Soil Input Research Articles

Response of Bacterial Communities upon Application of Different Innovative Organic Fertilizers in a Greenhouse Experiment Using Low-Nutrient Soil Cultivated with Cynodon dactylon

Assessing the response of microbial communities to nutrient inputs in man-managed soils is of primary importance to understand the impact on ecosystem services provided by the soil microbiome. In this study, a low-nutrient soil was supplemented with seven different innovative fertilizers including matrixes of plant, animal, fungal or synthetic origin, and dosed to deliver the same amount of nitrogen. Growth of a potted grass crop (Cynodon dactylon) was recorded and the fertilizers were scored by the plant yield obtained in a greenhouse study. Soil was sampled at 9 and 58 days after the addition and bacterial community composition was analyzed after soil DNA extraction through pyrosequencing of 16S rDNA gene amplicons. Over 900 bacterial genera were detected, belonging to 21 described and 19 candidate phyla. In spite of the equal dose of nitrogen delivered, specific groups were fostered by given fertilizers; in particular marked effects on some phyla were displayed by a yeast-based fertilizer, which was also most effective in plant productivity. The main shifts were observed shortly after the fertilizer application, followed by a gradual stabilization of the equilibrium and by a rise in community evenness.

Efficiency of microbially assisted phytoremediation of heavy-metal contaminated soils

Phytoremediation is the bioremediation of contaminated soils and waters by using plants and their associated microorganisms. Phytoremediation of heavy metal (HM)-contaminated soils is based on immobilization of metals in rhizosphere soil and roots (phytostabilization) and on mobilization, uptake, and transfer of metals into the aboveground plant organs (phytoextraction). In this review, we aimed to (i) discuss the fundamentals, potential, and limitations of plant-associated microorganisms (bacteria and fungi) to increase the efficiency of phytostabilization and phytoextraction of HM-contaminated soils and (ii) describe promising developments and future challenges to expanding their use. Controlled inoculations of plants with growth-promoting microorganisms can significantly increase their root growth, biomass production, and stress tolerance in HM-contaminated soils. A serious weakness of phytoremediation in general is the usually high and difficult to measure expenditure of time for successful completion. The bioconcentration factors (BCFs) and the translocation factors (TFs) are among the most important measures of the efficiency of phytoremediation. However, an overview of BCFs and TFs for a variety of combinations of plants with defined associated microorganisms is lacking. Moreover, the joint evaluation of model systems would allow an improved cost–benefit calculation of microbial inoculations in phytoremediation systems. For this purpose, the use of in vitro model systems is considered to be preferable to field experiments due to the savings in time and costs and the control of environmental conditions. However, the transferability of in vitro data to field conditions is limited. Currently, attention is focused on the use of artificial neural networks, mainly to avoid formulating any complex relationships between soil inputs (e.g., soil amendments, pH, carbon, nitrogen and hydrogen contents, electrical conductivity, and dissolved organic carbon) and design outputs (e.g., BCFs and TFs) beforehand and because of the high accuracy of the obtained models. The controlled use of associated microorganisms to increase the efficiency of phytoremediation of HM, mainly using combinations of Brassica and Salix spp. and rhizobacteria at contaminated soils, is a promising possibility. A crucial future challenge for the expansion of their use will be to develop well-defined cost- and time-efficient tools for a credible prediction of their effectiveness on contaminated field sites.

Prediction of N2O emissions under different field management practices and climate conditions

Due to the contributions of nitrous oxide (N2O) to global climate change and stratospheric ozone destruction, it is important to understand how climate and agricultural management affect N2O emissions. Although the process-based Denitrification Decomposition (DNDC) model is often used for quantifying emissions of N2O, the accuracy of these predictions remains in question, and it is not clear which input variables, environmental or field management, have the greatest effect on model performance. In this study, DNDC was evaluated for prediction of N2O fluxes from two climatically-different corn-field sites in the United States (a Colorado irrigated field and a Minnesota rainfed field). Besides climate, these sites offer the additional advantage that measurements are available for multiple field management practices, including fertilizer application, tillage, and crop rotation. This evaluation found that DNDC did not consistently, correctly predict daily-scale N2O fluxes. Cumulative growing season N2O fluxes were significantly under-predicted in Colorado and were both under- and over-predicted in Minnesota. Model calibration of four soil input parameters did not significantly improve N2O emission predictions at either site or time scale. Modeled and measured N2O fluxes and model error were all strongly correlated with precipitation. Over-predictions of N2O fluxes were associated with heavy precipitation and high modeled denitrification. Based on our results, model improvements to decrease model error for corn cropping systems in temperate climate zones should focus on better accounting for the effects of precipitation on denitrification. Despite discrepancies in daily and cumulative growing season N2O fluxes, DNDC correctly identified the only field management (fertilizer application rate) that significantly influenced the measured N2O fluxes.

