Soil Available Water Capacity Research Articles

Effect of Humic Amendment on Selected Hydrophysical Properties of Sandy and Clayey Soils

In recent years, products containing humic acids have been increasingly used in agriculture to improve soil parameters. Quantifying their impact on soil quality is, therefore, of key importance. This study seeks to evaluate the impact of the commercial humic acid product (HA) on the hydrophysical parameters of sandy and clayey soils sampled from different sites in Slovakia. Specifically, the study hypothesizes that humic amendment will enhance particle density (ρs), dry bulk density (ρd), porosity (Φ), saturated hydraulic conductivity (Ks), soil water repellency (SWR), and water retention capacity in sandy and clayey soils. The results of the laboratory measurements were analyzed using NCSS statistical software at a statistical significance of p < 0.05. In sandy soil, there was a statistically significant decrease in ρd and Ks and an increase in Φ and a contact angle (CA) after the application of 1 g/100 cm3 HA. At a dose of 6 g/100 cm3 HA, the values of ρs, ρd, and Ks decreased, and the Φ and CA values increased. In clayey soil, the Ks value significantly decreased by −35.5% only after the application of 6 g/100 cm3 HA. The addition of HA increased the full water capacity (FWC) and available water capacity (AWC) of clayey and sandy soils. The positive influence of HA on the studied soil parameters was experimentally confirmed, which can be beneficial, especially for their use in agricultural production.

Winter wheat irrigation parameters in the Brazilian Cerrado

Wheat is the second most produced cereal in the world. The gap between production and consumption in Brazil shows that wheat production must be increased to meet the domestic demand. In this context, the objective of this study was to determine the crop coefficient of wheat and the ideal moment for irrigation, based on the soil water depletion rate (f). The study was carried out in the tropics, on an Oxisoil (Typic Haplustox), in an experimental field of Embrapa Cerrados in Planaltina, Federal District of Brazil. The experimental design consisted of randomized blocks with three replications. The treatments were differentiated by the soil water depletion index (f) of 0.2, 0.4, 0.6, and 0.8. In other words, irrigation was initiated when 20, 40, 60 and 80% of the available soil water capacity (AWC) at a soil depth of 0.4 m was consumed by the crop. Wheat yield and yield components were evaluated. The phenological development was monitored based on Zadok’s scale, in days after emergence, and the management parameters crop coefficient (Kc) and irrigation timing were determined. The results indicated a soil water depletion index of 0.4 as the best indicator for beginning wheat irrigation. Under this condition, Kc can be estimated daily as a function of days after emergence (DAE) by the quadratic polynomial regression or curve fitting method, adjusted as follows: Kc = −0.000298 × DAE² + 0.036695 × DAE + 0.332486. Alternatively, the means of Kc of each phenological crop phase can be used: Kc = 0.45 (establishment); 0.81 (tillering); 1.21 (booting); 1.43 (flowering); 1.27 (grain formation); and 0.89 (maturation). Thus, there is a limit of consumption of soil available water, at which wheat still achieves the full yield potential, with a rational use of water which varies according to the development phase.

Effects of Land Use on Soil Physical-Hydric Attributes in Two Watersheds in the Southern Amazon, Brazil

Changes in land use can cause degradation of soil physical quality with negative effects on the environment and agricultural production. The effects of different land uses on soil physical-hydric attributes were studied in the Renato River and Caiabi River watersheds in the southern Brazilian Amazon. Three conditions of land use were evaluated: native forest, crops, and pasture in the headwater, middle, and mouth of each watershed. Particle size, particle density, bulk density, total porosity, macroporosity, microporosity, water contents at field capacity and permanent wilting point, and available water capacity in soil were evaluated in three soil layers down to 0.4 m. Data collected were subjected to the Kruskal–Wallis nonparametric test and Pearson’s correlations. Multivariate analyses were also performed using the principal component method. In the Renato watershed, in comparison with native forest, conventional management of pasture and crops caused soil physical degradation, increasing soil density in the surface layer and reducing macroporosity and total porosity. In the Caiabi watershed, converting native forest areas into pasture and crops altered water quality, influencing the water dynamics in the soil, by reducing soil water conductivity. Soil attributes varied by watershed, with texture variations between the headwater and mouth, indicating that changes in soil properties result from both management and the granulometric composition of the soil in different regions of the same watershed. Adoption of crop and pasture conservation practices can improve soil physical attributes in regions bordering agricultural areas in the southern Amazon.

