All Issue

2024 Vol.57, Issue 12

Research Article

Estimating rainfall using soil moisture data: application and validation of the SM2RAIN in the Korean Peninsula

토양수분 자료를 활용한 강우량 추정: 한반도에서의 SM2RAIN 알고리즘의 적용과 검증

Doyoung Kima
,
Seungkeun Chob
,
Shinhyeon Choc
,
Minha Choidef*
김 도영a
,
조 성근b
,
조 신현c
,
최 민하def*
aPh.D. Student, Department of Global Smart City, Sungkyunkwan University, Suwon, Korea
bPh.D. Candidate, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
cMaster Student, Department of Global Smart City, Sungkyunkwan University, Suwon, Korea
dProfessor, Department of Water Resources, Sungkyunkwan University, Suwon, Korea
eProfessor, School of Civil, Architecture Engineering and Landscape Architecture, Sungkyunkwan University, Suwon, Korea
fProfessor, Department of Global Smart City, Sungkyunkwan University, Suwon, Korea
a성균관대학교 글로벌스마트시티융합전공 박사과정
b성균관대학교 수자원전문대학원 수자원학과 박사수료
c성균관대학교 글로벌스마트시티융합전공 석사과정
d성균관대학교 수자원전문대학원 수자원학과 교수
e성균관대학교 건설환경공학부 교수
f성균관대학교 글로벌스마트시티융합전공 교수
*Corresponding Author
31 December 2024. pp. 977-988
PDF XML Citation
Abstract

The Korean Peninsula experiences significant seasonal variations in rainfall, making regional monitoring critical for effective water resource management. While current rainfall monitoring is densely conducted based on in-situ measurements, the acceleration of climate change necessitates rainfall data with finer spatial resolution. This study evaluates the performance of SM2RAIN in estimating rainfall across diverse soil and rainfall conditions in the Korean Peninsula and examines its applicability in monsoon climates using both in-situ and spatial soil moisture data. The results indicate that SM2RAIN, utilizing in-situ soil moisture data, demonstrated strong rainfall estimation performance in all regions except Bosung, with statistical indicators of Nash-Sutcliffe Efficiency (NSE) ranging from 0.52 to 0.94, correlation coefficient (R) from 0.73 to 0.97, and Root Mean Square Error (RMSE) from 6.09 to 29.44 mm/hr. Conversely, rainfall estimation using SMAP L4 soil moisture data exhibited limitations due to temporal and spatial resolution constraints, with NSE values between 0.33 and 0.67, R from 0.57 to 0.83, and RMSE from 10.09 to 20.25 mm/hr, showing discrepancies in accuracy compared to in-situ data. However, SMAP L4 data proved useful for medium- to long-term rainfall forecasting. This study confirms that optimizing the parameters to SM2RAIN enables accurate and reliable rainfall estimation.

Keywords
Soil moisture
Rainfall
SM2RAIN
Monsoon climate
SMAP L4

한반도는 강우량의 계절적 편차가 크게 나타나 효율적인 수자원 관리를 위해 지역별 강우 모니터링이 중요하다. 현재의 강우 모니터링은 지점 관측을 중심으로 조밀하게 수행되고 있으나, 기후변화의 가속화에 따라 보다 정밀한 공간 해상도의 강우 관측자료가 요구되고 있다. 본 연구에서는 한반도의 다양한 토양 및 강우 조건에서 SM2RAIN의 강우 추정 성능을 평가하고, 지점 및 공간 토양수분 자료를 활용하여 monsoon 기후에서의 적용 가능성을 분석하였다. 연구 결과, 지점 토양수분 자료를 활용한 SM2RAIN은 Nash-Sutcliffe Efficiency (NSE) 0.52~0.94, 상관계수(R) 0.73~ 0.97, Root Mean Square Error (RMSE) 6.09~29.44 mm/hr의 통계 지표를 보여 보성지역 이외에는 강우 모의 성능이 우수한 것으로 나타났다. 반면에, SMAP L4 토양수분 자료를 활용한 강우 추정은 시간 및 공간 해상도의 제약으로 NSE 0.33~0.67, R 0.57~0.83, RMSE 10.09~20.25 mm/hr의 통계 값을 나타내어 지점 자료 대비 정확도에서 차이가 있었으나, SMAP L4 자료는 중·장기 강우 예측에 유용하다는 것을 확인하였다. 본 연구를 통하여 SM2RAIN의 매개 변수를 최적화함으로써 정확하고 신뢰성 있는 강우 추정이 가능함을 확인하였다.

키워드
토양수분
강우
SM2RAIN
몬순 기후
SMAP L4
References
1

Baik, J., Park, J., Kim, K., and Choi, M. (2018). "Assessment and merging technique for GPM satellite precipitation product using ground based measurement." Journal of Korea Water Resources Association, Vol. 51, No. 2, pp. 131-40.

