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The filter paper (FP) method, a cost-effective, versatile, and convenient approach, has found extensive application in analyzing fine-grained soils, enabling the successful measurement of a broad spectrum of total and matric suctions. However, using the FP method in sand with a limited range of suction profiles has been notably underrepresented in the existing literature. Therefore, this study investigated the applicability of the contact FP method in establishing soil water retention curves (SWRCs) using five distinct FP calibration curves for 10 poorly graded sands. Among these calibration curves, the one presented by Chandler yielded the highest suction values, which were followed by those of ASTM. Furthermore, the FP results were subjected to fitting with a mathmatical model, which led to the observation that the overall trends in the obtained SWRCs displayed smooth sigmoidal shapes, resulting in a complete and coherent SWRCs. The SWRC results of five sand samples were assessed through validation against the hanging column technique (HCT) results, indicating a high degree of concordance and affirming the suitability of the FP method for sands characterized by a limited suction profile. Notably, the entire range of suction values fell within the 0.01–20 kPa range based on the calibration curves presented by Chandler and ASTM for all the examined sand samples, except sands 9 and 10. Furthermore, the suction values were unobtainable using the two aforementioned calibration curves within the ranges of 0.01–1.47 kPa and 0.01–0.172 kPa. [ABSTRACT FROM AUTHOR]

A positive effect of pulp and paper mill sludges as a rich source of organic substrates on soil properties was previously found for some types of sludge and soil. In this study, the effect of secondary pulp and paper sludge on water characteristics and thermal properties of Retisol, as well as the growth parameters of lettuce (Lactuca sativa L.), was tested on the basis of a pot experiment when watering plants with a 20 or 40% sludge solution. The sludge application enhanced plant growth with an increase in biomass accumulation of 21 and 53%, respectively, for 20 and 40% sludge treatments. When the sludge dose was increased from 0 to 40%, the number of leaves increased by 25%, and the leaf mass per area value increased by 42%. Due to the accumulation of more biomass in the shoots than in the roots, sludge causes a change in the allocation of plant biomass. A significant effect of the sludge application on soil particle and microaggregate sized compositions, as well as on the saturated soil hydraulic conductivity, was not found in this study. However, fitted soil water retention curves showed an increased soil water content in sludge-treated soil at all water content values exceeding field capacity. Secondary sludge application led to an increase in the saturated water content from 0.50 to 0.56 cm3 cm−3. The 40% sludge solution increased soil thermal conductivity from 0.92 to 0.98 W m−1 K−1 under saturated water content and from 0.83 to 0.92 W m−1 K−1 under field capacity. The thermal conductivity was higher in the sludge-treated than untreated soil due to a more pronounced positive effect of increased saturated water content than the negative effect of the increased organic matter content on heat transfer. The positive impact of secondary sludge application on both plant growth parameters and physical properties of Retisol, such as increased soil water-holding capacity and thermal conductivity coefficient confirms the possibility of using it to improve soil characteristics and plant productivity. [ABSTRACT FROM AUTHOR]

Mulch has been considered effective for saving water and promoting plant growth. However, little has been investigated about the effect of mulch from recycled shredded paper under different soil moisture conditions on spinach growth. A pot-grown Komatsuna spinach experiment with a factorial design was conducted under two main conditions, with and without shredded paper mulch. Each of these conditions was treated with three different soil moisture levels (SWC) 20%, 25%, and 30%. The smallest evapotranspiration amount was in the mulch-only, no-plant treatment with SWC 20% (92.88 mm), and the largest was in the plant-only, no-mulch treatment (226.19 mm). All biomass yield attributions were negatively influenced by increasing the frequency of irrigation and SWC levels. SWC 20% with shredded mulch resulted in the largest dry matter, although it was statistically non-significant. But it resulted in taller plant heights and a larger leaf area index (LAI) compared to soil with no shredded mulch (p < 0.05). For SWC 25% and 30% treatments, Komatsuna spinach with no shredded mulch resulted in slightly superior plant dry matter and plant height, compared to mulched plants. These results suggest that SWC 20% with shredded paper mulch has the highest potential for saving water among all treatments for growing spinach under limited water availability. [ABSTRACT FROM AUTHOR]

This study introduces a simple and cost-effective method for the indirect determination of field capacity (FC) in soil, a critical parameter for soil hydrology and environmental modeling. The relationships between FC and soil moisture constants, specifically maximum capillary water capacity (MCWC) and retention water capacity (RWC), were established using undisturbed soil core samples analyzed via the pressure plate method and the "filter paper draining method". The aim was to reduce the time and costs associated with traditional FC measurement methods, as well as allowing for the use of legacy databases containing MCWC and RWC values. The results revealed the substantial potential of the "filter paper draining method" as a promising approach for indirect FC determination. FC determined as soil water content at −33 kPa can be effectively approximated by the equation FC33 = 1.0802 RWC − 0.0688 (with RMSE = 0.045 cm3/cm3 and R = 0.953). FC determined as soil water content at −5 or −10 kPa can be effectively approximated by both equations FC5 = 1.0146 MCWC − 0.0163 (with RMSE = 0.027 cm3/cm3 and R = 0.961) and FC10 = 1.0152 MCWC − 0.0275 (with RMSE = 0.033 cm3/cm3 and R = 0.958), respectively. Historical pedotransfer functions by Brežný and Váša relating FC to fine particle size fraction were also evaluated for practical application, and according to the results, they cannot be recommended for use. [ABSTRACT FROM AUTHOR]

