• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.721-728
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• 2023

Agricultural drought is triggered by a depletion of moisture content in the soil, which hinders photosynthesis and thus increases carbon dioxide (CO₂) concentrations in the atmosphere. The aim of this study is to analyze the relationship between soil moisture (SM) and vegetation activity toward quantifying CO₂ concentration in the atmosphere. To this end, the MODerate resolution imaging spectroradiometer (MODIS), an optical multispectral sensor, was used to evaluate two regions in South Korea for validation. Vegetation activity was analyzed through MOD13A1 vegetation indices products, and MODIS gross primary productivity (GPP) product was used to calculate the CO₂ flux based on its relationship with respiration. In the case of SM, it was calculated through the method of applying apparent thermal inertia (ATI) in combination with land surface temperature and albedo. To validate the SM and CO₂ flux, flux tower data was used which are the observed measurement values for the extreme drought period of 2014 and 2015 in South Korea. These two variables were analyzed for temporal variation on flux tower data as daily time scale, and the relationship with vegetation index (VI) was synthesized and analyzed on a monthly scale. The highest correlation between SM and VI (correlation coefficient (r) = 0.82) was observed at a time lag of one month, and that between VI and CO₂ (r = 0.81) at half month. This regional study suggests a potential capability of MODIS-based SM, VI, and CO₂ flux, which can be applied to an assessment of the global view of the agricultural drought by using available satellite remote sensing products.

• Spatial Information Research
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• v.7 no.1
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• pp.39-48
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• 1999

A GRId-based Soil MOsture Routing Model(GRISMORM) which predicts temporal variation and spatial distribution of water balance on a daily time step for each grid element of the watershed was developed. The model was programmed by C-language which aims for high flexibility to any kind of GIS softwares. The model uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System)-GIS and generates daily or monthly spatial distribution map of water balance components within the watershed. The model was applied to Ipyunggyo watershed(75.6$km^2$) ; the part of Bocheongchun watershed. Predicted streamflows resulting from two years(95 and 96) daily data were compared with those observed at the watershed outlet. The results of temporal variation and spatial distribution of soil moisture are also presented by using GRASS.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.61-72
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• 2000

The purpose of this study is to improve the method of evaluating groundwater recharge by using grid-based soil moisture routing technique. A model which predicts temporal variation and spatial distribution of soil moisture on a daily time step was developed. The model uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System)-GIS and can generate daily and monthly spatial distribution map of surface runoff, soil moisture content, evapotranspiration within the watershed. The model was applied to Ipyunggyo watershed($75.6\;\textrm{km}^2$) located in the upstream of Bocheongchun watershed. Seven maps; DEM(Digital Elevation Mode]), stream, flow path, soil, land use, Thiessen network and free groundwater level, were used for input data. Predicted streamflows resulting from two years (l995, 1996) daily data were compared with the observed values at the watershed outlet. The results of temporal variations and spatial distributions of soil moisture are presented by using GRASS GIS. As a final result, the monthly predicted groundwater recharge was presented.sented.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.152-163
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• 2020

The present study introduces a procedure to prepare and manage a high-resolution rainfall and soil moisture (SM) database in the LAMP prediction system, especially for landslide researchers. The procedure also includes converting the data into spatial resolution suitable for their interest regions following proper map projection methods. The LAMP model precipitation and SM data are quantitatively and qualitatively evaluated to identify the model prediction characteristics using the ERA5 reanalysis precipitation and observed 10m depth SM data. A detailed process of converting LAMP Weather Research and Forecasting (WRF) output data for 10m horizontal resolution is described in a step-wise manner, providing technical convenience for users to easily convert NetCDF data from the WRF model into TIF data in ArcGIS. The converted data can be viewed and downloaded via the LAMP website (http://df.ncam.kr/lamp/index.do) of the National Center for AgroMeteorology. The constructed database will contribute to monitoring and prediction of landslide risk prior to landslide response steps and should be data quality controlled by more observation data.

• Korean Journal of Plant Resources
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• v.27 no.5
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• pp.546-555
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• 2014

