Soil Spatial Distribution Research Articles

Constructing Soil–Landscape Units Based on Slope Position and Land Use to Improve Soil Prediction Accuracy

Topography is one of the dominant factors in regional soil formation and development. Soil distribution has a certain pattern from high to low in space, and this pattern has a high degree of consistency with slope position. Most of the current research on soil mapping uses landscape types generated by existing methods directly as environmental covariates, and there are few landscape classification methods specifically oriented toward soil surveys. There is rarely any research on landform classification using relative slope position (RSP) and elevation. Therefore, we designed a landform classification method based on RSP and elevation, Terrainforms (TF), and combined the landform type with land use type to construct soil–landscape units for soil type and attribute spatial prediction. In this study, two commonly used landform classification methods, Geomorphons and Landforms, were also used to compare with this design method. It was found that the constructed soil–landscape units had a high consistency with the soil spatial distribution. The landform types based on RSP and elevation obtained the second-highest prediction accuracy in both soil type and soil organic carbon (SOC), and the constructed soil–landscape types obtained the highest prediction accuracy. The results show that the landform classification method based on RSP and elevation is not easily limited by the analysis scale, and is an efficient and accurate landform classification method. The TF landform type and its constructed soil–landscape types can be used as an important environmental variable in soil prediction and sampling, which can provide some guidance and reference for landform classification and digital soil mapping.

The Role of Leaching in Soil Carbon, Nitrogen, and Phosphorus Distributions in Subalpine Coniferous Forests on Gongga Mountain, Southwest China

To explore the role of leaching in mountainous nutrient cycling, we investigated the altitudinal distribution of soil carbon (C), nitrogen (N), and phosphorus (P) in the subalpine coniferous forest ranging from 2628 to 3044 m on the eastern slope of Mt. Gongga. The results revealed that concentrations of C and N, as well as the atomic ratios of C:N and N:P, showed no significant difference among the sampling sites (p > 0.05) in O horizons. The concentrations of P in O horizons increased gradually with altitude. In contrast, notable variations in C, N, and P concentrations and stoichiometry were observed in the mineral horizons. Lower concentrations of C, N, and P were found in A horizons, while higher contents were present in B and C horizons compared to previous studies. Additionally, results of the random forest model indicated that C and N concentrations in the O, B, and C horizons, as well as P concentration in the B horizons, were primarily influenced by Feox concentrations. This suggested that these nutrients leached from O horizons and accumulated in B and C horizons alongside Feox. Except for C:N ratios in the O horizon, the C:N, C:P, and N:P ratios in the O, B, and C horizons were mainly affected by concentrations of Feox or Alox. These results underscored the substantial impact of leaching processes on the spatial distribution of soil C, N, and P, ultimately leading to changes in the gradient distribution of soil C:N:P stoichiometry. Specifically, the C:N ratio in the mineral horizons at the 2781 m site was significantly higher compared to other sites (p < 0.05), indicating a greater movement of C relative to N. The C:P and N:P ratios in the B horizon at the 2781 m site were notably higher than at other sampling sites (p < 0.05). Conversely, the N:P ratio in the A horizon at the 2781 m site was relatively low. Furthermore, concentrations of C and N in the B horizon at the 2781 m site were significantly higher than in other sampling points, while P concentrations were notably lower (p < 0.05). This suggested a more pronounced downward leaching of C and N compared to P at the 2781 site, indicating stronger leaching effects. Overall, this study emphasizes the significant influence of leaching processes on the spatial distributions of soil C, N, and P in subalpine coniferous forests in Southwest China.

