• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.285-291
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• 2011

Accurate assessment of the water and energy cycles is essential to understand hydrologic, climatologic, and ecological processes. Common Land Model (CLM) is one of the well-developed Soil-Vegetation-Atmosphere Transfer (SVAT) models based on the water and energy balance equation for accurate prediction of hydro-environmental cycles. The CLM can estimate realistic and reliable results using relatively simple parameters. It has been widely used in the world, however in Korea practical applications of the CLM are rare due to lack of information and input data. In this study, the CLM with Korea Flux network (KoFlux) and Kore Land Data Assimilation System (KLDAS) data were individually validated for domestic applications. This study showed that all comparisons between observations and model results from KoFlux and KLDAS had reasonable correlation with determination coefficient of 0.73~1.00 via regression. The results confirmed the applicability of the CLM and the possibility of the KLDAS usage for the region where input data are not existed.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.108-108
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• 2011

기후 변화로 인한 수문 환경의 변화에 따라 수문 모형을 이용한 정확한 예측이 필요하다. 수문 현상의 예측을 위하여 사용되고 있는 수문 모형인 Common Land Model(CLM)은 Soil-Vegetation-Atmosphere Transfer(SVAT) 모형 중 하나로 비교적 적은 변수를 이용하여 현실적인 결과를 도출하므로 세계적으로 널리 이용되고 있다. 이에 반해 국내에서는 모형의 구동을 위한 입력 자료의 미흡으로 인해 실질적인 연구 사례가 부족한 실정이다. 본 연구에서는 해남의 KoFlux 지점을 대상으로 Korea Flux Network(KoFlux) 자료와 Korea Land Data Assimilation System(KLDAS) 자료를 CLM에 강제시켜 국내의 모형의 적용성에 대하여 검증하였다. KoFlux는 에디 공분산 시스템을 기반으로 지표면과 대기 사이의 Flux에 대한 측정 시스템을 운영하며 SVAT 모형의 구동을 위한 수문학적 인자들을 제공하고 있으며, KLDAS는 한반도지표동화자료체계로 위성 및 현장기반 관측 자료들을 지면모형에 적용시켜 자료동화방법을 통하여 지표 변수들을 제공하고 있다. 모형의 산출 결과는 해남 지점의 관측 자료와 비교를 통하여 CLM 모형의 적용 가능성을 검증하였고 두 결과 모두 관측 데이터와의 경향성이 일치하는 것으로 나타났다. 결과 모두 신뢰할 만한 값으로 추정되며, 이를 통하여 국내의 CLM 모형 적용 가능성을 확인하였고, 국내에서의 지점 자료가 부족한 부분에 대한 KLDAS 자료의 이용 가능성 또한 확인하였다.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.172-172
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• 2011

The interaction between land surface and atmosphere is essentially affected by hydrometeorological variables including soil moisture. Accurate estimation of soil moisture at spatial and temporal scales is crucial to better understand its roles to the weather systems. The KLDAS(Korea Land Data Assimilation System) is a regional, specifically Korea peninsula land surface information systems. As other prior land data assimilation systems, this can provide initial soil field information which can be used in atmospheric simulations. For this study, as an enabling high-resolution tool, weather research and forecasting(WRF-ARW) model is applied to produce precipitation data using GFS(Global Forecast System) with GFS embedded and KLDAS soil moisture information as initialization data. WRF-ARW generates precipitation data for a specific region using different parameters in physics options. The produced precipitation data will be employed for simulations of Hydrological Models such as HEC(Hydrologic Engineering Center) - HMS(Hydrologic Modeling System) as predefined input data for selected regional water responses. The purpose of this study is to show the impact of a hydrometeorological variable such as soil moisture in KLDAS on hydrological consequences in Korea peninsula. The study region, Chongmi River Basin, is located in the center of Korea Peninsular. This has 60.8Km river length and 17.01% slope. This region mostly consists of farming field however the chosen study area placed in mountainous area. The length of river basin perimeter is 185Km and the average width of river is 9.53 meter with 676 meter highest elevation in this region. We have four different observation locations : Sulsung, Taepyung, Samjook, and Sangkeug observatoriesn, This watershed is selected as a tentative research location and continuously studied for getting hydrological effects from land surface information. Simulations for a real regional storm case(June 17~ June 25, 2006) are executed. WRF-ARW for this case study used WSM6 as a micro physics, Kain-Fritcsch Scheme for cumulus scheme, and YSU scheme for planetary boundary layer. The results of WRF simulations generate excellent precipitation data in terms of peak precipitation and date, and the pattern of daily precipitation for four locations. For Sankeug observatory, WRF overestimated precipitation approximately 100 mm/day on July 17, 2006. Taepyung and Samjook display that WRF produced either with KLDAS or with GFS embedded initial soil moisture data higher precipitation amounts compared to observation. Results and discussions in detail on accuracy of prediction using formerly mentioned manners are going to be presented in 2011 Annual Conference of the Korean Society of Hazard Mitigation.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.65-81
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• 2021

