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A Study on Soil Moisture Estimates Performance Using Various Land Surface Models

다양한 지표모형을 활용한 토양수분 예측 성능 평가 연구

Ye-Geun Janga
,
Seoung-Hun Sinb
,
Tae-Hwa Leec
,
Won-Seok Jangd
,
Yong-Chul Shine
,
Keun-Chang Jangf
,
Jung-Hwa Chung
,
Jong-Gun Kimh†
장 예근a
,
신 승훈b
,
이 태화c
,
장 원석d
,
신 용철e
,
장 근창f
,
천 정화g
,
김 종건h†
aUndergraduate Student, Department of Regional Infrastructure Engineering, Kangwon National University
bUndergraduate Student, Department of Regional Infrastructure Engineering, Kangwon National University
cPh.D. Student, Major in Agricultural Civil Engineering, School of Agricultural Civil & Bio-Industrial Engineering, Kyoungpook National University
dResearch Fellow, Division of Public Infrastructure Assessment, Environmental Assessment Group, Korea Environment Institute
eAssociate Professor, Major in Agricultural Civil Engineering, School of Agricultural Civil & Bio-Industrial Engineering, Kyoungpook National University
fResearch Scientist, Division of Forest ICT Research Center, National Institute of Forest Science
gSenior Researcher, Division of Forest ICT Research Center, National Institute of Forest Science
hAssistant Professor, Department of Regional Infrastructure Engineering, Kangwon National University
a강원대학교 지역기반공학과 학부생
b강원대학교 지역기반공학과 학부생
c경북대학교 농업토목바이오산업공학부 농업토목공학전공 박사과정 학생
d한국환경연구원 환경평가단 공공기반시설평가과 연구위원
e경북대학교 농업토목생명공학부 농업토목공학전공 부교수
f국립산림과학원 산림정보통신연구센터 연구과학자
g국립산림과학원 산림정보통신연구센터 선임연구원
h강원대학교 지역기반공학과 조교수
† Corresponding author Tel.: +82-33-250-6467 E-mail: kimjg23@gmail.com
2022. pp. 79-89
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Abstract

Soil moisture is significantly related to crop growth and plays an important role in irrigation management. To predict soil moisture, various process-based model has been developed and used in the world. Various models (Land surface model) may have different performance depending on the model parameters and structures that causes the different model output for the same modeling condition. In this study, the three land surface models (Noah Land Surface Model, Soil Water Atmosphere Plant, Community Land Model) were used to compare the model performance (soil moisture prediction) and develop the multi-model simulation. At first, the genetic algorithm was used to estimate the optimal soil parameters for each model, and the parameters were used to predict soil moisture in the study area. Then, we used the multi-model approach based on Bayesian model averaging (BMA). The results derived from this approach showed a better match to the measurements than the results from the original single land surface model. In addition, identifying the strengths and weaknesses of the single model and utilizing multi-model methods can help to increase the accuracy of soil moisture prediction.

Keywords
Soil-moisture
land-surface-model
parameterization
multi-model
BMA
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Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 64
  • No :1
  • Pages :79-89
  • Received Date : 2021-10-12
  • Revised Date : 2021-12-15
  • Accepted Date : 2021-12-16
  • DOI :https://doi.org/10.5389/KSAE.2022.64.1.079
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