• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.153-153
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• 2019

Evapotranspiration (ET) is an important component of hydrological processes. Accurate estimates of ET variation are of vital importance for natural hazard adaptation and water resource management. This study first developed a soil water index (SWI)-based Priestley-Taylor algorithm (SWI-PT) based on the enhanced vegetation index (EVI), SWI, net radiation, and temperature. The algorithm was then compared with a modified satellite-based Priestley-Taylor ET model (MS-PT). After examining the performance of the two models at 10 flux tower sites in different land cover types over East Asia and Australia, the daily estimates from the SWI-PT model were closer to observations than those of the MS-PT model in each land cover type. The average correlation coefficient of the SWI-PT model was 0.81, compared with 0.66 in the original MS-PT model. The average value of the root mean square error decreased from $36.46W/m^2$ to $23.37W/m^2$ in the SWI-PT model, which used different variables of soil moisture and vegetation indices to capture soil evaporation and vegetative transpiration, respectively. By using the EVI and SWI, uncertainties involved in optimizing vegetation and water constraints were reduced. The estimated ET from the MS-PT model was most sensitive (to the normalized difference vegetation index (NDVI) in forests) to net radiation ($R_n$) in grassland and cropland. The estimated ET from the SWI-PT model was most sensitive to $R_n$, followed by SWI, air temperature ($T_a$), and the EVI in each land cover type. Overall, the results showed that the MS-PT model estimates of ET in forest and cropland were weak. By replacing the fraction of soil moisture ($f_{sm}$) with the SWI and the NDVI with the EVI, the newly developed SWI-PT model captured soil evaporation and vegetation transpiration more accurately than the MS-PT model.

• 한국농림기상학회지
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• 제22권1호
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• pp.1-12
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• 2020

토양수분은 농업에서 필수적인 자원으로 이의 변화와 부족을 예측함으로써 관리되어왔다. 최근 현장에서의 적용 용이성과 다양한 지역에 대한 일반화 가능성이 뛰어난 통계 및 기계학습 알고리즘을 활용한 토양수분 예측 연구가 활발히 진행되고 있다. 하지만 국내에서 생성되는 데이터를 이용한 연구들은 부족한 실정이다. 이에 본 연구는 1) 국내 공공기상 데이터만으로 충분한 성능을 내는 토양수분 예측 모델을 만들 수 있는지, 2) 어떠한 기계학습 모델이 국내에서 생산되는 데이터와 토양환경에서 가장 높은 예측 성능을 보이는지, 3) 단일 기계학습 모델을 이용해 다양한 지역에 적용 가능한지를 확인해보려 한다. 본 연구에서 Support Vector Machines (SVM), Random Forest (RF), Extremely Randomized Trees (ET), Gradient Boosting Machines (GBM), and Deep Feedforward Network (DFN) 알고리즘과 종관기상관측 자료, 농업기상관측자료를 활용하여 안동, 보성, 철원, 순천 지역의 토양 수분을 예측하는 모델을 만들었다. 그 결과, GBM을 이용한 모델이 R² : 0.96, Root Mean Squared Error(RMSE) : 1.8로 가장 낮은 예측 오차를 보였다. 또한 GBM을 사용한 모델이 가장 낮은 지역간 예측 오차 분산을 보여 가장 일반화하기에 적절한 모델로 확인되었다.

• 한국수자원학회논문집
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• 제49권5호
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• pp.423-429
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• 2016

본 연구에서는 GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer 2 (AMSR2) 센서의 토양수분 자료를 Land Parameter Retrieval Model (LPRM) 알고리즘을 통해 전처리하여 2014년도 한반도 지점관측 자료와의 비교 분석을 수행, 위성 토양수분 자료의 적합성을 평가하였다. 통계 분석 결과 AMSR2 X-band의 토양수분 자료는 38개의 지점관측 자료와 비교해 0.03의 평균 bias, 0.16의 평균 RMSE의 낮은 오차 수준을 보였으며, 최대상관계수는 0.67로 나타났다. 또한 AMSR2 센서의 ascending, descending 시간대별 위성 토양수분자료 분석과 X, C1, C2-band의 주파수 영역별 위성 토양수분 자료 분석 결과, ascending overpass time 시간대와, X-band 주파수의 토양수분자료가 지점 관측 자료와 더 좋은 상관관계를 보였다. 본 연구의 분석 결과는 한반도에서 최근 문제가 되고 있는 가뭄을 비롯한 각종 재해 분석 시 토양수분의 공간적 분포를 연구하는데 활용 될 수 있을 것으로 기대된다.

