• 한국농공학회논문집
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• 제61권1호
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• pp.1-8
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• 2019

Developing reliable soil moisture prediction techniques at agricultural regions is a pivotal issue for sustaining stable crop productions. In this study, a physically-based SWAP(Soil-Water-Atmosphere-Plant) model was suggested to estimate soil moisture dynamics at the study sites. ROSETTA was also integrated to derive the soil hydraulic properties(${\alpha}$, n, ${\Theta}_r$, ${\Theta}_s$, $K_s$) as the input variables to SWAP based on the soil information(Sand, Silt and Clay-SSC, %). In order to predict the soil moisture dynamics in future, the mid-term TIGGIE(THORPEX Interactive Grand Global Ensemble) and long-term S2S(Subseasonal to Seasonal) weather forecasts were used, respectively. Our proposed approach was tested at the six study sites of RDA(Rural Development Administration). The estimated soil moisture values based on the SWAP model matched the measured data with the statistics of Root Mean Square Error(RMSE: 0.034~0.069) and Temporal Correlation Coefficient(TCC: 0.735~0.869) for validation. When we predicted the mid-/long-term soil moisture values using the TIGGE(0~15 days)/S2S(16~46 days) weather forecasts, the soil moisture estimates showed less variations during the TIGGE period while uncertainties were increased for the S2S period. Although uncertainties were relatively increased based on the increased leading time of S2S compared to those of TIGGE, these results supported the potential use of TIGGE/S2S forecasts in evaluating agricultural drought. Our proposed approach can be useful for efficient water resources management plans in hydrology, agriculture, etc.

• 대한토목학회논문집
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• 제30권5B호
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• pp.459-469
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• 2010

본 연구에서는 GIS 공간자료(수치표고모델, 토지이용도, 토양도)와 Terra MODIS(Moderate Resolution Imaging Spectroradiometer) 위성영상에 의한 식생활력도를 이용하여 유역의 일단위 유출량을 모의하는 격자기반의 분포형 일유출 모형을 개발하고 그 적용성을 평가하였다. 모형은 격자단위로 지표유출, 중간유출 및 기저유출, 증발산량 그리고 토양수분의 시간적 변화와 공간적 분포를 모의할 수 있다. 모형은 크게 유출, 증발산, 토양수분의 3개 주요모듈로 구성하였다. 유출은 강우전의 토양수분을 추적하여 지표하 저류능을 계산하므로서, 총 유출체적에서 각 유출량을 배분하는 감수곡선을 도입하여 모의하도록 하였으며, 증발산은 MODIS 엽면적지수(Leaf Area Index; LAI)를 고려한 Penman-Monteith 증발산량을 산정하도록 하였다. 매일의 토양수분은 전일의 토양수분에서 당일의 유출량과 증발산량을 계산하는 물수지 방정식을 이용하여 추적하도록 하였다. 이 모형에 대한 적용성 평가는 유역면적 930 $km^2$의 용담댐 유역을 대상으로 수행하였다. 공간해상도를 1 km로 맞춘 GIS 입력자료(토지피복도, 토양도, 경계자료 등)와 RS 입력자료(LAI)를 구축하였으며, 2000년부터 2008년까지의 기상자료를 수집하여 IDW 방법으로 공간분포화 하여 모형에 적용하였다. 검보정은 유역 출구 지점의 유출량 자료를 모의치와 비교하여 수행되었고, 보정결과에 따른 모형의 적합성과 상관성을 판단하기 위한 목적함수로는 결정계수($R^2$)와 평균제곱근오차 (RMSE : Root Mean Square Error)를 사용하였으며, 모형의 효율성 검증을 위해 Nash와 Sutcliffe(1970)가 제안한 모형 효율성 계수를 사용하였다. 유출량에 대한 Nash-Sutcliffe 모형효율은 0.78~0.93로 모의치가 실측치의 경향을 잘 표현하는 것으로 나타났다. 유출량 분포도는 강우와 토양에 매우 민감하게 모의 되었다.