Carbon dynamics in surface and deep soil in response to increasing litter addition rates in an agro-ecosystem

Increasing atmospheric CO2 concentration and nitrogen deposition are predicted to increase fresh carbon (C) inputs in soils because of higher net primary productivity. However, relationship between soil C cycling and increased inputs of fresh C in soils is not clear. Moreover, most of the studies on soil organic carbon (SOC) focus on upper 20 cm although >50% SOC is present below this depth. We designed this study to unravel the response of SOC to 0% (control), 0.3%, 0.6%, 1.2% and 2.4% addition of maize litter (C4) to a surface (0–15 cm) and deep layers (55–75 cm) of a C3 soil. The isotopic difference between the maize litter and soil allowed distinguishing soil-derived (native) CO2-C from litter-derived CO2-C and calculating the priming effect (PE). Total respiration was measured over 78 d incubation whereas the PE was determined 39 d and 78 d after incubation. Our results showed that all the litter addition levels induced PE -stimulation of mineralization of the extant SOC in response to availability of fresh organic matter (FOM)- in surface and deep soil layers. Moreover, the PE was significantly higher in the deep than surface soil layer in response to all litter additions, except 2.4% treatment during the 2nd harvest. This result suggests that the deep SOC would mineralize at higher rates under similar supply of FOM to surface and deep soils in this agroecosystem. We also showed a significantly positive linear relationship between PE and litter addition rates for both soils implying continuous loss of SOC under increasing organic matter inputs. In conclusion, our study reveals that the deep soil C would be more vulnerable to priming effect in response to litter addition than the surface soil.

Hazard-dependent soil factors for site-specific elastic acceleration response spectra of Italian and European seismic building codes

To define the seismic input in non-liquefiable soils, current seismic standards give the possibility to treat local site effects using a simplified approach. This method is generally based on the introduction of an appropriate number of soil categories with associated soil factors that allow modifying the shape of the elastic acceleration response spectrum computed at rocky (i.e. stiff) sites. Although this approach is highly debated among researchers, it is extensively used in practice due to its easiness. As a matter of fact, for standard projects, this method represents the driving approach for the definition of the seismic input. Nevertheless, recent empirical and numerical studies have risen doubts about the reliability and safety of the simplified approach in view of the tendency of the current soil factors of Italian and European building codes to underestimate the acceleration at the free surface of the soil deposit. On the other hand, for certain soil classes, the current soil factors seem to overestimate ground amplification. Furthermore, the occurrence of soil nonlinearity, whose magnitude is linked to both soil type and level of seismic intensity, highlights the fallacy of using constant soil factors for sites with a different seismic hazard. The objective of this article is to propose a methodology for the definition of hazard-dependent soil factors and simultaneously quantify the reliability of the coefficients specified in the current versions of Eurocode 8 (CEN 2005) and Italian Building Code (NTC8 2008 and revision NTC18 2018). One of the most important outcome of this study is the quantification of the relevance of soil nonlinearity through the definition of empirical relationships between soil factors and peak ground acceleration at outcropping rock sites with flat topological surface (reference condition).

Correction to: Phosphorus addition enhances gross microbial N cycling in phosphorus-poor soils: a 15N study from two long-term fertilization experiments

The tight coupling between nitrogen (N) and phosphorus (P) suggests that P availability may affect soil microbial N dynamics in terrestrial ecosystems. However, how P addition affects the internal N transformations in P-deficient agricultural soil remains poorly understood. We hypothesized that an increase in gross microbial N rates in P-deficient soil should occur after long-term P inputs in agricultural soils. We thus conducted a 15N pool dilution experiment to quantify the gross microbial N transformation rates after long-term mineral fertilizer applications in an upland fluvo-aquic soil (from Fengqiu with pH 8.55) and upland red soil (from Qiyang with pH 5.49) in China. We found that P addition significantly enhanced the gross N mineralization and immobilization rates when N and K were also applied, probably due to the increased soil total C and N concentrations at both soils. Also, gross nitrification rate was stimulated by P addition, perhaps because of enhanced gross N mineralization rates and associated NH4+ substrate availability. Our results showed that long-term P addition may stimulate soil gross N dynamics and hence increase overall N availability for crops in P-deficient agricultural soils.

