• Journal of Soil and Groundwater Environment
• /
• v.7 no.3
• /
• pp.103-114
• /
• 2002

Knowledge of soil water retention characteristic is essential for many problems involving water flow and organic solute transport in unsaturated soils. A physico-empirical approach based on the translation of the particle-size distribution (PSD) into a corresponding water retention curve has been accomplished by others using the concept that the pore-size distribution is directly related to PSD. This approach implies that details of a PSD curve may affect the estimation of water retention characteristic (WRC). To determine whether the WRC estimation using the Arya-Paris model could be affected by the selection of a PSD model, four PSD models with one to four fitting parameters were used. The Jaky model with only one fitting parameter had greater WRC estimation ability than other models with greater number of fitting parameters. The better performance of the Jaky model may be explained by the effect of soil structure in field soils.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.322-322
• /
• 2020

토양수분량과 증발산량은 물의 순환과정에서 중요한 비중을 차지하고 있지만, 현재 우리나라에서는 토양수분량과 증발산량 관측소가 많이 설치되어 있지 않아 자료를 활용하는데 있어 어려움이 있으며, 유출특성 분석시에도 토양수분량과 증발산량 자료를 분석에 활용하지 않고 있다. 이에 본 연구에서는 청미천 유역에 위치한 여주시(원부교) 수위관측소와 청미천 토양수분-증발산 관측소 자료를 활용하여 최근 3개년 유출특성에 대하여 분석하였다. 여주시(원부교) 수위관측소는 청미천 유역의 대표 지점으로 2010년 이후 매년 수위-유량관계곡선식이 개발 되었고 청미천에 위치한 토양수분-증발산 관측소는 2007년 관측이 개시되어 현재까지 자료가 확보되어 있다. 유출특성 분석시에는 상류에 위치한 장호원환경사업소의 방류량 자료를 확보하여 유출률을 산정하였다. 또한, 강수량 자료는 자료의 정확성을 높이기 위해 면적평균강수량 자료를 산정하여 분석 활용하였다. 2017년은 강수량 1,183.3mm에 유출고는 495.4mm이며 손실고는 692.9mm로 산정되었고, 2018년은 강수량 1,433.8mm에 유출고는 647.5mm이며 손실고는 786.3mm로 산정되었다. 2019년은 강수량 962.3mm에 유출고는 265.2mm에 손실고는 697.1mm로 산정되었고 토양수분량과 증발산량에서 연평균 관측값으로는 토양수분량 2017년 23.0%, 2018년 24.5%, 2019년 23.8%이며 증발산량은 2017년 591.5mm, 2018년 415.8mm, 2019년 500.6mm로 관측되었다. 결과적으로 본 연구에서는 해당지점에 대한 장기간 모니터링과 흐름 특성의 변화를 분석하고 토양수분량 및 증발산량을 활용하여 수위-유량관계곡선의 적절성 검토를 하였으며, 이에 따른 유출특성을 검토하여 수위-유량관계곡선식과 유출특성 자료는 정확도가 매우 높은 것으로 분석되었다.

• Korean Journal of Soil Science and Fertilizer
• /
• v.32 no.3
• /
• pp.211-214
• /
• 1999

To acknowledge the differences in soil physical properties of cultivated land derived from major parent rocks in Yeong-nam areas, we investigated Riley's projection sphericity(one of the morphological properties) of sand and made up Soil Moisture Characteristics Curve(SMCC). The averages in Riley s projection sphericity range from 0.63 to 0.67 in soils derived from Sedimentary rocks than 0.56 to 0.61 in soils derived from igneous rocks. In case of soils derived from igneous rocks, the Riley's projection sphericity is lower as the particle size get to be smaller. The differences of SMCC were larger in the fine loamy soils than in coarse loamy soils. The moisture retention was higher in the soils derived from Sedimentary rocks than in the soils derived from Igneous rocks. After we transformed the water retention into dimensionless scale value by available water ratio, the SMCC was nearly unchangeable in the tested soils except for fine loamy soils derived from Sedimentary rock, but was not correlated with soil texture or parent rocks.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.7 no.1
• /
• pp.78-90
• /
• 2005

