Modeling Soil Water Movement under Low Head Ponding and Gravity Infiltration Using Data Determined with Different Methods

Шеин, Е. В.; Dembovetsky, A.V.; Panina, S.S.

doi:10.1016/j.proenv.2013.06.062

Cited by 10 publications

(9 citation statements)

References 2 publications

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“…Synchronous observations of water pressure and soil water content when monitoring meteorological conditions in the surface air layer that determine evapotranspiration make it possible to adapt a physically based model of water movement in the soil [12,15,26]. In other words, to adjust the model so that it gives the lowest error in the values of water content and water pressure in the stationary experiment.…”

Section: Resultsmentioning

confidence: 99%

Soil Hydrology of Agricultural Landscapes: Quantitative Description, Research Methods, and Availability of Soil Water

2021

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Soil hydrology has deep Russian roots, which are primarily related to the theory of soil hydrological constants and their practical application. These constants have been used to assess the hydrological soil conditions in stationary observations, for which attempts to arrange regular hydrological observations in the landscape faced impracticable complexity of work and calculations and provided unreliable quantitative predictions. At present, there are new opportunities for experimental research, digital analysis, and prediction of hydrological indicators of soils in the landscape. A new quantitative approach to the use of digital technologies for monitoring soil water and temperature in the soils of agricultural landscapes, their dynamics, and their probabilistic calculations has been developed. Based on the soil map, it is proposed to create an information and measurement system with the studied thermal and hydrophysical characteristics of soils using mathematical models to calculate the dynamics of moisture and temperature for given periods and conditions of different availability of heat and precipitation, which allows us to quantify the availability of moisture reserves in the soils of the agricultural landscape. This system of observations, assessment, and forecast includes the use of modern technologies for determining soil water content and temperature, the adaptation of predictive physically based models for calculating the dynamics of moisture reserves depending on the availability of precipitation and conditions at the lower boundary of soil profiles. The paper deals with the hydrological analysis of soils by the example of the agricultural landscape of the Zelenograd station of the Dokuchaev Soil Science Institute in the village of El’digino, Pushkino district, Moscow oblast.

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Section: Resultsmentioning

confidence: 99%

Soil Hydrology of Agricultural Landscapes: Quantitative Description, Research Methods, and Availability of Soil Water

2021

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“…크게 상회 하는 것으로 나타났다 (Table 5). 이와 같은 결과와 ｢적절하다｣라는 판단 기준 (Moriasi et al, 2007;Shein et al, 2013;Irsyard et al, 2019)에 근거하여 볼 때 본 EFM은 ｢매우 적절하다｣라고 판단되었다. WCM (Baghdadi et al, 2016;Meng et al, 2016)과 SAFY (Duchemin et al, 2008;Hadria et al, 2010;Fieuzal et al, 2011;Claverie et al, 2012) (Frot et al, 2008).…”

Section: Methodsunclassified

“…27 -Eq. 31과 같이 Gaussian function 형태의 추정모형 (GFM: (Moriasi et al, 2007;Shein et al, 2013;Irsyard et al, 2019) 에 근거하여 볼 때 본 SFM은 ｢매우 적절하다｣라고 판단되었다. (Moriasi et al, 2007;Shein et al, 2013;Irsyard et al, 2019)…”

Section: Methodsunclassified

“…경시적으로 토양수분 함량을 측정하기 위해서는 토양 비 파괴적인 간접적 측정방 법이 사용되며 그 측정치에는 오차가 포함될 수밖에 없다. 이러한 토양수분 측정방법에 따른 토양수분 함량의 오차 분 석에 관한 연구는 있으며 (Sinclair and Williams, 1979;Vauclin et al, 1984;Eom et al, 1988), 이외에도 오차 분석 방법에 관한 연구도 많이 이루어져 오고 있으나 (Goodman, 1960;Kendall and Stuart, 1963;Mandel, 1964;Shein et al, 2013;Irsyard et al, 2019;Eom et al, 2020) (Moriasi et al, 2007;Shein et al, 2013;Irsyard et al, 2019)에 근거하여 모형 을 검증하고 타 연구결과에서 개발된 모형들과의 상대적인 정밀도를 비교 검토하여, 모형 설정을 통한 토양수분 함량 의 변화양상을 구명코자 실시하였다. 변량에 대한 범위 (range)는 Eq.…”

Section: Introductionunclassified

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Estimation Models for Soil Water Content and Rainfall in Andong

Eom¹

2021

Korean J. Soil. Sci. Fert.

