: 4229-4256. https://doi.org/10.5194/hess-19-4229-2015
  14. Galloway, D. L., 2014. Retrospective of InSAR/DInSAR contributions to hydrology by way of bibliographic search, Proc. of 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, Canada, Jul. 13-18, pp.2637-2640.
  15. Galloway, D. L. and T. J. Burbey, 2011. Review: Regional land subsidence accompanying groundwater extraction, Hydrogeology Journal, 19: 1459-1486. https://doi.org/10.1007/s10040-011-0775-5
  16. Galloway, D. L. and J Hoffmann, 2007. The application of satellite differential SAR interferometrydrived ground displacements in hydrogeology, Hydrogeology Journal, 15(1): 133-154. https://doi.org/10.1007/s10040-006-0121-5
  17. Galloway, D. L., K. W. Hudnut, S. E. Ingebritsen, S. P. Phillips, and G. Peltzer, 1998. Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar, Antelope Valley, Mojave Desert, California, Water Resources Research, 34(10): 2573-2585. https://doi.org/10.1029/98WR01285
  18. Henry, C. M., D. M. Allen, and J. Huang, 2011. Groundwater storage variability and annual recharge using well-hydrograph and GRACE satellite data, Hydrogeology Journal, 19: 741-755. https://doi.org/10.1007/s10040-011-0724-3
  19. Hu, K., J. L. Awange, Khandu, E. Forootan, R. Mikosz Goncalves, and K. Fleming, 2017. Hydrogeological characterisation of groundwater over Brazil using remotely sensed and model products, Science of the Total Environment, 600: 372-386.
  20. Hu, L. and J. J. Jiao, 2015. Calibration of large-scale groundwater flow model using GRACE data: a case study in the Qaidam Basin, China, Hydrogeology Journal, 23: 1305-1317. https://doi.org/10.1007/s10040-015-1278-6
  21. Huang, J., J. Halpenny, W. van der Wal, C. Klatt, T. S. James, and A. Rivera, 2012. Detectability of groundwater storage change within the Great Lakes Water Basin using GRACE, Journal of Geophysical Research, 117(B8): B08401.
  22. Iqbal, N., F. Hossain, H. Lee, and G. Akhter, 2016. Satellite Gravimetric Estimation of Groundwater storage Variations Over Indus Basin in Pakistan, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9: 3524-3534. https://doi.org/10.1109/JSTARS.2016.2574378
  23. Jaques, A. L., P. Wellman, A. Whitaker, and D. Wyborn, 1997. High-resolution geophysics in modern geological mapping, AGSO Journal of Australian Geology and Geophysics, 17: 159-173.
  24. K-Water, 2017. Water and Future: Water and sustainable Development, Ministry of Land, Infrastructure and Transport (MOLIT) .
  25. Lee, S. R., Y. S. Kim, J. W. Lee, J. H. Park, and I. Woo, 2004. Development of a technique for lineament density calculation and its application to groundwater yield, Journal of the Geological Society of Korea, 40(3): 293-304 (in Korean with English abstract).
  26. Liesch, T. and M. Ohmer, 2016. Comparison of GRACE data and groundwater levels for the assessment of groundwater depletion in Jordan, Hydrogeology Journal, 24: 1547-1563. https://doi.org/10.1007/s10040-016-1416-9
  27. Long, D., X. Chen, B. R. Scanlon, Y. Wada, Y. Hong, V. P. Singh, Y. Chen, C. Wang, Z. Han, and W. Yang, 2016. Have GRACE satellites overestimated groundwater depletion in the Northwest India Aquifer, Nature Scientific Reports, 6: 24398. https://doi.org/10.1038/srep24398
  28. Ministry of Land, Transport and Maritime Affairs (MLTM), 2012. Basic Plan for Groundwater Management, Korea, Ministry of Land, Transport and Maritime Affairs (MLTM).
  29. Oh, K., M. Lee, B. Park. J. Lee, and J. Yoon, 2017. Analysis of the Research Trends by environmental Spatial-Information using Text-Mining Technology, Journal of the Korean Association of Geographic Information Studies, 20(1): 113-126 (in Korean with English abstract). https://doi.org/10.11108/kagis.2017.20.1.113
  30. Park, B, K. Oh, J. Lee, J. Yoon, S. K. Lee, and M. Lee, 2017. A study on Environmental Research Trends by Information and Communication Technologies using Text-Mining Technology, Korean Journal of Remote Sensing, 33(1): 189-199 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2017.33.2.7
  31. Reeves, J. A., R. Knight, H. A. Zebker, W. A. Schreuder, P. Shanker Agram, and T. R. Lauknes, 2011. High quality InSAR data linked to seasonal change in hydraulic head for an agricultural area in the San Suis Valley, Colorado, Water Resources Research, 47(12): W12510.
  32. Richey, A. S., B. F. Thomas, M. Lo, J. J. S. Famiglietti, S. Swenson, and M. Rodell, 2015a. Uncertainty in global groundwater storage estimates in a Total Groundwater Stress framework, Water Resources Research, 51: 5198-5216. https://doi.org/10.1002/2015WR017351
  33. Richey, A. S., B. F. Thomas, M. Lo, J. T. Reager, J. S. Famiglietti, K. Voss, S. Swenson, and M. Rodell, 2015b. Quantifying renewable groundwater stress with GRACE, Water Resources Research, 51: 5217-5238. https://doi.org/10.1002/2015WR017349
  34. Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J. K. Entin, J. P. Walker, D. Lohmann, and D. Toll, 2004. The Global Land Data Assimilation System, Bulletin of American Meteorological Society, 85(3): 381-394. https://doi.org/10.1175/BAMS-85-3-381
  35. Rodell, M., J. Chen, H. Kato, J. S. Famiglietti, J. Nigro, and C. R. Wilson, 2007. Estimating groundwater storage changes in the Mississippi River Basin (USA) using GRACE, Hydrogeology Journal, 15: 159-166. https://doi.org/10.1007/s10040-006-0103-7
  36. Rodell, M., I. Velicogna, and J. S. Famiglietti, 2009. Satellite-based estimates of groundwater depletion in India, Nature, 460: 999-1002. https://doi.org/10.1038/nature08238
  37. Roerink, G. J., Z. Su, and M. Menenti, 2000. S-SEBI: A Simple Remote Sensing Algorithm to Estimate the Surface Energy Balance, Physics and Chemistry of the Earth Part B Hydrology Oceans and Atmosphere, 25: 147-157. https://doi.org/10.1016/S1464-1909(99)00128-8
  38. Wang, H., L. Kgotlhang, and W. Kinzelbach, 2008. Using Remote Sensing Data to Model Groundwater Recharge Potential in Kaanye region, Botswana, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B8): 751-756.
  39. Wang, K., P. Wang, Z. Li, M. Cribb, and M. Sparrow, 2007. A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature, Journal of Geophysical Research Atmospheres, 112(D15): D15107. https://doi.org/10.1029/2006JD008351
  40. World Economic Forum, 2011. World Economic Forum Annual Report 2007-2008, World Economic Forum.

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