Grapevine yield gap: identification of environmental limitations by soil and climate zoning in the region of Languedoc-Roussillon (South of France)

Often unable to fulfill theoretical production potentials and to obtain the maximum yields set by wine quality labels, many vineyards and cellars need to solve the issue of so-called grapevine yield gaps in order to assure their durability. These yield gaps particularly occur in Mediterranean wine regions, where extreme events have intensified because of climate change. Yield gaps at the regional level have been widely studied in arable crops using big datasets, but much less so in perennial crops, such as grapevine. Understanding the environmental factors involved in yield gaps, such as those linked to climate and soil, is the first step in grapevine yield gap analysis. At a regional scale, there are numerous studies on ‘terroir’ linked to wine typicity and quality; however, none have classified spatial zones based on environmental factors identified as being involved in grapevine yield. In the present study, we aggregated into one big dataset information obtained from producers at the municipality level in the wine region Languedoc-Roussillon (South of France) between 2010 and 2018. We used a backward stepwise model selection process using linear mixed-effect models to discriminate and select the statistically significant indicators capable of estimating grapevine yield at the municipality level. We then determined spatial zones by using the selected indicators to create clusters of municipalities with similar soil and climate characteristics. Finally, we analysed the indicators of each zone related to the grapevine yield gap, as well as the variations among the grapevine varieties in the zones. Our selection process evidenced 6 factors that could explain annual grapevine yield annually (R2 = 0.112) and average yield for the whole period (R2 = 0.546): Soil Available Water Capacity (SAWC), soil pH, Huglin Index, the Climate Dryness Index, the number of Very Hot Days and Days of Frost. The clustering results show seven different zones with two marked yield gap levels, although all the zones had municipalities with no or high yield gaps. On each zone, grapevine yield was found to be driven by a combination of climate and soil factors, rather than by a single environmental factor. The white wine varieties showed larger yield gaps than the red and rosé wine varieties. Environmental factors at this scale largely explained yield variability across the municipalities, but they were not performant in terms of annual yield prediction. Further research is required on the interactions between environmental variables and plant material and farming practices, as well as on vineyard strategies, which also play an important role in grapevine yield gaps at vineyard and regional scale.

Digital mapping of the soil available water capacity: tool for the resilience of agricultural systems to climate change

Soil available water capacity (AWC) is a key function for human survival and well-being. However, its direct measurement is laborious and spatial interpretation is complex. Digital soil mapping (DSM) techniques emerge as an alternative to spatial modeling of soil properties. DSM techniques commonly apply machine learning (ML) models, with a high level of complexity. In this context, we aimed to perform a digital mapping of soil AWC and interpret the results of the Random Forest (RF) algorithm and, in a case study, to show that digital AWC maps can support agricultural planning in response to the local effects of climate change. To do so, we divided this research into two approaches: In the first approach, we showed a DSM using 1857 sample points in a southeastern region of Brazil with laboratory-determined soil attributes, together with a pedotransfer function (PTF), remote sensing and DSM techniques. In the second approach, the constructed AWC digital soil map and weather station data were used to calculate climatological soil water balances for the periods between 1917–1946 and 1991–2020. The result showed the selection of covariates using Shapley values as a criterion contributed to the parsimony of the model, obtaining goodness-of-fit metrics of R2 0.72, RMSE 16.72 mm m−1, CCC 0.83, and Bias of 0.53 over the validation set. The highest contributing covariates for soil AWC prediction were the Landsat multitemporal images with bare soil pixels, mean diurnal, and annual temperature range. Under the current climate conditions, soil available water content (AW) increased during the dry period (April to August). May had the highest increase in AW (∼17 mm m−1) and decrease in September (∼14 mm m−1). The used methodology provides support for AWC modeling at 30 m resolution, as well as insight into the adaptation of crop growth periods to the effects of climate change.

