Display omitted
•Cyanobacteria and moss biocrusts decrease constant infiltration rate by 29–52%.•Biocrusts decrease soil saturated hydraulic conductivity by 39–65%.•Reduced infiltrability was not ...explained by repellency and organic matter of biocrust.•Soil infiltrability was impacted by the fine content and thickness of the biocrusts.
Biocrust effects on soil water infiltration and hydropedological processes have attracted increasing attention in dryland ecosystems, but are nevertheless subjected to great controversy. According to some scholars, infiltration was assumed to decrease due to repellency and to increase with the organic matter content due to its role in increasing aggregate stability and porosity. These assumptions were checked in our study on the Loess Plateau of China. By using double-ring and disc infiltrometers, the infiltration curves of cyanobacteria and moss biocrusts as well as on bare soil were continuously measured, and the characteristics of water infiltration on biocrust-covered soil and its correlations with soil properties were analyzed. Our results showed that the cyanobacteria and moss biocrusts had significantly lower constant infiltration rates under ponding conditions (0.265 and 0.180 cm min−1, respectively) as compared with the bare sand (0.372 cm min−1), and they took significantly more time (41% and 105%) and water (14% and 73%) to reach steady-state infiltration. Similarly, the saturated hydraulic conductivities of the cyanobacteria and moss biocrusts were 39% (0.514 cm min−1) and 65% (0.295 cm min−1) lower than that of the bare sand (0.839 cm min−1), respectively. More importantly, biocrust infiltrability was closely related with biocrust characteristics and soil properties, especially particle-size distribution and crust thickness. Contrary to some assumptions that attributed impeded infiltration to crust repellency, and increased infiltration to the role played by OM, both variables could not have explained the current results. Under tension and ponding conditions, cyanobacteria and moss biocrusts were found to greatly reduce surface soil infiltrability and impede soil water infiltration. These findings should be considered for future analyses of hydropedological processes in arid and semiarid regions.
Biocrusts are promising ecosystem engineers in dryland ecosystems, but their effects on soil temperature, which is the most important environmental factor of soil biological and biochemical ...processes, have not yet been well understood. In a semiarid ecosystem on the Chinese Loess Plateau, the thermal properties of moss-dominated biocrust layer and bare soil (upper 2 cm) were measured, and their correlations with the biocrust characteristics as well as soil properties (especially soil water content, θ) were analyzed. Afterwards, the soil temperature dynamics of the biocrust covered soil and bare soil were continuously recorded at 2, 6, and 10 cm depths during a year. From in-situ measurements in wet season, we found that the biocrusts increased surface soil heat capacity (C) by 10.3% (1.42 vs. 1.28 MJ m−3 K−1), thermal conductivity (λ) by 27.7% (0.69 vs. 0.54 W m−1 K−1), and thermal diffusivity (α) by 27.9% (5.01 vs. 3.92 × 10−7 m2 s−1) as compared with the bare soil, through holding more soil water (θ of the biocrusts vs. bare soil = 0.06 vs. 0.03 cm3 cm−3). However, in dry season (θ < 0.05 cm3 cm−3) they decreased 33.4% of surface soil C (0.78 vs. 1.17 MJ m−3 K−1), 54.9% of λ (0.17 vs. 0.37 W m−1 K−1), and 22.9% of α (2.32 vs. 3.01 × 10−7 m2 s−1) mostly by decreasing surface soil bulk density. Accordingly, the biocrusts decreased soil temperature by as much as 6.3–11.1 °C at 0–10 cm depth in wet season (summer), and they increased soil temperature by up to 1.3–3.7 °C in dry season (winter). More importantly, the diurnal range of soil temperature of the biocrust covered soil was sometimes as much as 6.8–9.4 °C lower than that of the bare soil at 0–10 cm depth. The decreasing or increasing effects of the biocrusts on soil temperature were exactly explained by the increased thermal properties of the biocrust layer in wet season or reduced thermal properties of the biocrust layer in dry season. We concluded that the biocrusts regulated surface soil thermal properties through increasing soil water holding capacity and decreasing soil bulk density; thus, they generated considerable buffering effects on soil temperature dynamics. In dryland ecosystem, such buffering effects of the biocrusts on soil temperature should be highly considered in various soil biological and biochemical processes.