Effects of N fertilization and maize straw on the transformation and fate of labeled (15NH4)2SO4 among three continuous crop cultivations

The transformation and fate of fertilizer N applied to soil is particularly important for increasing N retention in soil-crop systems and minimizing N loss from agroecosystems. However, it is obscure how the transformation and fate of fertilizer N will be affected by N input rates and crop residue amendment. In present study, an outdoor experiment was conducted in Mollisols of Northeast China throughout three crop cultivations using 15N-labeled tracer techniques to evaluate the effects of N fertilization levels and maize straw application on the conversion of applied fertilizer N to newly synthesized organic N, recently fixed NH4+, and mineral N in soil-crop systems. Generally, six treatments were set up: no N fertilization (CK), application of only maize straw (M, 16.49 mg N kg−1 soil), low N input levels (N1, 44.64 mg N kg−1 soil), N1 plus maize straw (N1+M, 61.13 mg N kg−1 soil), high N input levels (N2, 89.28 mg N kg−1 soil), and N2 plus maize straw (N2+M, 105.77 mg N kg−1 soil). The results showed that the majority of applied fertilizer N was rapidly transformed into newly synthesized organic N, followed by recently fixed NH4+. Compared with the N1 and/or N2 treatments, maize straw amendment in the N1+M and N2+M treatments significantly increased the residual amount of applied fertilizer N in soil by accelerating the conversion of fertilizer N to newly synthesized organic N or recently fixed NH4+. Among three crop cultivations, the percentages of recovery of applied fertilizer N in crops (PR-Ncrop) and in soil (PR-Nsoil) were averagely 61.1% and 15.8%, respectively, while the percentage of N loss (PL-N) was 23.1%. Applying maize straw significantly elevated the PR-Ncrop and PR-Nsoil but decreased the PL-N compared to those without maize straw. These results suggested that the application of maize straw with high C/N ratio is important to retain applied fertilizer N in soil-crop systems. Balancing carbon and nitrogen inputs in soil through proper combination of fertilizer N and maize straw will be a potentially practical management to increase fertilizer N recovery in crop and soil, and therefore reduce fertilizer N loss from crop-soil systems.

Use of inverse modelling and Bayesian optimization for investigating the effect of biochar on soil hydrological properties

Physical properties of biochar such as small particle size and high porosity can modify soil properties and help to improve soil water dynamics. However, there has been no consistent long-term measurements of change in soil physical properties due to biochar application under real field conditions. In this study, we use a unique dataset of soil water content measurements in a corn-soybean cropping system (with biochar and no-biochar) for two years. Soil water content was measured every 30 min at 4 different depths and with 3 replications in corn plots. The effect of biochar was expected to be the difference between the physical soil properties of the two treatments. The APSIM model, a process-oriented crop model, was employed in order to find the physical properties of biochar and no-biochar treatments by using inverse modeling. First, a global sensitivity analysis was carried out to find the most sensitive inputs for the APSIM model for soil water simulation. Then the Metropolis-Hasting algorithm was used to inversely estimate the APSIM soil input properties using the soil moisture measurements. Results of the sensitivity analysis showed that the drainage upper limit (DUL) was the most sensitive soil property followed by saturated hydraulic conductivity (KS), saturated water content (SAT), maximum rate of plant water uptake (KL), maximum depth of surface storage (MAXPOND), lower limit volumetric water content (LL15) and lower limit for plant water uptake (LL). The difference between the posterior distributions (with and without biochar) showed an increase in DUL by approximately 10%. No considerable change was noted in LL15, MAXPOND and KS whereas SAT and LL showed a slight increase and decrease in biochar treatment respectively compared to no-biochar.

