Soil Moisture Variability Research Articles

Role of time variant and invariant terms on soil moisture spatio‐temporal variability in a subhumid coastal wetland

AbstractThe knowledge of soil moisture spatio‐temporal variability is highly relevant for water resources management. This paper reports an analysis of the spatial–temporal variability of soil moisture data for a small to medium‐scale soil‐sensors network in a coastal wetland of southwestern Spain. Measurements were taken from five sites located in the Doñana National Park over the time‐period of one hydrological year from September 2017 to September 2018. The total area of the soil‐sensors network shows an extension about 25 × 3 km. Soil moisture data was separated into time invariant (the temporal mean of the whole period at each site) and time‐variant terms (the deviations of soil moisture from the mean, or anomalies). The time‐invariant component was generally the main contributor to the total spatial variance of soil moisture and it was mostly controlled by the groundwater levels in the area. Nevertheless, the time variant terms have a huge effect on soil moisture variability in very dry states. Characteristic convex time‐dependent patterns for this field site were found between spatially averaged soil moisture and its variability. This information could be used for the up and downscaling of soil moisture from satellite data. Those patterns of relation between spatial mean and variability of soil moisture were only affected by heavy rainfalls giving rise to hysteretic behaviour. This study shows that even though groundwater level is a time‐variant variable, it significantly affects soil moisture's time‐variant but also time‐invariant terms due to the different average groundwater level depths at the different sites.

The importance of soil seed banks for biodiversity restoration in degraded grasslands

To effectively restore species and habitat diversity in poorly managed degraded grasslands, it is important to understand the relationship between the soil seed bank and aboveground vegetation. Our study aimed to describe changes in soil seed bank composition compared to aboveground vegetation under two ploughing regimes (annual and single ploughing) of narrow strips on the edges of artificially grassed old fields in Podyjí National Park, the Czech Republic. We used the seed germination method, multivariate analyses and Kruskal–Wallis tests to compare differences in the proportion of species and individual numbers in the soil seed bank based on the origin of species (native species, archaeophytes, neophytes) and their habitat preferences (segetal, ruderal, grassland, endangered species) in two types of grasslands with varying soil moisture content. The highest numbers of individuals were present in annually ploughed dry grasslands whereas single ploughing in mesic grasslands resulted in greater species diversity. Ploughing increased the numbers of seedlings of all groups and promoted archaeophytes, grassland specialists, native species and ruderals in dry grasslands whereas mesic grasslands hosted segetal specialists and neophytes. Threatened plants and invasive species rarely emerged from the soil seed bank. The study also revealed the highest similarity between the soil seed bank and aboveground vegetation in annually ploughed plots. It gradually decreased during vegetation succession in the single ploughed variants. Whereas annual ploughing supported segetal specialists, single ploughing promoted grassland species in dry habitats. Neither type of ploughing can be recommended in mesic grasslands because of the risk of inducing the spread of expansive ruderals or invasive neophytes.

Links between seasonal suprapermafrost groundwater, the hydrothermal change of the active layer, and river runoff in alpine permafrost watersheds

Abstract. The seasonal dynamic of the suprapermafrost groundwater significantly affects the runoff generation and confluence in permafrost basins and is a leading issue that must urgently be addressed in hydrological research in cold and alpine regions. In this study, the seasonal dynamic process of the suprapermafrost groundwater level (SGL), vertical gradient changes of soil temperature (ST), moisture content in the active layer (AL), and river level changes were analyzed at four permafrost watersheds in the Qinghai–Tibet Plateau using comparative analysis and the nonlinear correlation evaluation method. The impact of freeze–thaw processes on seasonal SGL and the links between SGL and surface runoff were also investigated. The SGL process in a hydrological year can be divided into four periods: (A) a rapid falling period (October to mid-November), (B) a stable low-water period (late November to May), (C) a rapid rising period (approximately June), and (D) a stable high-water period (July to September), which synchronously respond to seasonal variations in soil moisture and temperature in the AL. The characteristics and causes of SGL changes significantly varied during these four periods. The freeze–thaw process of the AL regulated SGL and surface runoff in permafrost watersheds. During period A, with rapid AL freezing, the ST had a dominant impact on the SGL. In period B, the AL was entirely frozen due to the stably low ST, while the SGL dropped to the lowest level with small changes. During period C, ST in the deep soil layers of AL (below 50 cm depth) significantly impacted the SGL (nonlinear correlation coefficient R2 > 0.74, P < 0.05), whereas the SGL change in the shallow soil layer (0–50 cm depth) showed a closer association with soil moisture content. Rainfall was the major cause for the stable high SGL during period D. In addition, the SGLs in periods C and D were closely linked to the retreat and flood processes of river runoff. The SGL contributed approximately 57.0 %–65.8 % of the river runoff changes in the period D. These findings will help to facilitate future hydrological research in the permafrost basins and the development and utilization of water resources in cold and alpine regions.