• 한국환경과학회지
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• 제24권4호
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• pp.515-524
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• 2015

The estimation of groundwater usage in Jeju island is important to understand hydrologic cycle system and to plan management of water resource because large amounts of groundwater have been used for agricultural and domestic purpose. The model has been developed to estimate agricultural groundwater usage for garlic at uplands and citrus at orchards raising outdoors using the soil water balance model from FAO 56, respectively. The total amount of water supplied for the crop evapotranspiration and the multipurpose function such as sprout promotion can be simulated by the model. However, due to the discrepancy of water use in initial stage between calculated and observed, the model was calibrated and verified using actual groundwater usage monitoring data for 3.5 years (2011.6 to 2014.12) at three uplands for garlic and three orchards for citrus. Consequently, it would be concluded that the model simulated efficiently actual water usage in that root mean square (RMS) and normalized RMS of the validation stage were less than 8.99 mm and 2.43%, respectively, in two different conditions.

• Agricultural and Biosystems Engineering
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• 제2권2호
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• pp.63-68
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• 2001

The objective of this study was to develop a real-time soil moisture meter using RF impedance. The impedance suchas capacitance and resistance (or conductance) was analyzed using parallel cylinder type capacitance probe(C-probe) and Q-meter (HP4342). The capacitance and conductance of soil increased as volumetric water content increased. The 5 MHz of modified Colpitts type crystal oscillator was designed to detect the capacitance change of the C-probe with moist soil. A third order polynomial regression model was proposed to describe the relationship between RF impedance and volumetric water content. The prototype real time moisture meter consisted of the C-probe, sample container, oscillator, frequency counter and related signal processing units. The calibration equation for measurement of volumetric moisture content of soil was developed and validated. The correlation coefficient and root mean square error between measured volumetric water content by oven method and predicted values by prototype moisture meter for unknown soil samples were 0.984 and 0.032$cm^3$$cm\^3$, respectively.

• Geomechanics and Engineering
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• 제33권1호
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• pp.1-9
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• 2023

The unconfined compression strength (UCS) of soils is commonly used either before or during the construction of geo-structures. In the pre-design stage, UCS as a mechanical property is obtained through a laboratory test that requires cumbersome procedures and high costs from in-situ sampling and sample preparation. As an alternative way, the empirical model established from limited testing cases is used to economically estimate the UCS. However, many parameters affecting the 1D soil compression response hinder employing the traditional statistical analysis. In this study, gene expression programming (GEP) is adopted to develop a prediction model of UCS with common affecting soil properties. A total of 79 undisturbed soil samples are collected, of which 54 samples are utilized for the generation of a predictive model and 25 samples are used to validate the proposed model. Experimental studies are conducted to measure the unconfined compression strength and basic soil index properties. A performance assessment of the prediction model is carried out using statistical checks including the correlation coefficient (R), the root mean square error (RMSE), the mean absolute error (MAE), the relatively squared error (RSE), and external criteria checks. The prediction model has achieved excellent accuracy with values of R, RMSE, MAE, and RSE of 0.98, 10.01, 7.94, and 0.03, respectively for the training data and 0.92, 19.82, 14.56, and 0.15, respectively for the testing data. From the sensitivity analysis and parametric study, the liquid limit and fine content are found to be the most sensitive parameters whereas the sand content is the least critical parameter.

• 한국농공학회논문집
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• 제62권6호
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• 한국농공학회지
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• 제36권2호
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• pp.96-110
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• 1994