Miscanthus sp. root exudate alters rhizosphere microbial community to drive soil aggregation for heavy metal immobilization

The heavy metals (HMs) spatial distribution in soil is intricately shaped by aggregation processes involving chemical reactions and biological activities, which modulate HMs toxicity, migration, and accumulation. Pioneer plants play a central role in preventing HMs at source, yet the precise mechanisms underlying their involvement in soil aggregation remain unclear. This study investigates HMs distribution within rhizosphere and bulk soil aggregates of Miscanthus sp. grown in tailings to elucidate the impact of root exudates (REs) and rhizosphere microbes. The results indicate that Miscanthus sp. enhance soil stability, increasing the proportion of macroaggregates by 4.06 %–9.78 %. HMs tend to concentrate in coarse-aggregates, particularly within rhizosphere environments, while diminishing in fine-aggregates. Under HMs stress, lipids and lipid-like molecules are the most abundant REs produced by Miscanthus sp., accounting for under up to 26.74 %. These REs form complex with HMs, promoting microaggregates formation. Charged components such as sugars and amino acids further contribute to soil aggregation. REs also regulates rhizosphere bacteria and fungi, with Acidobacteriota, Chloroflexi were the dominant bacterial phyla, while Ascomycota and Basidiomycota dominate the fungal community. The synergistic effect of REs and microorganisms impact soil organic matter and nutrient content, facilitating HMs nanoparticle heteroaggregation and macroaggregates formation. Consequently, soil structure and REs shape the distribution of HMs in soil aggregation. Pioneer plants mediate REs interaction with rhizosphere microbes, promoting the distribution of HMs into macroaggregates, leading to immobilization. This study sheds light on the role of pioneer plants in regulating soil HMs, offering valuable insights for soil remediation strategies.

SALINE MAPS OF SOME SOILS OF MUTHANNA GOVERNORATE

performed based on data collected from 15 soil samples from 0 to 20 cm deep. We used salinity of the irrigated soils of Al-Muthana governorate in southern Iraq. These maps were 20% of the world's land. This study was made in order to map the spatial distribution of soil or anthropogenic processes, which is certainly an environmental problem that affects more than environment and agricultural production. The main causes of this salinization come from natural It is important to study the problem of salinization, soil salinity has adverse effects both on the ordinary kriging (OK) to analyze the spatial variability of soil salinity, The results confirmed that the use of saline maps was supportive in giving a clear vision of the of 12.11 dS m-1, for developing probability maps to determine the distribution of risk areas. showed the different classes of salinity with the highest value of 23.17 dS m-1 and lowest value map predicted by the electrical conductivity (EC) values using the ordinary kriging (OK) method while indicator kriging (IK) was used to analyze salinity versus threshold values . The salinity salinity of the soils for the study area

Spatio-Temporal Changes in Land Cover and the Spatial Distribution of Soils in the Damyang Riverine Wetland

Spatio-Temporal Changes in Land Cover and the Spatial Distribution of Soils in the Damyang Riverine Wetland

Geotechnologies on the phosphorus stocks determination in tropical soils: General impacts on society

Phosphorus (P) is a critical nutrient for primary production in terrestrial and aquatic ecosystems. As P mineral reserves are finite and non-renewable, there is an increasing discussion on its sustainable utilization to safeguard food security for future generations. Understanding the spatial distribution of soil P is central in advancing effective phosphorus management and fostering sustainable agricultural practices. This study aims to digitally map the stocks of available P (AP) and total P (TP) in Brazil at a fine resolution (30 m). Using the Random Forest machine learning algorithm and a database of topsoil (0-20 cm) with 28,572 samples for AP and 3154 for TP, we predicted P stocks based on environmental covariates related to soil formation processes. By dividing Brazil into two sub-regions, representing areas with native coverage and anthropogenic ones, we built independent predictive models for each sub-region. Our results show that Brazil has a TP stock of 531 Tg and an AP stock of 17.4 Tg. The largest soil TP stocks are in the Atlantic Forest biome (73.8 g.m2), likely due to higher organic carbon stocks in this biome. The largest AP stocks were in the Caatinga biome (2.51 g.m2) because of younger soils with low P adsorption capacity. We also found that fertilizer use significantly increased AP stocks in agricultural areas compared to native ones. Our results indicated that AP stocks strongly influenced Brazil's agricultural production, with a correlation coefficient ranging from 0.20 for coffee crops to 0.46 for soybean. The maps generated in this study are expected to contribute to the sustainable use of P in agriculture and environmental systems.