Diverse spatiotemporal patterns of vapor pressure deficit and soil moisture across China

Study regionChina and the different climatic zones. Study focusVapor pressure deficit (VPD) and soil moisture (SM) are vital for the land-atmosphere hydrological cycle and vegetation growth. Understanding the spatiotemporal variations of VPD and SM is essential for exploring vegetation dynamics and ecosystem changes. However, our current understanding of the simultaneous variations of VPD and SM within specific regions remains limited. This study utilized Empirical Orthogonal Function (EOF) methods to analyze the spatiotemporal variability of VPD, surface SM (SMsurf), and root-zone SM (SMroot), respectively. We then investigated the synchronous and asynchronous variations of VPD and SM and examined their relationships with climatic factors. New hydrologic insights for the regionFrom 1980–2020, VPD exhibited a significant upward trend across China and in various climate zones, indicating an increase in atmospheric dryness. However, the trends of SMsurf and SMroot showed a slight upward trend across China but divergent patterns in different climate zones. In summary, approximately 43% of China experiences a significant simultaneous increase in both VPD and SM, mainly in semi-arid and arid regions. Conversely, about 4% of China shows contrasting changes in VPD and SM, primarily in humid tropical and subtropical regions. These findings enhance our understanding of VPD and SM patterns in various climates, emphasizing the significance of soil drought in humid and semi-humid regions.

Multiresolution soil moisture products based on a spatially adaptive estimation model and CYGNSS data

ABSTRACT The estimation of soil moisture (SM) utilizing the data from the Cyclone Global Navigation Satellite System (CYGNSS) has attracted significant interest in recent times. However, CYGNSS’ inherent capability of variable resolution has not been fully exploited, often resulting in a loss of detailed spatial information in the raw data. In this paper, a novel downscaling scheme tailored for CYGNSS data is introduced to yield a “self-adjusting adaptive resolution” SM product, which dynamically varies the resolution of SM estimates based on the available CYGNSS data resolution at different geographic locations. Initially, a direct quantitative relationship is established between the key CYGNSS parameters reflecting SM variations and the reference SM from the Soil Moisture Active Passive (SMAP) mission with a coarse resolution of 36 km. This model is then applied to CYGNSS observations with resolutions down to 3 km to generate high-resolution, self-adjusting SM estimates that better conserve the fine-scale information linked to the original CYGNSS data. Extensive experimental results with error ratio diagrams show that the advanced geographically weighted regression (GWR)-based SM estimation method outperforms other competing estimation models and better retains localized spatial relationships and patterns. This study underscores the potential of CYGNSS as a novel and robust independent data source capable of delivering fine-resolution SM estimations by harnessing its unique multiresolution observational capability.

Analysis of Effects of Spatial Distributed Soil Properties and Soil Moisture Behavior on Hourly Streamflow Estimate through the Integration of SWAT and LSM

This study addresses the challenge of accurately estimating hourly flow and soil moisture by integrating the Soil and Water Assessment Tool (SWAT) with a Land Surface Model (LSM). Our approach enhances SWAT by incorporating spatially distributed soil properties and a physically-based soil moisture process, using the Noah LSM for hourly soil moisture estimation. This integration captures spatial variations in soil moisture and hydraulic properties from remote sensing across the watershed. The parameter sensitivity analysis and the calibration of hourly flow were significantly impacted by the physically-based hourly soil moisture routing and the incorporation of spatially distributed soil properties. Consequently, the modified SWAT model showed improved accuracy in hourly flow simulations for long-term and multiple rainfall events. Validation results showed significant improvements, with Coefficient of Determination (R2) and Nash and Sutcliffe Efficiency (NSE) increasing by 25.95% and 33.3%, respectively, and Percent Bias (PBIAS) decreasing by 85.8%. Notably, the average error for peak flows across eight events decreased by 49%. These findings highlight the importance of initializing soil parameters based on spatial soil moisture distribution and incorporating physical process-based moisture routing to enhance hourly flow simulation accuracy. Future research should focus on validating the physical feasibility of the soil parameter set in the study area with detailed hourly flow and soil moisture data and exploring its applicability in various regions. This study provides valuable insights for the scientific community, water resources, and agricultural decision-makers regarding integrated modeling of soil moisture and hourly flow, which can inform dam operation management, disaster planning, and crop yield improvement.