Water Stress-Induced Divergence Growth of Picea schrenkiana in the Western Tianshan and Its Forcing Mechanisms

Since the 1950s, divergence problems have reduced the temporal stability of tree rings in response to climate, shaken the foundations of dendroclimatology, and affected the reliability of reconstructed models based on tree rings and the accuracy of historical climate series. Therefore, it is of great importance to investigate divergence problems, which will help us to better understand the growth strategies of trees in response to climate warming and provide a scientific basis for accurate climate reconstruction and simulation of forest dynamics. This paper aims to elucidate the mechanism of divergent growth of Picea schrenkiana at high altitudes in the western Tianshan from three aspects: variations in atmospheric circulation, changes in climatic factors, and the coping strategy of trees with climate change. High spring temperatures accelerate the melting of snow cover. Large amounts of snowmelt initially replenish soil water, leading to the rapid growth of trees, but later, the continuous consumption of snowmelt reduces the available water capacity of soil, resulting in water stress on trees. The pattern of trees’ response to changes in climate ranges from a pure temperature limitation to a collaborative temperature–moisture limitation. Since the 1990s, the weakening of the westerly circulation and the North Atlantic Oscillation has reduced their impacts on the hydroclimate in the Tianshan Mountains of Central Asia. The combination of heat-induced water deficit and a long-term weakening trend in atmospheric circulation has slowed tree growth over the past decade.

The effect of drip irrigation for potatoes on soil nitrogen dynamics

The effects of potato drip irrigation on soil nitrogen dynamics and potato yield was studied in small-plot field trials. The trials were evaluated at during three experimental times seasons (2016-2018). Four variants of irrigation were determined, ie non-irrigated, 60, 65 and 70 ASWC (Available Soil Water Capacity). At the same time, two pre-planting fertilization dates were set at a maximum of 120 kg N/ha a in divided i.e. 60 kg N/ha before planting and 60 kg N/ha by fertigation during vegetation. Pre-planting crop fertilization or in-season fertigation did not have any significant effect on the potato yields of most variants. In all studied parameters, the positive beneficial effect of irrigation was recorded and compared to the non-irrigated control. The mitigation of drought stress in plants during the growing season is the most important advantage of irrigation. In the trials, on average across all years and varieties, the yield of the irrigated variant increased by 41 % compared to the non-irrigated variant. Maintaining optimal soil moisture has a favourable effect use of applied fertilizers. The highest mineral nitrogen content in the soil was recorded for the variant without irrigation. Considering the increased use of nitrogen fertilizers, the subsurface drip line appeared to be optimal for the creation of suitable conditions for nitrogen availability to plants in the root zone.

Grapevine Yield Big-data for Soil and Climate Zoning. A case study in Languedoc-Roussillon, France

New winegrower and resource datasets appear to be a great opportunity to understand which are the environmental factors involved in grapevine yield spatially. Such analysis can help regional label managers and winegrowers for the conception of local adaptation strategies to climate change, reducing yield gaps. In the present study, we aggregated yield a big dataset obtained from Pays d’Oc winegrowers (n = 96677) between 2010 and 2018 at the municipality level (n = 606), located in the Languedoc-Roussillon region, in the South of France. We used a backward stepwise model selection process using linear mixed-effect models to discriminate and select significant indicators capable of estimating grapevine yield at the municipality level, these include: Soil Available Water Capacity (SAWC), soil pH, Huglin Index, the Climate Dryness Index, the number of Very Hot Days and Days of Frost. We then determined spatial zones by creating clusters of municipalities with similar soil and climate characteristics. The seven zones presented two marked yield levels. Yet, all zones had municipalities with both high yield and high yield gaps. On each zone, grapevine yield was found to be driven by a combination of climate and soil factors, rather than just by a single environmental factor. Environmental factors at this scale largely explained yield variability across the municipalities, but they were not performant in terms of annual yield prediction. Further research is required on the interactions between environmental factors, plant material and farming practices.

