In the last few decades, riverine sediment flux to the coastal zones has been decreasing globally. The sediment flux from rivers to seas is usually estimated based on the lowermost gauging stations free of tides in the rivers, for example the Yangtze River. Knowledge of decadal sediment budget and the morphological evolution in the tidal reach is still limited. Here, using historical bathymetry of the tidal reach of the Yangtze, the changes in the sediment budget and local morphology in this reach for three periods between 1970 and 2008 were investigated. In terms of input sediment flux, Period I 1970–1992 is a relatively steady period, Period II 1992–2003 is a decline period with a significant decrease in the sediment flux, and Period III 2003–2008 is a decline period after the closure of the Three Gorges Dam (TGD). The reach was nearly in equilibrium during Period I. Net erosion occurred in the reach during both the pre- and post-TGD decline periods 1992–2003 and 2003–2008, with annual erosion of approximately 65 and 37 Mt/yr, respectively. The contribution of the annual erosion in the reach to the annual sediment flux at the downstream end of the reach increased from around 16.9% during 1992–2003 to 19.1% during 2003–2008. These changes in the sediment budget are closely related to the decrease in the input sediment flux, coarsening of the sediment grain size after the closure of the TGD, and changes in the riverine water flux and tidal conditions. Characterized by a length scale of 4–32 km, local deposition/erosion patterns were quite complex, which relates to the complexity of the local geometry, bathymetry and flow condition. The horizontal location of the thalweg of the reach had limited changes during 1992–2008, likely owing to the fixed riverbank due to human intervention.

Understanding the spatial distribution and controlling factors of soil organic carbon (SOC) at different scales is essential for an accurate estimation of soil organic carbon stocks. Furthermore, this understanding is vital for evaluating the impact of soil management on both soil quality and climate change. This study was conducted in a Loess revegetated small watershed and the effects of the topography and vegetation factors on the content and distribution of SOC at different soil depths were evaluated. Soil profiles (0–200 cm; n = 122) were sampled that represent six vegetation types (i.e., natural mixed forests, artificial mixed forests, artificial forests with a single tree species, shrubbery, and grassland) and four topographic factors (i.e., elevation, slope gradient, slope position, and slope aspect). The following results were obtained: (1) The mean SOC of the 200 cm soil profile ranged from 2.34 g kg−1 to 5.70 g kg−1, decreasing with increasing soil depth. (2) The interactions between vegetation type and topography and soil depth significantly impacted SOC (P < 0.05). Significant differences in the SOC content (P < 0.05) were also found for slope gradient, slope position, slope aspect, and elevation for 0–200, 0–160, 0–100, and 0–200 cm, respectively. (3) The relative contribution of topographic factors to the SOC content exceeded that of vegetation type in entire soil profile. Topography was the dominant factor controlling the spatial distribution of SOC in the studied small watershed. Therefore, topographic factors should be considered more than vegetation type for an accurate estimation of SOC storage in a revegetated small watershed. This is particularly important for the complicated topography of the loess-gully region.

Information obtained from landform classification is fundamental for understanding physical, chemical, and biological soil processes. Digital elevation models (DEMs) can be used for landform classification using a geomorphic pattern recognition and classification approach such as geomorphons. In this study, we used geomorphons to predict soil types of the Uasin Gishu Plateau in western Kenya with the aim of improving the existing soil type maps. We ran the geomorphons classification on the 30 m Shuttle Radar Topographic Mission (SRTM) DEM using the module r.geomorphons “add-on” in GRASS GIS with look up distance (L) values of 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 cells (300 m to 3,000 m) and flatness threshold values of 2, 0.5 and 0.01 degrees. We grouped the resulting geomorphons into three classes: upland summits, upland midslopes, and bottomlands. We then assigned soil types according to the World Reference Base soil classification system to these three landscape positions after dividing the study area into the Lower Plateau and the Upper Plateau based on elevation and geomorphology. The predicted soil types were quantitatively evaluated against 50 soil point observations based on overall accuracy, precision, recall and Cohen’s kappa coefficient (k) metrics. Evaluation results showed that an L value of 20 cells performed best (k = 0.52; overall accuracy = 0.62) followed by an L value of 30 cells (k = 0.50; overall accuracy = 0.58). L values of 60, 70 and 80 cells performed worse (k = 0.35; overall accuracy = 0.48). Although an L value of 20 cells performed slightly better than an L value of 30 cells, the L value of 30 cells better captured the geomorphology and soil-landscape relationships based on our own expert knowledge, legacy data, and the fact that the bottomlands pattern was more continuous for an L value of 30 cells than for an L value of 20 cells. Upland summits occurred over ~ 32% of the plateau and were occupied by Nitisols on the Upper Plateau and Ferralsols on the Lower Plateau. Upland midslopes occurred over ~ 42% of the plateau and were occupied by Acrisols on the Upper Plateau and Acrisols/Ferralsols on the Lower Plateau. Bottomlands occurred over ~ 26% of the plateau and were occupied by Luvisols/Gleysols on both the Upper and Lower Plateau. Geomorphons, as a method of landform classification, correlated to geomorpho-pedological processes and captured soil variations and differences in the study area. The approach is computationally efficient and can be used for large areas, but is limited in that it only classifies landscapes according to shape. This means that the algorithm does not separate or identify soil types with different parent materials occurring within one landform class. Thus, Regosols and Cambisols on very steep slopes and Acrisols and Ferralsols on gentle slopes could not be separated.