Sensitivity of the Land–Atmosphere Coupling to Soil Moisture Anomalies during the Warm Season in China and its Surrounding Areas

Significant temporal and spatial variability in soil moisture (SM) is observed during the warm season in China and its surrounding regions. Because of the existence of two different evapotranspiration regimes, i.e., soil moisture-limited and energy-limited, averaging the land–atmosphere (L–A) coupling strength for all soil wetness scenarios may result in the loss of coupling signals. This study examines the daytime-only L–A interactions under different soil moisture conditions, by using two-legged metrics in the warm season from May to September 1981–2020, partitioning the interactions between SM and latent heat flux (SM–LH, the land leg) from the interactions between latent heat flux and the lifting condensation level (LH–LCL, the atmospheric leg). The statistical results reveal large regional differences in warm-season daytime L–A feedback in China and its surrounding areas. As the soil becomes wetter, the positive SM–LH coupling strength increases in arid regions (e.g., northwest China, Hetao, and the Great Indian Desert) and the positive feedback shifts to the negative one in semi-arid/semi-humid regions (northeast and northern China). The negative LH–LCL coupling is most pronounced in wet soil months in arid regions, while the opposite is true for the Tibetan Plateau. In terms of intraseasonal variation, the large variability of SM in north China, the Tibetan Plateau, and India due to the influence of the summer monsoon leads to the sign change in the land segment coupling index, comparing pre- and post-monsoon periods. To further examine the impact of SM anomalies on L–A coupling and to explore evapotranspiration regimes in the North China Plain, four sets of sensitivity experiments with different soil moisture levels over a period of 10 years were conducted. Under relatively dry soil conditions, evapotranspiration is dominated by the soil moisture-limited regime with positive L–A coupling, regardless of external moisture inflow. The critical soil moisture value separating a soil moisture-limited and an energy-limited regime lies between 0.24 m3/m3 and 0.29 m3/m3. Stronger positive feedback under negative soil moisture anomalies may increase the risk of drought in the North China Plain.

Spatial and Temporal Variability of Soil Moisture and Its Driving Factors in the Northern Agricultural Regions of China

Soil moisture, as an important variable affecting water–heat exchange between land and atmosphere, is an important feedback to climate change. Soil moisture is of great concern in Northern China, where arable land is extensive, but water resources are distributed unevenly and extremely sensitive to climate change. Using measured soil moisture data collected by the China Meteorological Administration from 164 stations during 1980–2021, we explored the drivers of soil moisture variation by analyzing its spatiotemporal variability using linear regression, partial correlation analysis, and geostatistical methods. The results indicated that (1) soil moisture increased from northwest to southeast in Northern China, with the lowest soil moisture in the IM; (2) the overall trend of soil moisture in most regions decreased, especially in the arid northwest and northeast China. However, soil moisture in some regions began to increase gradually in recent years, such as in northwestern Xinjiang and the central-eastern part of IM; and (3) soil moisture in the whole region was negatively correlated with temperature and sunshine duration and positively correlated with precipitation and relative humidity. The results of the study can provide valuable guidance for timely agricultural irrigation and the adjustment of cropping structures, thereby ensuring agricultural production and food security.

Soil moisture conditions alter behavior of entomopathogenic nematodes.

