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Understanding the dynamics of soil water content (SWC) is essential for effective land management, particularly in regions affected by underground mining. This study investigates the spatial and temporal patterns of SWC and its interaction with topographic and edaphic factors in coal mining and non-coal mining areas of the Chenghe watershed, located in the southeast of the Chinese Loess Plateau, which is divided by a river. Our findings revealed that the capacity to retain moisture in the top layer of coal mining areas is significantly higher (25.21%) compared to non-coal mining areas, although deeper layers exhibit lower SWC, indicating altered moisture dynamics due to underground mining disturbances. Coal mining areas show greater spatial and temporal variability in SWC, suggesting increased sensitivity to moisture fluctuations, which complicates water management practices. Additionally, underground mining activities introduce more intense effects on the relationship between SWC and topographic factors (i.e., GCVR across soil profile of 0–60 cm; slope at depth of 50 cm) or edaphic factors (i.e., soil organic matter and available potassium at depth of 30 cm; pH at depth of 50 cm) compared to non-coal mining areas. This variability is evident in the temporal shifts from positive to negative correlations, particularly in coal mining areas, reflecting modifications in both soil physical and chemical properties resulting from mining activities. In contrast, non-coal mining areas maintain a more stable moisture regime, likely due to preserved natural soil structures and processes. These contrasting findings emphasize the necessity for tailored management strategies in coal mining regions to address the unique challenges posed by altered soil characteristics and water dynamics. [ABSTRACT FROM AUTHOR]

A power-law formulation rooted in percolation theory has proven effective in depicting the vertical distribution of soil organic carbon (SOC) in temperate forest subsoils. While the model suggests the solute as the primary factor distributing SOC, this may not hold true in the surface soil in which roots contribute significantly to the SOC. This study in the Changbai Mountains Mixed Forests ecoregion (CMMF) evaluates the SOC profiles in three forests to assess the model's efficacy throughout the soil column. Prediction of the SOC profile based on the regional average values was also assessed using field data. The observed scaling aligned well with predictions in mixed broadleaved and broadleaved Korean pine mixed forests, but disparities emerged in birch forest, possibly due to waterlogging. The predicted SOC levels correlate strongly with the field data and align well with the normalized average SOC levels. The findings suggest that the model remains applicable in the CMMF when considering root-derived carbon. However, the hindrance of solute transport may have a greater impact than roots do. The spatial heterogeneity of the SOC means that a single predicted SOC value at a specific depth may not fit all sites, but the overall agreement highlights the potential of the model for predicting the average or representative SOC profiles, which could further aid in regional-scale carbon stock estimation. [ABSTRACT FROM AUTHOR]

Background: Vegetation roots are considered to play an effective role in controlling soil erosion by benefiting soil hydrology and mechanical properties. However, the correlation between soil hydrology and the mechanical features associated with the variation root system under different vegetation types remains poorly understood. Methods: We conducted dye-tracer infiltration to classify water flow behavior and indoor experiments (including tests on soil bulk density, soil organic carbon, mean weight diameter, soil cohesion, root density, etc.) to interpret variation patterns in three forest systems (coniferous and broad-leaved mixed forest, CBF; coniferous forest, CF; Phyllostachys edulis, PF) and fallow land (FL). Results: Based on the soil dye-tracer infiltration results, the largest dyeing area was observed in CF (36.96%), but CF also had the lowest infiltration rate (60.3 mm·min−1). The soil under CBF had the highest shear strength, approximately 25% higher than other vegetation types. CF exhibited the highest aggregate stability, surpassing CBF by 98.55%, PF by 34.31%, and FL by 407.41%, respectively. Additionally, PF forests showed the greatest root biomass and length. The results of correlation analysis and PCA reveal complex relationships among hydrological and mechanical soil traits. Specifically, soil cohesion does not exhibit significant correlations with hydrological traits such as the dyeing area, while traits like MWD and PAD show either positive or negative associations with hydrological traits. Root traits generally exhibit positive relationships with soil mechanical traits, with limited significant correlations observed with hydrological traits. Conversely, we found that root biomass contributes significantly to the dyeing area (accounting for 51.48%). Conclusions: Our findings indicate that the reforestation system is a successful approach for conserving water and reducing erosion by increasing soil-aggregated stability and shear strength, causing water redistribution to be more homogenized across the whole soil profile. [ABSTRACT FROM AUTHOR]