Numerous recent studies have argued that moisture limitation is leading to growth declines and mortality of black spruce (Picea mariana) and white spruce (Picea glauca) in the North American boreal forest. A parallel line of research suggests that increasingly common severe wildfires are altering successional pathways and leading to long‐term replacement of spruce forests with those dominated by paper birch (Betula papyrifera, Betula neoalaskana) and trembling aspen (Populus tremuloides). When both conifers and deciduous trees establish after fire, this biome shift hypothesis implicitly assumes that deciduous species will outcompete the conifers, owing to their more rapid vertical growth and because they might be less sensitive to warm and dry conditions.We established a research site in a white spruce‐paper birch forest on an east‐facing slope in interior Alaska and tested the hypothesis that Alaska paper birch are better adapted to warm and dry conditions than white spruce. Over 6 years (2013–2018), we made hourly measurements of microclimate and xylem sap flux of both species. We also collected increment cores and conducted climate‐growth analyses for both species.During our 6‐year study, growing seasons with low volumetric soil water content (SWC) were those that followed shallow winter snowpacks and had limited summer rainfall, not necessarily those with warm air temperature. Both species were sensitive to moisture limitation. The tree‐ring data revealed significant positive effects of cumulative water year precipitation on radial growth, with a steeper slope for paper birch than for white spruce. Radial growth of both species was also positively related to mean water year air temperature. Sap flux density declined progressively for white spruce over the range of observed SWC and abruptly for paper birch when SWC fell below ~15%.Synthesis. Our results show that, while paper birch might be less sensitive to mild drought than white spruce, it may be more sensitive to severe drought, raising questions about the ability of paper birch to outcompete co‐occurring white spruce in a drier climate. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Forest & Environment is the property of Journal of Forest & Environment Editorial and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A variety of routine methods are available for the detection of silver (I) (Ag+) ions, but most of them rely on expensive, sophisticated and desktop instruments. Herein, a low-cost, instrument-free and portable Ag+ biosensor was described by initially designing a new class of 3D origami microfluidic paper-based analytical devices (μPADs) into each of which one piece of reagent-loaded nanoporous membrane was integrated. It combines analyte-triggered self-growing of silver nanoparticles to block the membrane's pores in situ for rapid yet efficient signal amplification with a handheld personal glucose meter for a portable and sensitive quantitative readout based on the biocatalytic reactions between the glucose oxidase and glucose. Its utility is well demonstrated with the specific detection of the analyte with a limit of detection as low as ∼58.1 pM (3σ), which makes this new biosensing method one of the most sensitive Ag+ assays in comparison with many other typical methods recently reported. Moreover, the satisfactory recovery of analyzing several types of real water examples, i.e., tap water, drinking water, pond water and soil water, additionally validates its feasibility for practical applications. • A new type of 3D paper-based device is designed for biosensing of picomolar Ag+. • It integrates nanoporous membranes with self-growing for signal amplification. • It only requires a personal glucose meter for a portable, quantitative readout. • This instrument-free biosensor offers new opportunities for point-of-care uses. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Geotechnical Journal is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Infrastructures are mostly built on unsaturated soil in the tropical region such as Nigeria, yet soil investigations and designs are based on saturated soil mechanics owing to difficulties associated with soil suction measurements using direct methods such as pressure plate extractor, triaxial testing equipment for testing unsaturated soil, etc. Soil water characteristic curve is an important parameter for estimating unsaturated soil property function. This research considered an indirect method (filter paper) of laboratory soil suction measurement (which is relatively simple, fast and inexpensive) and predictive correlation equations for estimating soil water characteristic curve from index properties of soil for four unsaturated tropical soils of Nigeria, three predictive correlation equations were used in this research namely; Navid et al model (2012), Zapata et al model (2000) and Witczak model (2006), the soil water characteristic curve constant parameters computed from these models were fitted through either Van Genuchten model (1980) or Fredlund & Xing model (1994). Results of air entry values of soils from experimental work and predictive correlation equations were in close range which indicated that in spite of the difficulties experienced in performing laboratory suction test, the predictive correlation equations such as the ones used in this research were found to be proper for estimating soil water characteristic curve. [ABSTRACT FROM AUTHOR]

Soil water characteristic curve (SWCC) is a very important property of unsaturated soil and by extension tropical red earth soils. This is because several other important soils' properties can be related to it. The Filter paper method was employed in the determination of the A-7-5(5) tropical red earth WCC. The gravimetric water content was utilized in the computation of the SWCC. Four models, Fredlund and Xing (1994), FX; Van Genuchten (1980), VG; Brooks and Corey (1964), BC; and Kosugi (1996), K were used to estimate the SWCCs of the soil and the minimum SSEnorm (MSSE), Average Relative Error (ARE), and R² values were used to determine the most suitable model for predicting the SWCC. Results show that all four models can be used to predict A-7-5(5) WCC as they all had R2 value greater than 89% although BC and K models perform best with coefficient of determination of over 97%. MSSE and ARE% were also significantly low for BC and K models. [ABSTRACT FROM AUTHOR]

