Search

Abstract Biochar has been shown to improve soil properties and plant productivity in soils with inherently low fertility. However, little has been reported for upland corns under dry and wet precipitation regimes. This study investigates the effect of biochar addition on a range of soil physicochemical, biological, and hydrological properties, and corn growth and productivity under agrometeorological drought and wet conditions. Here, experiments were laid out in a randomized complete block design with three replications at two sites during 2017 and 2018 in South Korea. Treatments included (i) CN: control (ii) IF: inorganic fertilizer (N–P–K) at 145–30–60 kg ha−1; (iii) BS: barley straw at 5 t ha−1; (iv) CWBC: corn waste biochar at 5 t ha−1; (v) CWBC + IF: corn waste biochar + inorganic fertilizer; (vi) CWBC + BS: corn waste biochar + barley straw. The year 2017 was relatively dry, whereas the year 2018 was wet. Despite drought conditions in the year 2017, biochar facilitated soil water conservation. However, higher precipitation in 2018 increased the quantity and distribution of soil water and nutrients in the top 15 cm. Biochar reduced soil bulk density, and increased porosity, cation exchange capacity and total organic carbon in both years but increased total bacterial counts during the dry year only. Bacterial population was generally higher under wet conditions. Similarly, more soil CO2 was emitted in the wet year than in the dry year. Results further indicated that biochar can enhance corn biomass and grain yield regardless of precipitation conditions. The grain index was, however, affected by rainfall and was significantly different across treatments in the year 2018 only. All biomass, grain yield, and grain index were highest in CWBC + IF treatment and lowest under CN treatment. Indeed, biochar addition appeared to improve soil quality and soil conditioning effects in the drought and wet years, ameliorating soil and plant properties. Overall, biochar can improve water and nutrients storage, availability, and uptake, and therefore corn productivity during hydrological extremes. Graphical abstract

Objective Soil moisture information crucial for various applications, such as natural ecological restoration, farmland irrigation management, and soil engineering construction. One of the main sensors used to obtain this information is the capacitive soil moisture sensor. Methods To accurately calibrate the soil water content observation data of the 5TE capacitive soil water sensor, soil dielectric permittivity, electric conductivity and temperature observation experiments were carried out under different temperature, salt content and soil water content conditions. A soil water content estimation model based on the random forest machine learning method was established. Results The results showed that: ① The soil dielectric permittivity was significantly affected by varying salinity and temperature with constant soil water content. The traditional soil water content estimation model based only on soil dielectric permittivity became invalid, ② The soil water content estimation model based on the random forest method could effectively improve the soil water content estimation with the soil dielectric permittivity, electric conductivity and temperature data as input. Random forest method obtained soil moisture estimation with RMSE=0.05 m3/m3 and R2=0.77, while RMSE=0.07 m3/m3 and R2=0.54 were obtained by the modified Topp equation, and ③ The soil electric conductivity was the most important factor for soil water content estimation, followed by the dielectric permittivity and temperature. Nevertheless, the importance of the dielectric permittivity and temperature did not reach a negligible level. Conclusion This study provides a way to support the successful application of capacitive soil moisture sensors in areas with variable temperature and salinity.

The time elapsed between the moments of maximum rainfall intensity and maximum soil moisture, known as peak to peak (P2P), is part of the hydrological response of the soil, but literature has missed this metric in any woody crop. In a vineyard with permanent vegetation cover (humid climatic conditions), the influence of two cultivars (Agudelo and Blanco Legítimo) and two zones (rows and inter-row areas) on the values of soil moisture response time, absolute change in moisture (ΔS) and P2P was evaluated for 118 rainfall events in three soil layers. 12 capacitance probes and a weather station were used, and data measured every 15 min. A positive response (ΔS > 0) was observed in 79 %, 73 % and 67 % of all events at soil depth of 5, 15 and 25 cm, decreasing ΔS with increasing soil depth. Differences of ΔS were significant among layers, but not among cultivars and zones. The maximum ΔS occurred at 15 cm, while the minimum was observed at 25 cm. No response was evident when specific thresholds were not reached: rainfall depth (0.60 mm event−1), maximum intensity (1.20 mm h−1) or duration (30 min). Topsoil conditions –high rainfall interception by the dense cover and high soil organic matter content– influenced the results at 5 cm. Rain parameters correlated well with ΔS, but weak with the response time and P2P. P2P occurred earlier in the rows than between the rows, especially at 15 cm. Shorter P2P appeared in Agudelo, with significant differences in the rows at 5 cm. P2P differed significantly among layers, increasing P2P with soil depth. Similar ΔS values appeared in Spring and Autumn, and were significantly different than those in Summer, but P2P did not differ significantly among seasons. Therefore, the magnitude and timing of the soil hydrological response were independent processes.

Enhancing the spatial and temporal coordination between soil water and roots is very important for crop growth. The vertical distribution and relationship between soil water and root are however poorly understood during maize growth under different soil water conditions. In this study, two maize hybrids ZD958 and FM985 were treated with drip irrigation (DI), flood irrigation (FI), and rainfed (RF) in two–year field experiment as well as with irrigation at 0–30 (TI), 30–60 (MI), 60–90 (BI), 0–90 cm soil layers (AI) and no irrigation in three–year tube experiment. In field experiment, DI and FI both increased root dry weight, root length density (RLD), and the proportion of coarse root length at different soil layers relative to RF. DI increased grain yield by 10.0% in FM985 and by 10.8% in ZD958 compared with FI. Both total root and fine root length were greater in DI than in FI, which increased the nitrogen and water use efficiency and yield. In the tube experiment, irrigation at different soil layers increased root dry weight, RLD and the proportion of coarse root length compared with no irrigation, with AI increasing the most. FM985 distributed more roots at the 0–30 cm soil layer than ZD958. Grain yields were positively correlated with the RLD in each soil layer and coarse root proportion at the upper layer (r=0.493** in field experiment and r=426** in tube experiment) but negatively correlated with root–shoot ratio (r=−0.793** in field experiment and r=−670** in tube experiment) at maturity stage. In conclusion, there is a large potential to improve maize yield by enhancing the spatial coordination between root distribution and soil water movement.

Quantifying evapotranspiration (ET) in rainfed cropping systems can be challenging due to complicated interactions among site-specific soil, plant, and management factors. In Northeast China, ET and soil water status in maize fields often display strong spatial and temporal variations due to the changes in tillage practice, planting pattern, and maize plant density. Previous studies have shown that near-surface soil water content (θ) observations at multiple scales provide the potential to estimate surface soil water fluxes. In this study, we introduced a new method to estimate daily field ET by using a soil water flux model mainly based on the time-series of θ at a depth of 2.5 cm. The new method required a calibration of soil water diffusivity with maximum net water flux in the near-surface soil layer, which was related to precipitation redistribution below the canopy. Finally, the new method was evaluated using observed ET values over a 2-year period in a maize field, where independent measurements of soil water evaporation (E) and transpiration (T) were made with heat-pulse sensors and sap-flow gauges, respectively. Field observations showed that E dominated water loss during the seedling stage (16% of total ET). As the canopy was fully developed, E sharply decreased to a value of 0.4 mm d−1, and T accounted for about 89% of ET since the silking stage. The new method to estimate ET performed well in drying periods, while it tended to underestimate ET in wet periods with substantial infiltration into the surface layer. On rain-free days, the ET values estimated with the new method matched well with the measured E+T values, with R2 and RMSE values of 0.85 and 1.93 mm d−1. Therefore, the new approach provides an effective way to quantify maize ET.

Global warming may exacerbate cropland soil drought, affect microbial systems, and decrease grain yield. However, the compensatory effects of supplementary irrigation on winter wheat yield and soil microbial communities under increased temperatures have not been fully studied. Here, a three-year field experiment was conducted, to verify the effects of warming treatments (WS: winter and spring warming; FF: flowering and filling period warming) and irrigation (W0: conventional irrigation; W1: supplemental irrigation) on crop-soil systems during the winter wheat growth stages. The results demonstrated that warming measures have significant negative effects on the net assimilation rate of flag leaves and yield formation, which led to a reduction of wheat yield by 14–40%. However, increasing irrigation can compensate for a yield of 9.7–15%. In addition, warming increases the soil temperature and decreases the soil water content, resulting in decreased soil microbial diversity. The effect size (β) = −0.23 to −0.53 for index of phylogenetic diversity (PD) under warming, while β= 0.16 under increased irrigation. The SEM model further showed that supplementary irrigation during anthesis to filling can improve the soil environment and extend the validity of photosynthetic to increase production, which was an important mitigation measure to adapt to the warming climate in wheat production.