To avoid flooding and erosion hazards, post-fire management actions are essential in Mediterranean forests after severe wildfires. In this regard, mulching is the most common action but some mulch materials, such as straw, may lead to adverse impacts in burned forests. The use of yellow mistletoe fruits (Loranthus europaeus Jacq., hereafter "LE") for the production of biodegradable mulch and its effectiveness in post-fire hydrology have never been studied. To fill this gap, this study has evaluated surface runoff and rainsplash erosion in a pine forest in Central Eastern Spain burned by a wildfire and mulched by a mixture of LE fruits and straw (with or without adding clay particles) using a portable rainfall simulator. Compared to untreated sites, runoff increased in burned and mulched soils (by 13.6% for the mixture without clay and by 17.2% when clay was added, in the latter case significantly). This increase was mainly due to the compact layer created by mulch application on the soil surface. However, the peak flow and the time to peak were lower in mulched soils (on average by 32.7% and 60.5%, significantly only for the mulch mixture without clay), thus indicating that, in these soils, peak runoff takes longer and its maximum value is lower compared to untreated sites. Soil erosion noticeably and significantly decreased (up to 97%) in mulched areas in comparison to untreated sites without significant differences between the two mixtures. Overall, this study indicates to land managers that soil mulching with a mixture of Loranthus europaeus Jacq. and straw is an effective post-fire management action to reduce the soil erosion risk after a wildfire. [ABSTRACT FROM AUTHOR]

Real-time in situ measurements are increasingly being used to improve the estimations of simulation models via data assimilation techniques such as particle filter. However, models that describe complex processes such as water flow contain a large number of parameters while the data available are typically very limited. In such situations, applying particle filter to a large, fixed set of parameters chosen a priori can lead to unstable behavior, i.e., inconsistent adjustment of some of the parameters that have only limited impact on the states that are being measured. To prevent this, in this study correlation-based variable selection is embedded in the particle filter, so that at each step only a subset of the most influential parameters is adjusted. The particle filter used in this study includes genetic algorithm operators and Monte Carlo Markov Chain for alleviating filter degeneracy and sample impoverishment. The proposed method was applied to a water flow model (Hydrus-1D) in which soil water content at various depths and soil hydraulic parameters were updated. Two case studies are presented. Overall, the proposed method yielded parameters and states estimates that were more accurate and more consistent than those obtained when adjusting all the parameters. Furthermore, the results show that the higher the influence of a parameter on the model output under the current conditions, the better the estimation of this parameter is. [ABSTRACT FROM AUTHOR]

The mountain pine beetle epidemic in British Columbia has covered 18.1 million hectares of forest land showing the potential for exceptionally large-scale disturbance to influence watershed hydrology. Pine stands killed by the epidemic can experience reduced levels of evapotranspiration and precipitation interception, which can translate into an increase in soil moisture as observed by some forest practitioners during salvage logging in the epicenter of the outbreak. They reported the replacement of summer ground, dry firm soil areas, with winter ground areas identified by having wetter, less firm soils upon which forestry equipment operation is difficult or impossible before winter freeze-up. To decrease the likelihood of soil disturbance from harvesting, a set of hazard indicators was developed to predict wet ground areas in areas heavily infested by the mountain pine beetle. Hazard indicators were based on available GIS data, aerial photographs, and local knowledge. Indicators were selected by an iterative process that began with office-based selection of potential indicators, model development and prediction, field verification, and model refinement to select those indicators that explained most field data variability. Findings indicate that the most effective indicators were lodgepole pine content, understory, drainage density, soil texture, and the topographic index. [ABSTRACT FROM AUTHOR]

