Browse > Article
http://dx.doi.org/10.11108/kagis.2020.23.4.083

Calculation of Soil Moisture and Evaporation on the Korean Peninsula using NASA LIS(Land Information System)  

PARK, Gwang-Ha (Water Resources Management Research Center K-water Research Institute)
YU, Wan-Sik (Water Resources Management Research Center K-water Research Institute)
HWANG, Eui-Ho (Water Resources Management Research Center K-water Research Institute)
JUNG, Kwan-Sue (Dept. of Civil Engineering, Chungnam National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.23, no.4, 2020 , pp. 83-100 More about this Journal
Abstract
This study evaluated the accuracy of soil moisture and evapotranspiration by calculating the hydrological parameters in Korean peninsula using Land Information System(LIS) developed by US NASA. We used Noah-MP surface model to calculate hydrological parameters, and used MERRA2(Modern-Era Retrospective analysis for Research and Applications, Version 2) for hydrological forcing data. And, International Geosphere-Biosphere Program(IGBP) and University of Maryland(UMD) land cover maps were applied to compare the output accuracy, and Automated Synoptic Observing System(ASOS) of KMA was used as ground observation data. In order to evaluate the accuracy of the output data, the correlation coefficient(CC), BIAS, and efficiency factor (NSE, Nash-Sutcliffe Efficiency) were analyzed with soil moisture and evapotranspiration by ASOS ground observation data. As a result, the correlation coefficient of soil moisture using IGBP was 0.56 on average, and evapotranspiration was about 0.71. On the other hand, soil moisture using UMD was 0.68 on average and evapotranspiration was about 0.72, and the correlation coefficient by UMD was evaluated as high accuracy compared to the results by using IGBP. The correlation coefficient of soil moisture was an average of 0.68 and evapotranspiration was an average of 0.72 when MERRA2 was used as hydrological forcing data. On the other hand, the soil moisture applied with ASOS was an average of 0.66, and evapotranspiration was an average of 0.72. It is judged that the ASOS point data was reanalyzed as 0.65°× 0.5°grids, which is the same spatial resolution with MERRA2, resulting in differences in accuracy depending on the region.
Keywords
LIS; Noah-MP; Soil Moisture; Evapotranspiration; ASOS;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Arsenault, K.R., Kumar, S.V., Geiger, J.V., Wang, S., Kemp, E., Mocko, D.M. ... and Jacob, J. 2018. The Land surface Data Toolkit (LDT v7. 2)-a data fusion environment for land data assimilation systems. Geoscientific Model Development. 11(9):3605-3621.   DOI
2 Barlage M., Zeng, X. and Broxton, P. 2014. Improvement of Land Surface Parameters and States: Diagnosing Forecast and Model Deficiencies. JCSDA Science Meeting. 7pp.
3 Cai, X., Yang, Z. L., David, C.H., Niu, G.Y. and Rodell, M. 2014. Hydrological evaluation of the Noah‐MP land surface model for the Mississippi River Basin. Journal of Geophysical Research: Atmospheres. 119(1): 23-38.   DOI
4 Chae, H.S., Kim, S.J. and Koh, D.K. 2004. Extraction of hydrological information of unmeasured watershed using remote sensing data. Magazine of Korea Water Resources Association. 37(3):44-49.
5 Cho, C.H. 2015. Changes in the water cycle due to climate change. Magazine of Korea Water Resources Association. 48(11):4-6.
6 Cho, E.S., Song, S.U. and Yoo, C.S. 2017. Analysis and Validation of Soil Moisture Data over the Korean Peninsula Simulated by the VIC Model. Journal of Wetlands Research. 19(1):52-62.   DOI
7 Hamlet, A.F., Mote, P.W., Clark, M.P. and Lettenmaier, D.P. 2007. Twentieth-century trends in runoff, evapotranspiration, and soil moisture in the western United States. Journal of Climate. 20(8):1468-1486.   DOI
8 Jang, E.S. 2015. Estimation of surface fluxes using noah LSM and assessment of the applicability in korean peninsula. Paper of Masters Degree. Hanyang University. pp.1-31.