Alkali Lignin-Based Hydrogel: Synthesis, Characterization, and Impact on Soil Water Retention From Near Saturation to Dryness

Highlights A lignin-based hydrogel was synthesized and shown to possess a swelling ratio of 2013%. The hydrogel contained important hydrophilic hydroxyl groups and macropores for water retention. The hydrogel improved soil water retention in silt loam soil at high matric potentials and in the dry soil range. Increasing hydrogel concentration increased water retention in a loamy fine sand soil at high and low matric potentials. Abstract. Superabsorbent polymers (hydrogels) have been proposed as soil amendments to increase the amount of plant-available water in the soil. Synthetic hydrogels have been widely investigated for use in agriculture. Due to increasing environmental concerns related to synthetic hydrogels, naturally sourced hydrogels are of interest because of their potential for increased biodegradability and biocompatibility. A lignin-based hydrogel was synthesized for this study, and its swelling properties and water absorption capacity were determined. The hydrogel was characterized using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and gas pycnometry. A hanging water column, pressure plate apparatus, and dew point potentiometer were used to measure the soil water retention curve from saturation to oven-dryness for silt loam and loamy fine sand soils after amendment with the lignin-based hydrogel. Results showed a maximum swelling ratio in deionized water of 2013% of the hydrogel’s original mass, 1092% in tap water, and 825% in a 0.9% NaCl solution. The FTIR spectra of the hydrogel showed the presence of O-H bonds from the lignin structure, which renders the hydrogel reactive to a crosslinker and forms insoluble bonds, thereby allowing the hydrogel to swell when exposed to water. SEM images of the lignin hydrogels indicate large macropores, which allowed for water absorption. Applying hydrogels significantly increased the soil's water-holding capacity at 0.3% (w/w) treatment. Hydrogel treatment significantly increased water retention at saturation or near saturation by 0.12 cm3 cm-3 and at field capacity by 0.08 cm3 cm-3 for silt loam soil at 1% (w/w) treatment compared to the control treatment with no added lignin hydrogel. Hydrogel application increased water retention over the range of the soil water retention curve from -3 to -15,000 cm for the loamy fine sand soil at 1% (w/w) treatment. However, the application of lignin-based hydrogel did not affect plant available water capacity (PAWC) in either soil tested. These results serve as preliminary evidence upon which further lignin-based hydrogel amendment studies could be built by testing higher concentrations of hydrogel in the soil. Keywords: Lignin, Soil water retention curve, Super absorbent polymers, Swelling capacity, Water retention.

Atmospheric dryness impacts on crop yields are buffered in soils with higher available water capacity

Atmospheric dryness has been recognized as a dominant driver for agroecosystem functioning due to its limiting controls on stomatal behavior, even under sufficient soil moisture. Due to its relative importance in influencing carbon and water fluxes, atmospheric dryness has emerged as an important element of global change, jeopardizing food security and agricultural profitability via negative impacts on crop yields. Although negative impacts of atmospheric dryness are well recognized at various scales, it is unknown how heterogeneity in soils’ ability to retain water for plant uptake affects crop yields’ response to increasing atmospheric dryness. To address this, we analyzed how soil available water capacity (AWC) affects the response of crop yields to space and time variation in summer (June-July-August) vapor pressure deficit (VPDJJA) across the conterminous U.S. (CONUS) during 1980–2020 using 77,701 and 51,190 county-year records for maize and soybean, respectively. A distinct co-distribution of VPDJJA and AWC regimes is experienced by maize and soybean acreage and is subject to significant yield variation. Accounting for entire AWC heterogeneity in CONUS, both crops showed a positive yield response to increasing VPDJJA until 0.8 kPa, thereafter showing a gradually increasing negative response to VPDJJA increase. Upon soil-specific investigation of yield response to VPD, the yield sensitivity parameter to VPDJJA became less negative as soil AWC increased, implying buffering of dryness impacts on yields as the ability of soils to retain water increased. For VPDJJA increase between 1.0 kPa and 1.4 kPa, mean VPDJJA impacts on maize yields in soils with 10 %<AWC < 12.5 % were buffered by one-half (50.6 %) as compared with 7.5 %<AWC < 10 % soils. Increasing AWC from 10 to 12.5 % class to 12.5–15 % class further buffered VPDJJA impacts on maize yields by 26.2 %. VPDJJA impacts on soybean yields in soils with 15 %<AWC < 17.5 % were buffered by 40 % as compared with 12.5 %<AWC < 15 % soils. Further increase in AWC (17.5–20 %) resulted in additional 15.5 % buffering of VPDJJA impacts on soybean as compared to impacts recorded for 15 %<AWC < 17.5 % soils. The greatest buffering of negative impacts from VPDJJA were found when AWC is>10 % and 15 % for maize and soybean, respectively. Possible physical mechanisms responsible for this buffering are improved plant physiological function and fulfilment of evaporative demand due to additional soil water resulting from higher AWC, given sufficient water supply. This empirical large-scale evidence of mediating role of AWC for crop yield impacts from a dryer atmosphere underscores the critical nature of soils to support climate-smart agricultural practices via building soil organic matter as well as providing co-benefits for improved crop performance to meet current and future population’s food and fiber needs.

