The Relationship Between Soil Water Potential, Environmental Factors, and Plant Moisture Status for Poblano Pepper Grown Using Tensiometer-Scheduled Irrigation

2012 ◽  
Vol 18 (2) ◽  
pp. 137-152 ◽  
Author(s):  
Timothy Coolong ◽  
John Snyder ◽  
Richard Warner ◽  
John Strang ◽  
Susmitha Surendran
2021 ◽  
Vol 47 (3) ◽  
pp. 110-115
Author(s):  
Johannes Hertzler ◽  
Steffen Rust

Soil water potential can be used as a proxy for plant available water in irrigation scheduling. This study investigated the relationship between soil water potential and plant water status of pines (Pinus sylvestris L.) planted into two different substrates. Predawn leaf water potential as a well-established measure of the plant water status and soil water potential correlated very well. However, estimating the plant water status from individual sensor readings is subject to significant estimation errors. Furthermore, it was shown that heterogeneous soil/root ball combinations can lead to critical effects on the soil water balance, and that sensors installed outside of the root balls cannot estimate the plant water status without site-specific calibration.


1977 ◽  
Vol 23 (6) ◽  
pp. 811-817 ◽  
Author(s):  
R. J. Cook ◽  
A. M. Smith

Ethylene production at different soil water potentials was studied in a high organic matter, red basaltic soil from a rain forest avocado grove of Queensland, Australia, and in a Latah silt loam from a recropped wheat field of Idaho, U.S.A. The soils were sealed under air or N2 in glass vials and incubated at 25 and 35 °C, respectively. Although the two soils differed in physical and chemical properties, in water content – water potential relationships, and in amount of ethylene produced, the relationship between ethylene production and water potential was virtually identical for both soils: maximal at saturation, reduced by −1 bar, and nearly prevented by −5 bars or slightly lower. Onset of ethylene production was earlier under N2, but total ethylene produced and the water potential–ethylene production relationship were about the same under both N2 and air. Osmotic adjustments of the soil water potential with KCl solutions resulted in more ethylene production between −1 and about −15 bars, but little or no ethylene production below −22 bars.The need for high water potential for ethylene production indicates that soil bacteria are more important than fungi in the ethylene production process in soil. The results further indicate that, because ethylene production is possible even to −5 bars or slightly lower, soil water availability should be no more directly limiting to this process in nature than it is, for example, to nitrification or other bacteriological processes in soil.


2019 ◽  
Vol 23 (5 Part A) ◽  
pp. 2677-2683
Author(s):  
Weihan Wang

As drip irrigation is more and more beneficial to saving water resources, it has become a more popular way to irrigate farmland, so the research of drip irrigation farmland has been paid more attention. Based on the dynamic simulation of farmland under drip irrigation and the analysis of control variables, the relationship among thermodynamic functions such as temperature, water content, and soil water potential are studied by different methods in this paper and the corresponding conclusions are obtained. Under the condition of constant control temperature, the water conductivity of soil in farmland will decrease with the increase of soil water potential, that is, the conductivity of soil is inversely proportional to the water potential of soil. In the process of actual drip irrigation, it is impossible to control soil parameters such as temperature or water content and soil water potential separately. So the test in this paper is relatively ideal, but still has reference significance.


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

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1208
Author(s):  
Massimiliano Bordoni ◽  
Fabrizio Inzaghi ◽  
Valerio Vivaldi ◽  
Roberto Valentino ◽  
Marco Bittelli ◽  
...  

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.


1988 ◽  
Vol 68 (3) ◽  
pp. 569-576 ◽  
Author(s):  
YADVINDER SINGH ◽  
E. G. BEAUCHAMP

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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