Differences in shrimp pond bottom soil properties and bacterial load between acute hepatopancreatic necrosis disease (AHPND)‐infected ponds and AHPND‐free ponds and their relation to AHPND

AbstractThis study investigated the disparities in soil characteristics and pathogenic bacteria prevalence between shrimp ponds affected by acute hepatopancreatic necrosis disease (AHPND) and unaffected ponds, alongside examining the spatial distribution of soil attributes in flat‐oriented pond soil strata. Using Pearson correlation and logistic regression analyses, relationships among variables and indicators associated with AHPND prevalence were discerned, leading to the formulation of a predictive model for AHPND occurrence. Soil samples were collected from distinct locations and depths within ponds across three southern provinces of Thailand's Andaman Seaboard. The analysis revealed significantly higher concentrations of several variables, including SOD, TIC, NO2−‐N, Ca, Mn, Cu, Zn, and specified Vibrio strains, in AHPND‐afflicted ponds, especially at 0–5 cm depth. A prominent differentiation was the escalated concentration of easily decomposable organic matter (EDOM) within infected ponds, implicating potential soil and water quality deterioration alongside heightened shrimp susceptibility to AHPND. Correlational analysis showed links between bacterial densities and organic matter groupings, trace elements, exchangeable bases, and soil pH, in AHPND‐infected ponds. The logistic regression model encapsulated three soil variables (TOC, Mg, and Mn) and one pathogen variable (V. parahaemolyticus) and furnished an equation to estimate the log (odds) of AHPND occurrence, facilitating better understanding and potential forecasting of AHPND prevalence in shrimp cultivation environments.

Experimental model updating of slope considering spatially varying soil properties and dynamic loading

AbstractThe widespread threat posed by slope structure failures to human lives and property safety is widely acknowledged. Additionally, natural soil often displays spatial variability due to geological deposition and other factors. Therefore, predicting the seismic response of slopes subjected to ground motions and inversely analyzing the spatial distribution of soils remains an unresolved issue. In the present work, a shaking table experimental test is first designed and carried out, in which a soft‐soil slope dynamic system is established. To capture the seismic response of the soft‐soil slope, specifically the experimental characteristic of acceleration and soil pressure response in both spatial domain and time domain, a series of sensors were pre‐embedded in the slope. Subsequently, a model updating approach is proposed for slope seismic analysis that incorporates spatial variability of soil. In addition, to enhance computational efficiency, the dimensionality reduction of Karhunen–Loève expansion method is introduced to reduce inverse analysis parameters. On the basis of 34 samples collected from experimental data, it is shown that near‐fault pulse‐like ground motions deliver greater concentrated energy, causing more severe damage to slope structures, especially the topsoil layer. Furthermore, using data obtained from a shaking table test subjected to ground motion Recorded Sequence Number 158H1 from the Pacific Earthquake Engineering Research Center NGA‐West2 database as an example, it is also shown that the proposed approach demonstrates high accuracy in predicting the spatial distribution of the maximum shear modulus in soil slope dynamic systems. The present work not only addresses the challenges posed by mainshock–aftershock effects but also highlights the potential of model updating approaches to enhance the understanding of slope behavior under seismic loading conditions.

Spatial Distribution Characteristics of Soil C:N:P:K Eco-Stoichiometry of Farmland and Grassland in the Agro-Pastoral Ecotone in Inner Mongolia, China