Display omitted
•Biocrusts increased surface soil thermal properties by 10.3%–27.9% in wet season.•Biocrusts decreased surface soil thermal properties by 22.9%–54.9% in dry season.•Biocrusts decreased soil temperature by up to 6.3–11.1 °C at 0–10 cm depth in summer.•Biocrusts increased soil temperature by up to 1.3–3.7 °C at 0–10 cm depth in winter.•Biocrusts decreased diurnal range of soil temperature by up to 6.8–9.4 °C at 0–10 cm.
•Soil water evaporation under bare soil was higher than that under plastic mulch in daytime.•At nighttime bare soil evaporation was lower than that under plastic mulch.•Soil water evaporation under ...plastic mulch was 4.04–7.07% of the total evapotranspiration (374.95–513.84 mm).
Plastic mulching has been widely used in arid regions because it can decrease soil water evaporation and raise soil temperature. Previous studies, however, treated soil water evaporation under plastic mulch to be negligible, assuming that the plastic mulch can prevent water exchange between soil and atmosphere completely. In order to demonstrate validity of this assumption, experiments were conducted from 2014 to 2016 under irrigated maize (Zea mays) field in Northwest China, comparison experiments of soil water evaporation between mulched soil and the bare soil between mulches were carried out in two seed maize fields with different irrigation method, i.e. border irrigation under mulch (Site BM) and drip irrigation under mulch (Site DM), with micro-lysimeters placed under the plastic mulched soil and the bare soil between mulches to evaluate soil water evaporation of each experiment maize field. Our observations indicated that the soil water evaporation under plastic mulch (Ems) was about 4.04–7.07% of the total evapotranspiration, among which Ems in the daytime accounted for 3.58–5.37% of the total evapotranspiration and 0.99–2.10% of the total evapotranspiration in the nighttime. Thus Ems was considered not to be negligible. For two experiment sites, soil water evaporation under bare soil between mulches (Ebs) was obviously higher than the soil water evaporation under plastic mulch (Ems) in daytime, but the former was lower than the latter in the nighttime. At night, the mean soil temperature in the mulched soil was higher than that in the bare soil because of the warming effect of the plastic mulch. A soil-mulch-canopy-atmosphere model is used to consider the effects of the mulch, and the modeling results further support this finding. These results provide a new insight for understanding the effect of plastic mulch on water use efficiency.
Hurricane‐induced directional wave spectra in the Gulf of Mexico are investigated based on the measurements collected at 12 buoys during 7 hurricane events in recent years. Focusing on ...hurricane‐generated wave spectra, we only consider the wave measurements at the buoys within eight times the radius of the hurricane maximum wind speed (Rmax) from the hurricane center. A series of numerical experiments using a third‐generation spectral wave prediction model were carried out to gain insight into the mechanism controlling the directional and frequency distributions of hurricane wave energy. It is found that hurricane wave spectra are almost swell‐dominated except for the right‐rear quadrant of a hurricane with respect to the forward direction, where the local strong winds control the spectra. Despite the complexity of a hurricane wind field, most of the spectra are mono‐modal, similar to those under fetch‐limited, unidirectional winds. However, bi‐modal spectra were also found in both measurements and model results. Four types of bi‐modal spectra have been observed. Type I happens far away (>6 × Rmax) from a hurricane. Type II is bi‐modal in frequency with significant differences in direction. It happens in the two left quadrants when the direction of hurricane winds deviates considerably from the swell direction. Type III is bi‐modal in frequency in almost the same wave direction with two close peaks. It occurs when the energy of locally‐generated wind‐sea is only partially transferred to the swell energy by non‐linear wave‐wave interactions. Type IV was observed in shallow waters owing to coastal effects.