Distinguishing the Compositions and Sources of the Chromophoric Dissolved Organic Matter in a Typical Karst River During the Dry Season: A Case Study in Bitan River, Jinfo Mountain

Since resistant dissolved organic matter (RDOM) plays a critically important role in a karst carbon sink, one of the most important continental carbon sinks, research focusing on the origination, transportation, and translation of RDOM in a karst water system is important. Currently, 3D-fluorescence EEMs are used to detect the composition and origination of chromophoric dissolved organic matter (CDOM), an important part of RDOM. This is a very fast and efficient method for CDOM analysis. In this study, 3D-fluorencence EEMs combined with UV-visible absorption spectrum were used to analyze the composition and origination of CDOM in the Bitan River at Jinfo Mountain. Samples were collected from nine sampling sites from January to March 2017 and analyzed with CDOM EEMs and UV-visible absorption spectrums. In addition hydrochemical characteristics were determined and then samples were stimulated with PARAFAC to detect the chromophoric fluorescent groups and indexes. The PARAFAC stimulation revealed three chromophoric fluorescent groups in which fulvic acid was the largest component, accounting for about 44%, with a humic acid content of about 32% and tyrosine-like acid content of about 24%. Four indexes: FI, BIX, HIX, and β∶α, were calculated, and the mean values were 2.06, 0.87, 4.35 and 0.69, which showed relatively high FI, BIX, and β∶α values and a low HIX value, implying that the CDOM was autochthonous and originated from microbes and aquatic plants in the dry season. The spatial dynamic of the index revealed an increased BIX and decreased HIX from the upstream area to the downstream area, implying the impact of land-use and human activities. The forest soil input more humic acid and agriculture input more N and P resulting in flourishing aquatic plants and microbes. Moreover, the correlation coefficients of DIC and humic acid, tyrosine-like acid were 0.515 (P<0.05) and 0.644 (P<0.01), from which it could be inferred that DIC contributed to CDOM formation. The conclusions of this study revealed that DIC would be fixed by karst water aquatic plants and microbes and then sink as autochthonous CDOM and become part of karst water carbon sink.

Effects of Input Data Content on the Uncertainty of Simulating Water Resources

The widely used, partly-deterministic Soil and Water Assessment Tool (SWAT) requires a large amount of spatial input data, such as a digital elevation model (DEM), land use, and soil maps. Modelers make an effort to apply the most specific data possible for the study area to reflect the heterogeneous characteristics of landscapes. Regional data, especially with fine resolution, is often preferred. However, such data is not always available and can be computationally demanding. Despite being coarser, global data are usually free and available to the public. Previous studies revealed the importance for single investigations of different input maps. However, it remains unknown whether higher-resolution data can lead to reliable results. This study investigates how global and regional input datasets affect parameter uncertainty when estimating river discharges. We analyze eight different setups for the SWAT model for a catchment in Luxembourg, combining different land-use, elevation, and soil input data. The Metropolis–Hasting Markov Chain Monte Carlo (MCMC) algorithm is used to infer posterior model parameter uncertainty. We conclude that our higher resolved DEM improves the general model performance in reproducing low flows by 10%. The less detailed soil-map improved the fit of low flows by 25%. In addition, more detailed land-use maps reduce the bias of the model discharge simulations by 50%. Also, despite presenting similar parameter uncertainty (P-factor ranging from 0.34 to 0.41 and R-factor from 0.41 to 0.45) for all setups, the results show a disparate parameter posterior distribution. This indicates that no assessment of all sources of uncertainty simultaneously is compensated by the fitted parameter values. We conclude that our result can give some guidance for future SWAT applications in the selection of the degree of detail for input data.

Pressurised Dewatering of Sugarcane Press Mud for Logistical Transport Efficiency and Industrial Reuse

Press mud, a by-product from sugar milling, has agronomic soil input value, but its transport distance from the mill site is limited by its high moisture content (75–80%). This results in over-application close to the mill, concentrating nutrient sources from a wider harvest region, and has potential for environmental harm. Moisture reduction methods have traditionally focussed on centrifuge techniques, but pressurised systems have been shown to have benefit in other waste industries. This work investigates a press-based system for the dewatering of press mud with sequential loading. Subsequently, the solid and filtrate components were assessed for agricultural land application value, with the solid further assessed for livestock feed value. The observed weight reduction was between 20 and 50%, which increased the viability of land application. Results suggest a combination of mill by-products (PM, ash and bagacillo) could result in a product that is more suitable for dewatering. The separated solids had potential for both land application and livestock feed, while the filtrate nutrient value was observed as low.

