Wang, E., Cruse, R. M., Chen, X. and Daigh, A. 2012. Effects of moisture condition and freeze/thaw cycles on surface soil aggregate size distribution and stability. Can. J. Soil Sci. 92: 529–536. Freeze/thaw cycles can affect soil aggregate stability, which in turn impacts wind and water erosion. The objectives of this laboratory study were: (1) to determine the effect of variable freeze/thaw cycles and soil water conditions on aggregate size distribution and stability; and (2) to evaluate differences in aggregate size distribution and stability between disturbed soil and undisturbed soil cores as affected by freeze/thaw cycles and soil water conditions. Surface soil was collected before freezing in late fall of 2009. Aggregates isolated from disturbed soil or intact soil cores were subjected to a factorial combination of 3 gravimetric water content treatments: 0.15 m³ m⁻³, 0.23 m³ m⁻³ or 0.30 m³ m⁻³, and 3 freeze/thaw treatments: 0, 3, or 9 cycles. A freeze/thaw cycle involved soil freezing at –10^∘C for 24 h, followed by thawing at 5^∘C for 24 h. Most aggregate size classes were affected significantly (P5 mm. Dry-sieved aggregates were relatively more sensitive to the freeze/thaw treatment than wet-sieved aggregates. The mean weight diameter (MWD) of dry-sieved aggregates was significantly (P<0.05) greater at 0.30 m³ m⁻³ than 0.15 m³ m⁻³ water content, but the opposite trend was observed for MWD of wet aggregates and aggregate stability. There was a significant (P<0.05) response of the MWD in dry-sieved aggregates to the interactive freeze/thaw×water content effect that differed for aggregates obtained from disturbed soil and those in the undisturbed soil core, but not for the MWD of wet-sieved aggregates and aggregate stability.

Superabsorbent polymers (SAPs) are materials that can absorb significant amounts of water relative to their mass. The nature and properties of SAPs make them a widely utilized material across many disciplines. A systematic review was conducted to examine the use of SAPs within agriculture and environmental science. The method of application, rate, and the subsequent impact on soil properties were determined. Superabsorbent polymers can be used to improve and prolong soil water holding capacity, decrease drought stress, and increase time between irrigation events. There are results indicating SAPs can reduce compaction. Yield and plant growth characteristics were improved for all but one of the reviewed studies. While SAPs show potential as a tool, their economic feasibility on large‐scale and long‐term projects should be evaluated.

Precise soil moisture prediction is important for water management and logistics of on-farm operations. However, soil moisture is affected by various soil, crop, and meteorological factors, and it is difficult to establish ideal mathematical models for moisture prediction. We investigated various machine learning techniques for predicting soil moisture in the Red River Valley of the North (RRVN). Specifically, the evaluated machine learning techniques included classification and regression trees (CART), random forest regression (RFR), boosted regression trees (BRT), multiple linear regression (MLR), support vector regression (SVR), and artificial neural networks (ANN). The objective of this study was to determine the effectiveness of these machine learning techniques and evaluate the importance of predictor variables. The RFR and BRT algorithms performed the best, with mean absolute errors (MAE) of <0.040 m³ m⁻³ and root mean square errors (RMSE) of 0.045 and 0.048 m³ m⁻³, respectively. Similarly, RFR, SVR, and BRT showed high correlations (r² of 0.72, 0.65 and 0.67 respectively) between predicted and measured soil moisture. The CART, RFR, and BRT models showed that soil moisture at nearby weather stations had the highest relative influence on moisture prediction, followed by 4-day cumulative rainfall and PET, subsequently followed by bulk density and Ksat.

The drought of 2012 provides a unique opportunity to evaluate the effects of cover crop on soil moisture under relatively extreme conditions. The objective of this study was to quantify potential differences in soil moisture due to the presence of a rye (Secale cerale L.) cover crop in a corn (Zea mays L.)–soybean (Glycine max L.) rotation at various locations in the Midwestern United States during the drought of 2012. Soil volumetric water content (θ) and soil water storage (SWS) were monitored at three sites in Iowa and Indiana. Daily measurements of soil θ were taken at 10, 20, 40, and 60 cm (3.9, 7.9, 15.7, and 23.6 in) soil depths, and SWS was estimated to an 80 cm (31.5 in) depth. Soil water during the drought of 2012 was affected by a rye cover crop in comparison to without a rye cover crop for one (i.e., located in Iowa) of the three sites monitored. At the Iowa site, soil θ was on average 0.041 and 0.033 cm³ cm⁻³ (0.041 and 0.033 in³ in⁻³) greater at the 10 and 20 cm (3.9 and 7.8 in) depths, respectively, following termination of a rye cover crop than crops without a rye cover crop. Thus, during the 2012 drought, the use of a rye cover crop as compared to without a rye cover crop in a corn–soybean rotation did not significantly lower soil water conditions. The use of a cover crop either had no impact or significantly increased soil water conservation.