Key Points
Provides the most comprehensive picture of hurricane‐generated waves
Identifies three types of bi‐modal wave spectra based on in‐situ data
Proves quadruplet interaction, whitecapping and wind input all are crucial
A new model, which was based on the Do and Do (2000) model, was developed to describe soil water vapor sorption isotherms (SWSIs) including both adsorption and condensation processes. The model ...performance was evaluated using measured SWSIs of 33 soil samples with a wide range of clay contents (0.08–0.72 g g−1), clay mineralogy (montmorillonite, kaolinite, and mixed clay samples), and organic C contents (0.001–0.070 g g−1). The new model produced satisfactory fits to measured SWSIs, with the mean relative percentage deviation modulus less than 6.2%. For a given clay mineral type, the adsorption sites and condensation capacity increased with increasing clay content. At a given clay content, the number of adsorption sites was in the order of montmorillonitic samples (ML)>mixed clay samples (MX)>kaolinitic samples (KA), and the condensation capacities of ML and MX were lower than that of KA. For soils with low clay content (<0.12 g g−1) and similar clay mineralogy, the adsorption sites and condensation capacities were positively related to organic C. The model parameter S0 had the potential for deriving cation exchange capacity, specific surface area, and clay content. The C/S0 values could potentially be used as a proxy of the dominant clay mineral type in a sample.
Core Ideas
A new model was developed to describe soil water vapor sorption isotherms.
The proposed model yielded satisfactory fits to measured water vapor adsorption curves of different soils.
Model parameters accurately reflected the effects of soil properties on water vapor adsorption behavior.
Biocrust effects on soil infiltration have attracted increasing attention in dryland ecosystems, but their seasonal variations in infiltrability have not yet been well understood. On the Chinese ...Loess Plateau, soil infiltrability indicated by saturated hydraulic conductivity (Ks) of biocrusts and bare soil, both on aeolian sand and loess soil, was determined by disc infiltrometer in late spring (SPR), midsummer (SUM), and early fall (FAL). Then their correlations with soil biological and physiochemical properties and water repellency index (RI) were analysed. The results showed that the biocrusts significantly decreased Ks both on sand during SPR, SUM, and FAL (by 43%, 66%, and 35%, respectively; P < .05) and on loess (by 42%, 92%, and 10%, respectively; P <.05). As compared with the bare soil, the decreased Ks in the biocrusted surfaces was mostly attributed to the microorganism biomass and also to the increasing content of fine particles and organic matter. Most importantly, both the biocrusts and bare soil exhibited significant (F ≥ 11.89, P ≤ .003) seasonal variations in Ks, but their patterns were quite different. Specifically, the Ks of bare soil gradually decreased from SPR to SUM (32% and 42% for sand and loess, respectively) and FAL (29% and 39%); the Ks of biocrusts also decreased from SPR to SUM (59% and 92%) but then increased in FAL (36% and 588%). Whereas the seasonal variations in Ks of the biocrusts were closely correlated with the seasonal variations in RI, the RI values were not high enough to point at hydrophobicity. Instead of that, the seasonal variations of Ks were principally explained by the changes in the crust biomass and possibly by the microbial exopolysaccharides. We conclude that the biocrusts significantly decreased soil infiltrability and exhibited a different seasonal variation pattern, which should be carefully considered in future analyses of hydropedological processes.