Ecological stoichiometry (ES) is an important index that reflects the balance of various elements in ecological processes. Therefore, it is of great significance to understand the soil nutrient cycle to clarify the environmental control of soil carbon (C), nitrogen (N), phosphorus (P), and potassium (K). In this study, we analyzed the spatial distribution of soil C, N, P, and K contents and the C:N:P:K stoichiometric characteristics of 0–20 cm and 20–40 cm of farmland and grassland in four agro-pastoral areas in Inner Mongolia. Spearman correlation was used to analyze the effects of environmental factors on the soil C:N:P:K stoichiometric relationship. The results showed that there was no fixed Redfield ratio for the soil stoichiometric relationship of farmland and grassland in Inner Mongolia, and the values were 15:2:1:9 to 145:10:1:26 and 25:1:1:29 to 228:15:1:65, respectively. The stoichiometric relationships between farmland and grassland were consistent with the law of geographical and spatial heterogeneity. The ratios of C:N, C:P, C:K, N:P, and N:K showed an N distribution from west to east, while the ratio of P:K showed a V distribution. The stoichiometric relationships in grassland soil were mainly affected by soil organic carbon and total nitrogen content, while those in farmland were mainly affected by total nitrogen and total phosphorus content. The annual mean precipitation has a significant effect on stoichiometric relationships in farmland, while the annual mean temperature has a more significant effect on grassland. In conclusion, the spatial distribution difference in the soil stoichiometric relationship in the agro-pastoral ecotone of Inner Mongolia was more significant than the difference in the land use pattern. The influences of annual mean temperature and annual mean precipitation on soil ecological stoichiometry were in accordance with the geographical spatial similarity law. Compared with grassland, the stoichiometric relationship of farmland soil was greatly affected by fertilization, and farmland in this region was mainly limited by carbon and nitrogen. Thus, field management should be carried out according to local conditions. This study is of great significance as it promotes the rational utilization of land resources and the sustainable development of agriculture.

Impact of manure injection on spatial variability in soil nitrate, carbon, and small grain growth

AbstractManure injection alters the spatial distribution of manure by concentrating it in a subsurface band which can lead to differential soil nutrient distribution and growth in small grains. This study assessed the effects of fall manure applications on soil NO3‐N, active carbon, and small grain growth compared to broadcasting and a no manure control. Soil samples were taken to represent whole plot soil means for all treatments, while in‐band (IB) and between‐band (BB) soil samples were taken in injected plots to assess nutrient spatial distribution after injection. Small grain forage samples were also taken IB and BB to assess the effects of manure injection on small grain growth. Soil samples were analyzed for NO3‐N, permanganate oxidizable carbon (POXC), and carbon mineralization (C‐min), while small grain dry matter (DM) yield and forage quality parameters were measured from plant samples. Manure injection did not result in any differences between whole plot injection and broadcast soil NO3‐N concentrations. However, injection resulted in initially elevated soil NO3‐N concentrations IB compared to BB. There were no differences in soil POXC or C‐min under manured versus unmanured soils, nor between IB and BB samples. Manure injection did not increase small grain DM yield or forage quality compared to broadcasting, nor were these measurements altered IB and BB. Even though manure injection altered the spatial distribution of soil NO3‐N, it did not affect soil C‐min, POXC, or small grain growth under the conditions seen in this study. Therefore, differential small grain growth and quality is likely not a concern under injection.

Soil Phosphorus in Farmed Potholes: Assessing Concentrations and Testing Export Mitigation with Steel Media

Highlights Phosphorus concentrations were higher near the bottom of farmed potholes compared to soils outside of the potholes. Benchtop flow-through experiments demonstrated that steel shavings effectively adsorbed dissolved reactive phosphorus. A blind inlet amended with steel shavings reduced phosphorus export from a surface-drained pothole. Abstract. The Prairie Pothole Region, which extends from north-central Iowa northward into Canada and westward to Montana, is typified by closed depressions that formed over 10,000 years ago during the most recent glacial retreat. Today, many of these potholes contain artificial drainage to lower the water table, allowing for agricultural production of the land. Even when drained, farmed potholes can become inundated with phosphorus (P) enriched surface waters after large rain events. The goal of this study was to characterize the spatial distribution of soil P in farmed potholes and evaluate a steel media-modified blind inlet as a tool to reduce P export from farmed potholes. Results from the soil sampling indicated that Bray-1 soil test P concentrations are nine times higher near the bottom of the pothole compared to locations outside of the farmed pothole. Steel shavings were evaluated for P sorption in a laboratory flow-through cell evaluation where they removed between 60 and 70% (discrete P), even when cumulative P loading was over 6000 mg kg-1. In a field investigation, a modified blind inlet containing a mixture of steel shavings and pea gravel replaced a Hickenbottom surface intake. The modified blind inlet retained an average of 83% of the influent dissolved reactive P and 62% of the influent total P based on five paired samples. The results from this study demonstrate that farmed potholes contain a significant amount of legacy soil P and that blind inlets containing steel shavings can replace surface intakes and reduce P export from farmed potholes. This research could inform future design and implementation of these P removal structures. Keywords: Drainage, Farmed wetland, French drain, Iron filings, Iron shavings, Iron tailings, Prairie pothole, Surface intake, Tile.

