Effects of soil water potential and moisture content on sound speed.

2009 ◽  
Vol 125 (4) ◽  
pp. 2520-2520
Author(s):  
Zhiqu Lu ◽  
James Sabatier
Keyword(s):  
Moisture Content ◽  
Water Potential ◽  
Soil Water ◽  
Sound Speed ◽  
Soil Water Potential

scholarly journals Main Hydrological Parameters of the Drained Swamps of the Republic of Karelia and Murmansk Oblast

2020 ◽  
pp. 23-36
Author(s):  
Keyword(s):  
Moisture Content ◽  
Physical Properties ◽  
Water Potential ◽  
Soil Water ◽  
Soil Water Potential ◽  
Density Increase ◽  
Murmansk Oblast ◽  
Hydrological Parameters ◽  
Agricultural Use ◽  
The Republic

Melioration measures at swamps of the Republic of Karelia and Murmansk Oblast, and their successive agricultural use change water/physical properties of this wetland. Changes in potential of soil water that determines of energy of water-soil relationship accompany the peat density increase. The authors state that potential of soil water depends in functional manner on peat moisture and its density. It is fixed that under increase of wetland usage period peat density rises and, consequently, soil water potential rises as well. We suggested the method and calculating formula approximating potential dependency on moisture content within the whole range of its changes. The article defines dependency of moisture conduction on moisture (within the range from 30% to 80% of volume) that is based on relationship between coefficient of moisture conduction and potential.

scholarly journals Robusta coffee transpiration rate in smallholder coffee plantations on Inceptisols of Malang, East Java

2021 ◽  
Vol 9 (1) ◽  
pp. 3165-3173
Author(s):  
Jiyanti Yana Saputri ◽  
Sugeng Prijono ◽  
Budi Prasetya
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Water Potential ◽  
Soil Water ◽  
Transpiration Rate ◽  
Rainy Season ◽  
Soil Moisture Content ◽  
Soil Water Potential ◽  
Dry Season ◽  
Sunlight Intensity

Climate change and the erratic and uneven rainfall distribution are the causes of reduced water available in the soil for plant needs to the transpiration process. This study aimed to determine coffee transpiration rate on dry land with rain harvesting techniques during the dry season, transition season, and rainy season and the factors that influence it. This study used field observation and laboratory analysis with two treatments, i.e. a bench terrace as a control (P1) and an L-shaped silt pit (P2). The variables observed were soil moisture content, transpiration rate, soil water potential, leaf water potential, and microclimate, especially temperature and sunlight intensity. The results showed that the transpiration rate of coffee plants was significantly different in the two treatments. The highest transpiration rate was found in P2 as much as 13.17 mm week-1 or equivalent to 1.88 mm day-1 during the dry season. Application of the L-shaped silt pit (P2) increased soil moisture content compared to the control (P1). This increase was followed by an increase in soil water potential and leaf water potential, which could reach the highest values of 0.18 bar and 0.49 bar, respectively. The transpiration decreases with the change of seasons from the dry season to the transitional season and the rainy season. This decrease is caused by changes in the microclimate, especially the temperature and sunlight intensity. Both are the most variables that affect the rate of transpiration.

Effect of Soil Water Potential of Two Soils on Soybean Emergence 1

1979 ◽  
Vol 71 (6) ◽  
pp. 980-982 ◽  
Author(s):  
L. G. Heatherly ◽  
W. J. Russell
Keyword(s):  
Water Potential ◽  
Soil Water ◽  
Soil Water Potential

scholarly journals A Data-Driven Method for the Temporal Estimation of Soil Water Potential and Its Application for Shallow Landslides Prediction

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1208
Author(s):  
Massimiliano Bordoni ◽  
Fabrizio Inzaghi ◽  
Valerio Vivaldi ◽  
Roberto Valentino ◽  
Marco Bittelli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Water Potential ◽  
Soil Water ◽  
Temporal Trends ◽  
Soil Water Potential ◽  
Shallow Landslides ◽  
Water Dynamics ◽  
Data Driven ◽  
Machine Learning Techniques ◽  
Physically Based