The final aim of this study is to develop a biofiltration system integrated with plant vegetation for improving indoor air quality effectively depending on indoor space and characteristics. However, to approach this final goal, several requirements such as constant pressure drops (PDs) and soil moisture contents (SMCs), which influence the capacity design for a proper ventilation rate of biofiltration system, should be satisfied. Thus, this fundamental experiment was carried out to adjust a proper wind speed and to ensure a stabilization of initial SMCs within biofilter for uniform distribution of SMCs and PDs, and for normal plant growth, especially avoiding root stress by wind. Therefore, we designed horizontal biofliter models and manufactured them, and then calculated the ventilation rate, air residence time, and air-liquid ration based on the biofilter depending on three levels of wind speed (1, 2, and $3cm{\cdot}s^{-1}$). The relative humidity (RH) and PD of the humidified air coming out through the soil within the biofilter, and SMC of the soil and plant growth parameters of lettuce and duffy fern grown within biofilter were measured depending on the three levels of wind speed. As a result of wind speed test, $3{\cdot}sec^{-1}$ was suitable to keep up a proper RH, SMC, and plant growth. Thus, the next experiment was set up to be two levels of initial SMCs (low and high initial SMC, 18.5 and 28.7%) within each biofilter operated and a non-biofiltered control (initial SMC, 29.7%) on the same wind speed ($3cm{\cdot}sec^{-1}$), and measured on the RH and PD of the air coming out through the soil within the biofilter, and SMC of the soil and plant growth parameters of Humata tyermani grown within biofilter. This result was similar to the first results on RHs, SMCs, and PDs keeping up with constant levels, and three SMCs did not show any significant difference on plant growth parameters. However, two biofiltered SMCs enhanced dry weights of the plants slightly than non-biofiltered SMC. Thus, the stability of this biofiler system keeping up major physical factors (SMC and PD) deserved to be adopted for designing an advanced integrated biofilter model in the near future.

• Water for future
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• v.49 no.9
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• pp.44-54
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• 2016

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.88-99
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• 2007

Soil moisture is one of the essential components in determining surface hydrological processes such as infiltration, surface runoff as well as meteorological, ecological and water quality responses at watershed scale. This paper discusses soil moisture transfer processes measured at hillslope scale in the Gwangneung forest catchment to understand and provide the basis of stochastic structures of soil moisture variation. Measured soil moisture series were modelled based upon the developed univariate model platform. The modeling consists of a series of procedures: pre-treatment of data, model structure investigation, selection of candidate models, parameter estimation and diagnostic checking. The spatial distribution of model is associated with topographic characteristics of the hillslope. The upslope area computed by the multiple flow direction algorithm and the local slope are found to be effective parameters to explain the distribution of the model structure. This study enables us to identify the key factors affecting the soil moisture distribution and to ultimately construct a realistic soil moisture map in a complex landscape such as the Gwangneung Supersite.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.131-140
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• 2011

In this study, temporal variations of the Advanced Microwave Scanning Radiometer E (AMSR-E) soil moisture products were evaluated using ground based measurements from the Haenam flux monitoring network site for two years (2004 and 2006). Even if there were major comparison issues including spatial resolutions, AMSR-E soil moisture production showed a great potential to replicate temporal variability patterns with ground based measurements. Additional intensive validation efforts should be conducted at a variety of field conditions including vegetation type for better utilization of remotely sensed soil moisture and understanding of the land surface-atmosphere interactions in the view of hydrometeorology.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.942-942
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• 2012

강우-유출에 대한 수문해석에 있어 유효강우량 산정방법으로는 여러 가지가 있으나 국내외로 미농무부(United States Department of Agriculture)에서 제안한 NRCS-CN 방법이 널리 사용되고 있다. SCS-CN 방법은 1개의 매개변수만을 사용하여 방법이 간략하고 유역 토양특성의 반영이 가능하다는 장점이 있으나 공간적 규모에 따른 효과반영이 불가하고 초기손실우량비를 0.2로 고정하는 가정의 문제점 등이 있다. 많은 연구자들이 SCS-CN 방법의 문제점을 보완하고자 다양한 방법을 제시하였으며 특히 Michel 등(2005)은 토양수분계산가정(Soil Moisture Accounting Procedure)에서 유출기준저류고를 새로운 매개변수로 제안하여 초기손실우량비 가정의 불합리성을 개선하고 새로운 AMC 조건식을 산정하였다. 그러나 범용적인 AMC 조건식을 제안하고자 140개 유역에 적용한 결과를 통해 유출기준저류고는 토양의 최대잠재보유수량의 1/3으로 일괄 적용하는 문제점이 있으며, 민감도분석을 통해 전체 결과의 효율이 좋은 값으로 선정하였다. 이에 본 연구에서는 일 단위 집중형 장기유출모형인 GR4J(Ge'nie Rural a' 4 parame'tres Journalier)를 Michel이 제안한 모형을 적용하기 위해 선정하였으며 토양수분계산과정에서 새로운 매개변수인 유출기준저류고를 최적화기법인 화음탐색법을 적용하여 결정하였다. 적용대상은 국내의 달방댐, 횡성댐, 섬진강댐, 청주댐, 대청댐유역에 적용하였으며 본 연구에서 제안한 방법이 강우-유출 결과의 정확성을 향상시키는 것을 볼 수 있었다. 최종적으로 최적화된 유출기준저류고와 유역크기와의 상관성분석을 통하여 관계식을 도출하였다. 토양수분과정에 대한 고려는 유출량을 산정하는 데 있어서 정확성을 높이는 데 기여할 수 있으며 더불어 본 연구에서 제안한 관계식을 통하여 유출기준저류고와 유역특성과의 연관성을 확인할 수 있었다.