• 한국지리정보학회지
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• 제23권3호
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• pp.26-67
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• 2020

영상레이더(Synthetic Aperture Radar, SAR)는 기상조건이나 주야, 일조에 상관없이 지표면을 촬영할 수 있고, 토양수분이나 지하수 등 수문인자의 탐색이 가능하여 수자원 분야에서 그 중요성이 점차 두드러지고 있다. SAR는 1970년대부터 인공위성에 탑재되기 시작하여 2020년 현재 15기 이상의 SAR 위성이 운용되고 있고 향후 5년 내에도 10기 내외의 위성이 발사될 예정이다. 최근에는 관측 폭 및 해상도 증진, 다중 편파 및 다중주파수, 관측 각도의 다양화 등 다양한 형태의 SAR 기술들이 개발 및 활용 중이다. 이에 본 고에서는 SAR 시스템의 간략한 역사와 더불어 토양수분 및 수문인자 산출과 관련된 연구동향을 조사하였다. 현재까지 SAR 위성을 활용하여 산출 가능한 수문인자는 토양수분, 해저지하수유출, 강수, 적설분포면적, 식생지수 등이 있으며, 그 중 토양수분은 물리적 모델인 IEM(Integral Equation Model)과 인공지능 기반의 ANN(Artificial Neural Network)을 대표적으로 활용하여 우리나라를 포함한 북미, 유럽, 인도 등 총 17개국에서 연구가 진행되고 있다. 위성 탑재체는 RADARSAT-1, ENVISAT ASAR, 그리고 ERS-1/2가 가장 많이 사용되었으나 현재는 운영이 종료되었으며, 현재 운영 중인 RADARSAT-2, Sentinel-1, SMAP 등의 활용도 점차 늘어나고 있는 것으로 나타났다. 우리나라는 2025년 발사를 목표로 C-band SAR를 탑재한 수자원·수재해 중형위성을 개발 중이므로, SAR를 이용한 다양한 수문인자 산출 연구가 활성화될 것으로 예상된다.

• 농업과학연구
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• 제14권1호
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• pp.68-80
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• 1987

콩의 생육시기별(生育時期別) 증발산량(蒸發散量)과 토양수분(土壤水分) 변화량(變化量)을 추정(推定)하기 위한 토양수분추정모형(土壤水分推定模型)을 설정(設定)하였으며 라이시미터 실험(實驗)을 통한 실측치(實測値)와 비교(比較)한 결과(結果)는 다음과 같다. 1. 라이시미터 실험(實驗)을 통(通)하여 측정(測定)한 실제증발산량(實際蒸發散量)은 405.7mm 이었으며 Pan 증발량법(蒸發量法)과 Hargreaves식(式)에 의한 잠재증발산량(潛在蒸發散量)은 각각(各各) 547.8mm, 586.8mm이었다. 작물(作物)의 생육기간중(生育期間中) 작물계수(作物係數) K는 Table 1 과 같다. 2. 라이시미터 실험을 통한 전생육기간(全生育期間)(133일(日)) 동안의 실제증발산량(實際蒸發散量)은 405.7 mm이었으며 Pan 증발훈법(蒸發暈法)과 Hargreaves식(式)에 의해 추정(推定)된 실제증발산량(實際蒸發散量)은 각각(各各) 424.7mm, 426.1mm였다. 3. 콩의 생육기간별(生育期間別)로 10cm, 30cm, 50cm 깊이에서 관측된 토양수분변화(土壤水分變化)는 10 cm (첫 20cm 토층)에서는 변화(變化)가 크게 나타났으나 30 cm와 50 cm에서는 변화(變化)가 거의 없었다. 모형으로 추정(推定)된 토양수분변화(土壤水分變化)와 관측된 토양수분변화(土壤水分變化)사이에는 아직도 큰 차이가 있으므로 뿌리의 깊이별 토양수분소비형태(土壤水分消費形態)에 대한 연구(硏究)가 요구된다.