Use of cover crops have been suggested to increase agricultural sustainability by providing multiple ecosystems services. Replacing summer fallow with drought tolerant legumes could serve both as a cover and a green source of N for winter wheat (Triticum aestivum L.) and help mitigate economic and environmental problems by increasing resilience of agroecosystems in the United States (US) Southern Great Plains (SGP). Field experiments were conducted in 2018 and 2019 at the USDA - ARS Oklahoma and Central Plains Agricultural Research Center near El Reno, OK. The overall objective of the study was to quantify the potential of two summer legumes, tepary bean [Phaseolus acutifolius (A.) Gray] and moth bean [Vigna aconitifolia (Jacq.) Marechal], as green sources of N for winter wheat production in comparison with soybean [Glycine max (L.) Merr.]. The PROC MIXED procedure of the SAS statistical software was used to analyze biomass production by legumes, their impacts on soil water, soil N and yield of winter wheat, and N transfer from green N biomass to following winter wheat. Green N crops did not differ in biomass production, but soybean provided 22 % and 40 % more N than tepary bean and moth bean, respectively. Soil water was reduced under all green N crops than summer fallow at termination of green N crops and wheat planting. Biomass of green N crops increased N content in soils at wheat planting. Grain yield of winter wheat was significantly higher under tepary bean (5295 kg ha−1) than soybean (4300 kg ha−1), moth bean (4560 kg ha−1) and the control treatment (4323 kg ha−1). Nitrogen recovery in wheat biomass was greater under moth bean and tepary bean compared to soybean. Both moth bean and tepary bean could serve as green sources of N for winter wheat in the US SGP.

Large-scale afforestation poses threats to water resources security in water-limited areas, and the water availability affects plants growth and mortality. Shelterbelts degradation inevitably causes stand structure changes, which affect the soil water content (SWC). In this study, we used high-density sampling method to study the Populus simonii Carr stands located in the only 6.3 km2 Boluosu forest farm in the semiarid region of northern China, including healthy and degraded stands, and cropland and grassland plots as controls. The vertical profiles (0–200 cm) of SWC was measured in each plot in 73 selected locations, soil characteristics and stand structure of typical Populus simonii Carr were measured. The main purpose was to analyze the impact of the Populus simonii Carr degradation on the soil water vertical variation and to combine this information with stand structure and soil characteristics to analyze all their effects together. The results showed that compared with cropland (254.7 ± 14.96 mm) and grassland (237.9 ± 12.62 mm), the soil water storage of healthy Populus simonii Carr (198.91 ± 8.47 mm) decreased by 21.9 % and 16.4 %, respectively. The shallow layer (0–60 cm) SWC increased significantly with degradation degree (P

Film mulched ridge–furrow tillage (FMRF) has been successfully used to replace conventional tillage (CT) and increase maize yields in drylands in northwestern China. To increase maize production sustainably, however, investigations are warranted of the underlying mechanism through which FMRF affects soil quality and fertility. Therefore, we conducted an 18-year survey (2003–2020) and a 6-year (2015–2020) field experiment to systematically compare CT and FMRF with regard to soil bulk density (BD) and the concentration, storage, and stratification of soil organic carbon (SOC); labile organic carbon (LOC); total nitrogen, phosphorus, and potassium (TN, TP, and TK, respectively); and available N, P, and K (AN, AP, and AK, respectively). Data were collected in a soil layer of 0–30 cm in the survey and in a soil profile of 0–100 cm with 20-cm increments in the field experiment. The SOC, N, P, and K storage, C:N ratio, and their surface stratification ratios were calculated, and their contributions to soil quality and fertility were systematically evaluated. The results indicated that BD decreased with increasing years of FMRF application. Compared to CT, FMRF significantly increased the concentrations of AK, AP, AN, TK, TP, TN, LOC, and SOC, especially at the 0–40 cm soil horizon and the storage of SOC, TN, TP, and TK in the entire 0–100 cm soil profile, but significantly decreased the C:N ratio at 0–60 cm depth. The stratification ratios of AK, AP, AN, LOC, TK, TN, TP, and SOC were within 1–2.5 and were significantly higher under FMRF than CT for 0–60 cm depth. FMRF also significantly improved soil water status and contributed greatly to increasing the concentration and redistribution of SOC, N, P, and K. Therefore, FMRF improved the soil quality and fertility by increasing the concentration and stratification of SOC, N, P, and K. Further investigations should systematically consider the integrated effects of soil types, farming system, soil microbial processes, and climatic factors.

Aims: Root exudates contain polymers that form crosslinks and can create a jelly like substance known as mucilage, which adheres to soil and thus promotes the formation of rhizosheaths, i.e. soil that remains attached to the roots after gentle shaking. We hypothesized that rhizosheath formation is optimal at an intermediate chia seed mucilage concentration and water content, but that its formation is limited at both a high concentration of chia seed mucilage and under dry conditions as well as at a low concentration of chia seed mucilage and under wet conditions. We used an artificial root soil system in which soil moisture and mucilage concentrations could be varied independently from one another with respect to their effect on rhizosheath formation. Methods: Jute cords were disposed in sandy loam soil and in quartz sand. In a subsequent study, they were also amended to different moisture contents with five different concentrations of mucilage (from 0 to 0.2 g dry mucilage g−1 water), before being isolated from chia and flaxseed mucilage after swelling of the respective seeds in distilled water for 15 min. Results: We found that in dry soil, rhizosheath formation peaked at an intermediate chia seed mucilage concentration. This behavior was supported by our conceptual model of mucilage spreading and rhizosheath formation, which relies on a radial diffusion equation and assumes that at low mucilage concentration, molecule numbers are insufficient to support polymer-like networks that stick soil particles together. In a very concentrated gel, however, mucilage is too sticky to diffuse far into the soil. Increasing soil moisture promotes rhizosheath formation both in a low and a high mucilage concentration range, although only up to an intermediate volumetric water content of 0.15cm3 cm–3. Conclusions: We conclude that both water and chia seed mucilage concentration are important drivers of rhizosheath formation. The effects are not additive but can combine to an optimum range, with a maximum formation of rhizosheaths observed in this study at 0.12 g mucilage g−1 rhizosphere water. [ABSTRACT FROM AUTHOR]

We studied fairy circles 20 km west of Sesriem at one of the driest locations of fairy circles in Namibia, at the foot of the popular Sossusvlei dunes. These fairy circles lack the typical hexagonal order of the Namibian fairy circles. After years of drought, their pattern is more similar to that of vegetation rings, due to the sparse vegetation in the area between the circles. Cross-section measurements of the soil water content (SWC) show that the upper layer (12 cm) is very dry (~1%) and much below the wilting point of Stipagrostis ciliata grasses, whereas the deeper soil layer is wetter (4%). The grain size distribution of soil samples taken from inside and outside the fairy circles reveals considerable heterogeneity in the size fractions due to aeolian (wind-driven) sand sorting. The bare soil inside the fairy circles contains coarser grains, and the ground surface is covered by sand megaripples. There is a linear trend between the vertical soil moisture gradient and the median grain diameter. Fine particles trapped on the vegetated edges of the fairy circle result in small nebkhas that increase the soil water retention at the surface. The dry and loose coarser topsoil inside the fairy circles may prevent the recolonization of new seedlings with short root lengths inside the fairy circles. Our results highlight the role of aeolian sand transport and deposition in desert vegetation environments and seem to support the notion that fairy circle formation may be affected by the interplay between sand sorting and soil moisture gradients. [ABSTRACT FROM AUTHOR]