Soil water potential is a key factor to study water dynamics in soil and for estimating the occurrence of natural hazards, as landslides. This parameter can be measured in field or estimated through physically-based models, limited by the availability of effective input soil properties and preliminary calibrations. Data-driven models, based on machine learning techniques, could overcome these gaps. The aim of this paper is then to develop an innovative machine learning methodology to assess soil water potential trends and to implement them in models to predict shallow landslides. Monitoring data since 2012 from test-sites slopes in Oltrepò Pavese (northern Italy) were used to build the models. Within the tested techniques, Random Forest models allowed an outstanding reconstruction of measured soil water potential temporal trends. Each model is sensitive to meteorological and hydrological characteristics according to soil depths and features. Reliability of the proposed models was confirmed by correct estimation of days when shallow landslides were triggered in the study areas in December 2020, after implementing the modeled trends on a slope stability model, and by the correct choice of physically-based rainfall thresholds. These results confirm the potential application of the developed methodology to estimate hydrological scenarios that could be used for decision-making purposes.

NITROGEN TRANSFORMATIONS NEAR UREA IN SOIL WITH DIFFERENT WATER POTENTIALS

1988 ◽  
Vol 68 (3) ◽  
pp. 569-576 ◽  
Author(s):  
YADVINDER SINGH ◽  
E. G. BEAUCHAMP
Keyword(s):  
Water Potential ◽  
Soil Water ◽  
Incubation Period ◽  
Relative Rate ◽  
Soil Water Potential ◽  
Nitrification Inhibitor ◽  
Silt Loam ◽  
Nitrogen Transformations ◽  
Water Potentials ◽  
Initial Soil

Two laboratory incubation experiments were conducted to determine the effect of initial soil water potential on the transformation of urea in large granules to nitrite and nitrate. In the first experiment two soils varying in initial soil water potentials (− 70 and − 140 kPa) were incubated with 2 g urea granules with and without a nitrification inhibitor (dicyandiamide) at 15 °C for 35 d. Only a trace of [Formula: see text] accumulated in a Brookston clay (pH 6.0) during the transformation of urea in 2 g granules. Accumulation of [Formula: see text] was also small (4–6 μg N g−1) in Conestogo silt loam (pH 7.6). Incorporation of dicyandiamide (DCD) into the urea granule at 50 g kg−1 urea significantly reduced the accumulation of [Formula: see text] in this soil. The relative rate of nitrification in the absence of DCD at −140 kPa water potential was 63.5% of that at −70 kPa (average of two soils). DCD reduced the nitrification of urea in 2 g granules by 85% during the 35-d period. In the second experiment a uniform layer of 2 g urea was placed in the center of 20-cm-long cores of Conestogo silt loam with three initial water potentials (−35, −60 and −120 kPa) and the soil was incubated at 15 °C for 45 d. The rate of urea hydrolysis was lowest at −120 kPa and greatest at −35 kPa. Soil pH in the vicinity of the urea layer increased from 7.6 to 9.1 and [Formula: see text] concentration was greater than 3000 μg g−1 soil. There were no significant differences in pH or [Formula: see text] concentration with the three soil water potential treatments at the 10th day of the incubation period. But, in the latter part of the incubation period, pH and [Formula: see text] concentration decreased with increasing soil water potential due to a higher rate of nitrification. Diffusion of various N species including [Formula: see text] was probably greater with the highest water potential treatment. Only small quantities of [Formula: see text] accumulated during nitrification of urea – N. Nitrification of urea increased with increasing water potential. After 35 d of incubation, 19.3, 15.4 and 8.9% of the applied urea had apparently nitrified at −35, −60 and −120 kPa, respectively. Nitrifier activity was completely inhibited in the 0- to 2-cm zone near the urea layer for 35 days. Nitrifier activity increased from an initial level of 8.5 to 73 μg [Formula: see text] in the 3- to 7-cm zone over the 35-d period. Nitrifier activity also increased with increasing soil water potential. Key words: Urea transformation, nitrification, water potential, large granules, nitrifier activity, [Formula: see text] production

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