Soil reinforcement using synthetic fibers is a proven technique for enhancing engineering properties to meet the requirements of subgrade materials for pavement projects. The safe and economical design of fiber-reinforced pavement layers requires better insights into their unsaturated behavior. The soil–water characteristic curve (SWCC) is a measure of the water content inside soil pores at a given suction and is considered an essential property to better understand or predict the behavior of unsaturated fiber-reinforced soils. This paper centers on investigating the soil–water characteristic curves for typical expansive clay reinforced with two different types of polypropylene fibers having different surface morphological properties. The effect of an increase in the fiber dosage (0.2% and 0.6% by dry weight of soil) and fiber lengths (6 and 12 mm) on the resultant SWCC patterns is investigated. The addition of lime is considered to enhance the bonding between clay particles and fiber elements to ensure better friction mobilization levels. SWCCs were determined for all experimental mixtures using a combination of axis translation and filter paper techniques that cover the entire matric suction range during measurements. Volume changes undergone during suction measurements have been duly highlighted and discussed. Furthermore, the one-dimensional deformation (swelling/consolidation) characteristics of these lime-blended fiber-reinforced mixtures at different levels of initial matric suction are studied, and the correlations between initial matric suction with both compression index (Cc) and swell index (Cs) are established. The results indicate a significant change in the shape of the SWCC for lime-blended fiber-reinforced mixtures compared with the shape of the SWCC for natural clay. The contribution of fiber inclination to altering the shape of the SWCC curve is observed as slight regardless of the type, length, and dosage of fiber. Compression and swell indices for tested mixtures increased proportionately with an increase in initial matric suction levels. Doubling the length of the fiber also induced an increase in the compression index. Under no stress conditions did both fiber type and fiber length have a marginal effect on the swell potential and SWCCs. [ABSTRACT FROM AUTHOR]

In the present scenario, soil mechanics plays a vital role. In the past few decades there is a wide range of exposure to the unsaturated soils as a significant portion of earth is consisting of arid and semi-arid climatic conditions. Unsaturated soils frequently undergo wetting and drying process due to seasonal variations. Due to this process, expansive soil may undergo swelling-shrinkage process. Considering the similarity between wetting-drying and freezing-thawing process, this study was an attempt to analyse the effect of the freezingthawing process on suction behaviour of expansive soil. Suction is the basic and most important parameter which influences the behaviour of soil. Filter Paper method is used to for the study as an economical approach to evaluate suction. For the experimental study, samples were moulded to achieve full compaction (100% of Proctor density) for different degree of saturation. The moulded samples were passed through required number of the freezing-thawing cycles (0, 1, 3, & 5 nos.) and soil-water characteristic curves (SWCC) are formulated for all F-T cycles. [ABSTRACT FROM AUTHOR]

Throughfall (TF) is an important water input of rainfall redistribution into floor, and its spatial-temporal variability under some species' canopies has been documented to evaluate effect on splash erosion. However, the understanding of TF variability under large broad-leaved canopy remains insufficient. In this study, the spatial heterogeneity, temporal stability and drop size of TF were quantified using variogram fitting, normalised ranking and filter paper staining, respectively, under banana (Musa nana Lour.) canopy comprising long and wide leaves. Results indicated TF pattern showed strong spatial correlation at a range of 3-5 m. High spatial variability of TF was found, which was affected by rainfall event size and was accompanied by great canopy disturbance. TF plots revealed high time variability, which was mainly controlled by unstable banana canopy structure. TF drop size from leaf dripping points varied in 3-10 mm and showed significant differences (p,0.05) among five kinds of leaf shapes, implying that concave and broken banana leaves were involved in the variability of TF drop size. Overall, results demonstrate the spatial-temporal variability of TF is dramatically induced by banana canopy with broad leaves, which may result in non-uniform soil water content and splash erosion under the canopy. [ABSTRACT FROM AUTHOR]

Most Penman-Monteith-Leuning (PML) evapotranspiration (ET) modeling studies are dominated by consideration of meteorological, energy, and land use information, etc., but the dynamic coupling of soil moisture content (SM), especially in terms of improving accuracy through assimilation, lacks sufficient attention. This paper proposes a research framework for the dynamic coupling simulation of PML model and SM based on data assimilation, i.e., the remote sensing monitored SM is combined with soil evaporation of PML to obtain high-precision time-continuous SM data through data assimilation; simultaneously, dynamical soil evaporation coefficients are generated based on the assimilated SM to improve the simulation accuracy of the PML model. The new scheme was validated at a typical irrigation zone in north China and showed obvious improvements in both SM and ET simulations. Moreover, the effect of the assimilation of SM on the simulation accuracy of ET for different crop growth periods is further analyzed. This research provides a new idea for the coupling simulation of the SM and PML models. [ABSTRACT FROM AUTHOR]

This work presents a simple and innovative protocol employing a microfluidic paper-based analytical device (µPAD) for equipment-free determination of mercury. In this method, mercury (II) forms an ionic-association complex of tetraiodomercurate (II) ion (HgI42−(aq)) using a known excess amount of iodide. The residual iodide flows by capillary action into a second region of the paper where it is converted to iodine by pre-deposited iodate to liberate I2(g) under acidic condition. Iodine vapor diffuses across the spacer region of the µPAD to form a purple colored of tri-iodide starch complex in a detection zone located in a separate layer of the µPAD. The digital image of the complex is analyzed using ImageJ software. The method has a linear calibration range of 50–350 mg L−1 Hg with the detection limit of 20 mg L−1. The method was successfully applied to the determination of mercury in contaminated soil and water samples which the results agreed well with the ICP-MS method. Three soil samples were highly contaminated with mercury above the acceptable WHO limits (0.05 mg kg−1). To the best of our knowledge, this is the first colorimetric µPAD method that is applicable for soil samples including mercury contaminated soils from gold mining areas. [ABSTRACT FROM AUTHOR]