A variety of environmental factors can disrupt biotic interactions between plants, insects and soil microorganisms with consequences for agricultural management and production. Many of these belowground interactions are mediated by volatile organic compounds (VOCs) which can be used for communication under appropriate environmental conditions. Behavioral responses to these compounds may likewise be dependent on varying soil conditions which are influenced by a changing climate. To determine how changing environmental conditions may affect VOC-mediated biotic interactions, we used a belowground system where entomopathogenic nematodes (EPNs) - tiny roundworm parasitoids of soil-borne insects - respond to VOCs by moving through the soil pore matrix. Specifically, we used two genera of EPNs - Heterorhabditis and Steinernema - that are known to respond to four specific terpenes - α-pinene, linalool, d-limonene and pregeijerene - released by the roots of plants in the presence of herbivores. We assessed the response of these nematodes to these terpenes under three moisture regimes to determine whether drier conditions or inundated conditions may influence the response behavior of these nematodes. Our results illustrate that the recovery rate of EPNs is positively associated with soil moisture concentration. As soil moisture concentration increases from 6% to 18%, substantially more nematodes are recovered from bioassays. In addition, we find that soil moisture influences EPN preference for VOCs, as illustrated in the variable response rates. Certain compounds shifted from acting as a repellent to acting as an attractant and vice versa depending on the soil moisture concentration. On a broad scale, we demonstrate that soil moisture has a significant effect on EPN host-seeking behavior. EPN efficacy as biological control agents could be affected by climate change projections that predict varying soil moisture concentrations. We recommend that maintaining nematodes as biological control agents is essential for sustainable agriculture development, as they significantly contribute not only to soil health but also to efficient pest management. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Climate Change & Crop Adaptation: Geophysical Data on Soil Moisture Changes & Agricultural Strategies

This study aims to determine the effect of soil moisture variability on plant productivity. This was done using an integrated approach that combined quantitative research on soil water issues with crop yields and farmer characteristics. Soil moisture measurements were collected from five locations using multiple sampling methods, surveys, and interviews with local farmers. Statistical analysis showed a significant relationship between soil moisture levels and crop yields, indicating that optimum moisture conditions are associated with increased yields. Qualitative findings may shed light on farmer's adaptation strategies and their perceptions of soil moisture management practices. The findings of this study highlight the importance of soil moisture in influencing agricultural yields and the need to adapt soil and water management strategies to unique conditions. These findings improve the current understanding of the complex dynamics of soil moisture changes. They provide practical ideas to increase agricultural livelihoods and influence the development of sustainable land management policies and practices.

Alternative streamflow-based approach to estimate catchment response time in medium to large catchments: case study in Primary Drainage Region X, South Africa

Event-based estimates of the design flood in ungauged catchments are normally based on a single catchment response time parameter expressed as either the time of concentration (TC), lag time (TL) and/or time to peak (TP). In small, gauged catchments, a simplified convolution process between a single observed hyetograph and hydrograph is generally used to estimate these time parameters. In medium to large heterogeneous, gauged catchments, such a simplification is neither practical nor applicable, given that the variable antecedent soil moisture status resulting from previous rainfall events and spatially non-uniform rainfall hyetographs can result in multi-peaked hydrographs. In ungauged catchments, time parameters are estimated using either empirical or hydraulic methods. In South Africa (SA), unfortunately, the majority of the empirical methods recommended for general use were developed and verified in catchments ≤ 0.45 km² without using any local data. This paper presents the further development and verification of the streamflow-based approach developed by Gericke (2016) to estimate observed TP values and to derive a regional empirical TP equation in Primary Drainage Region X, SA. A semi-automated hydrograph analysis tool was developed to extract and analyse complete hydrographs for time parameter estimation using primary streamflow data from 51 flow-gauging sites. The observed TP values were estimated using three methods: (i) duration of total net rise of a multi-peaked hydrograph, (ii) triangular-shaped direct runoff hydrograph approximations, and (iii) linear catchment response functions. The combined use of these methods incorporated the high variability of event-based time parameters, and Method (iii), in conjunction with an ensemble-event approach sampled from the time parameter distributions, should replace the event-based approaches to enable the improved calibration of empirical time parameter equations. The conceptual approach used to derive the regional empirical TP equation should also be adopted when regional equations need to be derived at a national scale in SA.

Dominance of soil moisture over aridity in explaining vegetation greenness across global drylands