A phenomenon causing instability of soil structure and associated hydraulic properties in recently tilled soils is aggregate fragmentation induced by wetting and drying cycles. We analyzed data from three experiments in Puerto Rico, the UK and China measuring fragmentation and resulting evolution of aggregate size distributions during successive wetting and drying cycles in heavy textured soils. Aggregate distributions were represented as the cumulative fraction F of aggregates passing through successively larger sieve sizes X. To a good approximation, all distributions exhibited similarity in that the aggregate diameter X(F) corresponding to F in a given test distribution was always a characteristic multiple α ¯ of X(F) in a fixed reference distribution, where α ¯ for a distribution was calculated as its mean weight aggregate diameter (MWD) divided by the MWD of the reference distribution. In most cases, α ¯ for a given soil varied inversely with the square of the number of wetting and drying cycles. For different soils of similar initial aggregate sizes, α ¯ for a given wet–dry cycle decreased with increasing activity coefficient, reflecting the enhancing effect of soil shrink–swell potential on fragmentation. Results highlight usefulness of the van Bavel mean weight diameter as a natural scaling parameter for characterizing aggregate distributions. [ABSTRACT FROM AUTHOR]

Improved mechanistic understanding of soil methane (CH4) exchange responses to shifts in soil moisture and temperature in forest ecosystems is pivotal to reducing uncertainty in estimates of the soil-atmospheric CH4 budget under climate change. We investigated the mechanism behind the effects of soil moisture and temperature shifts on soil CH4 fluxes under laboratory conditions. Soils from the Huai River Basin in China, an area that experiences frequent hydrological shifts, were sampled from two consecutive depths (0–20 and 20–50 cm) and incubated for 2 weeks under different combinations of soil moisture and temperature. Soils from both depths showed an increase in soil moisture and temperature-dependent cumulative CH4 fluxes. CH4 production rates incubated in different moisture and temperature in surface soil ranged from 1.27 to 2.18 ng g−1 d−1, and that of subsurface soil ranged from 1.18 to 2.34 ng g−1 d−1. The Q10 range for soil CH4 efflux rates was 1.04–1.37. For surface soils, the relative abundance and diversity of methanotrophs decreased with moisture increase when incubated at 5 °C, while it increased with moisture increase when incubated at 15 and 30 °C. For subsurface soils, the relative abundance and diversity of methanotrophs in all samples decreased with moisture increase. However, there was no significant difference in the diversity of methanogens between the two soil depths, while the relative abundance of methanogens in both depths soils increased with temperature increase when incubated at 150% water-filled pore space (WFPS). Microbial community composition exhibited large variations in post incubation samples except for one treatment based on the surface soils incubated at 15 °C, which showed a decrease in the total and unique species number of methanotrophs with moisture increase. In contrast, the unique species number of methanogens in surface soils increased with moisture increase. The analysis of distance-based redundancy analysis (db-RDA) showed that soil pH, dissolved organic carbon (DOC), dissolved organic nitrogen (DON), microbial biomass carbon (MBC), NO3−-N, and NH4+-N mainly performed a significant effect on methanotrophs community composition when incubated at 60% WFPS, while they performed a significant effect on methanogens community composition when incubated at 150% WFPS. Overall, our findings emphasized the vital function of soil hydrology in triggering CH4 efflux from subtropical plantation forest soils under future climate change. [ABSTRACT FROM AUTHOR]

Direct measurement of unsaturated hydraulic parameters is costly and time-consuming. Pedotransfer functions (PTFs) are typically developed to estimate soil hydraulic properties from readily available soil attributes. For the first time, in this study, we developed PTFs to estimate the soil hydraulic conductivity (log(K)) directly from measured data. We adopted the pseudo continuous neural network PTF (PCNN-PTF) approach and assessed its accuracy and reliability using two independent data sets with hydraulic conductivity measured via the evaporation method. The primary data set contained 150 international soils (6963 measured data pairs), and the second dataset consisted of 79 repacked Turkish soil samples (1340 measured data pairs). Four models with different combinations of the input attributes, including soil texture (sand, silt, clay), bulk density (BD), and organic matter content (SOM), were developed. The best performing international (root mean square error, RMSE = 0.520) and local (RMSE = 0.317) PTFs only had soil texture information as inputs when developed and tested using the same data set to estimate log(K). However, adding BD and SOM as input parameters increased the reliability of the international PCNN-PTFs when the Turkish data set was used as the test data set. We observed an overall improvement in the performance of PTFs with the increasing number of data points per soil textural class. The PCNN-PTFs consistently performed high across tension ranges when developed and tested using the international data set. Incorporating the Turkish data set into PTF development substantially improved the accuracy of the PTFs (on average close to 60% reduction in RMSE). Consequently, we recommend integrating local HYPROPTM (Hydraulic Property Analyzer, Meter Group Inc., USA) data sets into the international data set used in this study and retraining the PCNN-PTFs to enhance their performance for that specific region. [ABSTRACT FROM AUTHOR]