Improving soil thickness estimations and its spatial pattern on hillslopes in karst forests along latitudinal gradients

Soils provide storage space for nutrients and water, which governs many hydrological processes and functions in the natural ecosystems. Due to the complex soil-rock structures and localized climate, soil thickness and stock vary distinctly in different karst areas in southwest China. The difficulties of soil detection and the non-transparent underground soil-rock structures limit a deeper understanding of the spatial distribution of soils and their ecological functions. In this study, we employed electrical resistivity tomography (ERT) combined with soil probes to detect the spatial distribution of soils on hillslopes in karst forests in southwest China. The ERT surveys were conducted at six sites with 19 plots (20 × 30 m2) along latitudinal gradients. The results show that the ERT method performs well in visualizing the complex soil–bedrock interfaces and patchy distribution of soils in karst hillslopes, with remarkable consistency with the observed soil thickness and rock outcrops. Soil probes often hit rocks in soils (which we call a “rock barrier effect”), resulting in an underestimation of the mean soil thickness within the one-meter exploration depth by ∼0.18 m. This indicates that soil stock estimates derived from soil probes may be obviously underestimated in karst areas where the rock barrier effects are widespread. Meanwhile, the concept of equivalent soil thickness is proposed to remove the impact of scattered bedrock on soil stock estimation. For the six selected sites, the ERT-inferred mean soil thickness, equivalent soil thickness, and stock are 0.86 m, 0.60 m, and 0.10 m3/m3 respectively, with a trend of decreasing from high to low latitudes. Moreover, the rock outcrop coverage rate explains 52 % (60 %) of the variation in soil thickness (stock), followed by the annual mean temperature. This study emphasizes the importance of considering bedrock topography and its distribution in improving the detection of soil distribution, and the implications of the findings in this study are perhaps most profound for soil thickness-related soil erosion, soil water storage, and carbon storage in karst critical zones.

Evaluating Spatial Soil Parameters of an Apple Orchard in ‘R’ Software: A Study from Kashmir Valley

Maintaining the ecological balance of the physical and biological environment depends greatly on the spatial variation of soil parameters across a given region and its elucidation using remote sensing and GIS applications. R software was used to apply the geostatistical methods of Ordinary Kriging and Inverse Distance Weightage to the study of the spatial distribution and variability of the soil parameters of an apple orchard in the Valley of Kashmir. Average values for available phosphorus (P), potassium (K), calcium (Ca), available nitrogen (N), and soil organic carbon (OC) were 1.15 percent, 315 percent, 22.5 kg, 221.4 kg, and 250 mg, respectively. Ordinary kriging (OK) and IDW were used to plot the spatial distribution of soil parameters using spherical (pH, OC, and Ca), steradian (EC, N, P, and K), and mean square error (MSE) values. According to the semi-variogram analysis, there was a strong to moderate spatial dependence. The interpolated maps showed various soil distribution patterns for pH (5.4-5.7), EC (0.46-0.56 DSM-1), OC (0.9-1.4 percent), N (296-335) kg ha-1, P (20-25 kg ha-1), K (221-221.8 kg ha-1), and Ca (100-400 mg kg-1) at the regional scale. This study represented a wide range of spatial soil variability. The estimation of MSE for Ordinary Kriging and IDW was used to predict the best model after performing a validation accuracy assessment. The best fit model for interpolation was the standard kriging model with low MSE. The maps of soil spatial distribution created to serve as an effective tool for policymakers and those planning farms.