Drylands are one of the most sensitive areas to climate change. Despite being characterized by water scarcity and low precipitation, drylands support a wide range of green biodiversity and nearly 40 % of the global population. However, the climate change impacts on dryland characteristics and vegetation dynamics are debatable as the reasons remain poorly understood. Here, we use hydro-meteorological variables from ERA5 reanalysis and GIMMS-NDVI to analyze the changes in dryland aridity and vegetation greenness in the eight selected global dryland regions. The total dryland area (excluding hyperarid) has increased by 12 %, while arid, semiarid, and dry sub-humid areas have increased by 10.5 %, 8 %, and 25 %, respectively. We find a significant increase in aridity in drylands across the globe, except for South Asia. A decrease (increase) in precipitation is the major driver for a significant increase (decrease) in dryland aridity, with a notable contribution from climate warming. Despite decreasing trends in precipitation, vegetation greenness has significantly increased in most dryland regions due to increased soil moisture. Cropland expansion in Europe, Asia, and Australia resulted in the maximum increase in NDVI (Normalized Difference Vegetation Index) in dryland regions. The highest increase, with a ΔNDVI of 0.075, was observed in South Asia. The enhanced vegetation greenness observed is attributed to the expansion of croplands in recent decades, which has increased soil moisture. Overall, we show that monitoring soil moisture variability can provide a more robust explanation for vegetation greenness in the global drylands than aridity change. Moreover, human interventions of climatic alteration through land use change practices, such as cropland expansion, cannot be ignored while explaining the ecosystem dynamics of the drylands.

Intensive land restoration projects alter mechanisms underpinning spatiotemporal soil moisture variability at a catchment scale: A case study in China

Soil moisture (SM) is a critical factor for material circulation and energy exchange in Earth’s critical zone, but it is spatially and temporally variable. This study aimed to provide new insight into spatiotemporal SM variability and its associative controls in areas where land restoration projects have been implemented. Specifically, we compared environmental controls on spatiotemporal SM variability in deep soil layers (0–500 cm) of two paired catchments, one of which was treated by the Gully Land Consolidation (GLC) project and the other which was not, where the slopes of both catchments had initially been impacted by the Grain for Green (GFG) program. For this purpose, we used the empirical orthogonal function (EOF) to decompose spatial and temporal SM anomalies. Two dominant spatial and temporal EOF anomalies (EOF1 and EOF2) were obtained from six soil layers in both catchments, with an explained variance of 86%–97% and 32%–53%, respectively. These spatial anomalies that derived from spatial structures exhibited similar characteristics and controls in both catchments, while underlying temporal SM dynamic mechanisms differed. Temporal dynamics of the treated catchment were lower in the gully area (a relative flat region), while the opposite was true for the gully area (at a lower elevation) in the untreated catchment. The GLC and GFG programs both altered catchment scale temporal SM dynamic forcings. Results obtained from this study are helpful for understanding spatiotemporal SM variability with associated the hydrological processes in areas where the intensive land restoration projects have been implemented at a catchment scale.

The physical, mechanical, and chemical properties of black cherry tree wood (Prunus serotina Ehrh.) and its susceptibility to fungal decomposition in areas where it is secondary and invasive: a case study in the Kampinos National Park (Poland)

The properties of black cherry mature wood (Prunus serotina Ehrh.) and its susceptibility to fungal decay were studied in the invaded range of the species on six trees aged between 39 and 47 years old growing in poor, acidic soils with varying levels of moisture and organic carbon and nitrogen content. Wood from trees that grew in wetter and richer soil had better physical properties. Of the 95 parameters analyzed, 80 showed significant differences in favor of this wood. These differences included wider rings that averaged 3.25 mm, a higher density of 662.71 kg/m3 at 12% humidity, and 1.5 times higher content of extractives. Gas chromatography with mass spectrometry revealed the presence of 44 extractives. Out of these, six had antifungal properties and were found in the wood of trees grown in richer soil, corresponding to 62.93% of the peaks area of all identified substances. Only three were found in trees grown in poorer soil, corresponding to 8.68% of the peaks area respectively. The wood of trees grown in more fertile soil was also less prone to fungal decay, which was generally low. Only Trametes versicolor caused a mass loss of more than 10% of the wood in both sites out of the four basidiomycete species tested. The results indicate that even slight variations in soil fertility and moisture can benefit black cherry, leading to differences in wood features and properties in its exotic range.