Accurate information on the dry end (matric potential less than -1500 kPa) of soil water retention curves (SWRCs) is crucial for studying water vapor transport and evaporation in soils. The ...objectives of this study were to assess the potential of the Oswin model for describing the water adsorption curves of soils and to predict SWRCs at the dry end using the hygroscopic water content at a relative humidity of 50% (θRH50). The Oswin model yielded satisfactory fits to dry-end SWRCs for soils dominated by both 2:1 and 1:1 clay minerals. Compared with the Oswin model, the Campbell and Shiozawa model combined with the Kelvin equation (CS-K) produced better fits to dry-end SWRCs of soils dominated by 2:1 clays but provided poor fits for soils dominated by 1:1 clays. The shape parameter α of the Oswin model was dependent on clay mineral type, and approximate values of 0.29 and 0.57 were obtained for soils dominated by 2:1 and 1:1 clays, respectively. Comparison of the Oswin model combined with the Kelvin equation, with water potential estimated from θRH50 (Oswin-KRH50), CS model combined with the Arthur equation (CS-A), and CS-K model, with water potential obtained from θRH50 (CS-KRH50) indicated that for soils dominated by 2:1 clay minerals, the predictive ability of the Oswin-KRH50 model was comparable to the CS-KRH50 model in which θRH50 was the input parameter but performed better than the CS-A model where clay content was the input parameter. The Oswin-KRH50 model also has the potential for predicting dry-end SWRCs of soils dominated by 1:1 clays.
Understanding the spatial distribution of soil organic matter (SOM) and total nitrogen (STN) at different scales is helpful for elucidating relationships between soil properties, environmental ...factors and human activities. The objectives of this study were to compare the spatial patterns of SOM and STN and to explore the main factors affecting SOM and STN distribution in suburban Beijing at three spatial scales: large-scale (Pinggu County), medium scale (Plain area) and small-scale (Machangying town). For the county and plain scales, a total of 973 soil samples (0–20cm) were collected on a 400×400m grid across an area of 1075km2. For the town scale, a total of 171 topsoil samples were collected on a 100×100m grid within an area of 28.6km2. The SOM and STN concentrations were determined for each soil sample. Descriptive statistics and geostatistical methods were used to analyze the data at the three spatial scales. The results showed that the mean values of SOM concentrations at large, medium and small scales were 14.88, 13.14 and 10.91gkg−1, respectively. The corresponding values for STN were 0.91, 0.79 and 0.66gkg−1, respectively, which also showed a decreasing trend with downscaling. The SOM and STN concentrations at the county scale had the largest spatial correlation distances, 88.2km and 25.3km respectively, while their spatial correlation distances at the town scale were the smallest, 2.5km and 3.4km, respectively. The spatial distribution patterns of SOM and STN were different. At county scale, the SOM and STN concentrations showed decreasing trends from the northeast to the southwest across the county, and topography, soil types, soil texture and land use types were the main influencing factors. At the plain scale, the SOM and STN exhibited a similar spatial distribution pattern as at the county scale, and soil types and farming practices were the main factors affecting the SOM and STN distribution patterns. At town scale, SOM and STN showed relatively uniform distributions, and soil texture and farming practices were the main affecting factors. It was concluded that manipulation of farming practices and land use types should be considered for improving SOM and STN levels in soils.
•The spatial patterns of SOM and STN contents are different at three scales.•The average values of SOM and STN decreased with the downscaling.•The spatial correlation distances of SOM and STN decreased with the downscaling.•Topography, soil types and land use were the main affecting factors at large scale.•Farming practices were the main affecting factors at medium and small scales.