In the paper of [6], maps of suitability predictions for a handful relevant tree species in 30 × 30 m resolution are presented based on ecograms that are linked with interpolated, modeled soil data (subsoil pH, subsoil texture and derived plant available water to 160 cm). We ignore statistical principles if we accept interpolated tree species suitability predictions based on limited sets of soil properties without verifying them with observed, local site and soil data. Commentary to the paper by Roell, Nord-Larsen et al. 'Mapping tree species ecograms based on soil pH and soil water availability across Denmark'. [Extracted from the article]

Soil hydraulic properties significantly affect the occurrence and development of collapsing gully walls. The effect of temperature on the hydraulic properties of soil in collapsing gully walls remains unclear. In this study, the hydraulic properties of the red soil layer, the sandy soil layer and the detritus layer in a collapsing gully wall were investigated using the filter paper method, and the soil water retention curves of the different soil layers at 25 and 40 °C were determined. The aim of this study was to investigate the impact of temperature on the soil hydraulic properties of different soil layers in collapsing gully walls. The study found that when the water content in the red soil layer and sandy soil layer exceeded 20% and in the detritus layer exceeded 10%, the soil's matric suction significantly decreased as the temperature increased from 25 to 40 °C. Additionally, the parameters of θ s , α , n and m all exhibited a decreasing trend, and the soil water content in the detritus layer was primarily influenced by the temperature change, which resulted in a decrease of 38.10%. The unsaturated hydraulic conductivity of the detritus layer exhibited higher values than that of the sandy layer and red soil layer under identical temperature conditions. Moreover, the unsaturated hydraulic conductivity of the red soil layer, sandy soil layer and detritus layer increased with increasing temperature. It was observed that the unsaturated hydraulic conductivity of the detritus layer increased by 0.18 cm h−1 at a soil water content of 44%. This increase in conductivity was more pronounced than the corresponding changes in the red soil layer and sandy soil layer. An elevated temperature caused the water-holding capacity of the different soil layers of the collapsing gully wall to decrease and the unsaturated hydraulic conductivity to increase. However, the influence of the clay particle content within the soil of the collapsing gully wall rendered the temperature effect more distinct. Therefore, the destabilizing deformation of the soil in the collapsing gully wall during the summer under high temperatures and precipitation may have played a key role in its collapse. [ABSTRACT FROM AUTHOR]

Pollution of air, water, and soil is a pressing global issue with significant implications for environmental and human health. This research paper explores the various methods and technologies employed for the monitoring and remediation of pollutants in these three crucial environmental compartments. It discusses the challenges associated with pollution, the importance of effective monitoring, and the diverse strategies available for pollutant remediation. By synthesizing current research and technologies, this paper aims to provide insights into the state-of-the-art approaches for addressing pollution and promoting environmental sustainability [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) started as a radio echo sounding technology during the second half of the last century, but it is now a well-established and widely adopted technology for producing high-resolution images of subsurface. Novel processing schemes, including full waveform inversion and machine learning, advanced GPR transmission, and elastic wave methods, are among the research topics regarded as fundamental for the future. By taking into account the UWB nature of GPR methodology, as well as the experienced inefficiencies in traditional design solutions, this paper provides a robust ground for evaluating the optimal choice for GPR system design. [Extracted from the article]

Soil moisture (SM) is a key variable driving hydrologic, climatic, and ecological processes. Although it is highly variable, both spatially and temporally, there is limited data availability to inform about SM conditions at adequate spatial and temporal scales over large regions. Satellite SM retrievals, especially L-band microwave remote sensing, has emerged as a feasible solution to offer spatially continuous global-scale SM information. However, the coarse spatial resolution of these L-band microwave SM retrievals poses uncertainties in many regional- and local-scale SM applications which require a high amount of spatial details. Numerous studies have been conducted to develop downscaling algorithms to enhance the spatial resolution of coarse-resolution satellite-derived SM datasets. Machine Learning (ML)-based downscaling models have gained prominence recently due to their ability to capture non-linear, complex relationships between SM and its driving factors, such as vegetation, surface temperature, topography, and climatic conditions. This review paper presents a comprehensive review of the ML-based approaches used in SM downscaling. The usage of classical, ensemble, neural nets, and deep learning methods to downscale SM products and the comparison of multiple algorithms are detailed in this paper. Insights into the significance of surface ancillary variables for model accuracy and the improvements made to ML-based SM downscaling approaches are also discussed. Overall, this paper provides useful insights for future studies on developing reliable, high-spatial-resolution SM datasets using ML-based algorithms. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to reduce the dimensionality of unknown coefficient vectors of finite-element (FE) solutions in two-grid (CN) FE (TGCNFE) format for the nonlinear unsaturated soil water flow problem by using a proper orthogonal decomposition (POD) and to design a new reduced-dimension iteration TGCNFE (RDITGCNFE). For this objective, a new time semi-discrete CN (TSDCN) scheme for the nonlinear unsaturated soil water flow problem is first designed and the existence, stability, and error estimates of TSDCN solutions are demonstrated. Subsequently, a new TGCNFE format for the nonlinear unsaturated soil water flow problem is designed and the existence, unconditional stability, and error estimates of TGCNFE solutions are demonstrated. Next, a new RDITGCNFE format with the same FE basis functions as the TGCNFE format is built by the POD method and the existence, unconditional stability, and error estimates of RDITGCNFE solutions are discussed. Ultimately, the rightness of theory results and the superiority of the RDITGCNFE format are verified by two sets of numerical tests. It is worth noting that the RDITGCNFE format differs completely from all previous reduced-dimension methods, including the authors' previous works. Therefore, the study of this paper can not only provide a new theoretical method for the dimensionality reduction of numerical models for nonlinear problems but also provide an algorithm implementation technology for the numerical simulation of practical engineering problems. [ABSTRACT FROM AUTHOR]