The spatial and temporal distribution of soil moisture was characterized from soil moisture data through the intensive monitoring using Time Domain Reflectometry (TDR). The recession of soil moisture after a rainfall event was characterized and the empirical equation was used in the recession curve analysis. Recession analysis provides features of soil moisture variation such as recharge and stability depending upon locations of monitoring. The wetness index was useful for explaining spatial and temporal distributions of soil moisture and recession characteristics at hillslope scale.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.6
• /
• pp.823-827
• /
• 2010

This study was conducted to assess the propriety of models for soil water characteristics estimation in anthropogenic soil through the measurement of soil water content and soil water matric potential. Soil profile was characterized with four different soil layers. Soil texture was loamy sand for the first soil layer (from soil surface to 30 cm soil depth), sand for the second (30~70 cm soil depth) and the third soil layers (70~120 cm soil depth), and sandy loam for the fourth soil layer (120 cm < soil depth). Soil water retention curve (SWRC), the relation between soil water content and soil water matric potential, took a similar trend between different layers except the layer of below 120 cm soil depth. The estimation of SWRC and air entry value was better in van Genuchten model by analytical method than in Brooks-Corey model with power function. Therefore, it could be concluded that van Genuchten model is more desirable than Brook-Corey model for estimating soil water characteristics of anthropogenic soil accumulated with saprolite.

• Korean Journal of Soil Science and Fertilizer
• /
• v.39 no.6
• /
• pp.329-333
• /
• 2006

Most of volcanic ash soils in South Korea are distributed in Jeju province which is an island placed on southern part of Korea and has steep slope mountain area. There are many soils containing high contents of organic matter (OM) derived from volcanic ash in Jejudo, also. Therefore, irrigation and drainage in volcanic ash soil different with general soil which has low OM content have to be applied with another management way, but studies searching appropriate methods for them are set on insufficient situation because the area of volcanic ash soil in South Korea is only 1.3% (130,000ha). This study was conducted for analysis of soil water content and irrigation quantity appropriate for crops cultivated in volcanic ash soil with high OM content. Although soils with different soil color have the same soil texture, soil water characteristics curve by soil color showed the difference of water retention capability by OM content. But, this characteristics classified with soil color could be unified by scaling technique with similitude analysis method which get dimensionless water content using a present water content, a residual water content and saturated water content (or water content at 10kPa). A relation of gravimetric soil water content (GSWC) and dimensionless water content by the results showed a form of power function. The dimensionless water content (DWC) express a relative saturation degree of present water content. This was also expressed by van Genuchten model which describe the relation between relative saturation degrees and matric potentials. These results on soil water characteristics curve (SWCC) of volcanic ash soil will be the basic of irrigation plan in area having high organic contents into soil.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.1686-1690
• /
• 2010