Soil surface roughness (SSR) significantly influences hydrological and erosion processes under different conditions. Land use and its adjustment may greatly influence SSR via altering near soil surface characteristics and tillage operations, but few studies have been performed to quantify their effects on soil surface roughness. This study was conducted to investigate the variation in soil surface roughness under different land use types, and identify the main influencing factors contributing to these changes in a small watershed on the Loess Plateau, China. Eighteen sites were selected from five typical land use types (cropland, grassland, shrub land, orchard, and woodland) to measure random roughness (RR) by a photogrammetric method. The results showed that random roughness was greatly affected by land use types, plant species, and tillage operations. The mean RR under different land use types ranged from 9.47 to 10.06 mm. Woodland had the maximum RR, followed by cropland, shrub land, orchard, and grassland. For a given land use type, RR differed significantly between different plant species. The variation in random roughness was greatly influenced by the changes in near soil surface characteristics and tillage operations induced by land use adjustment. For the testing sites without tillage operations, RR increased linearly with soil median grain size, sand content, organic matter content, plant litter coverage, litter thickness, and litter density, while it decreased linearly with soil cohesion, silt content, and clay content. For the testing sites with tillage operations, RR was dominated by tillage operations. These results are helpful to understand the potential effects of vegetation restoration on hydrological and erosion processes on hillslopes in arid and semi-arid regions.

Many predictive soil mapping (PSM) methods encounter two problems. One is how to construct a similarity index that can indicate not only the similarity of an environmental covariate between sites but also the directional difference of the covariate itself between sites and predict the soil property values beyond the range of sample values. Another is how to determine which soil samples should be used when estimating the soil property value at an unknown site. We propose a new asymmetrical environmental contrast index between an unknown site and a sample site to address the first problem, based on which we developed an enhancive predictive coefficient (EPC)-based soil mapping (EPSM) method. EPC integrates the contrasts of associated environmental principal component covariates by the weights of the covariates influencing a certain soil property. A member recruiting process was programmed to determine the calculating samples for an unknown site after conducting an uncertainty threshold (ut) test for all the sample sites. We applied the EPSM method to five data groups with different numbers and distributions of sample sites for prediction. The results showed that the EPSM method performs better than the soil-land inference model (SoLIM) method regardless the value of ut and thus can be used to estimate the soil property values well at most unknown sites. The method is especially valid when the unknown sites are spatially far from the sample sites and when sample sites are limited in number or spatially distributed at a local area. Our study suggests that the EPSM method is an effective PSM method that can be widely used in soil mapping.