The purpose of this study is to develop soil salt prediction model for the estimation of irrigation water requirements for dry field crops in reclaimed tidelands. The simulation model based on water balance equation, salt balance equation, and salt storage equation was developed for daily prediction of sa]t concentration in root zone. The data obtained from field measurement during the growing period of tomato were used to evaluate the applicability of this model. The results of this study are summarized as follows: 1.The optimum irrigation point which maximizes the crop yield in reclaimed tidelands of silt loam soil while maintaining the salt concentration within the tolerance level, ws found to be pF 1.6, and total irrigation requirement after transplanting was 602mm(6.7 mm/day)for tomato. 2.When the irrigation point was pF 1.6, the deviation between predicted and measured salt concentration was less than 4 % at the significance level of 1 7% 3.Since the deviations between predicted and measured values data decrease as the amount of irrigation water increases, the proposed model appear to be more suitable for use in reclaimed tidelands. 4.The amount of irrigation water estimated by the simulation model was 7.2mm/day in the average for cultivating tomato at the optimum irrigation point of pF 1.6.The simulation model proposed in this study can be generalized by applying it to other crops. This, model, also, could be further improved and extended to estimate desalinization effects in reclaimed tidelands by including meteorological effect, capillary phenomenon, and infiltration.

• 대한건축학회논문집:구조계
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• 제34권7호
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• pp.19-26
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• 2018

This study tested 25 lightweight aggregate concrete (LWAC) mixtures using the expanded bottom ash and dredged soil granules to examine the compressive strength gain of such concrete with different ages. The test parameters investigated were water-to-cement ratios and the natural sand content for the replacement of lightweight fine aggregate. The compressive strength gain rate in the basic equation specified in fib model code was experimentally determined in each mixture and then empirically formulated as a function of the water-to-cement ratio and oven-dried density of concrete. When compared with 28-day compressive strength, the tested LWAC mixtures exhibited relatively low gain ratios (0.49~0.82) at an age of 3 days whereas the gain ratios (1.16~1.41) at 91 days were higher than that (1.05~1.15) of the conventional normal-weight concrete. Thus, the fib model equations tend to overestimate the early strength gain of LWAC but underestimate the long-term strength gain. The proposed equations are in good agreement with the measured compressive strength development of LWAC at different ages, indicating that the mean and standard deviation of the normalized root mean square errors determined in each mixture are 0.101 and 0.053, respectively.

• Journal of Biosystems Engineering
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• 제33권4호
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• pp.260-268
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• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• 한국수자원학회논문집
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• 제50권6호
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• pp.387-395
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• 2017

기후변화에 따른 해수면 상승으로 인하여 해안지역의 지하수계에 해수침투가 가중된다. 지하수의 염분농도가 증가하면 지하수면 상부의 불포화 토양에서도 염분 농도가 증가할 수 있으며, 이는 농경지에서 작물피해를 일으킬 수 있다. 해수면이 상승함에 따라 내륙의 지하수위도 함께 상승한다. 이는 불포화 토양층의 두께를 감소시켜 해안 저지대의 경작에 피해를 끼칠 수 있다. 본 연구에서 지하수 해수침투는 3차원 모델, 토양 염류화 평가는 연직 1차원 모델을 합성 적용하여 해안 농경지에 대한 해수면 상승 피해를 평가하는 방법을 개발하였다. 3차원 해수침투 모델에서 지하수면의 수위와 농도분포를 계산하고 최상부 절점 중에서 염분 농도가 기준 값 이상인 절점에서 지하수면과 지표면 사이의 토양층에서 연직 1차원 모델링으로 토양층의 염분 농도와 불포화대 두께를 계산하였다. 농경지의 토양 염류화는 작물의 뿌리 심도에서 보통 작물의 생육한계 염분농도를 기준으로 판단하였다. 개발된 모델링 방법을 가상의 간척농경지에 적용하였다. 해수면 상승자료로 IPCC의 RCP 4.5와 8.5 시나리오를 사용하였다. 평가 결과는 2050년과 2100년에 대하여 제시하였다. 연구결과 대상지역에서 기후변화 시나리오 RCP 8.5에서 2100년에는 지하수 염류화 피해 면적은 간척지 육지면적 대비 7.8%, 염류화 토양 면적은 6.0%, 불포화층의 두께가 뿌리심도보다 적은 지역의 면적은 1.6% 증가하는 것으로 분석되었다.