Nutrient input in litters and soil of Bambusa vulgaris stands in a secondary rainforest, Ile-Ife, Nigeria

Nutrient input in litters and soil of Bambusa vulgaris stands in a secondary rainforest, Ile-Ife, Nigeria

Analysis of metal(loid)s contamination and their continuous input in soils around a zinc smelter: Development of methodology and a case study in South Korea

Soil contamination due to atmospheric deposition of metals originating from smelters is a global environmental problem. A common problem associated with this contamination is the discrimination between anthropic and natural contributions to soil metal concentrations: In this context, we investigated the characteristics of soil contamination in the surrounding area of a world class smelter. We attempted to combine several approaches in order to identify sources of metals in soils and to examine contamination characteristics, such as pollution level, range, and spatial distribution. Soil samples were collected at 100 sites during a field survey and total concentrations of As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, and Zn were analyzed. We conducted a multivariate statistical analysis, and also examined the spatial distribution by 1) identifying the horizontal variation of metals according to particular wind directions and distance from the smelter and 2) drawing a distribution map by means of a GIS tool. As, Cd, Cu, Hg, Pb, and Zn in the soil were found to originate from smelter emissions, and As also originated from other sources such as abandoned mines and waste landfill. Among anthropogenic metals, the horizontal distribution of Cd, Hg, Pb, and Zn according to the downwind direction and distance from the smelter showed a typical feature of atmospheric deposition (regression model: y = y0 + αe−βx). Lithogenic Fe was used as an indicator, and it revealed the continuous input and accumulation of these four elements in the surrounding soils. Our approach was effective in clearly identifying the sources of metals and analyzing their contamination characteristics. We believe this study will provide useful information to future studies on soil pollution by metals around smelters.

Evaluation of Contamination and the Ecological Risk of the Heavy Metals in the Farmland Soil Influenced around an Uranium Mine in Southwest China

The farmland surface soils effected by uranium tailing were sampled, and the contents of 238U, 232Th, 226Ra, Cu, As, Cd, Pb and Zn in the samples were analyzed. The Index of Geoaccumulation and the Potential Ecological Risk Index were employed to evaluate the pollution degree of heavy metals in the soil. The results showed the content of Cd, As, Pb, 238U and 226Ra in the farmland soil exceeded background value. The Index of Geoaccumulation indicated the main polluted factor influencing farmland soil was 226Ra (highly contaminated), the next was 238U and Cd (uncontaminated-moderate contaminated). The potential ecological risk intensity caused by Cu, Zn, Pb and As are all low, and by Cd was moderate contaminated. The potential ecological risk level of integrated heavy metals was low in the study area, and Cd was the main factor. However, the potential ecological risk assessment did not take into account the effects of radionuclide 238U, 232Th, 226Ra, so that and the results of the potential ecological risk were less than that of actual. The metals input in farmland soil are possibly caused by uranium tailings loss and their seepage.

Key functional soil types explain data aggregation effects on simulated yield, soil carbon, drainage and nitrogen leaching at a regional scale

The effects of aggregating soil data (DAE) by areal majority of soil mapping units was explored for regional simulations with the soil-vegetation model CoupModel for a region in Germany (North Rhine-Westphalia). DAE were analysed for wheat yield, drainage, soil carbon mineralisation and nitrogen leaching below the root zone. DAE were higher for soil C mineralization and N leaching than for yield and drainage and were strongly related to the presence of specific soils within the study region. These soil types were associated to extreme simulated output variables compared to the mean variable in the region. The spatial aggregation of these key functional soils within sub-regions additionally influenced the DAE. A spatial analysis of their spatial pattern (i.e. their presence/absence, coverage and aggregation) can help in defining the appropriate grid resolution that would minimize the error caused by aggregating soil input data in regional simulations.

Spatial-Temporal Sediment Hydrodynamics and Nutrient Loads in Nyanza Gulf, Characterizing Variation in Water Quality