• 대한원격탐사학회지
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• 제10권2호
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• pp.17-35
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• 1994

A semi-empirical model for microwave polarimetric radar backscattering from bare soil surfaces was developed using polarmetric radar measurements and the knowledge based on the theoretical and numerical solutions. The microwave polarimetric backscatter measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10` to 70`. Since the accrate target parameters as well as the radar parameters are necessary for radar scattering modeling, a complete and accurate set of ground truth data were also collected using a laser profile meter and dielectric probes for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. At first, the angular and spectral dependencies of the measured radar backscatter for a wide range of roughnesses and moisture conditions are examined. Then, the measured scattering behavior was tested using theoretical and numerical solutions. Based on the experimental observations and the theoretical and numerical solutions, a semi-empirical model was developed for backscattering coeffients in terms of the surface roughness parameters and the relative dielectric constant of the soil surface. The model was found to yield very good agreement with the backscattering measurements of this study as well as with independent measurements.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.187-192
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• 2000

The severity of drought could be evaluated by the accumulative rainfall method, soil moisture condition method, storage ratio method, and water supply restriction intensity method, etc. The pattern of drought could be forecast with the most similar pattern of accumulative rainfall out of the file of past rainfall history. The information that how much rainfall should be expected to overcome the present drought could be obtained from the reservoir storage ratio and soil moisture condition.

• 한국지열·수열에너지학회논문집
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• 제8권1호
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• pp.21-31
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• 2012

This paper reviewed and evaluated some of the commonly used prediction models for thermal conductivity of soils with the experimental data. Semi-theoretical models for two-component materials were found inappropriate to estimate the thermal conductivity of dry state soils. It came out that the model developed by Cote and Konrad gave the best overall prediction results for unsaturated soils available in the literature. However, it still needs to be improved to cover a wider range of soil types and degrees of saturation. In the present study, parametric analysis is also conducted to investigate the effect of soil type and moisture content on the horizontal ground heat exchanger design. The analysis shows that horizontal ground heat exchanger pipe length is reduced with the increase of soil thermal conductivity and water content. The calculation results also show that horizontal ground heat exchanger size can be reduced to a certain extent by using backfilling material with a higher thermal conductivity of solid particles.

• Journal of Biosystems Engineering
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• 제28권1호
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• pp.1-10
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• 2003

A computer simulation was carried out to determinate the optimum capacity of bulk type trailer which is used as a tractor attachment. Soil physical properties. such as soil moisture content. bulk density, soil hardness and soil texture were measured in the 10 major rice production area for computer simulation. Mathematical model which include soil physical properties and vehicle factor was used for computer simulation. Most of the soil texture of the investigated area was silty loam. Soil moisture content ranged between 30 and 40% mostly. Soil bulk density was in the range of 1.500 to 1.700 kg/㎥. Soil hardness ranged between 1 to 18 kg/$\textrm{cm}^2$. Soil hardness incorporate the effects of many soil physical properties such as moisture content texture and bulk density, and so the range of soil hardness was greater than any other physical properties. The capacity of bulk type trailer was above 3000 kg$_{f}$ fer the most of the investigated area. and mostly in the range of 4000 to 6000 kg$_{f}$ depending upon the slip. But for the soft soil area such as Andong and Namyang. tractor itself had mobility problem and showed minus trailer capacity for some places. For this area. the capacity of bulk type trailer ranged between 1000 and 2000 kg$_{f}$ mostly so bulk type trailer should be designed as a small capacity compared to the other area.ared to the other area. area.

• 한국토양비료학회지
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• 제47권1호
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• pp.48-58
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• 2014

In order to evaluate water balance at upland according to RCP8.5 climate change scenario distributed by Korean Meteorological Administration (KMA), we simulated soil moisture using estimation model, called AFKAE0.5 for 66 sites from 2011 to 2020, and established the water balance maps. The amount of annual average precipitation by RCP8.5 scenario was highest in 2016 as recorded 2,062 mm and lowest in 2011 with 1,134 mm. As result of analysis for monthly precipitation and runoff, the amounts of precipitation and runoff have been especially intensive in July in 2014, 2016, 2019, and 2020. Overall, the area of Kyeongbuk and Gyeonggi was estimated more dried status of soil compared with precipitation. Except 2015 and 2020, soil water balance was recorded as negative value in other years which was calculated by subtracting output from input. The status of soil moisture was the most dry in 2020 among those in other years.