Plant available water capacity of soils at regional scale: Analysis of fixed and dynamic field capacity

Estimation of the plant available water capacity (PAWC) of soils at a regional scale helps in adopting better land use planning, developing suitable irrigation schedules for crops, and optimising the use of scarce water resources. In the current study, 72 soil profiles were sampled from the Barossa Region of South Australia to estimate pedo-transfer functions deduced from easily estimated soil properties. These functions were then used to estimate the fixed (10, 33 kPa) and dynamic pressure head ( h fc ) water content at field capacity (FC) for minimum drainage flux ( q = 0.01 and 0.001 cm/day), which serves as the upper boundary for plant-available water in the soils. The estimated crop lower limit (CLL, θ wp ) was corrected for subsoil constraints, especially the exchangeable sodium percentage (ESP). The data showed that the mean values of h fc in sand-dominated light and medium textures (i.e. sand, loamy sand, sandy loam, and loam) varied in a narrow range (15.8–18.2 kPa), while in the clay-dominated heavy textured soils (i.e. clay loam) showed the widest range of h fc (11.3–49.3 kPa). The data showed wide variability in the PAWC for dynamic FC (PAWC fc ) and fixed FC at 10 kPa (PAWC 10 ), 33 kPa (PAWC 33 ), and a mix of 10 and 33 kPa (PAWC 10,33 ) pressure heads depending on soil texture. Normally, the difference between PAWC at h fc and 10 kPa (ΔPAWC 10 ) was positive, whereas the corresponding difference between PAWC at 33 kPa and h fc (ΔPAWC 33 ) was negative across all sites. Nevertheless, the estimation of PAWC assuming a fixed FC at 10 and 33 kPa pressures (PAWC 10,33 ) for sandy, clay, and silty soils reduced the deviation between dynamic and fixed pressure PAWC < 10% across the region. The estimation of PAWC was improved by incorporating the impact of subsoil constraints, such as high ESP in the soil, which was more pronounced for clay and silty texture soils occurring at lower depths. These findings demonstrate the inherent inconsistencies between static pressure and flux-based dynamic field-capacity estimations in soils. Soil heterogeneity, intra-texture variability, subsoil constraints, and swell–shrink clays can have great impacts on the water retention capacity in response to dynamic and fixed pressure FC values.

Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

Soil available water capacity (SAWC) is a key factor to be considered when assessing soil capability to provide ecosystem services. The current study deepens the use of remotely sensed data for mapping SAWC and its components from crop model inversion. The inversion was conducted using the STICS (Simulateur mulTIdiscplinaire pour les Cultures Standard) crop model along with the GLUE (Generalized Likelihood Uncertainty Estimation) algorithm on a panel of 14 sites within a rainfed vineyard catchment located in Southern France. Several constraint variables derived from Landsat7 ETM + satellite imagery (leaf area index - LAI - and evapotranspiration - ET) or in-situ measurements (surface soil moisture - SSM), were used in the inversion process alone or in combination.Three main outcomes could be reported when comparing retrievals of both SAWC and its components against field estimates. First, retrievals were significantly correlated with ground estimates for some SAWC components and some scenarios of constraint variables, although overall retrieving performances were quite poor. Second, poor retrieving performances for two scenarios of constraint variables were related to few sites for which specific processes were disregarded by the modelling framework, namely allochthonous water supply and waterlogging during wet autumn and summer. Third, we could identify some promising combinations of constraint variables, after the removal of the aforementioned sites with specific processes. These promising combinations were (LAI, ET) and even more (LAI, ET, SSM) for estimating SAWC and root zone thickness, as well as SSM for estimating soil moistures at field capacity and wilting point of the topsoil layer. Provided we can avoid site-specific processes, our approach may further provide spatial sampling of SAWC and related components, to be used as surrogate input data for DSM models.