2

Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Schüller, L., Bojkov, B., and Wagner, W. (2019). "SM2 RAIN-ASCAT (2007-2018): Global daily satellite rainfall data from ASCAT soil moisture observations." Earth System Science Data, Vol. 11, No. 4, pp. 1583-1601.

10.5194/essd-11-1583-2019
3

Brocca, L., Massari, C., Ciabatta, L., Moramarco, T., Penna, D., Zuecco, G., Pianezzola, L., Borga, M., Matgen, P., and Martínez-Fernández, J. (2015). "Rainfall estimation from in situ soil moisture observations at several sites in Europe: An evaluation of the SM2RAIN algorithm." Journal of Hydrology and Hydromechanics, Vol. 63, No. 3, pp. 201-209.

10.1515/johh-2015-0016
4

Brocca, L., Moramarco, T., Melone, F., and Wagner, W. (2013). "A new method for rainfall estimation through soil moisture observations." Geophysical Research Letters, Vol. 40, No. 5, pp. 853-858.

10.1002/grl.50173
5

Cho, E., and Choi, M. (2014). "Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula." Journal of Hydrology, Vol. 516, pp. 317-329.

10.1016/j.jhydrol.2013.12.053
6

Choi, S.-W., Park, J., Kang, M., Kim, J., Sohn, S., Cho, S., Chun, H., and Jung, K.-Y. (2022). "Development of correction formulas for KMA AAOS soil moisture observation data." Korean Journal of Agricultural and Forest Meteorology, Vol. 24, No. 1, pp. 13-34.

7

Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S., Paulik, C., Dorigo, W., Kidd, R., and Wagner, W. (2018). "SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture." Earth System Science Data, Vol. 10, No. 1, pp. 267-280.

10.5194/essd-10-267-2018
8

Colliander, A., Jackson, T., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh, M., Dunbar, R., Dang, L., Pashaian, L. et al. (2017). "Validation of SMAP surface soil moisture products with core validation sites." Remote Sensing of Environment, Vol. 191, pp. 215-231.

10.1016/j.rse.2017.01.021
9

Du, J., Kimball, J.S., Chan, S.K., Chaubell, M.J., Bindlish, R., Dunbar, R.S., and Colliander, A. (2023). "Assessment of surface fractional water impacts on SMAP soil moisture retrieval." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 16, pp. 4871-4881.

10.1109/JSTARS.2023.3278686
10

Entekhabi, D., Njoku, E.G., O'Neill, P.E., Kellogg, K.H., Crow, W.T., Edelstein, W.N., Entin, J.K., Goodman, S.D., Jackson, T.J., Johnson, J. et al. (2010). "The Soil Moisture Active Passive (SMAP) mission." Proceedings of the IEEE, Vol. 98, No. 5, pp. 704-716.

10.1109/JPROC.2010.2043918
11

Famiglietti, J.S., and Wood, E.F. (1994). "Multiscale modeling of spatially variable water and energy balance processes." Water Resources Research, Vol. 30, pp. 3061-3078.

10.1029/94WR01498
12

Furtak, K., and Wolinska, A. (2023). "The impact of extreme weather events as a consequence of climate change on the soil moisture and on the quality of the soil environment and agriculture - a rev-iew." Catena, Vol. 231, 107378.

10.1016/j.catena.2023.107378
13

Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P., and Yoo, S.H. (2015). "NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG)." Algorithm theoretical basis document (ATBD) version, 4(26), NASA/GSFC, Greenbelt, MD, U.S., pp. 8-23.

14

Jongjin, B., Jongmin, P., Dongryeol, R., and Minha, C. (2016). "Geospatial blending to improve spatial mapping of precipitation with high spatial resolution by merging satellite-based and ground-based data." Hydrological Processes, Vol. 30, No. 16, pp. 2789-2803.

10.1002/hyp.10786
15

Kang, M., Hao, Y., and Choi, M. (2023). "The effects of flash drought on the terrestrial ecosystem in Korea." Journal of Hydrology, Vol. 624, 129874.

10.1016/j.jhydrol.2023.129874
16

Kim, H.R., Moon, M., Yun, J., and Ha, K.J. (2023a). "Trends and spatio-temporal variability of summer mean and extreme precipitation across South Korea for 1973-2022." Asia-Pacific Journal of Atmospheric Sciences, Vol. 59, No. 3, pp. 385-398.

10.1007/s13143-023-00323-737359475PMC10078061
17

Kim, K., Park, J., Baik, J., and Choi, M. (2017). "Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia." Atmospheric Research, Vol. 187, pp. 95-105.