Recent changes in water availability can be crucial for the development, growth and carbon budget of forests. Therefore, our aim was to determine the effect of reduced throughfall and severe summer drought on stem CO2 efflux as a function of temperature and stem increment. Stem CO2 efflux was measured using the chamber method on oak and hornbeam under four treatments: coppice, thinned coppice, and both coppice and thinned coppice with 30 %-reduced throughfall. The first year of the experiment had favourable soil water availability and the second year was characterized by a dry summer. While reduced throughfall had no effect on stem CO2 efflux, the summer drought decreased efflux by 43–81 % during July and August. The stem CO2 efflux was reduced less severely (by 13–40 %) in September when the drought persisted but the stem increment was already negligible. The stem increment was also strongly affected by the drought, which was reflected in its paired relationship with stem CO2 efflux over the two experimental years. The study showed that summer dry periods significantly and rapidly reduce stem CO2 efflux, whereas a constant 30 % rainfall reduction needs probably a longer time to affect stem properties, and indirectly stem CO2 efflux. [ABSTRACT FROM AUTHOR]

Savannas are water‐limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna‐wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site in Arizona, USA. We distinguished between SWC across two different depth intervals (shallow, <0–30 cm and deep, >30–100 cm). We found that tree greenness increased with SWC at both depths, while understory greenness was only sensitive to the shallower SWC measurements. Onset of ecosystem dormancy, estimated from satellite observations close to the eddy covariance tower, explained more variability in annual gross primary productivity (GPP) than in other phenometrics. Higher SWC led to an extended growing season, caused by delayed dormancy in trees, but the understory showed no evidence of delayed dormancy in wetter periods. We infer that the timing of ecosystem scale dormancy, driven by trees, is important in understanding changes in a savanna's GPP. These findings highlight the important effects of rainfall during the winter. These findings suggest that savanna GPP is conditional on different responses to moisture availability in each of the dominant vegetation components. [ABSTRACT FROM AUTHOR]

Purpose: Slight changes in soil respiration significantly affect atmospheric carbon dioxide (CO2) concentrations and the global carbon balance. How soil respiration responds to the change of precipitation and what factors drive the change of soil respiration under the change of soil water content remain largely unexplored. Materials and methods: This study conducted a manipulative field experiment along a precipitation gradient [reducing precipitation by 50% (W1), natural precipitation (W2), increasing precipitation by 50% (W3), and increasing precipitation by 100% (W4)] in a desert steppe within the Siziwang Banner, Inner Mongolia. Results and discussion: We found that the soil respiration rate increased first and then decreased, the peak appeared in August over the 2-year growing season (June to October), which was consistent with the change of soil water content. With the increase of soil water content, soil respiration tended to increase. Plant properties had the strongest explanatory to soil respiration, followed by soil physicochemical properties and biological properties, and soil respiration was also regulated by these three factors. Soil water content not only directly affected soil respiration, but also affected soil respiration by promoting plant biomass and inhibiting soil nutrients. Conclusions: Soil water content was an important factor affecting soil respiration rates, carbon released from the soil increased when precipitation increased. Plant biomass and soil nutrients were the driving factors of soil respiration under precipitation change. [ABSTRACT FROM AUTHOR]

In West Africa, the validation of distributed models is limited by the quality and availability of point station data measured in-situ. ERA5 is a climate reanalysis produced by European Centre for Medium-range Weather Forecasts (ECMWF) and suggested to overcome this constraint. This study assessed and compared over the Benin basins at spatial and monthly time scale, the quality of ERA5 and its variant ERA5-Land (namely LAND). ERA5 relies on the single-levels version with 0.25° x 0.25° resolution while LAND is the land surface version with 0.1° x 0.1° resolution. Four variables were collected including runoff, evapotranspiration (ETR), water table depth (WTD), and soil water content (SWC). Point station data were analyzed using the correlation performance evaluators, Mean Absolute Error (m) and Relative Mean Absolute Error (r). The results showed that LAND simulates well the peaks of mean runoff. It showed the best runoff performance in terms of correlation (~0.61) compared with ERA5 (correlation ~0.49). Both reanalysis showed high correlations (generally > 0.80) for SWC, but the correlations obtained from ETR are slightly lower (ERA5~0.58 vs. ERA5-Land~0.54). Correlations were below 0.5 on both reanalyses for WTD with slight overestimation (m=4.73 m for ERA5 vs. m=3.13 m for LAND). This study does not identify any reanalysis that is better than another, both spatially and monthly scale. Nevertheless, this study indicated that the choice of reanalyses must rely on their performance and the given water cycle element. Correcting the variables of these reanalysis could also improve their performance. [ABSTRACT FROM AUTHOR]

Knowledge of the soil water content (SWC) is important for many aspects of agriculture and must be monitored to maximize crop yield, efficiently use limited supplies of irrigation water, and ensure optimal nutrient management with minimal environmental impact. Single-location sensors are often used to monitor SWC, but a limited number of point measurements is insufficient to measure SWC across most fields since SWC is typically very heterogeneous. To overcome this difficulty, several researchers have used data acquired from unmanned aerial vehicles (UAVs) to predict the SWC by using machine learning on a limited number of point measurements acquired across a field. While useful, these methods are limited by the relatively small number of SWC measurements that can be acquired with conventional measurement techniques. This study uses UAV-based data and thousands of SWC measurements acquired using geophysical methods at two different depths and before and after precipitation to predict the SWC using the random forest method across a vineyard in the central United States. Both multispectral data (five reflectance bands and eleven vegetation indices calculated from these bands) and thermal UAV-based data were acquired, and the importance of different reflectance data and vegetation indices in the prediction of SWC was analyzed. Results showed that when both thermal and multispectral data were used to estimate SWC, the thermal data contributed the most to prediction accuracy, although multispectral data were also important. Reflectance data contributed as much or more to prediction accuracy than most vegetation indices. SWC measurements that had a larger sample size and greater penetration depth (~30 cm sampling depth) were more accurately predicted than smaller and shallower SWC estimates (~18 cm sampling depth). The timing of SWC estimation was also important; higher accuracy predictions were achieved in wetter soils than in drier soils, and a light precipitation event also improved prediction accuracy. [ABSTRACT FROM AUTHOR]

The intensification of nitrogen deposition and the change of global rainfall pattern are important features of global change. The input of exogenous nitrogen and the change of soil water conditions will inevitably affect soil microbial diversity and community composition. Illumina Miseq high-throughput sequencing technology was used to study the effects of nitrogen addition, water change and their interaction on bacterial and fungal diversity and community composition of red soil in a modeling subtropical plantation, as well as their relationships with soil properties. The results showed that: soil bacterial diversity decreased with the decrease of water content, and the inhibition effect was enhanced by the addition of nitrogen. The Shannon index of soil fungi under medium water treatment was significantly higher than that under low water treatment. Nitrogen addition significantly decreased the relative abundance of Acidobacteria, while increased the relative abundance of Actinobacteria and Bacteroidetes. In the soil, the relative abundance of Acidobacteria and Bacteroidetes increased with the increase of soil water content, while Actinobacteria and Firmicutes were on the contrary. Drought intensified the inhibition effect of nitrogen addition on the relative abundance of Acidobacteria. Nitrogen addition and soil water interaction significantly affected the relative abundance of Cyanobacteria. But nitrogen addition, soil moisture and their interactions had no significant effects on soil fungal community composition. The results of redundancy analysis showed that the changes of soil bacterial community composition were significantly related to soil water content, pH, NO3 – -N content and TN, which accounted for 65.6%, 26.1%, 21.5% and 20.7% of the changes of soil bacterial community composition, respectively. These results suggest that nitrogen addition may alter the intensity and direction of the effects of drought on soil bacterial diversity and community composition. [ABSTRACT FROM AUTHOR]

Soil sampling and in situ measurements were conducted at 24 locations at three time points from May 2015 to April 2016. The statistical analysis showed that the variabilities of soil water content and soil penetration were moderate, while particle size and soil saturated hydraulic conductivity varied considerably. Rainfall before measurements contributed positively to the mean soil water content and negatively to particle size. This was mainly due to the soil aggregates and large soil particles being broken into smaller particles from rain splash. The detached small-sized soil particles could coalesce into larger-sized ones and even soil aggregates. Stressors in zones differ, resulting in variations between soil physical quality indices. The point-topoint comparisons indicated that the mean measured soil water content and soil saturated hydraulic conductivity were similar, if the measurements for these two indices were conducted under similar weather conditions during the same period between years. The investigation on the relationships among soil physical quality indices showed a negative relationship between the measured soil water content and soil saturated hydraulic conductivity. A positive correlation was also found between soil particle size and soil saturated hydraulic conductivity. Lower soil strength resulted in higher soil saturated hydraulic conductivity [ABSTRACT FROM AUTHOR]