Effect of soil spatial aggregation caused by the calculation unit division on runoff and sediment load simulation in the SWAT model

Distributed hydrological model divides watersheds into distinct calculation units to simulate hydrological processes. Within the model, different calculation unit division schemes induce input elements, such as soil and land use, to certain degrees of generalization, thus affecting the simulation result. Analyzing the effect of the calculation unit division on the simulation result is an important methodology to reduce uncertainty and improve the simulation accuracy of the model. Previous researchers have focused on the comprehensive effect of underlying surface generalization (such as soil, land use, and terrain generalization) caused by the calculation unit division on the simulation results, while it did not separate the effect of the generalization of the individual input factor on the simulation result. In this paper, the Dongjiang headwater region in southern China was selected as the study area. The single type of land use and slope were input into the Soil and Water Assessment Tool (SWAT) model to fix the effects of land use and terrain caused by calculation unit division on the simulation results. Eleven calculation unit division schemes were used to analyze the impact of soil spatial aggregation on runoff and sediment load simulations. The calculation unit division schemes included 11 sub-watershed division schemes and their hydrological response unit (HRU) thresholds were set at 8 %. The drainage area thresholds of the 11 sub-watershed division schemes were 30 ha, 60 ha, 120 ha, 240 ha, 480 ha, 1000 ha, 1600 ha, 2200 ha, 2800 ha, 3400 ha and 4000 ha. The results demonstrated that the soil spatial distribution showed an obvious aggregation with an increase in the drainage area threshold in the SWAT model. Of these, the Krasnozem soil type which covers the largest area in the watershed, increased significantly with an increase in the drainage area threshold. However, the areas of all the other soil types decreased significantly. The Lioth soil type covers the smallest area in the watershed decreased and even disappeared when the threshold in the SWAT model was greater than 1000 ha. Furthermore, soil spatial aggregation caused a significant increase in the annual runoff and sediment load (P < 0.05), with the sediment load (Re = 29.78 %) increasing at a greater rate compared to runoff (Re = 1.74 %). Increased soil aggregation significantly increased the sediment loads in the maximum 1-day, the continuous maximum 5-day, the continuous maximum 7-day, and the sediment load in flood processes (P < 0.001). Refining the calculation unit division scheme will cause a significant increase in the number of calculation units. Due to the computer processing power limitations, we cannot further refine the calculation unit division scheme. Based on our current operational calculation unit division scheme, we did not identify the optimal division scheme in the study region. These results can provide reference information for future research into hydrological model uncertainty and can improve the SWAT model simulation accuracy.

Effect of Ridging Shapes on the Water–Salt Spatial Distribution of Coastal Saline Soil

The Yellow River Delta, located in China, experiences prevalent soil salinization and serves as a crucial ecological management zone within the Yellow River Basin. The shallow groundwater depth and high mineralization contribute to salt accumulation in the soil, which has a negative impact on crop growth. The sustainable use of saline land in the Yellow River Delta hinges on managing the soil salinity within the crop root zone. This study investigated the spatial distribution of soil salinity in coastal saline soil in the Yellow River Delta under various ridging configurations: triangular, arch, and trapezoidal, using flat land as a control. It also examined the impact of evaporation on soil salinity migration. The findings revealed that the ridge–furrow system successfully caused salt to accumulate in the superficial layer of the ridge. Among the three ridge shapes, the triangular ridge was the most effective at concentrating salt on the ridge surface, with 54.04% of the salt mass accumulation in the ridge’s top layer (0–1 cm) and with the furrow bottom achieving a maximum desalination rate of 93.07%. The results implied that the triangular ridge fostered a favorable soil environment for crop growth by minimizing the salt content in the furrow. This research provides a theoretical foundation for the sustainable advancement of saline–alkali agriculture in the Yellow River Delta, which can lead to higher crop yields and better land management practices.

