Applying soil amendments plays a critical role in relieving water stress in arid and semiarid areas. The natural clay mineral attapulgite (ATP) can be utilized to adjust the balance of water and soil environment. In this study, we investigated four different particle size distribution typical soils in the Loess Plateau: (1) lou soil (LS), (2) dark loessial soil (DS), (3) cultivated loess soil (CS), (4) sandy soil (SS). Five ATP application rates (0, 1%, 2%, 3%, and 4%) were selected to test the effect of ATP on the soil water retention curve, soil saturated hydraulic conductivity, and soil structure. The results showed that applied ATP significantly increased the soil clay content, and the relative change of SS with 3% ATP applied increased by 53.7%. The field water holding capacity of LS, DS, CS, and SS with 3% ATP applied increased by 8.9%, 9.6%, 18.2%, and 45.0%, respectively. Although applied ATP reduced the saturated hydraulic conductivity, the values of CS and SS were opposite when the amount of ATP applied was >3%. The relative change in the amount of 0.25–1 mm soil water-stable aggregates of SS was 155.9% when 3% ATP was applied. Applied ATP can enhance soil water retention and soil stability, which may improve limited water use efficiency and relieve soil desiccation in arid and semiarid areas or similar hydrogeological areas.

Reasonable planning of water delivery schedules for canal systems can reduce losses caused by water seepage and improve the utilization efficiency of irrigation water. Empirical methods of water delivery scheduling for canal systems usually cause problems such as insufficient discharge, excessively delayed water delivery, and large losses under given water requirements. In this study, a canal water delivery scheduling model was set up, and a customized algorithm based on particle swarm optimization was proposed. Typical heuristic algorithms often become trapped in local optima and often search inefficiently under numerous constraints; however, the proposed algorithm can overcome these typical problems. The proposed method was evaluated for two typical canal irrigation systems, and the results showed that the algorithm is robust and efficient and can quickly meet the water delivery optimization schedules for canal irrigation systems. Compared with empirical methods, the algorithm reduced the leakage loss of delivered water from 7.29% to 5.40%, and 8.97% to 7.46% for the two tested canal systems. The discharge of the main canal is relatively stable, which can reduce the difficulty of head gate adjustment. The proposed optimization algorithm can provide practical and efficient water delivery schedules for irrigation canal systems.

Soil gas diffusivity ( D _p / D _o , gas diffusion coefficients in soil and in free air, respectively) and its relation to soil moisture is of great importance for describing and quantifying essential provisional and regulatory functions associated with terrestrial ecosystems such as soil aeration and greenhouse gas (GHG) emissions. Because gas migration in terrestrial soil systems is predominantly diffusion controlled, soil gas diffusivity becomes a fundamental prerequisite to quantify diffusive gas fluxes. Descriptive–predictive models are often used to estimate D _p / D _o from easily measurable soil physical properties. Most of the available models take the form of power‐law functions and often tend to mischaracterize soil moisture effects at high moisture regimes. Based on a wide range D _p / D _o data available in literature representing both intact and repacked soils, this study developed a novel air‐saturation‐dependent exponential (ASEX) gas diffusivity model to model D _p / D _o in relation to soil air saturation. The model variable α, which represents the diffusivity at half air saturation normalized by the same in complete soil air saturation, could potentially differentiate moisture effects on different soil structural states. For specific applications in intact soils, we propose corresponding α values for upper‐limit (α = .6) and lower‐limit (α = .05) estimates of diffusivity, while an average value (α = .3) for general applications in both intact and repacked soils. As expected, our model based on a few a priori measured supportive data showed a better performance over the classical predictive models that do not use such measurements. The new model was further used to derive useful implications to showcase soil density effects on D _p / D _o .

Soil-gas diffusivity and its variation with soil moisture plays a fundamental role in diffusion-controlled migration of climate-impact gases from different terrestrial agroecosystems including cultivated soils and managed pasture systems. The wide contrast in soil texture and structure (e.g., density, soil aggregation) in agriculture topsoils (0–10 cm) makes it challenging for soil-gas diffusivity predictive models to make accurate predictions across different moisture conditions. This study characterized gas diffusivity and gas-phase tortuosity in soils sampled from managed pasture and cultivated sites in Sri Lanka at 0–10 cm depth, together with selected soil-gas diffusivity data from the literature. Soil-gas diffusivity was measured using a one-chamber diffusion apparatus using N₂ and O₂ as experimental gases. The measured diffusivity, together with literature data representing both intact and repacked soils, were tested against five existing widely known gas diffusivity predictive models. The tested models tended to mischaracterize the two-region behavior in some of the aggregated soils, suggesting the need of soil-specific diffusivity models to better describe gas diffusivity in agricultural soils. We suggested a new parametric two-region model, developed in line with literature-based models, to represent both unimodal and bimodal/two-region behavior of selected soils. The new model statistically outperformed the existing predictive models for both intact and repacked soils and, hence, demonstrated its applicability to better characterize site-specific greenhouse gas emissions under different soil water regimes.

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.

Using the extremely limited water for deficit irrigation is a notable measure to improve crop yield in water shortage regions. Hence, determining a reasonable irrigation period in large regions is crucial. In this study, a simple and applicable process to determine the irrigation period in a large area by using the precipitation-yield integral regression method of crop growth period was proposed, and the winter wheat planting regions with a serious water shortage in Shaanxi, China were referred to as an example. According to the regional topography, soil, precipitation, temperature, and evaporation, the study area was first divided into four subregions; then, the rainfall water surplus and deficit characteristics of the subregions during the growth period of winter wheat were analyzed, and the precipitation-yield integral regression function of the subregions was calculated. In accordance with the sensitivity of rainfall to crop yield in different periods, the reasonable irrigation period of winter wheat in each subregion was determined. The results are basically consistent with irrigation habits of local farmers, and can be used to guide the irrigation of local winter wheat. They also demonstrate that the method has the advantages of requiring fewer data and being simple and reliable, and can overcome the problem that the existing method is difficult to determine the optimal irrigation period in the large-scale region, due to the lack of test points and representativeness. The proposed method application value in determining the deficit irrigation period with small water amount, in a large region lacking research materials.