Converting degraded croplands into perennials has been proposed as an effective method of soil N sequestration, however, the dynamics of deep soil N (>100 cm) following cropland conversion are not well understood. In this study, we synthesized 3049 observations to detect the changes in deep soil N content following cropland conversion on the arid and semiarid Loess Plateau. Our results showed that converting croplands into perennials significantly increased the soil N content by an average of 57.4%, 23.1%, and 29.5% in the surface (0–20 cm), subsurface (20–100 cm), and deep (100–200 cm) layers, respectively. The extent of the increase was influenced significantly by the land‐use conversion types and tree species. Specifically, the conversion of croplands into deep‐rooted forests or shrubs, particularly Robinia pseudoacacia and Caragana microphylla, exhibited higher advantages in deep soil N sequestration. Moreover, deep soil N sequestration increased significantly with time since cropland conversion (p < 0.001), and the rates in deep soils were approximately 26.1% and 66.7% of that in 0–20 and 20–100 cm soils, respectively. In the long term, converting croplands into forests and shrubs showed higher potential for deep soil N sequestration. Linear regression analysis showed that the changes of deep soil N sequestration were influenced significantly by initial soil N content (p < 0.001) and humidity index (p < 0.001), with the slopes in >100 cm layers being 2 to 3 times than that in the top meter, indicating higher sensitivity in deep soils. Overall, this study provides evidence that converting degraded croplands into perennials may contribute to deep soil N accumulation in N‐limited regions, which could potentially alleviate N limitation and sustain long‐term ecosystem carbon sequestration. [ABSTRACT FROM AUTHOR]

Despite their small size, cryptogams (lichen, liverwort, and moss) are important for ecosystem stability. Due to their strong stress resistance, cryptogams often cover extreme environments uninhabitable for vascular plants, which has an important impact on the material cycle and energy flow of various terrestrial ecosystems. In this article, we review and discuss the effects of cryptogams on soil properties (moisture and fertility) and vascular plant regeneration over the past two decades. Cryptogams strongly affect soil water content by influencing precipitation infiltration, non-rainfall water input, soil evaporation, soil water holding capacity, and soil permeability, ultimately helping to reduce soil water content in areas with low annual precipitation (<500 mm). However, in areas with high annual precipitation (>600 mm) or where the soil has other water sources, the presence of cryptograms is conducive to soil water accumulation. Cryptogam plants can increase soil fertility and the availability of soil nutrients (TOC, TN, TP, TK, and micronutrients) in harsh environments, but their effects in mild environments have not been sufficiently investigated. Cryptogam plants exert complex effects on vascular plant regeneration in different environments. The primary influence pathways include the physical barrier of seed distribution, shading, allelopathy, competition, influences on ectomycorrhizal development and individual reproduction, and the regulation of soil water content, temperature, and nutrients. [ABSTRACT FROM AUTHOR]

In an upland forested micro-catchment during the growing season, we tested soil responses to precipitation events as well as soil water content (SWC). We asked ourselves if what is the difference of SWC response to precipitation events depending on the presence and proximity of a tree? The environmental heterogeneity of the small 7.5-ha headwater area was captured by soil probes at specific locations: (i) probe measurements of SWC at 10-, 30-, 60-, and 100-cm depths; (ii) resolution of near-tree (NT) and between-tree (BT) positions; and (iii) resolution of four slope classes. The results revealed significant differences between the hydrological responses of the soil. NT soils had faster infiltration but were also faster to dry out when compared to BT soils, which were less affected by the presence of trees. Water input threshold values, measured as the precipitation amount needed to cause a significant increase in SWC, were also significantly different, with NT positions always lower than BT positions. Total infiltration of the topmost NT and BT soil layers reached 185 and 156 mm during the study period, corresponding to 43% and 36% of the total 434 mm of precipitation, respectively. Infiltration into the deepest horizon was significantly higher in NT soils, where it reached 114 mm (26%) as opposed to 9 mm (2%) in BT soils, and was indicative of significant vertical hydraulic bypass flow in the proximity of trees. These observations contribute to better understanding the hydrological processes, their nonlinearity, and the expansion of conceptual hydrological models. [ABSTRACT FROM AUTHOR]

For wheat (Triticum aestivum), sustained crop yield at limited soil water availability has been linked to osmotic adjustment (OA) – a physiological mechanism that aids maintenance of leaf hydration status, turgor (P) and growth. 'Canada Western Red Spring' (CWRS) wheat cultivars are typically grown in rainfed areas with milder climates, but ongoing climate change is increasesing the frequency and intensity of drought events. The overarching goal of this study was to elucidate if commercially used CWRS cultivars ('Superb', 'Stettler', 'AAC Viewfield') have the ability for leaf OA. Measurements of leaf water relation parameters (water potential, Ψ ; solute potential, Ψ s; stomatal conductance, g s; relative water content, RWC) showed that all three cultivars reached zero P (= Ψ – Ψ s) at a leaf Ψ of −1.1 MPa. Prior to that, P maintenance in 'Superb' and 'AAC Viewfield' was associated with a significant reduction in leaf Ψ s and OA contributed 0.53 MPa ('Superb') and 0.73 MPa ('AAC Viewfield'). Our data analyses provided no support for the existence of OA in 'Stettler'. Under water deficit, leaf g s was significantly higher in 'AAC Viewfield' compared to 'Stettler'; it was intermediate in 'Superb'. Together, drought tolerance in CWRS wheat cultivars is most likely linked to the degree of OA. 'Canada Western Red Spring' wheat cultivars are typically grown in rainfed areas with milder climates, but drought is increasing with climate change. Wheat can maintain yield under dry conditions through the physiological mechanism of osmotic adjustment. We show that two of three studied cultivars of 'Canada Western Red Spring' are capable of osmotic adjustment, permitting a degree of drought tolerance. [ABSTRACT FROM AUTHOR]

Background and aims: The abandonment of alfalfa fields is increasing in a semi-arid region. To determine the change of soil physicochemical properties and plant diversity in abandoned alfalfa fields for a long-term is essential for vegetation restoration. This study surveyed alfalfa fields of different planting ages in 2003 (1–30 years), 2014 (12–41 years), and 2022 (20–49 years) to explore the change in various indicators using a space-for-time method. Results: The results suggested that abandoned alfalfa fields converted into natural grasslands after 15 years, where the abundances of Gramineae and Asteraceae (59.1–84.0%) increased, whereas those of legumes decreased (16.5–9.4%). As the plant composition changed, the soil water content (SWC) decreased by 19.0% 1–15 years after abandonment, but increased by 54.5% 15–49 years after abandonment. The plant diversity (Margalef, Pielou, Simpson, and Shannon–Wiener indices), and soil organic carbon (SOC), and total nitrogen (TN) contents increased by 0.5% to 51.5% with the number of years alfalfa planting. Furthermore, the plant composition significantly affected the SWC through the soil physicochemical characteristics and plant diversity. Conclusions: This study demonstrated that the longest time of alfalfa planting was 15 years. Furthermore, the plant composition changed from alfalfa to local grasses due to the natural succession of abandoned alfalfa fields, with increases in SWC, SOC, TN, and plant diversity in the semi-arid region. [ABSTRACT FROM AUTHOR]