Accelerated aging and eutrophication of water resources is a world menace attributed to influx of nutrient rich sediment from its catchment, resulting in poor water quality and shifts in ecological dynamism. Nyanza Gulf is a paramount source of livelihood, portable water, and of service to the rich biodiversity making it indispensable to the entire Lake Victoria watershed ecosystem. This water resource has been deteriorating over the past decades as a consequent of anthropogenic socio-economical activities. This has effectuated an increase in phytoplankton and hydrophyte colonies. The objective of this study was to track the quality and quantity of sediment inundation into the gulf considering the catchment micro-basins processes and influence of human socio-economical activities. Using Quantum Geographic Information System (QGIS) as an interface to Soil and Water Assessment Tool (SWAT) with input of satellite digital elevation model (DEM), local rainfall, soil and land use data sets were utilized to determine the daily variability in sediment and nutrient loads from five major river basins. The SWAT model was successfully calibrated, and the performance validated with observed hydrological and water quality data. The model achieved identification of seasonal water quality budget filling in knowledge gaps about the catchment. River Nyando, Sondu-Miriu, Awach-Kibuon, Awach-Tende and Kibos discharge sediment loads of 3.91, 1.6, 1.18, 1.06 and 0.78 tons/ha respectively. Total suspended solids (TSS) concentration of up to 578mg/L on average daily is discharged by River Awach-Kibuon. This was associated with intense agricultural activities (>54% of the entire basin) on steep slopes (average 12.97) with Acrisols (15%of the basin) soils that is prone erosion. Poorly managed range-bush land that covers about 10% of this basin also contribute significantly to the TSS yield. River Kibos discharge least TSS concentration of 144.43 mg/L in comparison with other rivers mainly due gentle slope falling into a plain, low erodible Cambisols (covers 20% of the basin) and Ferralsols (10%) as well as Nanga forest effect at its exit. River Awach-Tende and Awach-Kibuon on average discharge 1.67 mg/L and 1.58 mg/L respectively of Total Nitrogen (TN) daily. This was linked to intensive farming on poorly managed dominant Phaeozems and Acrisols that are susceptible to leaching. River Sondu-Miriu is the least contributor with a daily average of 1.1101 mg/L dominated with low leached Nitisols. The bay receives highest Total Phosphorus (TP) loads from River Nyando with daily average of 0.3699 mg/L alluded to high biomass production in the basin and Sondu-Miriu least with 0.0288 mg/L. The fluctuation of nutrients and sediment fluxes correlated positively with rainfall events. The long rainfall season with average regular storm events in March to June yield highest monthly loads as compared to short rainfall season (September to November) with isolated intense storm events over a shorter time. The study depicted poor water quality discharged into the gulf throughout the year by the 5 major basins to be above average of conventional ecological healthy basins.

Global sensitivity and uncertainty analyses of a web based crop simulation model (web InfoCrop wheat) for soil parameters

Sensitivity and uncertainty analyses are critical for identifying the most sensitive parameters of the crop simulation models. These analyses will help the users to concentrate more on calibrating those sensitive parameters. The soil parameters are important input parameters as the soils regulate the supply of nutrients and water required for the growth and yield of crops. The aim of this investigation is to perform the sensitivity and uncertainty analyses of the soil parameter inputs of the Web InfoCrop Wheat model, especially under the water deficit- and high temperature stress conditions for different agro-climatic conditions of India. Sensitivities of soil input parameters (15) were analysed by crop simulations under the no stress (potential), water deficit- (limited irrigation), high temperature- (+3 °C above ambient), and their combined stress conditions for a period of 10 years across four sites in the wheat-growing regions of India. The partial rank correlation coefficients (PRCC) were computed, followed by the top-down concordance coefficients. Amongst the soil input parameters (15) and outputs (10) considered, the nutrient parameters such as NITRATE, ORG_CARB (Organic carbon), AMMONIUM were the most sensitive input parameters under the no stress (potential) and high temperature stress conditions. On the contrary, the parameters related to the soil moisture such as CLAY (Clay %), FLD_CAP (Field capacity), SATU (Saturation) and MOISTURE (initial soil moisture contents) were the most sensitive input parameters under water deficit stress conditions. Both the sensitivities and uncertainty of soil parameters under different crop production and environmental conditions influenced the outputs of the Web InfoCrop model significantly. Identification of the most sensitive soil parameters that need to be measured accurately improved the simulation efficiencies of this crop model.

REY‐Th‐U Solute Dynamics in the Critical Zone: Combined Influence of Chemical Weathering, Atmospheric Deposit Leaching, and Vegetation Cycling (Mule Hole Watershed, South India)