Plant available water capacity (PAWC) of soils predicted from crop yields better reflects within-field soil physicochemical variations

Within field variations of plant available water capacity (PAWC) of soil is one of the major causes of spatial yield variability in dryland agriculture systems, as PAWC interacts with pre-season and in-season rainfall and other climatic variables to determine crop growth and final yield. Quantification of such variations helps to better understand the changes in soil texture and subsoil constraints to inform spatially explicit management practice. An inverse modelling approach to estimate PAWC from crop yields was developed as a more cost-effective alternative to traditional soil sampling methods. In this study, we further extend this approach to predict and map in-field variations of PAWC from yield maps of single and multiple crops. Soil PAWC maps were produced based on inversely predicted PAWC using crop yield maps together with in-field management information, and compared with: 1) available water capacity derived using laboratory-measured soil properties, and 2) soil types derived from proximally sensed soil spectra and ground geophysics for four representative farms in Australia. The results show that the predicted PAWC maps matched well with within-field spatial variation of soil types, and well reflected the impact of soil constraints (e.g. salinity), and soil classifications from soil survey and local experience. This demonstrates that the predicted PAWC from crop yield using inverse modelling can reflect the soil physicochemical variations within-field. The generated PAWC maps can be combined with process-based modelling to predict crop yield and yield zones and to inform spatial field management and soil sampling.

Available water capacity of sandy soils as affected by biochar application: A meta-analysis

Sandy soils have inherently low available water capacity (AWC), making their use for agricultural production a challenging task. Biochar amendments have been recommended to enhance the hydrological properties of sandy soils. A meta-analysis of existing literature was conducted to investigate the overall effect of biochar on the AWC of sandy soils. Key factors related to biochar characteristics (specific surface area, particle size, carbon content) and production conditions (pyrolytic temperature, feedstock), soil properties (pH, textural class, organic carbon content), and experimental setting and duration were also included in the analysis. Sandy soils amended with biochar had their AWC significantly increased, on average, by 28.5% compared to un-amended soils. Biochar had no significant effect on AWC when it had a large particle size (PS > 5 mm) or when applied to soils with high carbon content (SOC > 2%). No significant changes in AWC were found among biochar feedstocks, pyrolytic temperatures, and specific surface areas. Available water capacity was higher due to the application of biochar with fine PS compared to coarse PS and with low C (C < 50%) than high C (C > 70%) content. The increase in AWC in biochar-amended sandy soils was most pronounced in those with the highest sand content, acidic pH, and the lowest C content. Our analysis further showed that the effects of biochar application on AWC were greater under controlled laboratory conditions compared to field trials and in short-term rather than in long-term experiments. Overall, the current meta-analysis revealed that biochar technology has the potential to contribute towards the alleviation of the hydrological constraints of sandy soils leading to more drought-resistant soils in the face of an expected dryer climate.

Increasing available water capacity as a factor for increasing drought resilience or potential conflict over water resources under present and future climate conditions

The close relationship between the onset and severity of agricultural and hydrological drought is considered self-evident, yet relatively few studies have addressed the effects of applying agricultural drought adaptation to hydrological drought characteristics. The present study applies a model cascade capable of simultaneously considering the interactions between agricultural and hydrological droughts. The study area covers all river basins in the Czech Republic and includes the periods of 1956–2015 (baseline) and 2021–2080 (future). The model cascade was shown to explain 91% of the variability in the seasonal and annual accumulated runoff and allows for the analysis of increasing/maintaining/decreasing available water capacity (AWC) across the 133 defined basins with a total area of c. 78,000 km2. The study reports that the probability and extent of agricultural drought increased over the entire period with higher AWC scenario showing slower pace of such increase especially from April to June. The trends in the extent or severity of hydrological droughts were of low magnitude. The future climate has been projected through the use of ensembles of five global (CMIP5) and five regional (EURO-CORDEX) climate models. The results showed a significant increase in the duration of agricultural drought stress and in the area affected throughout the year, particularly in July–September. The hydrological drought response showed a marked difference between areas with a negative and positive climatic water balance, i.e., areas where long-term reference evapotranspiration exceeds long-term precipitation (negative climatic water balance) and where it does not (positive climatic water balance). The overall results indicate that increasing soil AWC would decrease the frequency and likely also impact of future agricultural droughts, especially during spring. This result would be especially true if the wetter winters predicted by some of the models materialized. Hydrological droughts at the country level are estimated to become more pronounced with increasing AWC, particularly in catchments with a negative climatic water balance.