Soil erosion is a key factor in soil quality degradation and carbon balance in arid ecosystems. However, many models ignore the soil erosion process in arid regions, which may lead to limits in our understanding of ecosystem processes in arid regions. In this study, we added the soil erosion process according to field observed data of soil hydrothermal regimes and carbon flux. We validated this coupling version of IBIS (Integrated Biosphere Simulator) and RUSLE (RU–IBIS) by examining four different vegetation types and the carbon budget in the arid region on the Loess Plateau (LP). Our results indicated that the coupling model (RU–IBIS) produced more reliable simulations of the soil water content (with the r from 0.23–0.90 to 0.71–0.97) and evaporation (ET) (the average r was 0.76) and significantly improved the simulation of the leaf area index (LAI) (the average r was 0.95) and net primary production (NPP) (the average r was 0.95). We also conducted sensitivity experiments to determine how soil texture and aerodynamic roughness (Z0m) affect the soil water content. Moreover, it was revealed that specific leaf area (SLA) plays a key role in the simulation of NPP and NEE. Our study suggests that the coupled soil erosion process and parameterization can effectively improve the performance of IBIS in arid regions. These results need to be considered in future Earth system models. [ABSTRACT FROM AUTHOR]

Finding and optimizing sustainable approaches could increase yield by modifying the structural and physiological traits by reducing lodging and competition for soil water. A higher yield could be achieved by optimizing planting density under appropriate mulching. In this experiment, we studied the effect of mulching (no mulch, straw mulch, and plastic mulch) on soil water consumption, canopy structure, lodging, and yield traits of maize under different planting density rates (52,500–90,000 plants ha− 1). Results indicated that the lodging was minimum at lower planting densities while the higher density rates induced lodging by reducing the diameter and increasing the internode length. The weight of 100-grains, the number of grains per ear, ear length, and photosynthesis rate were decreased by increasing planting density but grain yield ha− 1 was increased with planting density up to 67,500 plants ha− 1 under no mulch and 75,000 plants ha− 1 under straw and plastic mulch. This showed that the higher planting density could be used by adopting plastic mulch increasing yield and saving soil moisture. The planting density at which the highest grain yield was attained under no mulch was 67,500 plants ha− 1 which was increased to 7500 plant ha− 1 under straw and plastic mulch. The yield showed 8–10% increase at plastic mulching at 75,000 plants ha− 1 as compared to no mulch at 52,500 plants ha− 1. Thus, higher density could be adopted under plastic mulching, and plastic and straw mulching decreased the lodging rate. [ABSTRACT FROM AUTHOR]

Soil hydrological properties play a key role in the balance of water and heat, as well as the stability of ecosystems. Understanding the differences in soil hydrological properties between rubber-woody plant and rubber-herb agroforestry systems (RW and RH) is important to construct suitable rubber-based agroforestry systems. Soil physical and hydrological properties from 105 soil cores were measured in three types of rubber plantations in Xishuangbanna, Southwest China. Results showed that at depth of 0–10 cm, the soil bulk density was highest in rubber monoculture (RM), which also had the lowest soil porosity. Soil initial gravimetric water content in different types of plantations followed the order RH > RW > RM at depth of 0–10 cm. Coefficient of variation among soil saturated water capacity, capillary holding capacity, field water capacity and initial gravimetric water content in different plantations followed the order RM > RW > RH. Correlation coefficients among soil saturated water capacity, capillary holding capacity and field water capacity were 0.882–0.990, whereas those between initial gravimetric water content and them were 0.290–0.547. These results indicate that the soil water retention capacity in different types of plantations followed the order RH > RW > RM. Intercropping can improve soil structure and hydrological properties of topsoil, particularly intercropping herbs with rubber was better than woody plants for improving the soil hydrological functions in rubber plantation. [ABSTRACT FROM AUTHOR]

In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future. [ABSTRACT FROM AUTHOR]

Relative soil water content (RSWC) is widely used to characterize the impact of water stress (WS) on vegetation. In bi-layer ecosystems, such as olive groves, this impact must be primarily estimated for the tree component, which, having greater rooting depth, responds more slowly to WS than understory grass. This complicates the application of methods for RSWC prediction, which must be properly adapted to consider the deeper soil layer influential on olive trees. The current study investigates the modification of a recently proposed RSWC simulation method based on a combination of meteorological and satellite-derived normalized difference vegetation index (NDVI) data. The application of the method to an olive grove in Central Italy requires the estimation of both weather and NDVI contributions affecting solely olive trees, which is carried out through the use of appropriate data processing techniques. The RSWC estimates obtained reasonably reproduce the ground RSWC observations referred to the 1 m soil layer, which are representative of the WS affecting olive trees (r2 = 0.795, RMSE = 0.15 and MBE = −0.09). The limits and prospects of this method are finally discussed with particular reference to the possible integration of the RSWC estimates within more complex ecosystem models. [ABSTRACT FROM AUTHOR]

Elevating soil water content (SWC) through irrigation was one of the simple mitigation measures to improve crop resilience to heat stress. The response of leaf function, such as photosynthetic capacity based on chlorophyll fluorescence during the mitigation, has received limited attention, especially in field conditions. A two-year field experiment with three treatments (control treatment (CK), high-temperature treatment (H), and high-temperature together with elevating SWC treatment (HW)) was carried out during grain filling with two maize hybrids at a typical station in North China Plain. Averagely, the net photosynthetic rate (Pn) was improved by 20%, and the canopy temperature decreased by 1–3°C in HW compared with in H in both years. Furthermore, the higher SWC in HW significantly improved the actual photosynthetic rate (Phi2), linear electron flow (LEF), variable fluorescence (Fv), and the maximal potential quantum efficiency (Fv/Fm) for both hybrids. Meanwhile, different responses in chlorophyll fluorescence between hybrids were also observed. The higher SWC in HW significantly improved thylakoid proton conductivity (gH+) and the maximal fluorescence (Fm) for the hybrid ZD958. For the hybrid XY335, the proton conductivity of chloroplast ATP synthase (vH+) and the minimal fluorescence (Fo) was increased by the SWC. The structural equation model (SEM) further showed that SWC had significantly positive relationships with Pn, LEF, and Fv/Fm. The elevating SWC alleviated heat stress with the delayed leaf senescence to prolong the effective period of photosynthesis and enhanced leaf photosynthetic capacity by improving Phi2, LEF, Fv, and Fv/Fm. This research demonstrates that elevating SWC through enhancing leaf photosynthesis during grain filling would be an important mitigation strategy for adapting to the warming climate in maize production.

Unlike traditional ridging, mulching broad ridges with a woven polypropylene fabric (WPF) can reduce soil evaporation during the drought season and avoid long saturation time in the root zone of pear trees during the rainy season. In this study, field experiments were conducted from 2017 to 2020 in a pear orchard in the North China Plain to investigate the effects of mulching broad ridges (0.3 m in height and 2 m in width) with WPF on soil temperature and moisture, nitrogen leaching, vegetative and reproductive growth of young pear trees (Pyrus bretschneideri Rehd. ‘Yuluxiang’). The experiments involved two treatments, namely, control (traditional no-ridge planting without mulching) and mulching broad ridges with WPF (RM treatment). The results showed that the RM treatment increased soil moisture and temperature and decreased nitrogen leaching, resulting in vigorous growth of the young pear trees. Moreover, the RM treatment increased the tree trunk cross-sectional area and height of the young pear trees by 37% and 8% in 2020, respectively. The nitrate nitrogen content at the soil layer depth of 0–30 cm was significantly higher in the RM than that in control. Furthermore, the RM treatment significantly increased the fruit yield due to larger tree size. In addition, compared with control, significantly higher fruit soluble solid content of RM treatment was detected in 2020. High precipitation (423 mm) occurred during fruit enlargement stage in 2020, RM treatment decreased the rainfall infiltration in the ridge and the soil moisture in root region, resulting in the improvement of fruit quality, compared with control. Therefore, mulching broad ridges with WPF can be implemented to increase soil moisture during drought season, soil temperature, and nitrate nitrogen content, thereby improving the growth and fruit yield of young pear trees. Additionally, it can reduce soil moisture in the root zone during the rainy season and improve the fruit quality of the trees. Finally, it can reduce nitrate nitrogen leaching, thereby reducing environmental pollution.