AbstractThe source and proportion of REY, Th, and U exported by groundwater and by the ephemeral stream along with the elemental proportions passing through vegetation have been assessed in the subhumid tropical forested CZO of Mule Hole, Southern India. The study relies on a pluriannual hydrogeochemical monitoring combined with a hydrological model. The significant difference between the soil input (SI) and output (SO) solute fluxes (mmol/km2/yr) of LREE (SI‐SO = 13,250‐1,500), HREE (1,930‐235), Th (64‐12), and U (63‐25) indicates a strong uptake by roots carried by canopy and forest floor processes. The contribution of atmospheric dust leaching can reach about 60% of LREE and 80% of HREE. At the watershed scale, the U solute flux exported by groundwater (180 mmol/km2/yr) mainly originates from the breakdown of primary U‐bearing accessory minerals and dominates by a factor of 25 the stream flux. The precipitation of authigenic U‐bearing phases and adsorption onto Fe‐oxides and oxyhydroxides play a significant role for limiting the U mobility. In the groundwater, the plagioclase chemical weathering is efficiently traced by the positive Eu‐anomaly. The very low (REY) to nil (Th) contents are explained by the precipitation of authigenic phases. In the stream flow, dominated by the overland flow (87% of the yearly stream flow), the solute exports (in mmol/km2/yr) of REY (1,080 for LREE and 160 for HREE) and of Th (14) dominate those by groundwater. Their mobility is enhanced by chelation with organic ligands produced by forest floor and canopy processes.

Evaluation of the wall deflections of a deep excavation in Central Jakarta using three-dimensional modeling

This paper presents a case study and numerical simulations regarding a large-scale deep excavation in Central Jakarta, Indonesia, and its three-dimensional (3D) effects on wall deformation. The soil profile in Central Jakarta is generally soft to firm alluvial clay overlying stiff to hard alluvial and diluvial clay. In this study, the geotechnical engineering properties of soil (i.e., undrained shear strength and modulus) were established using data from a site investigation, in situ and laboratory tests, and empirical correlations with standard penetration numbers (SPT-N). A summary of simplified soil input properties for subsurface soil in Central Jakarta was provided. To analyze the deep excavation case, a 3D finite element model was developed by considering a top-down construction method, a supporting system of concrete slabs, and the influence of the soil modulus. The numerical results indicated that the hardening soil model with the soil modulus obtained from in situ pressuremeter tests yields reasonable predictions for excavation-induced wall deformation. The applicability of 3D finite element analyses to capturing the 3D corner effect on the wall deformation was validated. According to the parametric study, the plane strain ratio (PSR) was determined for the excavations in Jakarta clay. Compared with the PSR developed for Taipei clay, this study revealed that the PSR value was influenced not only by the 3D corner effect but also by the stiffness of the subsurface soil. In addition to PSR, the wall deflection path was also affected by the 3D corner effect and soil modulus.

Application of the DIDAS program for the design and scheduling of drip irrigation

The DIDAS software package assists in drip-irrigation system design and irrigation scheduling. It is based on analytical solutions of the linearized water flow equation. The problem of water flow and uptake is described by superposing solutions for positive sources (on-surface or subsurface emitters) and negative sinks (root systems). Steady water flow is assumed in the design module and unsteady flow in the irrigation-scheduling module. The design tool, based on the relative water-uptake rate (RWUR) criterion, assesses the effects on water-use efficiency of geometrical attributes: distances between emitters along drip lines, separation between drip lines, depth of subsurface emitters, and size and depth of root systems. For design purposes, it is assumed that there is no plant-atmosphere resistance to water uptake, i.e., roots are assumed to apply maximum suction and water-uptake rate depends only on the soil's ability to conduct water from sources to sinks. The RWUR computations require only three parameters describing soil texture, root-zone size, and potential evaporation. The optimizing tool for irrigation scheduling is based on a relative water-uptake volume (RWUV) criterion. The RWUV computations for a given drip-irrigation design require additional information on the diurnal pattern of plant resistance to water uptake and soil hydraulic conductivity. DIDAS also contains a diurnal pattern module to evaluate diurnal water-uptake patterns; it assumes quasi-steady flow, accounts for diurnal variations in plant-atmosphere resistance and evaporation, and serves for fine-tuning the design and in preliminary evaluation of scheduling scenarios. DIDAS was programmed in Delphi, runs on a PC under the Windows operating system, and requires no further software. The drip-irrigation scenario is constructed via a few GUI windows, which also contain a library of the required soil input parameters, and a best-fitting procedure to determine them. The computed RWURs and RWUVs are displayed graphically and the tabulated output results can be exported to, e.g., Microsoft Excel for further processing. An updated DIDAS version can be downloaded freely from http://app.agri.gov.il/didas. From March 2014 through July 2016, 877 people from 94 countries downloaded the first or second DIDAS versions (1.0.1 and 1.1.1, respectively). We briefly introduce drip irrigation and other available programs for its design and scheduling, outline the major DIDAS concepts, and illustrate the operation of the main software modules.