Abstract Clay content in soil potentially has strong influence on soil structure and thereby controls soil physical, hydraulic, and gas transport properties. Only few studies have investigated the effect of clay content on saturated hydraulic conductivity ( K s ) and gas transport parameters such relative gas diffusivity ( D p /D 0 ) and air permeability ( K a ) under varying conditions of clay contents. In this study, two clay gradients were investigated: a natural clay gradient and an induced (clay mineral attapulgite‐controlled) clay gradient. We determined the effect of the two clay gradients on soil air and water parameters and identified the potential relationships between these parameters and other physical properties. The results indicated that all D p /D 0 , K a , and K s decreased with increasing clay content. The differences among the various treatments were dependent on the soil pore characteristics (air‐filled porosity, ε; pore continuity, PO A ; pore tortuosity, τ; and pore size distribution). Under the natural clay gradient, the increased clay content resulted in 52.8% more micropores and 35.2% fewer macropores. The slope of τ vs. clay content under the induced clay gradient was found to be higher than that under the natural gradient. Statistically meaningful correlations could be found between K s and K a (| r| = .904) and also between K s and D p /D 0 (| r| = .810), whereas D p /D 0 was evidenced to be better correlated with K s regardless of the type of clay gradient ( P < .01). The results thus provide a valuable experimental and numerical insight to develop useful correlations among K s , K a , and D p /D 0 under differing clay gradients.
Abstract Climate events, such as drought and rainfall, can lead to a cycle of drying and wetting that may cause changes in soil structure, leading to deteriorations in the health of saline soils. However, little is known about the extent and behavior of soil structure degradation under the combined influences of salinity and drying–wetting (D‐W) cycles. Thus, we systematically investigated the effects of salinity (0, 5, 30, and 100 g/L, labeled as CK, T5, T30, and T100) and D‐W cycles on soil structure by determining soil volume, shrinkage, and swelling potentials along with soil pore character obtained from soil shrinkage characteristics curve, intending to explore how D‐W cycles and salinity affect soil structure. The results showed that soil deformation behaviors in saline and non‐saline soils varied with the number of D‐W cycles. Irreversible deformation of the soil was observed during continual D‐W cycles. The soil volume increased by 3.75%–15.73% after three D‐W cycles. In vertical direction, the maximum expansion magnitude for each treatment was reached with the value of 29.03%, 23.42%, 34.23%, and 35.87% in CK, T5, T30, and T100, respectively. The magnitudes of shrinkage and expansion were equal in the horizontal direction since the soil samples consistently returned to their original dimensions. Furthermore, the decrease was observed in the micropores and capillary pores affected by salinity, with values of 50%, 58.6%, and 70.4% in CK, T5, T30, and T100, respectively. However, the D‐W cycles primarily affected large pores. High salinity levels enhanced swelling potential and inhabit shrinkage potential, prolonging the water processes required for the soil structure to achieve stability. The results of this study underscore the necessity of understanding the hysteresis of soil volume change and elucidate the mechanisms of soil structure deterioration driven by salinity and D‐W cycles. These findings provide a valuable reference for healthier soil management.
Purpose Traditional laboratory measurements of soil water diffusivity ( D ) and soil water retention curve (SWRC) are always time-consuming and labor-intensive. Therefore, this paper aims to present a simple and robust test method for determining D and SWRC without reducing accuracy. Design/methodology/approach In this study, a D model of unsaturated soil was established based on Gardner–Russo model and then a combination of Gardner–Russo model with one-dimensional horizontal absorption method to obtain n and a parameters of Gardner–Russo model. One-dimensional horizontal absorption experiments on loam, silt loam and sandy clay loam were conducted to obtain the relationships between measured infiltration rate and cumulative infiltration with wetting front distance. Based on the obtained relationships, the measured infiltration data from the one-dimensional horizontal absorption tests were used to calculate n and a parameters and further constructing D and SWRC. Findings Both the calculated D and SWRC inversed from the infiltration data were in good agreement with the measured ones that obtained from the traditional horizontal absorption method and the centrifuge method, respectively. Error analysis indicated that only the infiltration data are enough to reliably synchronously determine D and SWRC. Originality/value A simple and robust method is proposed for synchronous determination of soil water diffusivity and water retention curve.
Due to the soil nutrient distribution caused by complex mountain topography, it is difficult to achieve the precise fertilization. This study investigated variable-rate fertilization based on the spatial variability of soil nutrients in a custard apple orchard. Soil grid sampling was used to determine the variability of soil nutrients in a 1656‑m2 orchard. The spatial variability of soil nutrients showed a moderate to high spatial dependency and variable-rate fertilization decision-making was made based on the nutrient distribution. The variable-rate fertilizer applicator controlled by code was assembled with a small self-propelled fertilizer applicator as the carrier to test its fertilizing effect in the field. Based on the results, variable-rate fertilization reduced nitrogen, phosphorus, and potassium fertilization by 42%, 46%, and 19%, respectively, compared with traditional fertilization, and custard apple yield increased by 22 and 34% in 2022 and 2023, respectively. In the 2‑year tracking experiment, the levels of soluble protein and vitamin C also increased significantly. The results showed that it was feasible to calculate fertilizer input at any location of the plot based on soil experiment data and to provide spatial data for the fertilizer operator control system for variable-rate fertilization, thereby improving fertilizer use efficiency and quality of custard apples.
Precise estimation of daily reference crop evapotranspiration (ET0) is critical for water resource management and agricultural irrigation optimization worldwide. In China, diverse climatic zones pose challenges for accurate ET0 prediction. Here, we evaluate the performance of a support vector machine (SVM) and its hybrid models, PSO-SVM and WOA-SVM, utilizing meteorological data spanning 1960–2020. Our study aims to identify a high-precision, low-input ET0 estimation tool. The findings indicate that the hybrid models, particularly WOA-SVM, demonstrated superior accuracy with R2 values ranging from 0.973 to 0.999 and RMSE values between 0.123 and 0.863 mm/d, outperforming the standalone SVM model with R2 values of 0.955 to 0.989 and RMSE values of 0.168 to 0.982 mm/d. The standalone SVM model showed relatively lower accuracy with R2 values of 0.822 to 0.887 and RMSE values of 0.381 to 1.951 mm/d. Notably, the WOA-SVM model, with R2 values of 0.990 to 0.992 and RMSE values of 0.092 to 0.160 mm/d, emerged as the top performer, showcasing the benefits of the whale optimization algorithm in enhancing SVM’s predictive capabilities. The PSO-SVM model also presented improved performance, especially in the temperate continental zone (TCZ), subtropical monsoon region (SMZ), and temperate monsoon zone (TMZ), when using limited meteorological data as the input. The study concludes that the WOA-SVM model is a promising tool for high-precision daily ET0 estimation with fewer meteorological parameters across the different climatic zones of China.
The paper calculated reference crop evapotranspiration (ET0) and analyzed its annual and interannual characteristics of Panjin Area in details based on the FAO56Penman-Monteith formula, and the daily mean meteorological data of fifty years between 1957 and 2006. The results showed that the peak of annual ET0 mainly appeared between May and September, and the curve fluctuated severer and more unstable with the increase of ET0. The interannual variation of ET0 turned to be periodicity with 5 years and the value of it appeared to have a decline trend. The value of interannual ET0 in summer and winter was the largest and the smallest respectively and it in summer turned to be downward trend apparently while it in other seasons turned to be stable trend basically. It provides references for local agriculture development.
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