10.1016/j.atmosres.2016.12.007
18

Kim, S., Kwon, J.H., Om, J.S., Lee, T., Kim, G., Kim, H., and Heo, J.H. (2023b). "Increasing extreme flood risk under future climate change scenarios in South Korea." Weather and Climate Extremes, Vol. 39, 100552.

10.1016/j.wace.2023.100552
19

Koohi, S., Azizian, A., and Brocca, L. (2021). "Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran." Science of the Total Environment, Vol. 779, 146535.

10.1016/j.scitotenv.2021.14653534030270
20

Lai, Y., Tian, J., Kang, W., Gao, C., Hong, W., and He, C. (2022). "Rainfall estimation from surface soil moisture using SM2RAIN in cold mountainous areas." Journal of Hydrology, Vol. 606, 127430.

10.1016/j.jhydrol.2022.127430
21

Lee, C.S., Sohn, E., Park, J.D., and Jang, J.D. (2019). "Estimation of soil moisture using deep learning based on satellite data: A case study of South Korea." GIScience & Remote Sensing, Vol. 56, No. 1, pp. 43-67.

10.1080/15481603.2018.1489943
22

Massari, C., Brocca, L., Pellarin, T., Abramowitz, G., Filippucci, P., Ciabatta, L., Maggioni, V., Kerr, Y., and Fernandez Prieto, D. (2020). "A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products." Hydrology and Earth System Sciences, Vol. 24, No. 5, pp. 2687-2710.

10.5194/hess-24-2687-2020
23

Mosaffa, H., Filippucci, P., Massari, C., Ciabatta, L., and Brocca, L. (2023). "SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies." Scientific Data, Vol. 10, No. 1, 749.

10.1038/s41597-023-02654-637907558PMC10618238
24

Neelin, J.D., Martinez-Villalobos, C., Stechmann, S.N., Ahmed, F., Chen, G., Norris, J.M., Kuo, Y.H., and Lenderink, G. (2022). "Precipitation extremes and water vapor: relationships in current climate and implications for climate change." Current Climate Change Reports, Vol. 8, No. 1, pp. 17-33.

10.1007/s40641-021-00177-z
25

Park, J.S., Kang, H.S., Lee, Y.S., and Kim, M.K. (2011). "Changes in the extreme daily rainfall in South Korea." International Journal of Climatology, Vol. 31, No. 15,pp. 2290-2299.

10.1002/joc.2236
26

Piepmeier, J.R., Johnson, J.T., Mohammed, P.N., Bradley, D., Ruf, C., Aksoy, M., Garcia, R., Hudson, D., Miles, L., and Wong, M. (2014). "Radio-frequency interference mitigation for the soil moisture active passive microwave radiometer." IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, No. 1, pp. 761-775.

10.1109/TGRS.2013.2281266
27

Reichle, R.H., De Lannoy, G.J.M., Liu, Q., Ardizzone, J.V., Colliander, A., Conaty, A., Crow, W., Jackson, T.J., Jones, L.A., Kimball, J.S. et al. (2017). "Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements." Journal of Hydrometeorology, Vol. 18, No. 10, pp. 2621-2645.

10.1175/JHM-D-17-0063.1
28

Reichle, R.H., Liu, Q., Ardizzone, J.V., Crow, W.T., De Lannoy, G.J.M., Dong, J., Kimball, J.S., and Koster, R.D. (2021). "The contributions of gauge-based precipitation and SMAP brightness temperature observations to the skill of the SMAP Level-4 soil moisture product." Journal of Hydrometeorology, Vol. 22, No. 2, pp. 405-424.

10.1175/JHM-D-20-0217.1
29

Saeedi, M., Sharafati, A., Brocca, L., and Tavakol, A. (2022). "Estimating rainfall depth from satellite-based soil moisture data: A new algorithm by integrating SM2RAIN and the analytical net water flux models." Journal of Hydrology, Vol. 610, 127868.

10.1016/j.jhydrol.2022.127868
30

Soldo, Y., le Vine, D.M., Bringer, A., de Matthaeis, P., Oliva, R., Johnson, J.T., and Piepmeier, J.R. (2018). "Location of radio- frequency interference sources using the SMAP L-band radiometer." IEEE Transactions on Geoscience and Remote Sensing, Vol. 56, No. 11, pp. 6854-6866.

10.1109/TGRS.2018.2844127
Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 57
  • No :12
  • Pages :977-988
  • Received Date : 2024-05-27
  • Revised Date : 2024-11-01
  • Accepted Date : 2024-11-05
  • DOI :https://doi.org/10.3741/JKWRA.2024.57.12.977
Journal Informaiton Journal of Korea Water Resources Association Journal of Korea Water Resources Association
Online Submission
Archives
  • scopus
  • KCI-수자원
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close