Nitrous Oxide Emissions during Cultivation and Fallow Periods from Rice Paddy Soil under Urea Fertilization

Rice cultivation serves as a significant anthropogenic source of methane (CH4) and nitrous oxide (N2O). Although N2O emissions remain relatively small compared to CH4 emissions, they are remarkably affected by nitrogen-fertilized soil conditions during rice cultivation. While numerous studies have investigated nitrous oxide emissions in response to nitrogen fertilization, existing research assessing nitrous oxide emissions based on nitrogen fertilizer levels has often been limited to cultivation periods. Therefore, there is a need for comprehensive analyses covering the entire year, including the dry periods, to address nitrous oxide emissions as an important source throughout the entire agricultural cycle. In this case study, we investigated the characteristics of N2O emissions in a central region of South Korea, where a single rice-cropping cycle occurs annually over a span of three whole years, from May 2020 to May 2023. We investigated the impact of variations in temperature and soil moisture on N2O emissions during rice cultivation and fallow periods. In this context, we attempted to discover the complex dynamics of N2O emissions by comparing longer fallow periods with the rice cultivation periods and extended non-dry periods with irrigated periods. We discovered that the greater contribution of cumulative N2O emissions during the fallow period made a much greater contribution (up to approximately 90%) to the whole-year N2O emissions than those during the rice cultivation period. During the fallow period from rice harvest to rice planting in the following year, variations in N2O emissions were associated with high-flux events after rainy periods on dry soils. This highlights the considerable influence of soil moisture content and weather conditions on N2O emissions during the fallow period. This affects high emission events, which in turn significantly impact the cumulative emissions over the entire period. We underscore that assessing N2O emissions solely based on the rice cultivation period would underestimate annual emissions. To prevent underestimation of N2O emissions, periodic gas collection throughout a year covering both rice cultivation and fallow phases is required in alignment with the monitoring of different temperature and soil moisture conditions. We captured statistical differences in cumulative N2O emissions due to nitrogen fertilization treatments across the three years. However, no significant difference was observed in the three-year average emissions among the different (one, one-and-a-half, and double) nitrogen fertilization treatments, with the exception of the control treatment (no fertilization). Based on the findings, we recommend at least three whole-year evaluations to ensure the estimation accuracy of N2O emissions under different nitrogen fertilization conditions. The findings from this study could help prepare the further revision or refinement of N2O emission factors from rice cultivation in the national greenhouse gas inventories defined by the inter-governmental panel on climate change (IPCC).

Downscaled GRACE/GRACE-FO observations for spatial and temporal monitoring of groundwater storage variations at the local scale using machine learning

Groundwater utilization for several purposes such as irrigation in agriculture, industry, and domestic use substantially impacts water storage. Groundwater Storage Anomaly (GWSA) estimates have improved owing to the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) advancements. However, the characterization of GWSA fluctuation hotspots has been hindered by the coarse resolution of GRACE data. To better measure groundwater storage and depletion variations throughout an area and identify GWSA variation hotspots, a fine spatial resolution of GWSA estimations is required. Therefore, due to the coarse resolution of GRACE measurements, the eXtreme Gradient Boosting (XGBoost) model was developed to simulate fine resolution 0.1° GWSA combining climatic variables (soil moisture storage, evapotranspiration, temperature, surface runoff, and rainfall) from improved spatial high resolution FLDAS (Famine Early Warning Systems Network Land Data Assimilation System) model derived data and geospatial variables (elevation, slope, and aspect) extracted from Digital Elevation Model (DEM). A correlation of 0.98 demonstrated that the XGBoost model successfully simulated groundwater storage at a finer scale over the Upper Indus Plain Aquifer (UIPA). The findings suggested that the UIPA's groundwater storage has been depleted at an annual rate of 0.44 km3/yr which was 7.94 km3 in total between 2003 and 2020. According to the results, there seems to be consistency between the downscaled and original GWSA regarding temporal and spatial variability. The results were verified to show an improved correlation of 0.77 between the downscaled and the in-situ GWSA, compared to 0.75 between the GRACE-derived and the in-situ GWSA.

Behaviour of enzymatic soil stabilization at elevated temperatures using advanced micro structural investigations

ABSTRACT Soil moisture variation plays a key role in maintaining the engineering properties of soils. One of the main factors that impact the soil moisture content is the temperature, which has a strong impact to change the initial or design moisture and results in significant soil volume changes. This study aims to investigate the effects of temperature on the performance of enzymatically stabilised soils. The enzyme used in this study is Eko-soil and the soil used is clayey silt of low plasticity (ML). The mechanical behaviour was first assessed through the unconfined compression strength and weight measurements based on samples exposed to a series of operational temperatures. X-ray μCT tomography images were then used to assess the microstructure. Porosity, size and geometrical shape of the pores were analysed at elevated temperatures. Results revealed that the enzyme is effective in maintaining the initial pore structure under the tested temperature range.