Due to the economic benefits, land use change (e.g. deforest to tea or fruit plantation) has been widely occurred in the south-eastern hilly area of China. This may stimulate serious soil nitrogen (N) losses due to large fertilizer inputs (about 1–2 times of that in regular rice-wheat rotation). Therefore, we investigated the soil N2O fluxes and leachate NO3–-N concentrations and their responses to multiple factors on a tea garden (TG) hillslope and an adjacent bamboo forest (BF) hillslope. Soil N2O fluxes and leachate NO3–-N concentrations on the TG hillslope were 3.28 and 4.24 times of those on the BF hillslope, respectively. Soil N2O fluxes measured in spring were the greatest while those measured in winter were the lowest. However, the measured leachate NO3–-N concentrations were the greatest in winter but the lowest in summer. On both hillslopes, soil temperature (ST) and precipitation during the previous seven days (API7) were positively related to soil N2O fluxes but negatively related to leachate NO3–-N concentrations, while the ground water table depth was opposite. Soil water content (SWC) and the ratio of SWC/field capacity (SWC/FC) negatively influenced leachate NO3–-N concentrations on both hillslopes. Positive influences of SWC and SWC/FC on soil N2O fluxes were observed on the TG hillslope, while quadratic relationships were observed on the BF hillslope. Thresholds of ST and API7 were existed in the controlling the spatial variations of soil N2O fluxes and leachate NO3–-N concentrations on both hillslopes. When ST was > 9.5 °C, spatial variations in soil N2O fluxes were controlled by topography, soil properties and soil hydrological parameters on both hillslopes. Similarly, when API7 were < 58.0 mm, the spatial variations in leachate NO3–-N concentrations were also influenced by these factors on both hillslopes. Finding of this study will supplement the knowledge of soil N2O emissions and NO3–-N leaching from the tea planation and bamboo forest.

Quantifying annual soil CO2 emissions and the effects of physical and geochemical factors on soil CO2 efflux will improve the carbon budget estimates, as well as enhance predictions of how soil CO2 emission will response to climate change in arid areas. To data, variability in soil respiration rates caused by land use conversion in the desert-oasis ecoregion of Northwest China remains poorly characterized, especially the contribution of cold season (November-February) CO2 emission. Soil respiration was measured in a Haloxylon ammodendron desert shrubland, a Zea mays cropland, a Populus gansuensis forest, and a Tamarix chinensis Lour wetland using a LI-COR 8100 Soil Respiration Observation System from April 2016 to March 2019. Annual soil CO2 emissions totaled 176, 778, 918, and 397 g C m−2 in the desert shrubland, cropland, forest, and wetland, respectively. The ratio of cold season CO2 emissions to the annual varied from 6 to 15% across ecosystems. Therefore, ignoring cold season CO2 emissions would lead to underestimates of carbon losses in the desert-oasis ecoregion. The soil respiration rate at 10 °C was influenced by soil organic carbon content in all four ecosystems. In the cropland and forest, soil respiration rate was affected by the interaction of soil moisture and soil temperature, while in the wetland and desert shrubland, soil respiration was sensitive to a single factor, soil temperature. Land use conversion induced differences in organic matter accumulation, soil temperature, and soil moisture, and as a consequence, produced variability in soil respiration rates across the desert-oasis ecoregion.

The negative hydrological effects of wildfire are very difficult to predict in Mediterranean forest ecosystems, due the intrinsic climate and soil characteristics of these areas. Among the hydrological models simulating surface runoff and soil erosion in these environmental contexts, the semi-empirical Morgan-Morgan-Finney (MMF) model can ensure the representation of the main physical processes, while offering ease of use and limiting the number of input parameters. However, literature reports very few modelling studies using MMF in burned areas of the Mediterranean environment with or without post-fire rehabilitation measures. To fill this gap, the capacity of the MMF model to predict the seasonal surface runoff and soil loss in a Mediterranean forest was verified and improved for unburned plots and areas affected by a wildfire, with and without post-fire straw mulch treatment. The application of MMF with default input parameters (set up according to the original guidelines of the model’s developers) led to poor performance. Conversely, after introducing some changes in input data for both the hydrological and erosive components (seasonal values of evapotranspiration, reduction of the soil hydrological depth, including soil water repellency effects in burned soils, and modelling erosive precipitation only), MMF was able to predict seasonal runoff volumes and soil loss with good reliability in all the experimented conditions. This modelling experiment has shown the capacity of the MMF model to simulate the seasonal hydrological and erosion response of the experimental unburned and burned soils of Mediterranean semi-arid forests. Although more research is needed to validate the model's prediction capacity in these conditions, the use of MMF as a management tool may be suggested to predict the hydrogeological risk in these delicate ecosystems threatened by wildfire, as well as to evaluate the potential efficiency of soil treatments after fire.