Sensitivity analysis (SA) has been used to evaluate the behavior and quality of environmental models by estimating the contributions of potential uncertainty sources to quantities of interest (QoI) in the model output. Although there is an increasing literature on applying SA in environmental modeling, a pragmatic and specific framework for spatially distributed environmental models (SD-EMs) is lacking and remains a challenge. This article reviews the SA literature for the purposes of providing a step-by-step pragmatic framework to guide SA, with an emphasis on addressing potential uncertainty sources related to spatial datasets and the consequent impact on model predictive uncertainty in SD-EMs. The framework includes: identifying potential uncertainty sources; selecting appropriate SA methods and QoI in prediction according to SA purposes and SD-EM properties; propagating perturbations of the selected potential uncertainty sources by considering the spatial structure; and verifying the SA measures based on post-processing. The proposed framework was applied to a SWAT (Soil and Water Assessment Tool) application to demonstrate the sensitivities of the selected QoI to spatial inputs, including both raster and vector datasets - for example, DEM and meteorological information - and SWAT (sub)model parameters. The framework should benefit SA users not only in environmental modeling areas but in other modeling domains such as those embraced by geographical information system communities. • A pragmatic framework of sensitivity analyses is provided for spatially distributed environmental models. • The framework prescribes sequential steps in which important considerations are highlighted. • The framework benefits users of sensitivity analyses in environmental modeling and GIS communities. [ABSTRACT FROM AUTHOR]

The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño-Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of -0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (-0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (-0.66), with precipitation leading by 4-5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 Pg C yr-1 K-1 and -0.46 ± 0.07 Pg C yr-1 100 mm-1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land-atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 Pg C yr-1 K-1 and -0.67 ± 0.04 Pg C yr-1 100 mm-1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than soil respiration. Because NPP is largely driven by precipitation, this suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such "emergent constraint". [ABSTRACT FROM AUTHOR]

This paper presents a new analytical solution to predict the ultimate depth and holding capacity of plate anchors based on an integrated analysis of the anchor and mooring system. The configuration equations of the mooring line, both in soil and water, have been solved to obtain the complete line profile. A key advancement is that the mooring line angle at mudline varies compatibly with the whole anchor–mooring system. This is different from the solutions available in literature that neglect the mooring line segment in water and only assume a constant mooring line angle at the mudline. The system of equations is solved by using an iteration scheme, and parametric studies are demonstrated. The effects of line length, water depth, and seabed strength profile are explored by demonstrating the performance of a commercial plate anchor. It is found that neglecting the mooring line in water can significantly overestimate the ultimate embedment and capacity, especially when the mooring line length is relatively short. This paper can be used as an engineering tool to predict the ultimate capacity of an anchor–mooring system considering the integrated behavior of the whole system. [ABSTRACT FROM AUTHOR]

Clogging is a major geohazards risk in mechanized tunnelling through cohesive soils. Clay clogging results from the high adhesion between the clay and metal. Based on the water film theory and Reynolds fluid equation, the interfacial adhesion between metal and soil is simplified in this study as viscous hydrodynamic behavior between planes. Considering the influence of capillary force and the viscous force of water film at the interface between metal and soil, a theoretical calculation model of interfacial adhesion between metal and soil is established. The influence of water film thickness and separation rate on the interfacial adhesion between metal and soil is qualitatively analyzed. Then, the adhesion stress between the clay and the metal surface was tested with a pullout test and the influence of moisture content, pullout rates and types of clay minerals on the adhesion stress was analyzed. Finally, the calculation model of adhesion force was compared with the experimental results. The calculation model of soil adhesion stress established in this paper can quantitatively describe the relationship between soil adhesion force and moisture content and can also qualitatively reveal the influence mechanism of soil moisture content on adhesion stress. [ABSTRACT FROM AUTHOR]