Mapping the impact of subsoil constraints on soil available water capacity and potential crop yield

Context The depth-to a constraint determines how much of the soil profile, and the water it contains, can be accessed by plant roots. Information describing the impacts of soil constraints on available water capacity (AWC) and yield is important for farm management, but is rarely considered in a spatial context. Aims and methods The depth-to three yield-limiting constraints (sodicity, salinity, and alkalinity) was mapped across ∼80 000 ha in northern New South Wales, Australia using machine learning and digital soil mapping techniques. Soil AWC was calculated using soil data and pedotransfer functions, and water use efficiency equations were used to determine potential yield loss due to the presence of soil constraints. From this, the most-limiting constraint to yield was mapped. Key results One or more constraints were found to be present across 54% of the study area in the upper 1.2 m of the soil profile, overall reducing the AWC by ∼50 mm and potential yield by an average of 1.1 t/ha for wheat and 0.8 bales/ha for cotton. Sodicity (Exchangeable Sodium Percentage &gt; 15%) was identified as the most-limiting constraint to yield across the study area. Implications The simplification of multiple sources of information into a single decision-making tool could prove valuable to growers and farm managers in managing soil constraints and understanding important interactions with available water and yield.

Underpinning terroir with data: on what grounds might subregionalisation of the Barossa Zone geographical indication be justified?

Background and Aims Winegrowers in the Barossa Zone geographical indication of South Australia are interested in understanding subregional terroir. A previous analysis of biophysical variation over the entire Barossa Zone was not strongly supportive of the subregionalisation favoured by local winegrowers. Here, we use an updated, contemporary climate data set and focus just on land under vineyard as a platform for better understanding the biophysical component of the Barossa terroir. Methods and Results Clustering (k-means) of digital map layers describing a range of climatic and topographic indices along with soil properties of viticultural importance was used to explore regional-scale patterns of spatial variation. Marked soil, topographic and climatic variation was noted within the Barossa Zone, and the clustering suggested a useful biophysical basis for exploring the merits of dividing the geographical indication more finely than the existing Barossa and Eden Valley regions. Conclusions Whilst there are clear differences between the Barossa and Eden Valleys in terms of temperature, rainfall, soil fertility and the plant available water capacity of soil, the clusters identified suggest that a re-evaluation of the presently proposed subdivision of the Barossa Valley region may be warranted. Wine chemical and sensory data would need to be integrated with the biophysical data to confirm the expression of subregional terroir effects within the Barossa Valley. Significance of the Study This data-driven analysis provides further evidence of the desirability of terroir analysis being free of the bias that is introduced by heuristics, or by examination of historically delineated terroirs, and of focussing solely on the land which is under vine in evaluating terroir.

RETRACTED: Biochar and compost amendment impacts on soil water and pore size distribution of a loamy sand soil