Phosphorus stocks and pools in eroding streambank soils

Phosphorus (P) in streambank soils can directly enter waterbodies via streambank erosion. How much and what form of P is entailed by this terrestrial-aquatic transfer has implications for the degree and timespans of downstream water quality impacts. Quantifying the bioavailability and spatial distribution of soil P species in streambanks is needed to comprehensively assess the fate of P eroded into streams and their potential risk to downstream water quality. This study quantitatively evaluated the abundance and speciation of P in streambank profiles of Polecat Creek, IL, USA using sequential (Hedley) P fractionation. The HCl extractable fraction, interpreted as Ca-P and insoluble in water, was the dominant form of P accounting for 12–73% of total P (14–344 g m−2) with higher stocks in C horizons (131 ± 26 g m−2) than the overlying B (36 ± 7.6 g m−2) and A (41 ± 12 g m−2) horizons. Ca-P was strongly positively correlated with soil pH and inorganic carbon (IC) content, demonstrating the influence of apatite-rich loess parent material of this region in driving P speciation. Organic P (Org-P) accounted for 1–33% of total P (0.1–104 g m−2) with significantly higher stocks in A horizon (39 ± 5 g m−2) than B (11 ± 7 g m−2) and C (22 ± 7 g m−2) horizons, concomitant with the pattern of organic carbon (OC) and reflective of strong biological (riparian vegetation) controls on this pool of potentially mineralizable P. Subsurface increases in Org-P occurred for buried A horizons in banks created by alluvial depositions indicated the strong influence of fluvial processes on streambank P distribution and speciation. Fe/Al-P accounted for 1–21% of total P stocks and was generally enriched in the surface A (50 ± 30 mg kg−1) and B (35 ± 39 mg kg−1) horizons. The most immediately bioavailable pool, exchangeable P (Exc-P), was the smallest across streambanks, constituting < 10% of total P and largely relegated to A horizon (1.2–20.4 g m−2). This proof of concept offers valuable information about the variation of P stocks and speciation by genetic horizons in streambanks.

Effect of spatial scale of soil data on estimates of soil ecosystem services: Case study in 100 km2 area in France

AbstractOver the last decade, the ecosystem services (ESs) framework has been increasingly used to support mapping and assessment studies for sustainable land management purposes. Previous analysis of practical applications has revealed the significance of the spatial scale at which input data are obtained. This issue is particularly problematic with soil data that are often unavailable or available only at coarse scales or resolutions in various part of the world. In this context, four soil‐based ecosystem services, namely biomass provision, water provision, global climate regulation, and water quality regulation, are assessed using three conventional soil maps at the 1:1,000,000, 1:250,000 and 1:50,000 scales. The resulting individual and joint ES maps are then compared to examine the effects of changing the spatial scale of soil data on the ES levels and spatial patterns. ES levels are finally aggregated to landforms, land use, or administrative levels in order to try to identify the determinants of the sensitivity of ES levels to change in the scale of input soil data. Whereas the three soil maps turn out to be equally useful whenever ESs levels averaged over the whole 100 km2 territory are needed, the maps at the 1:1,000,000 and 1:250,000 induced biases in the assessment of ESs levels over spatial units smaller than 100 and 10 km2, respectively. The simplification of the diversity and spatial distribution of soils at the two coarsest scales indeed resulted in local differences in ES levels ranging from several 10 to several 100%. Identification of the optimal representation of soil diversity and distribution to obtain a reliable representation of ESs spatial distribution is not straightforward. The ESs sensitivity to scale effect is indeed context‐specific, variable among individual ESs, and not directly or simply linked with the soil typological diversity represented in soil maps. Forested and natural lands in the study area appear particularly sensitive to soil data scales as they occupy marginal soils showing very specific ESs signatures.