【Objective】 Greenhouse vegetable production relies on irrigation and fertilization. Improving their use efficiency can reduce the operational costs and environmental impact. The objective of this paper is to find their optimal combination for greenhouse tomato production. 【Method】 The experiment consisted of three irrigation treatments: conventional drip irrigation at 4 800 m3/hm2 (W1), reducing W1 by 25% (W2), and 50% (W2); and three fertilizations: high fertilization at 7 200 kg/hm2 (F1), and reducing F1 by 30% (F2), and 60% (F3). In each treatment, we measured soil water distribution, and yield and water use efficiency of the tomato. 【Result】 Fertilization and irrigation were strongly interacted in their impact on tomato yield, soil water and nutrients. Compared to W1+F1, W2+F2 and W3+F2 reduced the fruit yield by 16.26% and 6.54%, and increased water use efficiency by 11.62% and 66.56%, respectively. Soil water content in the 0~20 cm soil layer exhibited oscillation in the range of 13.33%~24.53%, but overall showed a declined trend as the crop grew. With the decrease in irrigation and fertilization, the gradient of soil water content at the depth of 60 cm became steeper. The average soil water content under W2+F2 and W3+F2 was 16.53% and 16.84%, respectively. Soil organic matter and bioavailable nutrients were more abundant in the later growth stage than in the middle growth stage. Soil organic matter and bioavailable phosphorus, potassium in root zone were comparable in all treatments, both decreasing with the decrease in fertilization when the irrigation amount was the same. When the fertilization was the same, a moderate reduction in irrigation amount could reduce the downward movement of alkali-hydrolyzed nitrogen, bioavailable phosphorus and potassium, thereby increasing nutrients in the root zone. 【Conclusion】 Among all the treatments we compared, the optimal irrigation and fertilization to give the best yield and water use efficiency was drip-irrigation with 2 400~3 600 m3/hm2 of water, and fertilization with 3 600 kg/hm2 of liquid organic fertilizer and 1 440 kg/hm2 of water-soluble fertilizer.

Evapotranspiration (ET) is one of the most critical components in hydrological processes and is of great importance to water resource management. Data-oriented deep learning (DL) has been increasingly utilized to forecast hydrological variables over recent years. In this study, the ability of the widely-used DL methods, including long short-term memory (LSTM), bi-directional LSTM (BiLSTM), deep neural network (DNN), and deep belief network (DBN), on the estimation of actual daily ET over the heterogeneous surfaces, was investigated using four groups of experiments. Firstly, the influence of the different input variables on the above DL-based ET model over the various land cover types was explored and analyzed. The results showed that the DL-based ET model can accurately estimate the actual daily ET over the heterogeneous surfaces using a few key conventional observations, i.e., net radiation (Rn), relative humidity (RH), air temperature (Ta), and wind speed (u), as well as soil water content (SWC). However, the performance of the DL-based ET model varied from the different combinations of input variables. SWC was crucial to the estimation of ET, with RMSD decreased from 0.94 to 0.76 mm d−1 when SWC was added to the DL model. Then, the comparison of the four DL-based ET model performances was done. The minor difference in ET estimates was caused by the algorithm differences between LSTM, BiLSTM, DNN, and DBN. Based on the above work, a unified DL-based ET model over the heterogeneous surfaces was developed. The unified DL-based model improved the applicability of DL in ET estimation although it underperformed the separate DL-based model. Finally, the comparison of the performance of the TSEB model and DL method was done. Evaluated with the results of heterogeneous surface, the DL-based model had a better accuracy with a MAPE of 16 – 50%; while the TSEB model had a larger MAPE of 20 – 55%. The results of this research suggest that the DL-based ET model is a promising alternative for the simulation of the daily ET over the heterogeneous surfaces.

Investigating the soil water dynamics in relation to rainfall events is of great importance for enhancing our understanding of eco-hydrological processes and improving soil hydrological models. However, the lack of long-term, in-situ observational data and the neglect of soil moisture decoupling have hindered the study of dynamic responses in soil water regimes to rainfall events in China’s boreal forests with permafrost. This study utilized soil water content monitoring and rainfall observational data from the Xing’an larch (Larix gmenilii) forest in Northeast China during the growing seasons of 2015–2021 to evaluate the dynamic response of soil water regimes to rainfall events. The results show a significant increase in the decoupling strength between soil water and rainfall with increasing soil depth. The thresholds of rainfall amount (RA), duration (RD), and intensity (RI) for triggering soil wetting events also increased. Soil water dynamic processes exhibited inconsistent and complex patterns in response to the hierarchical effects of RA, RD, and RI along the vertical soil profile. However, the dominant controls on soil water dynamic responses to RA, RD, and RI varied depending on specific response metrics, such as the accumulated soil water content increments (ASMI), duration time (DT), and the mean slope of the soil wetting curve (Sm). Interestingly, the dominant factor for affecting response time (RT) changed from RI to RD as soil depths increased. Importantly, the decoupling of soil moisture led to a substantial reduction in the responsiveness of these metrics of subsurface soil water to rainfall, and the role of the decoupling effect diminished with increasing soil depths. These findings highlight the complexity of the dynamic response of soil water to rainfall events and provide new insights into the relationship between soil water dynamics and rainfall features through the introduction of the decoupling of soil moisture in boreal forests.

Acoustic waves offer a non-destructive, safe, and cost-effective means of monitoring the environment, with a potential application in soil water content monitoring. However, extracting soil water information from acoustic signals is still challenging. To tackle this issue, we have developed a low-frequency swept acoustic signal detection device and system. We conducted soil penetration testing using low-frequency swept acoustic signals. The swept-frequency acoustic signals passing through the soil were transformed into time–frequency spectrogram. Using the Swin-Transformer model, we established a regression model between the time–frequency spectrogram of the swept frequencies and the soil water content. Predictions were made both on a laboratory test dataset and through field trials using the calibrated model. The results indicate that the RMSE, MAE, and R2 values between the observed and the model's outputs of water content (%) for the test laboratory dataset are 0.191, 0.081, and 0.999, respectively, using the Swin-Transformer model. In the case of the field trials, the RMSE, MAE, and R2 values between the predicted and observed values are 6.715 %, 1.829 %, and 0.711, respectively. These studies demonstrate that this method is highly effective in predicting soil water content, with the best results achieved at a resolution of 20 PPI (Pixels Per Inch) and within the frequency range of 260–360 Hz. It provides an efficient approach for acoustic soil water content detection, effectively resolves the difficulty in building models caused by the single-parameter limitation in traditional acoustic model.

Coffee (Coffea spp.) is one of the leading commodities, which contributed 42.98 percent to the export value of the annual crop agricultural sector in 2013-2020. The productivity of Robusta coffee plants in the Jember region has tended to decrease significantly over the last 5 years. Geographic Information Systems (GIS) can be used to determine the distribution of organic C and soil water content as a basis for proper land management. The results showed that the percentage of ideal distribution area for organic C content was 94.94%, and the soil water content was at a value of 6.92-18.68%, where the status of moderate soil water content dominated by 59% of the total land. The results of simple linear regression analysis showed that the organic C variable (X1) had an effect of 29% and soil water content (X2) 10% productivity values. In addition, multiple linear regression analysis showed a strong influence of 63% on the value of productivity. The age factor also has an effect of 57% on the value of productivity.

ABSTRACTRelative soil water content (RSWC) is widely used to characterize the impact of water stress (WS) on vegetation. In bi-layer ecosystems, such as olive groves, this impact must be primarily estimated for the tree component, which, having greater rooting depth, responds more slowly to WS than understory grass. This complicates the application of methods for RSWC prediction, which must be properly adapted to consider the deeper soil layer influential on olive trees. The current study investigates the modification of a recently proposed RSWC simulation method based on a combination of meteorological and satellite-derived normalized difference vegetation index (NDVI) data. The application of the method to an olive grove in Central Italy requires the estimation of both weather and NDVI contributions affecting solely olive trees, which is carried out through the use of appropriate data processing techniques. The RSWC estimates obtained reasonably reproduce the ground RSWC observations referred to the 1 m soil layer, which are representative of the WS affecting olive trees (r2 = 0.795, RMSE = 0.15 and MBE = −0.09). The limits and prospects of this method are finally discussed with particular reference to the possible integration of the RSWC estimates within more complex ecosystem models.