우리나라 면적의 약 67%에 이르는 660만ha의 산림 중 침엽수림은 혼효림을 포함하여 약 74%를 차지해 활엽수림보다 넓게 분포하고 있다. 이와 같이 넓은 산림은 가뭄, 홍수와 같은 수문현상과 관련이 있으며 강우에 따른 유출에의 기여하는 바가 클 뿐만 아니라 강우, 증발산, 침투 유출에 이르는 다양한 수문현상이 복합적으로 나타난다. 특히, 최근 임목밀도의 증가가 오히려 증발산량의 증가, 옆면에 의한 강우 차단량의 증가 등을 발생시켜 가뭄과 홍수 또는 산사태의 원인이 될 수 있으며, 수자원 함양을 저해하는 요소로 작용하고 있다는 우려의 목소리가 나오고 있다. 따라서 산림지역의 증발산과 관련 있는 토양수분의 지속적인 모니터링과 감쇄특성 및 토양수분 환경에 대한 연구는 중요한 요소 연구가 될 수 있다. 봄에서 여름으로 진행되는 시기에는 강우발생에 비해 수목의 생육이 활발하여 증발산에 따른 토양수분 변화 및 감소가 급격하게 일어나며, 여름에는 토양수분의 감소도 뚜렷한 반면, 강우사상도 많이 발생하여 이에 따른 변화폭이 크게 나타난다. 또한, 가을에서 겨울로 진행되는 시기에는 수목의 생육의 둔화와 기온 하강으로 인하여 토양수분 감쇄현상 및 변화가 적게 나타나 토양수분의 변화양상이 계절마다 다르게 나타난다. 이에 토양수분의 감쇄현상을 파악하면 곧 산림지역에서의 증발산량 및 토양수분 소비특성을 파악할 수 있기 때문에, 산림에서 실제 토양수분 모니터링과 이를 통한 시간별, 깊이별 토양수분 변화 및 감쇄현상을 파악하는 것은 중요하다. 따라서 본 연구에서는 침엽수 산림에서의 토층별 월별 토양수분의 감쇄특성을 분석하기 위하여 침엽수림에서 토양수분 장기 모니터링 시스템을 구축하여 시간별, 토층별 토양수분 모니터링을 실시하고, 이를 바탕으로 침엽수림에서의 토양수분 감쇄현상을 분석하였다. 또한 토양수분 데이터 및 기상자료를 활용하여 월별, 기간별 토양수분 감쇄곡선을 산정하고 감쇄상수를 비교하였으며, 감쇄특성에 대하여 비교 분석하였다.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.4
• /
• pp.407-414
• /
• 2010

Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.

• Water for future
• /
• v.21 no.2
• /
• pp.193-201
• /
• 1988

A simplified model for higher order scanning curves in the soil water characteristic function is suggested. The conceptual hysteresis models developed by $Mualem_{8,9}$ are simplied for higher order scanning curves. Higher order drying curves are regarded as primary drying curves and the last wetting reversal point is assumed to be on the main wetting curve by moving that point vertically downward. For the higher order wetting curves, it is assumed that these curves can be regarded as primary curves and the last wetting reversal point sits on the imaginary main drying curve which passes through the last wetting reversal point. The water content computed from the simplified model are compared with those obtained from Mualem's original model for second order scanning curves. It is found that absolute differences between the two methods aree relatively small and the simplified model always underestimates for higher order drying curves while it overestimates for higher order wetting curves. Hence, those two tend to compensate each other for repeated drying-wetting processes. The simplified model approximates higher order scanning curves well and reduces computation considerably.

• Korean Journal of Soil Science and Fertilizer
• /
• v.28 no.3
• /
• pp.227-232
• /
• 1995

The model equations including scaling factors to estimate the soil water characteristics curve(SWCC) without direct measurement of soil water tension were developed. Scaling were applied to a data set of soil water content, soil water tension, particle size distribution, and OM contents of the 134 soil samples with the 10 soil textural classes. The capability of the model equations was tested on another 205 soil samples. The parameter, ${\theta}^*$, of soil water contents was used by scale transformation as follows : ${\theta}^*=[{\theta}i-{\theta}(1.5MPa)]$/$[{\theta}(10KPa)-{\theta}(1.5MPa)]$ Using ${\theta}^*$ a model equation to estimate SWCC, which was applicable to all textural classes, was developed as follows: $H(0.1MPa)=0.13{\cdot}({\theta}^*)^{-2.04}$. Other model equations to estimate the water content at the soil water tension of 10KPa [${\theta}(10KPa)$] and 1.5MPa [${\theta}(1.5MPa)$], which are required to ${\theta}^*$ were developed by using scale factors of sand(S) and silt(Si) content and organic matter content(OM) as foilows : ${\theta}(10KPa)=26.80-3.99ln[S]+2.36{\sqrt{[Si]}}+2.88[OM]$ ($R=0.81^{**}$) ${\theta}(1.5KPa)=15.75-2.86ln[S]+0.55{\sqrt{[Si]}}+0.70[OM]$ ($R=0.76^{**}$) The measured and estimated values of ${\theta}(1/30MPa)$ on the 205 soil samples were highly correlated on 1 : 1 corresponding line with $R=0.85^{**}$.