AbstractSoil structure, which refers to aggregates and pore characteristics, reflects the spatial arrangement of soil particles and is a key component for crop yield and soil health. Well‐formed soil structure has favorable pore size distribution, which supports soil water flow and retention and healthy plant growth. Compost and biochar, important organic amendments, have a potential to influence soil structure, but their effects on specific soil types and soil properties have not been fully investigated. The main objective of this study was to investigate the impact of the additions of compost and/or date palm biochar on selected soil water indicators and pore size distribution of a loamy sand soil using disturbed soil samples. Statistical parameters of pore size distribution properties such as SD, kurtosis, skewness, modal diameter (dmode), median diameter (dmedian), and mean diameter (dmean) as well as plant available water capacity (PAWC), available soil water capacity (ASWC), saturated soil water content, and measured saturated hydraulic conductivity (Ksat) were measured and evaluated. The results showed that the dmode, dmedian, dmean, SD, skewness, and kurtosis values for untreated soil (control) were 31.6 μm, 25.8 μm, 23.5 μm, 3.3, −0.16, and 1.14, respectively. Biochar, compost, and a mixture of biochar–compost additions to a loamy sand soil significantly reduced dmode, dmedian, and dmean values in comparison with nonamended soil. Application of these amendments increased PAWC and ASWC and reduced Ksat of the loamy sand soil, significantly. Biochar–compost mixture has the most significant effect on improving soil water retention and PAWC.

Mapping available soil water capacity in New South Wales, Australia using sparse data - An inverse Bayesian approach

Data sparsity is a major limitation in modelling soil hydraulic properties across large spatial extents, such as the continent of Australia, and can lead to erroneous models being developed. Inverse modelling can be used to make inferences about underlying environmental processes, even when the data is subject to error. Bayesian inverse modelling is one method to quantify uncertainties from multiple sources, including data, model structure, and model parameters. Although, Bayesian inverse modelling approaches have been proven useful in many applications, they are still not commonplace in digital soil mapping (DSM). In this work, we present a Bayesian inverse model for predicting available water capacity (AWC) of soils using sparse data. Specifically, we estimate upper and lower drainage limits (DUL and LL15) using a Bayesian geostatistical model. DUL and LL15 are then differenced to estimate the AWC. This study was carried out using measurements of upper and lower drained limits (DUL & LL15) across NSW, Australia. Two separate Bayesian inverse models were calibrated and validated for the DUL and LL15 soil hydraulic parameters. The calibrated models were then used to spatially predict AWC of soils across a cropping region in New South Wales (NSW), Australia on a 90-m grid. We also present the uncertainty of the parameters and output maps. Our results gave similar estimates of AWC values when compared to those predicted using the Cubist machine learning model. Although the predictions are similar, the Bayesian method allows for the direct quantification of the prediction uncertainties, while the Cubist method cannot.

Uncertainty assessment of soil available water capacity using error propagation: A test in Languedoc-Roussillon

Soil available water capacity (SAWC) is a key soil indicator that plays a major role in many ecosystem services, such as food production, irrigation management, soil drought, flood control, and climate and gas regulation. Digital soil mapping (DSM) can be used to obtain needed SAWC maps. However, SAWC differs from the usual soil properties considered in DSM in that it involves several soil properties determined at several soil layers. Therefore, a specific approach is required to obtain SAWC maps and the associated uncertainty predictions.The objective of this study was to build a SAWC mapping approach that could predict SAWC values at three maximum rooting depths (60, 100 and 200 cm) and their associated prediction uncertainties.The approach was tested in the Languedoc-Roussillon region (southern France). Elementary available water capacities of each layers (in cm.cm−1) and soil layer thicknesses were first mapped separately at 0–30, 30–60, 60–100 and 100–200 cm and then aggregated to estimate the SAWCs at the three mentioned maximum rooting depths. SAWC uncertainty was estimated with an error propagation model that used a first-order Taylor analysis. This analysis considered the mapping errors of each involved property, which were estimated by the quantile regression forest algorithm. We tested different error propagation models that differently considered the correlations between these mapping errors: no correlation considered, correlations between soil layer thicknesses and elementary water capacities per soil layer only, correlations between soil layers only, or all correlations considered.The performances of both SAWC predictions and their uncertainties were assessed with a 10-fold cross validation that was iterated 20 times. The SAWC predictions showed poor accuracies (percentages of explained variance ranged from 0.12 to 0.13). The uncertainties of SAWC predictions were best estimated when the correlations between the soil layer errors were considered in the error propagation model whereas the uncertainties of SAWC predictions were severely underestimated when these correlations were neglected.In spite of the poor performance in predicting SAWC at the punctual level due to the low density of soil observations (1/19 km2), the SAWC approach appeared promising since it produced maps that agreed with the available pedological knowledge and precisely estimated the uncertainties.