9 Kim, K.S., Kang, M.S., Jeong, H.N. and Kim, J. 2013. Comparison of crop growth and evapotranspiration simulations between Noah Multi Physics model and CERES-Rice model. Korean Journal of Agricultural and Forest Meteorology. 15(4):282-290.   DOI
10 Kumar, S.V., Peters-Lidard, C.D., Santanello, J., Harrison, K., Liu, Y. and Shaw, M. 2012. Land surface Verification Toolkit (LVT)-a generalized framework for land surface model evaluation. Geoscientific Model Development. 5(3):869-886.   DOI
11 Kumar, S.V., Peters-Lidard, C.D., Tian, Y., Houser, P.R., Geiger, J., Olden, S., ... and Adams, J. 2006. Land information system: An interoperable framework for high resolution land surface modeling. Environmental modelling & software. 21(10):1402-1415.   DOI
12 Lawston, P.M. 2017. Impacts of Irrigation on Land-atmosphere Interactions in High-resolution Model Simulations. Doctoral Dissertation. University of Delaware. pp.1-105.
13 Lee, J.H. 2017. Assimilation of satellite based soil moisture data into a land surface model. Paper of Masters Degree. Hongik University. pp.1-47.
14 Lee, T.H. 2018. Estimation and utilization of distributed soil moisture in time-spacial using remote sensing data and soil moisture data assimilation. Paper of Masters Degree. Kyungpook National University. pp.1-49.
15 Son, K.H. 2010. Assessment of Global Hydrologic Model on East Asia Regio. Paper of Masters Degree. Sejong University. pp.1-71.
16 McNally, A., Arsenault, K., Kumar, S., Shukla, S., Peterson, P., Wang, S. and Verdin, J.P. 2017. A Land Data Assimilation System for sub-Saharan Africa Food and Water Security Applications. Scientific data. 4(1):1-19.
17 Pachauri, R.K., Allen, M.R., Barros, V.R., Broome, J., Cramer, W., Christ, R. ... and Dubash, N.K. 2014. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Ipcc. 151pp.
18 Peters-Lidard, C.D., Houser, P.R., Tian, Y., Kumar, S.V., Geiger, J., Olden, S. ... and Mitchell, K. 2007. High-performance Earth system modeling with NASA/GSFC's Land Information System. Innovations in Systems and Software Engineering. 3(3):157-165.   DOI
19 Rosero, E., Gulden, L.E. Yang, Z.L., De Goncalves, L.G., Niu, G.Y. and Kaheil, Y.H. 2011. Ensemble evaluation of hydrologically enhanced Noah-LSM: Partitioning of the water balance in high-resolution simulations over the Little Washita River experimental watershed. Journal of Hydrometeorology. 12(1):45-64.   DOI
20 Sheffield, J., Goteti, G. and Wood, E. F. 2006. Development of a 50-year High-resolution Global Dataset of Meteorological Forcings for Land Surface Modeling. Journal of Climate. 19(13):3088-3111.   DOI
21 Wang, A., Lettenmaier, D.P. and Sheffield, J. 2011. Soil Moisture Drought in China, 1950-2006. Journal of Climate. 24(13): 3257-3271.   DOI
22 Xu, C.Y. and Singh, V.P. 2005. Evaluation of three complementary relationship evapotranspiration models by water balance approach to estimate actual regional evapotranspiration in different climatic regions. Journal of Hydrology. 308(1-4):105-121.   DOI
23 MOIS. 2018. Statistical yearbook of natural disaster.
24 Nijssen, B., Schnur, R. and Lettenmaier, D.P. 2001. Global retrospective estimation of soil moisture using the variable infiltration capacity land surface model. 1980-93. Journal of Climate, 14(8):1790-1808.   DOI