Soil creep is common along the hillslopes of the tropical Andes of Colombia, where very heterogeneous soils develop on old debris flow deposits and are subjected to abundant rainfall with a bimodal annual regime. In particular, the western hillside of the city of Medellín, Colombia, is comprised of a series of debris and earth flow deposits in which landslides and soil creep are common. To explore linkages between soil creep and hydrology, we selected an experimental site in the western hillslope of the Medellín valley to assess the behavior of water within the soil mass, its relationship with rainfall, and its connection with soil displacement. In experimental plots, we systematically measured runoff, percolation, water table levels, and volumetric water content, for a period of almost 2 years; we also conducted several alti-planimetric positioning surveys to estimate relative displacements of the soil surface. Moisture content of the soil remained above field capacity for most of the year (~68% of the time) and active and quasi-permanent lateral subsurface flow occurred within the upper 80 cm of the profile. The shallow flow likely facilitates the downslope movement. Additionally, our results suggest that displacement magnitudes are largest during the wet season of September–October–November, when a highly humid soil experiences changes in water content, so it is during this time that the effects of expansion / contraction of the soil particles (associated to wetting / drying cycles) contribute the most to the movement. This observational study represents a contribution to the understanding of soil creep in tropical hillslopes, where it responds to the wetting / drying cycles, with the particularities of a rainy weather (>1500 mm/year), warm temperatures (~22 °C on average), and a bimodal precipitation seasonality. [ABSTRACT FROM AUTHOR]

The effects of soil data sources on the performance of hydrologic model simulations remain poorly understood compared to the effects of other data inputs. This paper investigated the effects of different soil datasets in simulating streamflow and sediment yield using the Soil and Water Assessment Tool (SWAT). Furthermore, potential improvements in watershed simulations were evaluated by integrating field measured soil parameters (user soil) with global soil datasets. Five soil datasets, namely user soil, AfSIS (Africa Soil Information Service), Food and Agriculture Organization (FAO), and two integrated soils (User-AfSIS and User-FAO) produced by assimilating the user soil with the latter two, were evaluated. The benefits of the user soil in improving streamflow simulations to better replicate observed flow were greater at daily time steps than monthly. Compared to the individual AfSIS and FAO soils, their integration with the user soil improved the daily Nash-Sutcliffe Efficiency (NSE) by 0.19 and 0.17 during model calibration, respectively. Overall, all soils performed relatively similar with monthly sediment yield simulations, which were improved when it was integrated with the user soil. Based on selected rainfall events, the watershed response time was less than 1 h, which suggests that the watershed has a quick runoff response time. This paper showed that streamflow and sediment yield simulation performances of freely available global soil datasets can be improved through integration with locally measured soil information. This study demonstrated that the availability of local soil information is critical for daily hydrologic model simulations, which is critical for planning effective soil and water management practices at plot and field scales. [ABSTRACT FROM AUTHOR]

Soil hydrology determines the water–soil–plant interactions in the Earth's system, because porous medium acts as an interface within the atmosphere and lithosphere, regulates main processes such as runoff discharge, aquifer recharge, movement of water and solutes into the soil and, ultimately, the amount of water retained and available for plants growth. Soil hydrology can be strongly affected by land management. Therefore, investigations aimed at assessing the impact of land management changes on soil hydrology are necessary, especially with a view to optimize water resources. This Special Issue collects 12 original contributions addressing the state of the art of soil hydrology for sustainable land management. These contributions cover a wide range of topics including (i) effects of land-use change, (ii) water use efficiency, (iii) erosion risk, (iv) solute transport, and (v) new methods and devices for improved characterization of soil physical and hydraulic properties. They involve both field and laboratory experiments, as well as modelling studies. Also, different spatial scales, i.e., from the field- to regional-scales, as well as a wide range of geographic regions are also covered. The collection of these manuscripts presented in this Special Issue provides a relevant knowledge contribution for effective saving water resources and sustainable land management. [ABSTRACT FROM AUTHOR]