Water availability is the most critical constraint for the healthy and sustainable development of agroforestry systems in arid and semi-arid regions; consequently, it is essential to clarify soil water dynamics and quantify water exchange within agroforestry systems. In this study, a two-year field experiment and a HYDRUS-2D numerical simulation model were used to clarify the characteristics of the two-dimensional distribution of soil water and the horizontal water exchange in an agroforestry system under the background of film-mulching drip irrigation of farmland. The results showed that the HYDRUS-2D for agroforestry systems had high accuracy in calculating the water flow and capturing the dynamic water exchange in various soil layers. The model simulation results showed that there were differences in soil water content between forest belt and farmland, and the two-dimensional distribution of soil water content showed vertical water transport and horizontal water exchange in the agroforestry system. During the growing season, the horizontal water flow exchange was mainly from the forest belt side and the farmland side to the agroforestry transition zone, with inflows of 61.3 mm and 199 mm at depths of 0–100 cm, respectively. A long-term severe ''water stress zone'' developed at a depth of about 0–40 cm in the forest belt, so the 0–40 cm soil depth was the main area of water competition in the agroforestry system. The results could provide a reference for the long-term healthy development of agroforestry systems and the management of agricultural water resources in oasis-desert systems under film-mulching drip irrigation conditions.

In this study, the effects of foliar applied methyl jasmonate (MeJA) on drought-stressed Impatiens walleriana growth and leaf physiology parameters: stomatal conductance, chlorophyll, flavonoid, anthocyanin, and nitrogen balance index (NBI), were evaluated. These parameters could serve as indicators of drought tolerance of I. walleriana, a popular horticultural plant worldwide that is very sensitive to drought. The experiment included four treatments: control, drought-stressed plants sprayed with distilled water, drought-stressed plants sprayed with 5 µM MeJA, and drought-stressed plants sprayed with 50 µM MeJA. Foliar spraying with MeJA was performed twice: seven days before and on the day of drought induction. The stressed plant groups were non-irrigated to achieve soil water contents (SWC) of 15 and 5%, while control plants were well-watered throughout the experiment (35–37% SWC). The results of this study showed that drought significantly reduced I. walleriana fresh and dry shoot weight, as well as total leaf area, but did not impact on dry matter content. The foliar application of MeJA improved growth parameters of I. walleriana, depending on the elicitor concentration and drought intensity. Stomatal conductance was slightly reduced at 5% SWC, and foliar applied MeJA at both concentrations. The flavonoid index was slightly reduced at 15 and 5% SWC when 50 µM MeJA was foliar applied, while there were no observed changes in the anthocyanin index in any treatments. The foliar application of 50 µM MeJA increased the chlorophyll index and NBI of I. walleriana at 5% SWC, indicating a contribution of the elicitor to plant drought tolerance at the physiological level.

Dryland winter wheat is the most widely grown crop in Oklahoma, where water availability and temperature variations are the major factors affecting the yield of this crop. These effects were assessed using the AquaCrop model. Model calibration and validation were performed using field measurements collected from 11 site-years. The validated model satisfactorily simulated soil water content, maturity biomass, and yield, with overall normalized root mean square errors of 11%, 5%, and 9%, respectively. The model was then used in long-term (1994-2019) simulations of winter wheat at three locations in Oklahoma's wheat belt under five sowing dates (15 Sept., 25 Sept., 5 Oct., 15 Oct., and 25 Oct.) and three soil water contents (SWC) of 40%, 70%, and 100% of the total available water at sowing. The highest simulated average dryland yields (6.4 to 6.6 Mg ha-1) were obtained for early to mid-October sowing dates under the largest SWC at sowing. The lowest average yields (2.67 to 4.15 Mg ha-1) belonged to earlier sowing (mid-September) under the smallest SWC at sowing. Irrigation had a positive impact on the yield of winter wheat and this impact increased for later sowing. The yield of winter wheat sowed in mid-September increased by 0.28 Mg ha-1 under irrigation when averaged for all years and sites, while late-October average yield was 0.96 Mg ha-1 higher than dryland average yield. Irrigation water productivities also increased with later sowing dates. [ABSTRACT FROM AUTHOR]

Arid and semi-arid ecosystems dominate the RS variability due to the multiple changing factors that control it. Consequently, any variation, in addition to climate change and land use change, impacts the concentration of CO2 in the atmosphere. Here, the effect of the interannual variation and the controlling factors of RS in native xeric shrublands and agricultural systems is investigated. This study was conducted in four sites per condition for two years (2019 to 2020), where RS and the soil properties were measured. The RS presented a higher variation in the xeric shrubland. The agricultural plots showed the highest RS (0.33 g CO2 m−2 hr−1) compared to the xeric shrubland (0.12 g CO2 m−2 hr−1). The soil water content was the main controlling variable for RS in both land uses. However, soil temperature affected RS only in agricultural plots. The variation in the RS under different land uses confirms that changes in the soil and environmental conditions (i.e., season) control the RS. In addition, if current management practices are maintained in agricultural sites and under a temperature increase scenario, a significant increase in the RS rate is expected. [ABSTRACT FROM AUTHOR]

Establishing slash pine plantations is the primary method for restoring sandification land in the Houtian area of South China. However, the microbial variation pattern with increasing stand age remains unclear. In this study, we investigated microbial community structure and function in bare sandy land and four stand age gradients, exploring ecological processes that determine their assembly. We did not observe a significant increase in the absolute abundance of bacteria or fungi with stand age. Bacterial communities were dominated by Chloroflexi, Actinobacteria, Proteobacteria, and Acidobacteria; the relative abundance of Chloroflexi significantly declined while Proteobacteria and Acidobacteria significantly increased with stand age. Fungal communities showed succession at the genus level, with Pisolithus most abundant in soils of younger stands (1- and 6-year-old). Turnover of fungal communities was primarily driven by stochastic processes; both deterministic and stochastic processes influenced the assembly of bacterial communities, with the relative importance of stochastic processes gradually increasing with stand age. Bacterial and fungal communities showed the strongest correlation with the diameter at breast height, followed by soil available phosphorus and water content. Notably, there was a significant increase in the relative abundance of functional groups involved in nitrogen fixation and uptake as stand age increased. Overall, this study highlights the important effects of slash pine stand age on microbial communities in sandy lands and suggests attention to the nitrogen and phosphorus requirements of slash pine plantations in the later stages of sandy management. [ABSTRACT FROM AUTHOR]

Floods and droughts on farmland seriously damage agricultural production. Porous fiber materials (PFM) made from mineral rocks have high porosity, permeability, and water retention and are utilized widely in green roofs and agricultural production. Therefore, studying the impact of PFM on the improvement of farmland is of great importance for soil and water conservation. We set 64 extreme rainfalls to analyze the impact of PFM on soil water content (SWC), runoff, nutrient loss, microorganism, and plant growth. The results showed that PFM can effectively reduce runoff and improve soil water distribution, and enhance the soil water holding capacity. Furthermore, PFM reduced the loss of nitrogen and phosphorus by 18.3% to 97% in the runoff, and the soil erosion of summer corn was more strongly influenced by lower vegetation cover, compared with winter wheat. Finally, when PFM was buried in the soil, the wheat yield increased by -6.7%-20.4%, but the corn yield in some PFM groups decreased by 5.1% to 42.5% under short-duration irrigation conditions. Our study emphasizes that the effectiveness of PFM depends mainly on the following: First, PFM with high porosity can increase soil water holding capacity and timely replenish the water lost from the surrounding soil. Second, PFM with high permeability can increase infiltration during rainfall and decrease runoff and nutrient loss, reducing the risk of farmland flooding and pollution. Finally, PFM consists of gold ions and alkali metal oxides, which can stabilize agglomerates and improve soil enzyme activity, thereby increasing the relative abundance of some microbial strains and promoting crop growth. However, when the rainfall amount was low or PFM volume was large, PFM could not store water sufficiently during rainfall, which seriously reduced the maximum saturated moisture content and water absorption performance. Meanwhile, the PFM could not release water in time and replenish the soil water deficit, which increased drought risk. In conclusion, the appropriate volume of PFM and irrigation system may enhance soil water storage capacity, minimize agricultural pollution, and promote crop production. [ABSTRACT FROM AUTHOR]

