scholarly journals Effect of the Particle Size of Clinoptilolite Zeolite on Water Content and Soil Water Storage in a Loamy Sand Soil

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 607
Author(s):  
Hesham M. Ibrahim ◽  
Abdulaziz G. Alghamdi

Limited water resources in arid and semi-arid regions require innovative management to maintain crop production while minimizing the amounts of water used for irrigation. We investigated the impact of the particle size of natural clinoptilolite zeolite (CZ) on water content (WC) and hydraulic properties of a loamy sand soil. WC was measured using 5TE sensors installed at five depths (10, 20, 30, 40, and 50 cm) in soil columns (7.4 cm ID, 56 cm length). Three sizes of macro- and nano-CZ particles (20, 2.0, and 0.2 µm) were added to the soil at an application rate of 1%. The columns were subject to 14 wetting/drying cycles from 24 February to 8 December 2020. The HYDRUS-1D model was used to simulate WC and soil water storage inside the soil columns. WC increased with the decreasing particle size of CZ, especially when columns were subject to long drying periods. The larger surface area and smaller pore size of CZ altered the pore-size distribution of the loamy sand soil and increased the amount of microporosity inside the soil system, leading to increased water retention. Available water and soil water storage were increased by 3.6–14.7% and 6.8–10.5%, respectively, with larger increases with the decrease in CZ particle size. Variations in infiltration rate and hydraulic conductivity were statistically significant only with the smallest CZ particle size, with a reduction of 25.6% and 19.3% compared to the control, respectively. The HYDRUS-1D model accurately simulated WC and soil water storage, with only slight overestimation of WC (2.4%) at depths ≤ 30 cm. The results suggest that, in light-textured soils, the application of CZ in the ultra-fine nanoparticle size would increase water-holding capacity and reduce hydraulic conductivity, which would enhance the efficiency of water use and contribute to water conservation in dry regions.

1992 ◽  
Vol 6 (2) ◽  
pp. 317-321 ◽  
Author(s):  
Rick A. Boydston

Experimental controlled release starch granules (CRSG) containing 5.3% a.i. (w/w) norflurazon or 6% a.i. (w/w) simazine retarded the leaching of both herbicides in loamy sand soil columns when compared to commercial formulations of norflurazon [80% (w/w) dry flowable] or simazine [90% (w/w) water dispersible granule]. Barley bioassays indicated norflurazon and simazine remained in the surface 0 to 2.5 cm of soil when applied as CRSG formulations and moved to a depth of 15 cm when applied as commercial dry formulations and leached with 6 cm of water. CRSG placed on pre-wetted soil columns began to release norflurazon by 7 d at 25 C or 14 d at 15 C, and subsequent leaching moved norflurazon beyond the top 2.5 cm of the soil column.


Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.


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