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Main objective of this study was to develop the models to estimate soil water content (WTR) and rainfall during four years in Andong with verification. Trigonometric function model (TFM), Fourier function model (FFM) and exponential function model (EFM) for soil water content (WTR) were developed. Gaussian function model (GFM) and sigmoid function model (SFM) for rainfall were developed. Amplitude of mean WTR from 10 cm to 50 cm was 12.64%. Range of periodicity according to period and soil depth was 660 days and 427 days, respectively. The deeper soil depth the shorter in WTR periodicity. Slope of accumulated rainfall change was the highest in 2009, the critical point was the earliest in 2011. Average RMSE of TFM, FFM, EFM, GFM and SFM was 1.352%, 1.356%, 2.117%, 21.37 mm and 27.09 mm, respectively, and average NSE was 0.696, 0.694, 0.857, 0.937 and 0.996, respectively. Four models (TFM, EFM, GFM and SFM) were deemed ｢very appropriate｣ and FFM was judged to be ｢appropriate｣ based on the criteria of error analysis.

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“…Numerous hydrological models have been formulated to clarify water infiltration in soil (Ranatunga et al ., ; Köhne et al ., ; Shein et al ., ). However, difficulties in accurately describing and predicting the hydraulic behaviour of soil water remain because water infiltration in soil is a complicated process affected by many factors.…”

Section: Introductionmentioning

confidence: 97%

Effects of DLVO, hydration and osmotic forces among soil particles on water infiltration

Luo

Ding

et al. 2018

European J Soil Science

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Summary Soil water infiltration is closely associated with the transport of nutrients and contaminants in soil. The physical mechanism by which electrolyte concentration influences water infiltration is not clear, however. Recent studies have shown that interaction forces between soil particles play a crucial role in the stability of soil aggregates and pores, which further affects soil water infiltration. In this research, column experiments were used to elucidate the effects of soil particle interaction forces on water infiltration in a permanently charged and a variably charged soil using different concentrations of KNO3 solutions (0.0001, 0.001, 0.01 and 0.1 mol l−1), and some interesting results on soil water infiltration were discovered. They indicated that: (i) four forces in soil (long‐range van der Waals attractive, electrostatic repulsive, hydration and osmotic repulsive forces) co‐determined the rate of soil water infiltration for both soil types tested, (ii) at smaller soil water content (large electrolyte concentration) the osmotic repulsive force became more important in soil water infiltration, and yet with a larger water content (small electrolyte concentration) the electrostatic repulsive force became more important, and (iii) the osmotic force affected water infiltration through its effect on particle interaction forces rather than its influence on the osmotic potential of water. This paper presents a quantitative description of how particle interaction forces affect water infiltration into soil. Highlights Elucidation of physical mechanisms of effects of clay charge and electrolyte concentration on soil water infiltration. Quantified effects of interaction forces of soil particles on soil water infiltration. Electrostatic repulsive and osmotic forces play a critical role in water infiltration. DLVO, hydration and osmotic forces among soil particles co‐determined soil water infiltration rate.

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Modeling Soil Water Movement under Low Head Ponding and Gravity Infiltration Using Data Determined with Different Methods

Cited by 10 publications

References 2 publications

Soil Hydrology of Agricultural Landscapes: Quantitative Description, Research Methods, and Availability of Soil Water

Soil Hydrology of Agricultural Landscapes: Quantitative Description, Research Methods, and Availability of Soil Water

Estimation Models for Soil Water Content and Rainfall in Andong

Effects of DLVO, hydration and osmotic forces among soil particles on water infiltration

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