Silver origins and spatial distribution in soils of southwestern France: A first assessment with cokriging

Ag is a rare, non-essential metal with many applications in different forms, including nanoparticles (Ag-NPs). Its release into the soil environment can represent a risk, due to the toxicity of silver. This study is based on the analysis of samples from the two sampling campaigns of the Soil Quality Measurement Network, RMQS1 and RMQS2, to establish the spatial distribution and origin of Ag in the soils of southwestern France (area of 90,293 km2). Given the progress of the second campaign (completion in 2027), we chose to do a cokriging to estimate the spatial distribution, with Pb, Cd or Cu as potential secondary variables. The results of the analyzes of the 35 samples of the RMQS2 indicate a range of Ag concentration in the soils going from 0.015 to 0.222 mg kg−1 and a median of 0.081 mg kg−1. Correlations were found between the concentrations of Ag Cd, Cu and Pb, and also between Ag concentrations and distance to Pb mines and deposits (r = 0.62). This suggests a common origin for Ag and Pb linked to historical exploitations of argentiferous galena. No link could be demonstrated between the concentration of Ag and the high density of anti-hail ground generators in the region. The analysis of the (auto-)variograms showed that Pb is the most relevant variable compared to Cd and Cu to achieve a cokriging. Thus, based on Ag concentrations from RMQS2 and Pb concentrations from RMQS1 (356 samples), a linear co-regionalization model was established and the co-kriging of Ag concentrations in soils calculated. Compared to ordinary kriging, cokriging improved the quality of the interpolation (decrease in the root mean square error).

Micro pore analysis of suffusion in filter layer using tri-layer CFD–DEM model

Filter layers are extensively employed in dam structures as a mitigation method against internal erosion, which facilitates the interlocking and clogging of the suffused base soil due to its void geometry reduction. A series of tri-layer CFD–DEM models is established considering eight mono- and poly-dispersed filter materials to study the effect of particle size distribution (PSD) on its retention capability. The suffusion results, including the percentage of eroded mass (PME), soil spatial distribution and the velocity field, are analyzed in comparison of the 3D pore structure based on the maximal inscribed sphere (MIS) method. It is found that in contrast with the stable PME from lower soil, the internal erosion from the upper soil is mitigated to varying degrees with filter media of different PSDs from less than 5% of PME the filter of “seal with no erosion” to 19.8% in that of “large or continuous erosion”. The analysis of Pore-PME correlation links the averaged MIS size with the suffusion results and provides reference for quantifying or estimating the mitigation effect of filter soil medium at a given PSD by evaluating its pore features based on the MIS method.

Assessment of some extractable macro and micro-nutrients along with multivariate analysis of their spatial distribution in soils of Haridwar district of Uttarakhand

An investigation was carried out to analyze the general soil properties and extractable macro- (N, P, K, Ca, Mg, S) and micro-nutrients (Zn, Cu, Fe, Mn, B, Mo) in the soils of Haridwar district and the relationships between general soil properties and soil extractable nutrients. Surface (0-15 cm) soil samples (n=300) were taken from the all six developmental blocks of Haridwar district. The ranges for general properties were: sandy loam to sandy clay loam texture, 5.18-8.31 soil pH and 0.074-0.731 dSm-1 electrical conductivity (EC) (1:2 soil-water suspension) and 1.49-9.84 g kg-1 soil organic carbon content. The amount of alkaline KMnO4 extractable N in these soils ranged from 105.0-290.05 kg ha-1 while Olsen’s or Bray’s extractable P content ranged from 5.88-67.42 kg ha-1. Neutral 1 N ammonium acetate extractable K, Ca and Mg varied from 89.6-548.8 kg ha-1, 1102 - 4359 mg kg-1 soil and 30-1002 mg kg-1 soil, respectively. Calcium chloride (0.15 percent) extractable S ranged from 5.3-29.4 mg kg-1 soil. The contents of DTPA extractable Zn, Cu, Fe, and Mn were 0.13-9.14 mg kg-1 soil, 0.01-1.8 mg kg-1 soil, 1.26-61.77 mg kg-1 soil and 0.66-41.87 mg kg-1 soil, respectively. Hot water-soluble B ranged from 0.31-1.19 mg kg-1 soil and ammonium oxalate (pH 3.3) extractable Mo varied from 0.25-1.59 mg kg-1 soil. The nutrient index (N.I.) computed for different extractable soil nutrients for the entire district of Haridwar showed that the overall the district was low in N, medium in K S, Zn and high in all other nutrients (P, Ca, Mg, Cu, Fe, Mn, B and Mo).