This paper focuses on the possible impact of the thermal soil regime on the occurrence of forest fires in the Zaječar administrative district in Eastern Serbia. The study uses data on soil temperature from the Republic Hydrometeorological Service of the Republic of Serbia and the ERA5-Land gridded reanalysis dataset for monthly temperature and volumetric soil water of the soil level 1 (0-7 cm), and soil level 2 (7-28 cm) with horizontal resolution of 0.1°C (approximately 12 km × 12 km) during the period of 2009-2021. Differences in soil temperature at depths of 2 cm, 5 cm, 10 cm, and 20 cm at the meteorological station in Zaječar for the periods 1961-1990 and 2009-2021 are observed. By analyzing the data on the registered number of forest fires for the period 2009-2021, pronounced oscillations in the dynamics of forest fires can be observed. The minimum number of forest fires (0) is registered in 2014, when the maximum of soil moisture in the soil levels 1 and 2 is observed. A high number of forest fires corresponds to high soil temperatures in 2012 and 2017. Soils drier and hotter than the average are registered in 47.0% of all months with the fire occurrences. About 50% of fires occurred in dry and hot soils during 2012 and 2017. This percentage was zero in 2014, when there were no fires. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a vital climate variable in the interaction process between the Earth's atmosphere and land. However, global soil moisture products from various satellite missions and land surface models are affected by inherently discontinuous observations and coarse spatial resolution, which limits their application at fine spatial scales. To address this problem, this paper integrates three diverse types of datasets from in situ, satellites, and models through Spherical cap harmonic analysis (SCHA) and Helmert variance component estimation (HVCE) to produce 1 km of spatio-temporally continuous SM products with high accuracy. First, this paper eliminates the bias between different datasets and in situ sites and resamples the datasets before data fusion. Then, multi-source SM data fusion is performed based on the SCHA and HVCE methods. Finally, this paper evaluates the fused products from three aspects, including the performance of representative sites under different climate types, the overall performance of validation sites, and the comparison with other products. The results show that the fused products have better performance than other SM products. In the representative sites, the minimal correlation coefficient (R) of the fused products is above 0.85, and the largest root mean square error (RMSE) is below 0.040 m3 m−3. For all validation sites, the R and RMSE of the fused products are 0.889 and 0.036 m3 m−3, respectively, while the R for other products is below 0.75 and the RMSE is above 0.06 m3 m−3. In comparison to other SM products, the fused products exhibit superior performance, generally align more closely with in situ measurements, and possess the ability to accurately and finely capture the spatial and temporal variability of surface SM. [ABSTRACT FROM AUTHOR]

Accurate irrigation water-use data are essential to agricultural water resources management and optimal allocation. The obscuration presented by ground cover in farmland and the subjectivity of irrigation-related decision-making processes mean that effectively identifying regional irrigation water use remains a critical problem to be solved. In view of the advantages of satellite microwave remote sensing in monitoring soil moisture, previous studies have proposed a method for estimating irrigation water use using the satellite microwave remote sensing of soil moisture. However, the method is affected by false irrigation signals from soil moisture increases caused by non-irrigation factors, causing irrigation water use to be overestimated. Therefore, the purpose of this study is to improve the estimation of irrigation water use in drylands by using irrigation signals from SMAP soil moisture data. In this paper, the irrigation water use in Henan Province is estimated by using the irrigation signals from SMAP (soil moisture active and passive) soil moisture data. Firstly, a method for recognizing irrigation signals in soil moisture data obtained by microwave satellite remote sensing was used. Then, an estimation model of the amount of irrigation water (SM2Rainfall model) was built on each data pixel of the satellite microwave remote sensing of soil moisture. Finally, the amount of irrigation water utilized in Henan Province was estimated by combining the irrigation signals and irrigation water-use estimation model, and the results were evaluated. According to the findings, this study improved the estimation accuracy of irrigation water use by using the irrigation signals in Henan Province. The result of this study is of great importance to accurately obtain irrigation water use in the region. [ABSTRACT FROM AUTHOR]

The effects on climate of land-cover change, predominantly from forests to crops or grassland, are reasonably well understood for low and high latitudes but are largely unknown for temperate latitudes. The main reason for this gap in our knowledge is that there are compensating effects on the energy and water balance when land cover changes. To obtain a better understanding of the direction of this response, we analyse the differential response of tall and short vegetation to the 2003 European drought. We analyse precipitation, temperature and normalized difference vegetation index data and compare these with direct measurements of vegetation height. At the height of the 2003 drought we find for tall vegetation a significantly smaller decrease in vegetation index and a smaller diurnal temperature range, indicating less water stress on tall vegetation, which can be explained by access of tall vegetation to deeper soil water. Based on these results we question the current parameterizations of short and tall vegetation in some land-surface models. [ABSTRACT FROM AUTHOR]

This paper introduces and presents the Spatial Processes in HYdrology (SPHY) model (v2.0), its development background, its underlying concepts, and some typical applications. The SPHY model is developed using the best components of existing and well-tested simulation models, and is developed with the explicit aim to simulate terrestrial hydrology at flexible scales, under various land use and climate conditions. SPHY is a spatially distributed leaky bucket type of model, and is applied on a cell-by-cell basis. The model is written in the Python programming language using the PCRaster dynamic modelling framework. Compared to other hydrological models, that typically focus on the simulation of streamflow only, the SPHY model has several advantages: it (i) integrates most relevant hydrological processes, (ii) is setup modular, (iii) is easy adjustable and applicable, (iii) can easily be linked to remote sensing data, and (iv) can be applied for operational as well as strategic decision support. The most relevant hydrological processes that are integrated in the SPHY model are rainfall-runoff processes, cryosphere processes, evapotranspiration processes, the simulation of dynamic vegetational cover, lake/reservoir outflow, and the simulation of rootzone moisture contents. Studies in which the SPHY model was successfully applied and tested are described in this paper, and range from (i) real-time soil moisture predictions to support irrigation management in lowland areas, to (ii) detailed climate change impact studies in snow and glacier-fed river basins, to (iii) operational flow forecasting in mountainous catchments. [ABSTRACT FROM AUTHOR]