Load-Settlement Analysis of Axially Loaded Piles in Unsaturated Soils

Unsaturated soil covers a significant part of the world, and studying the behavior of deep foundations in this medium is an important step in increasing accuracy and economic efficiency in geotechnical studies. This paper presents an analytical solution to investigate the load-carrying characteristics of single piles embedded in unsaturated soils, accounting for the effect of groundwater level on the pile’s response. For this purpose, relationships for shear modulus and Poisson’s ratio for unsaturated soils were collected from the literature to consider their effects as key parameters on pile performance. A parametric study was conducted to evaluate the effect of soil moisture content on the behavior of the pile-soil system for different soil types, and the effect of pile slenderness on its load-settlement behavior was studied for varying soil moisture contents. The results indicate that the pile stiffness increases as the soil suction increases while below a critical slenderness value, hence increasing the pile load capacity. However, this improvement occurs within a limited range of soil suction that is narrower for coarse-grained soils. The pile settlement corresponding to soil failure was also evaluated by modifying the existing solutions for unsaturated soils. The developed solutions were verified against the predictions of published solutions as well as the results of finite element analysis and pile load tests. It was found that the system stiffness decreases by 50% when the water table rises from the pile toe level to the ground surface in the studied soil.

Assessing soil moisture variability in a vineyard via frequency domain electromagnetic induction data

IntroductionIn agriculture, accurate hydrological information is crucial to infer water requirements for hydrological modeling, as well as for appropriate water management.MethodsTo achieve this purpose, geophysical frequency domain electromagnetic induction (FDEM) measurements are increasingly used for integration with traditional point-scale measurements to provide effective soil moisture estimations over large areas. The conversion of electromagnetic properties to soil moisture requires specific tools that must take into account the spatial variability of the two measurements and the data and model uncertainties. In a vineyard of about 4.5 ha located in Southern Italy, we tested an innovative assessment approach that uses a freeware code licensed from USGS, MoisturEC, to integrate electromagnetic data, collected with a CMD Mini-Explorer electromagnetic sensor, and point-scale soil moisture data.ResultsAbout 30,000 data measurements of apparent electrical conductivity (sa) allowed us to build a 3D inverted electromagnetic model obtained via an inversion process. Soil properties at different depths were inferred from the FDEM model and confirmed through the ground truth sampling.DiscussionThe data analysis tool allowed a more accurate estimation of the moisture distribution of the investigated area by combining the accuracy of the point-scale soil moisture measurements and the spatial coverage of the electrical conductivity (EC) data. The results confirmed the capability of the electromagnetic data to accurately map the moisture content of agricultural soils and, at the same time, the need to employ integrated analysis tools able to update such quantitative estimations in order to optimize soil and water management.

Nitrogen addition regulates the effects of variation in precipitation patterns on plant biomass formation and allocation in a Leymus chinensis grassland of northeast China.

Global warming is predicted to change precipitation amount and reduce precipitation frequency, which may alter grassland primary productivity and biomass allocation, especially when interact with other global change factors, such as nitrogen deposition. The interactive effects of changes in precipitation amount and nitrogen addition on productivity and biomass allocation are extensively studied; however, how these effects may be regulated by the predicted reduction in precipitation frequency remain largely unknown. Using a mesocosm experiment, we investigated responses of primary productivity and biomass allocation to the manipulated changes in precipitation amount (PA: 150mm, 300mm, 450mm), precipitation frequency (PF: medium and low), and nitrogen addition (NA: 0 and 10 g N m-2 yr-1) in a Leymus chinensis grassland. We detected significant effects of the PA, PF and NA treatments on both aboveground biomass (AGB) and belowground biomass (BGB); but the interactive effects were only significant between the PA and NA on AGB. Both AGB and BGB increased with an increment in precipitation amount and nitrogen addition; the reduction in PF decreased AGB, but increased BGB. The reduced PF treatment induced an enhancement in the variation of soil moisture, which subsequently affected photosynthesis and biomass formation. Overall, there were mismatches in the above- and belowground biomass responses to changes in precipitation regime. Our results suggest the predicted changes in precipitation regime, including precipitation amount and frequency, is likely to alter primary productivity and biomass allocation, especially when interact with nitrogen deposition. Therefore, predicting the influence of global changes on grassland structure and functions requires the consideration of interactions among multiple global change factors.