•The EU-Rotate_N model was validated for greenhouse tomato in Northern China.•Nitrate leaching and gaseous N loss are the main pathways of N loss.•Optimal fertilizer and drip irrigation can ...significantly reduce nitrate leaching.•Adding crop residues can reduce nitrate leaching.•Evaluating and optimizing the combinations of water and fertilizer practices
The objectives of this study were to compare nitrate leaching and gaseous N loss from greenhouse tomato grown under different water and fertilizer management, and to optimize water and nitrogen management practices. A greenhouse experiment with different water and nitrogen management practices was conducted in Shouguang county, northern China, from August 2010 to June 2011. Four treatments were imposed: furrow irrigation+conventional fertilizer (farmer's practice, FP), FP+crop residues (FPR), drip irrigation+optimal fertilizer (DO), and DO+crop residues (DOR). The EU-Rotate_N model was used to simulate tomato growth, water movement and N fate. The simulation results indicated that nitrate leaching and gaseous N loss were the main pathways of N loss in greenhouse tomato production in the study area. The amounts of nitrate leaching under furrow treatments accounted for 43–67% of total N input. Gaseous N loss under all treatments accounted for about 3–14% of total N input. Drip irrigation and optimal N fertilizer application can significantly reduce nitrate leaching and improve water and nitrogen use efficiencies (WUE, NUE). Compared with farmer's practices (FP, FPR), nitrate leaching under drip irrigation (DO and DOR treatments) decreased by about 90%, while the NUEs was increased 2- to 3-fold. In addition, adding crop residues (DOR, FPR) reduced nitrate leaching by 15% compared to the treatments with no crop residues (DO, FP), while it increased the gaseous N loss by about 35%. Furrow irrigation is the most commonly practiced method for most vegetable production in northern China, and this farmer's practice was selected to obtain the best management practices (BMPs) for irrigation schedules and N fertilization rates. More than 288 scenarios combining various types of irrigation and fertilizer practices were simulated per season. Agronomic indices (tomato yield, WUE and NUE), environmental indices (nitrate leaching and gaseous N loss), and economic index (value to cost ratio) were selected as the evaluation indices to identify the BMPs. An osculating value method was used to evaluate combinations of irrigation and fertilizer practices. The results indicated that the BMPs under furrow irrigation conditions are to irrigate tomato with 300mm and apply fertilizer N at a rate of 150kg Nha−1 in the autumn–winter season, and to irrigate with 300mm and apply fertilizer N at a rate of 250kg Nha−1 in the spring–summer season.
The adsorbed water content is an attractive predictor for estimation of soil specific surface area (SSA) as its measurement is less laborious and more cost effective than standard laboratory ...techniques. We analysed the effects of total specific surface area (SSAtot), external specific surface area (SSAex) and internal specific surface area (SSAin) on water vapour sorption on 21 soil samples, and proposed models for estimating SSAex, SSAtot and SSAin from organic carbon content and the slope of soil water vapour sorption isotherm (SL0.5) and water content (WC0.5) at a water activity of 0.5. The results indicated that the variation of correlation coefficients between water content change at 0.05 water activity interval (WCC0.05) and SSAtot with water activity was mainly due to the differences in water vapour adsorption in interlayer spaces at different water activity levels. Furthermore, in the soil water content range from ~0.001 to ~0.03 g g−1 (within the water activity range from ~0.45 to ~0.75), water vapour adsorption was related closely to SSAex. Cross‐validation results on estimated SSAex, SSAtot and SSAin of the 21 samples produced root mean square error (RMSE) values less than 9.39 m2 g−1 and Nash‐Sutcliffe model efficiency coefficients (E) greater than 0.93, suggesting that the proposed models provided reasonable estimates of SSA components. Thus, soil water vapour adsorption data can be applied to simultaneously estimate SSAex, SSAtot and SSAin. Variation of correlation between WCC0.05 and SSAtot with water activity depended on SSAin. Soil water vapour sorption is related closely to SSAex at water activities from ~0.45 to ~0.75. The proposed models yield reasonable estimates of SSAtot, SSAex and SSAin. Adsorbed water content can be used as a predictor for SSA estimation.
Highlights
Variation of correlation between WCC0.05 and SSAtot with water activity depended on SSAin.
Soil water vapor sorption relates closely to SSAex at water activities from ~0.45 to ~0.75.
The proposed models yield reasonable estimates of SSAtot, SSAex, and SSAin.
Adsorbed water content can be used as a predictor for SSA estimation.