In this study, soil moisture and evapotranspiration were calculated throughout South Korea using the Korea Land Data Assimilation System(KLDAS) of the Korea-Land Surface Information System(K-LIS) built on the basis of the Land Information System (LIS). The hydrometeorological data sets used to drive K-LIS and build KLDAS are MERRA-2(Modern-Era Retrospective analysis for Research and Applications, version 2) GDAS(Global Data Assimilation System) and ASOS(Automated Synoptic Observing System) data. Since ASOS is a point-based observation, it was converted into grid data with a spatial resolution of 0.125° for the application of KLDAS(ASOS-S, ASOS-Spatial). After comparing the hydrometeorological data sets applied to KLDAS against the ground-based observation, the mean of R² ASOS-S, MERRA-2, and GDAS were analyzed as temperature(0.994, 0.967, 0.975), pressure(0.995, 0.940, 0.942), humidity (0.993, 0.895, 0.915), and rainfall(0.897, 0.682, 0.695), respectively. For the hydrologic output comparisons, the mean of R² was ASOS-S(0.493), MERRA-2(0.56) and GDAS (0.488) in soil moisture, and the mean of R² was analyzed as ASOS-S(0.473), MERRA-2(0.43) and GDAS(0.615) in evapotranspiration. MERRA-2 and GDAS are quality-controlled data sets using multiple satellite and ground observation data, whereas ASOS-S is grid data using observation data from 103 points. Therefore, it is concluded that the accuracy is lowered due to the error from the distance difference between the observation data. If the more ASOS observation are secured and applied in the future, the less error due to the gridding will be expected with the increased accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.298-306
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• 2010

In this study, we evaluated the performance of Korea Land Data Assimilation System (KLDAS) for the estimation of evapotranspiration (ET) by comparing the modeled against the observed ET at Gwangneung deciduous forest of KoFlux site (GDK) from 2006 to 2008. Although the magnitudes of ET by KLDAS overestimated the observed ET, the seasonal patterns of KLDAS ET were comparable with the correlation coefficient of 0.78. The difference between the KLDAS ET and the observed ET was larger in spring and summer due to rapid plant growth and frequent rainfalls with high cloud cover, respectively. Compared to the ET estimated by NASA Global Land Data Assimilation System (GLDAS) with $0.25^{\circ}$ and $1^{\circ}$ resolution, the ET by KLDAS with 10 km resolution showed better agreement with the observation at the GDK site. Albeit further improvement is necessary, our results suggest that KLADS can be used as a practical tool to map ET and to examine its spatiotemporal variability over the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1611-1623
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• 2021

Thisstudy demonstratessoil moisture and evapotranspiration performance using Korea Land Data Assimilation System (KLDAS) under Korea Land Information System (KLIS). Spin-up was repeated 8 times in 2018. In addition, low-resolution and high-resolution meteorological data were generated using meteorological data observed by Korea Meteorological Administration (KMA), Rural Development Administration (RDA), Korea Rural Community Corporation (KRC), Korea Hydro & Nuclear Power Co.,Ltd. (KHNP), Korea Water Resources Corporation (K-water), and Ministry of Environment (ME), and applied to KLDAS. And, to confirm the degree of accuracy improvement of Korea Low spatial resolution (hereafter, K-Low; 0.125°) and Korea High spatial resolution (hereafter, K-High; 0.01°), soil moisture and evapotranspiration to which Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and ASOS-Spatial (ASOS-S) used in the previous study were applied were evaluated together. As a result, optimization of the initial boundary condition requires 2 time (58 point), 3 time (6 point), and 6 time (3 point) spin-up for soil moisture. In the case of evapotranspiration, 1 time (58 point) and 2 time (58 point) spin-ups are required. In the case of soil moisture to which MERRA-2, ASOS-S, K-Low, and K-High were applied, the mean of R² were 0.615, 0.601, 0.594, and 0.664, respectively, and in the case of evapotranspiration, the mean of R² were 0.531, 0.495, 0.656, and 0.677, respectively, indicating the accuracy of K-High was rated as the highest. The accuracy of KLDAS can be improved by securing a large number of ground observation data through the results of this study and generating high-resolution grid-type meteorological data. However, if the meteorological condition at each point is not sufficiently taken into account when converting the point data into a grid, the accuracy is rather lowered. For a further study, it is expected that higher quality data can be produced by generating and applying grid-type meteorological data using the parameter setting of IDW or other interpolation techniques.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.350-353
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• 2011

전 세계적으로 기후변화로 인한 자연재해가 빈번하게 발생함에 따라 수자원 분야에서 또한 환경의 변화에 대한 정확한 예측이 더욱 요구되고 있다. 국내에서도 이를 위하여 다양한 방법을 통하여 연구가 이루어지고 있으나 본 연구에서 사용된 Common Land Model (CLM)은 국내에서의 실질적인 적용이 아직 부족하다. 이 모형은 Soil-Vegetation-Atmosphere Transfer 모형 중 대표적 모델로 Land Surface Model (LSM), Biosphere-Atmosphere Transfer Scheme (BATS), Chinese Academy of Sciences Institute of Atmospheric Physics LSM의 세 모형이 결합되어 발전하였다. CLM의 강제입력자료로는 위성, 지면모형 등을 기반으로 만들어진 자료를 제공하는 Korea Land Data Assimilation Systme (KLDAS; 한반도지표자료동화체계)의 격자화 된 자료를 사용하여 모형에 강제시켰다. KLDAS는 기존의 Land Data Assimilation System (LDAS)에서 발전한 형태로 동아시아 지역을 대상으로 자료를 제공하고 있으며, 본 연구에서는 이 자료를 사용하여 국내 전반에 걸쳐 격자에 대한 수문 기상학적 인자를 산출하였다.