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0, coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost-hardening), soil moisture (linearity of stress with relative saturation), and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood, and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leafout and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan-Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US), and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost-hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs. [ABSTRACT FROM AUTHOR]

Phenology is essential to our understanding of biogeochemical cycles and the climate system. We develop a global mechanistic model of leaf phenology based on the hypothesis that phenology is a strategy for optimal carbon gain at the canopy level so that trees adjust leaf gains and losses in response to environmental factors such as light, temperature and soil moisture, to achieve maximum carbon assimilation. We fit this model to five years of satellite observations of leaf area index (LAI) using a Bayesian fitting algorithm. We show that our model is able to reproduce phenological patterns for all vegetation types and use it to explore variations in growing season length and the climate factors that limit leaf growth for different biomes. Phenology in wet tropical areas is limited by leaf age physiological constraints while at higher latitude leaf seasonality is limited by low temperature and light availability. Leaf growth in grassland regions is limited by water availability but often in combination with other factors. This model will advance the current understanding of phenology for ecosystem carbon models and our ability to predict future phenological behaviour. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a significant factor in the climate system. The accurate determination of SM has high importance in food production to satisfy the increasing demand for food and the chemical processes of soil. This paper applies decision tree regression to estimate SM considering different parameters including air temperature, time, relative humidity, and soil temperature. The presented method holds a mighty advantage to determine SM since the stimulant of the decision tree regression is an algorithm that generates a decision tree from given instances. Besides, usage of decision tree regression provides an opportunity to save time. Numerical results show that the presented method offers a high coefficient of determination value (R2), low mean squared error (MSE), and mean absolute error (MAE). The depth of the decision tree equals to five by providing higher fitness values than other depth levels. The best fitness values in the training stage are 0.00019, 0.007, and 0.842 for MSE, MAE, and R2, respectively. In conclusion of the paper, applied decision tree regression can handle the data of SM estimation in satisfying fitness criterion. [ABSTRACT FROM AUTHOR]

The HT ht value versus time of clays is shown in Fig. When the HT ht value is equal to 100%, it means the strength of soil has recovered its original intact shear strength. The regained strength of YS-1 clay is also considerable, and the value of HT ht is greater than 40% after 2 months. By contrast, the HT ht of YS-2 and ES-2 clays in the corresponding deep layer is much lower (see Table 1 in the original paper). [Extracted from the article]

Soil exchange of carbonyl sulfide (COS) is the second largest COS flux in terrestrial ecosystems. A novel application of COS is the separation of gross primary productivity (GPP) from concomitant respiration. This method requires that soil COS exchange is relatively small and can be well quantified. Existing models for soil COS flux have incorporated empirical temperature and moisture functions derived from laboratory experiments, but not explicitly resolved diffusion in the soil column. We developed a 1-D diffusion-reaction model for soil COS exchange that accounts for COS uptake and production, relates source-sink terms to environmental variables, and has an option to enable surface litter layers. We evaluated the model with field data from a wheat field (Southern Great Plains (SGP), OK, USA) and an oak woodland (Stunt Ranch Reserve, CA, USA). The model was able to reproduce all observed features of soil COS exchange such as diurnal variations and sink-source transitions. We found that soil COS uptake is strongly diffusion controlled, and limited by low COS concentrations in the soil if there is COS uptake in the litter layer. The model provides novel insights into the balance between soil COS uptake and production: a higher COS production capacity was required despite lower COS emissions during the growing season compared to the post-senescence period at SGP, and unchanged COS uptake capacity despite the dominant role of COS emissions after senescence. Once there is a database of soil COS parameters for key biomes, we expect the model will also be useful to simulate soil COS exchange at regional to global scales. [ABSTRACT FROM AUTHOR]

The variance of soil moisture, vegetation and evapotranspiration over land has been recognized to be strongly connected to the variance of precipitation. However, the feedbacks and couplings between these variables are still not well understood and quantified. Furthermore, soil moisture and vegetation processes are associated to a memory and therefore they may have important implications for predictability. In this study we apply a generalized linear method, specifically designed to assess the reciprocal forcing between connected fields, to the latest available observational datasets of global precipitation, evapotranspiration, vegetation and soil moisture content. For the first time a long global observational dataset is used to investigate the spatial and temporal land variability and to characterize the relationships and feedbacks between land and precipitation. The variables considered show a significant coupling among each other. The analysis of the response of precipitation to soil moisture evidences a robust coupling between these two variables. In particular, the first two modes of variability of the precipitation forced by soil moisture appear to have a strong link with volcanic eruptions and ENSO cycles, respectively, and these links are modulated by the effects of evapotranspiration and vegetation. It is suggested that vegetation state and soil moisture provide a biophysical memory of ENSO and major volcanic eruptions, revealed through delayed feedbacks on rainfall patterns. The third mode of variability reveals a trend very similar to the trend of the inter-hemispheric contrast in SST and appears to be connected to greening/browning trends of vegetation over the last three decades. [ABSTRACT FROM AUTHOR]