Biochar has been shown to improve soil properties and plant productivity in soils with inherently low fertility. However, little has been reported for upland corns under dry and wet precipitation regimes. This study investigates the effect of biochar addition on a range of soil physicochemical, biological, and hydrological properties, and corn growth and productivity under agrometeorological drought and wet conditions. Here, experiments were laid out in a randomized complete block design with three replications at two sites during 2017 and 2018 in South Korea. Treatments included (i) CN: control (ii) IF: inorganic fertilizer (N–P–K) at 145–30–60 kg ha−1; (iii) BS: barley straw at 5 t ha−1; (iv) CWBC: corn waste biochar at 5 t ha−1; (v) CWBC + IF: corn waste biochar + inorganic fertilizer; (vi) CWBC + BS: corn waste biochar + barley straw. The year 2017 was relatively dry, whereas the year 2018 was wet. Despite drought conditions in the year 2017, biochar facilitated soil water conservation. However, higher precipitation in 2018 increased the quantity and distribution of soil water and nutrients in the top 15 cm. Biochar reduced soil bulk density, and increased porosity, cation exchange capacity and total organic carbon in both years but increased total bacterial counts during the dry year only. Bacterial population was generally higher under wet conditions. Similarly, more soil CO2 was emitted in the wet year than in the dry year. Results further indicated that biochar can enhance corn biomass and grain yield regardless of precipitation conditions. The grain index was, however, affected by rainfall and was significantly different across treatments in the year 2018 only. All biomass, grain yield, and grain index were highest in CWBC + IF treatment and lowest under CN treatment. Indeed, biochar addition appeared to improve soil quality and soil conditioning effects in the drought and wet years, ameliorating soil and plant properties. Overall, biochar can improve water and nutrients storage, availability, and uptake, and therefore corn productivity during hydrological extremes. Highlights: Biochar application consistently increased soil water content. Biochar improved soil physicochemical characteristics in the drought and wet year. Biochar increased bacterial population during the drought year. Grain yield was higher in the wet year than in the drought year. Grain yield and grain index was highest under CWBC + IF and lowest under CN treatment. [ABSTRACT FROM AUTHOR]

Cover crops (CCs) can affect the cropping systems’ N dynamics and soil water content (SWC), but optimizing their potential effects requires knowledge of their growth pattern, N accumulation, and mineralization. For this purpose, a 3-year field experiment was initiated in northeast Italy involving a maize-soybean rotation. The objectives of this study were to (i) evaluate the use of time series vegetation indices (VIs) obtained from the Sentinel-2 satellite for monitoring the growth of CCs and estimating their biomass and N uptake at termination; (ii) investigate the effects of different CCs on cash crop yield and SWC; and (iii) use the simulation model CC-NCALC to predict the nitrogen contribution of CCs to subsequent cash crops. Three CC systems were tested: a fixed treatment with triticale; a 3-year succession of rye, crimson clover, and mustard; and a control with no CCs. Satellite imagery revealed that rye and triticale grew faster during the winter season than clover but slower compared to mustard, which suffered a frost winterkilling. Both grasses and mustard produced greater biomass at termination compared to clover, but none of the CC species affected SWC or yield and N uptake of the cash crop. A net N mineralization of all the CC residues was estimated by the model (except for the N immobilization after triticale roots residues). During the subsequent cash crop season, the estimated clover and mustard N released was around 33%, and the triticale around 3% of their total N uptake, with a release peak 2 months after their termination. The use of remote sensing imagery and a prediction model of CC residue decomposition showed potential to be used as instruments for optimizing the CCs utilization and enhancing cropping water and N fertilization management efficiency; however, it must be further analyzed with other CCs species, environmental conditions, and cropping systems. [ABSTRACT FROM AUTHOR]

[Objective] The study aims to clarify the dynamic changes and differences in water balance elements between Robinia pseudoacacia woodland and apple orchard, and to provide theoretical guidance for ecological sustainable development. [Methods] This study used the dual pore model and calibrated parameters in Hydras-1D to simulate the dynamic changes of various elements of water balance in Robinia pseudoacacia woodland and apple orchard from 2012 to 2021. [Results] The R² and RMSE of the two hole model in the optimization and validation periods of Hydras-1D were 0.61 and 0.76, respectively, and 0.026 and 0.048 cm³/cm³, respectively. The water balance errors in the simulation period were 0.18% and 0.04%, respectively; The transpiration of Robinia pseudoacacia forestland and apple orchard were (372±70) mm and (320±34) mm, respectively, and the evaporation was (256±44) mm and (288±36) mm. Variation of soil water storage was (-0.61±96) mm and (-3.26±87) mm, and deep leakage was (34±45) mm and (59±48) mm. [Conclusion] The model can better simulate the dynamic changes of water balance elements in Robinia pseudoacacia woodland and apple orchard. Compared with apple fields, Robinia pseudoacacia forest has a larger transpiration, a smaller evaporation and deeper leakage, and a more significant fluctuation in soil water storage. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) and soil temperature (ST) are important indicators of environmental change in permafrost regions. In this study, we conducted soil sampling at 89 locations in the Three Rivers Headwaters Region (TRHR) to investigate the individual and synergistic effects of environmental factors on SWC and ST. We used multivariable regression and random forest modelling to analyse the data. The results show that SWC and ST were higher in the southeast TRHR than in the northwest and higher in surface layers than deeper soil layers. The most important factors affecting SWC in the 0–20 cm and 20–40 cm soil layers were soil bulk density and precipitation, while bulk density was the most important factor in the 40–60 cm layer, and soil bulk density and steppe vegetation were the most important factors in the 60–80 cm layer. For ST, altitude, temperature and slope gradient were the drivers in the 0–20 cm surface layer, while altitude and temperature were the most critical drivers in the 20–40 cm, 40–60 cm and 60–80 cm layers. Overall, bulk density and altitude were the key environmental factors influencing SWC and ST values, respectively. The outcomes of this study provide valuable insights into the environmental factors that impact the SWC and ST in permafrost regions, which can guide decision‐making processes for sustainable soil management in the context of climate change. [ABSTRACT FROM AUTHOR]

The cosmic-ray neutron technology is a novel method for upscaling soil moisture, holding significant importance in drought monitoring, soil water storage estimation, calibration of remote sensing products, and data assimilation of land surface models. However, most studies conducted soil moisture measurement experiments using static Cosmic-Ray Neutron Sensors (CRNS) and are often limited to a single landscape, lacking in-situ measurement for the cosmic-ray neutron rover across various landscapes. This study carried out soil moisture observation experiments using a cosmic-ray neutron rover in nine grassland plots, nine farmland plots, and nine desert plots of the Heihe River Basin, Northwest China. The neutron counts displayed clear variations among different plots, and an equation could represent the relationship between neutron intensity and multiple variables near the ground. The parameter N0 was the smallest for grassland and greatest for desert, and there was a significant negative correlation between Normalized Difference Vegetation Index and N0 (P <0.05). Furthermore, the performance of CRNS notably improved after considering soil lattice water and soil organic matter. The Root Mean Square Error (RMSE) between the measured and oven-dried soil moisture increased with radius. Soil moisture measured by CRNS strongly supported the 100 m diameter footprint assumption (RMSE <0.044 g/g). The study offers valuable insights into the application and promotion of cosmic-ray neutron technology across various landscapes within a basin. [ABSTRACT FROM AUTHOR]

The article presents a revue of the estimates of soil surface moisture, soil water content, and evapotranspiration as elements of water and heat regimes of land surface areas at various spatial scales, made with the use of remote sensing data for Earth in various spectral ranges. In most cases considered in the study, such estimates were obtained with the use of land surface models. A special section is focused on the results of estimating soil surface moisture and water content using satellite data from microwave range, including radar data. Estimates of soil surface moisture content obtained with the use of neural networks are presented. A brief description is given to international hydrological–atmosphere experiments carried out under world research projects aimed to obtain data on the processes of moisture and heat exchange between the land surface and the surface atmosphere layer. Land surface, satellite, and model databases that have been formed using the results of studies in the field under consideration since the mid-1980s are reviewed. Prospects of further studies based on the development of new multispectral instrumentation, the creation of new databases, and the use of a new generation of satellites—global-coverage microsatellites with high-resolution sensors are presented. [ABSTRACT FROM AUTHOR]