This study focuses on the reliable parametrization of the full Soil Water Retention Curve (SWRC) from saturation to oven-dryness using high resolution but limited range measured water retention data by the Hydraulic Property Analyzer (HYPROP) system. We studied the performance of five unimodal water retention models including the Brooks and Corey model (BC model), the Fredlund and Xing model (FX model), the Kosugi model (K model), the van Genuchten constrained model with four free parameters (VG model), and the van Genuchten unconstrained model with five free parameters (VGm model). In addition, eleven alternative expressions including Peters–Durner–Iden (PDI), bimodal, and bimodal-PDI variants of the original models were evaluated. We used a data set consisting of 94 soil samples from Turkey and the United States with high-resolution measured data (a total of 9264 measured water retention data pairs) mainly via the HYPROP system and supplemented for some samples with measured dry-end data using the WP4C instrument. Among unimodal expressions, the FX and the K models with the Mean Absolute Error (MAE) values equal to 0.005 cm3 cm−3 and 0.015 cm3 cm−3 have the highest and the lowest accuracy, respectively. Overall, the alternative variants provided a better fit than the unimodal expressions. The unimodal models, except for the FX model, fail to provide reliable dry-end estimations using HYPROP data (average MAE: 0.041 cm3 cm−3, average r: 0.52). Our results suggested that only models that account for the zero water content at the oven dryness and properly shift from the middle range to dry-end (i.e., the FX model and PDI variants) can adequately represent the full SWRC using typical data obtained via the HYPROP system. [ABSTRACT FROM AUTHOR]

A high-resolution soil water retention data set (81 repacked soil samples with 7729 observations) measured by the HYPROP system was used to develop and evaluate the performance of regression parametric pedotransfer functions (PTFs). A total of sixteen soil hydraulic models were evaluated including five unimodal water retention expressions of Brooks and Corey (BC model), Fredlund and Xing (FX model), Kosugi (K model), van Genuchten with four free parameters (VG model) and van Genuchten with five free parameters (VGm model). In addition, eleven bimodal, Peters–Durner–Iden (PDI) and bimodal-PDI variants of the original expressions were studied. Six modeling scenarios (S1 to S6) were examined with different combinations of the following input predictors: soil texture (percentages of sand, silt and clay), soil bulk density, organic matter content, percent of stable aggregates and saturated water content (θs). Although a majority of the model parameters showed low correlations with basic soil properties, most of the parametric PTFs provided reasonable water content estimations. The VGm parametric PTF with an RMSE of 0.034 cm3 cm−3 was the best PTF when all input predictors were considered. When averaged across modeling scenarios, the PDI variant of the K model with an RMSE of 0.045 cm3 cm−3 showed the highest performance. The best performance of all models occurred at S6 when θs was considered as an additional input predictor. The second-best performance for 11 out of the 16 models belonged to S1 with soil textural components as the only inputs. Our results do not recommend the development of parametric PTFs using bimodal variants because of their poor performance, which is attributed to their high number of free parameters. [ABSTRACT FROM AUTHOR]

This study discusses the influence of soil compaction on runoff generation with a special focus on forested Andosol sites. Because of their typical soil physical characteristics (low bulk density, high pore volumes) and the existent land use, these areas are expected to show low to no measurable overland flow during heavy rainfall events. However, due to heavy machinery traffic in the course of forestry actions and pumice excavations, skid trails have been established. Here, a distinct shift of soil dry bulk density (DBD) was observable, using a detailed soil mapping and data interpolation in order to generate in-depth DBD-cross profiles. Additionally, infiltration measurements and rainfall simulations (I = 45 mm·h−1, t = 30 min) were conducted to evaluate effects of observed soil compaction on infiltration rates and overland flow formation. Results show that soil compaction was increased by 21% on average in skid trail wheel ruts. As a consequence, observed runoff was 8.5-times higher on skid trails, while saturated hydraulic conductivity was diminished by 36%. These findings show, that soil compaction leads to a higher possibility of runoff formation during heavy rainfall events, especially at sites which showed initial conditions with presumably low tendencies of runoff formation. [ABSTRACT FROM AUTHOR]