In environmentally sensitive areas, especially the arid and semi-arid regions, the greening stability process and its influencing factors can directly affect the sustainable development of the ecological environment. In this study, multi-source remote sensing data such as land use/cover data, MODIS NDVI, and soil moisture, methods such as stability index, vegetation quantitative remote sensing, and Geodetector were employed to analyze the sustainability of the greening process in the Mu Us Sandy in 2000–2020, which were viewed from three aspects: changes in stability of land use types and function, soil moisture change and influencing factors on greening stability. The results showed that, (1) From the stability of land use types, continuous stable ecological land accounted for more than 50%, showing that decreased from northwest toward southeast. (2) From the functional stability, NDVI showed a fluctuated growth (0.035/a), with an increasing distribution pattern from northwest to southeast. Additionally, Vegetation changes were unstable and concentrated in the western part of the study area (OtogBanner and Otog Front Banner), while the eastern part was stable, in which vegetation improvement took the main position. Moreover, mobile dunes almost disappeared, and semi-fixed dunes decreased and gradually shrank to the west of the sandy area, while fixed dunes soared and were concentrated in the middle of the sandy land. (3) From the soil moisture change, soil moisture at different underground depths showed an overall increasing trend, but the deep soil moisture was higher than the shallow, and spatial distribution varied greatly. (4) From the influencing factors, natural factors significantly influence greening stability, among which precipitation had a particularly profound impact, and interactions with other natural and social factors were higher explanatory. The paper aims to explore whether the ecological environment is developing in a good and orderly direction in the Mu Us Sandy Land, and the potential factors that cause its changes, to provide a theoretical basis for scientific governance in the Mu Us Sandy Land and other arid and semi-arid areas in the future. [ABSTRACT FROM AUTHOR]

Agricultural drought events have become more frequent in the Inner Mongolia inland river basin in recent years, and the spatio-temporal evolution characteristics and development rules can be accurately and comprehensively understood using the three-dimensional identification method. In this paper, standardized soil moisture index (SSMI) was used to characterize agricultural drought, and modified Mann–Kendall trend test (MMK) and 3D recognition of drought events were used to analyze the spatio-temporal evolution characteristics of agricultural drought events in this basin and reveal the drought development law. The relationships between drought and temperature (T), precipitation (P), evapotranspiration (E), and humidity (H) were analyzed using a cross-wavelet method. The results are as follows: (1) When the time scale of agricultural drought was short (monthly scale), the alternations of dry and wet were frequent, but the SSMI index of all scales showed a downward trend; (2) The spatial distribution characteristics of drought change trend in four seasons were similar, but the area with a significant downward trend of drought in spring was the largest, and the area of high frequency region was also the largest, and the drought trend was the most obvious; (3) The most serious agricultural drought event occurred from October 2000 to May 2002, and reached its maximum value in September 2001 (drought area and drought severity of 2.26 × 105 km2 and 3.61 × 105 months·km2, respectively), which mainly experienced five processes—drought onset–intensification–decay–re-intensification–termination—and the migration path of the drought center showed the characteristics of southwest–northeast transmission; (4) All the four meteorological factors were correlated with SSMI, and P had a greater impact on SSMI. This article aims to reveal the spatio-temporal evolution of agricultural drought events in the Inner Mongolia inland river basin, and provide a new way to accurately evaluate the spatio-temporal evolution of drought. [ABSTRACT FROM AUTHOR]

This paper presents a comparison between the Sentinel-1 (S1)/Sentinel-2 (S2)-derived soil moisture products at plot scale (S2MP) and in situ soil moisture measurements at a 10 cm depth for several winter and summer crops. Specifically, the paper discusses the consistency between the in situ soil moisture measurements, usually performed at a 10 cm soil depth, and the variable S1 C-band penetration depth in soil due to soil humidity conditions, vegetation development and S1 acquisition configuration. The aim is to provide end users with the strength and limitations of S1-derived soil moisture, mainly the S2MP soil moisture product, for their further applications. Both the estimated and measured soil moisture (SM) were evaluated over three testing fields in a Mediterranean climatic context, with crop cycles including wheat, tomato, cover crops and soybeans. The main results showed that the comparison between the S2MP-estimated SM based on S1 backscattering (at ~5 cm depth) with a 10 cm in situ SM is not always relevant during the crop cycle. In dry conditions, the S1 SM significantly underestimated the 10 cm SM measurements with an underestimation that could reach around 20 vol.% in some extremely dry conditions. This high underestimation was mainly due to the difference between the topsoil SM captured by the S1 sensor and the 10 cm in depth SM. Moderately wet conditions due to rainfall or irrigation showed less of a difference between the S1-estimated SM and the 10 cm in situ SM and varying between −10 and −5 vol.% due to the homogeneity of the SM at different soil depths. For extremely wet conditions, the S1 SM started to underestimate the SM values with an underestimation that can reach an order of −10 vol.%. A comparison of the S1-estimated SM as a function of the vegetation development showed that, for the studied crop types, the S1 SM estimates are only valid for low and moderate vegetation cover with a Normalized Difference Vegetation Index (NDVI) of less than 0.7. For dense vegetation cover (NDVI > 0.7), overestimations of the SM (average bias of about 4 vol.%) are mainly observed for developed tomato and soybean crops due to fruits' emergence, whereas an extreme underestimation (average bias reaching −15.5 vol.%) is found for developed wheat cover due to the vertical structure of the wheat kernels. The results also suggest that the optimal SM estimations by S1 could be mainly obtained at low radar incidence angles (incidence angle less than 35°). [ABSTRACT FROM AUTHOR]