The semiarid region of Brazil undergoes constant changes in land use due to the process of deforestation and high water seasonality, represented among other variables by a decline in the soil moisture content. In this study, the influence of land use on the soil moisture dynamics is analysed. For this purpose, three experimental sites were evaluated, characterised by different types of land use: an agroecosystem of forage cactus, a deforested environment and an area of Caatinga vegetation, located in the semiarid central hinterlands of Brazil. Calibration of the Diviner2000® capacitive probes was carried out using the relationship between the soil volumetric moisture content (θv), obtained by the gravimetric method, and the relative frequency readings of the probes. Weekly measurements of the moisture content were taken at 22 points at depths of 0.00–0.60 m from November 2014 to October 2017, providing 157 sampled days. The mean values and standard deviations of the θv variable for the three surfaces were analysed over twelve periods, and grouped according to the local water regime into rainy, dry and transitional. To analyse the temporal stability of θv, the relative difference and the Spearman correlation matrix were calculated. Finally, multivariate principal component analysis (PCA) was used to identify associations between the mean values of θv and physical properties in the different soil layers. Based on the results, the local calibration curves presented significant coefficients of determination, showing that the equations can be used for reliable estimates of θv. The θv was higher in the Caatinga (0.086 m3 m−3), intermediate in the forage cactus (0.064 m3 m−3) and lower in the deforested area (0.045 m3 m−3). Changes in land use influence the spatial variability of θv in the soil layers, which responded to the local rainfall regime, especially in the upper layers (0.05–0.25 m). Significant differences in θv between soil surface coverage occurred during the dry sub-periods and the transition periods, when the Caatinga was superior to the other areas. The temporal stability analysis identified the forage cactus area as the most representative location for θv estimates, while the Spearman correlation matrix detected the more-unstable areas of moisture, with persistent moisture patterns between the dry sub-periods and transition periods only. Associations between moisture and different soil properties were affected by soil surface coverage and soil layer depth. All the proprieties explained moisture distribution along the profile. It can be concluded that converting the Caatinga vegetation into other soil surface coverages changes soil-moisture distribution patterns, resulting in a reduction in θv of 26% and 47% for forage cactus and deforested areas, respectively. Therefore, the establishment of forage cactus in current deforested areas of the Brazilian semiarid may attenuate the temporal variability and reduction of soil moisture compared to bare soil surfaces.

Soil respiration is the second largest flux of carbon between terrestrial ecosystems and the atmosphere and it is substantially sensitive to climate change. Monitoring CO2 efflux and its upscaling from field measurements to the ecosystem level is a complex task, due to the high spatial and temporal variability of the fluxes. Human intervention, e.g. through forest harvest, may change both CO2 efflux and its spatial heterogeneity. The objective of our study was to quantify spatial heterogeneity of soil CO2 efflux within and among plots distributed within a topographically variable sessile oak forest stand before and after harvesting. Forest floor CO2 efflux, soil temperature and soil water content were measured monthly in a sessile oak forest during two growing seasons: one before and one after harvesting. Stand structure characteristics (gap fraction, leaf area index, tree number and size) and the amount of understory also were determined. Relationships between individual variables and spatial heterogeneity were analyzed. The small-scale spatial heterogeneity (expresses as the coefficient of variation) of forest floor CO2 efflux and soil water content (SWC) in the undisturbed forest was low, at maximum 0.22 and 0.13, respectively. Studied variables had no effect on spatial heterogeneity of forest floor CO2 efflux except for the amount of understorey vegetation which positively correlated with forest floor CO2 efflux. Although the studied forest was situated in topographically variable terrain, we observed that inter-plot heterogeneity of forest floor CO2 efflux was lower than that within plots. Stand harvest increased the intra-plot heterogeneity of forest floor CO2 efflux but did not affect the inter-plot heterogeneity. This leads to the conclusion that the number of positions within an individual plot should increase after harvest but the number of plots may remain unchanged to determine adequately ecosystem forest floor CO2 efflux.

Changes in carbon (C) and nitrogen (N) reserves reflect the impacts of land use and management. The objective was to evaluate the changes in organic matter stocks and quality in an Oxisol under intensive vegetable cultivation in the Brazilian Cerrado region. Four areas were selected: one under Cerrado vegetation (CV) and three under vegetable production with 15 (VG15), 20 (VG20) and 30 (VG30) years of cultivation. Soil samples were collected for the determination of total C (TC) and total N (TN) in soil organic matter fractions and the biochemical composition of particulate organic matter (POM) and mineral-associated organic matter (MOM). The smallest C stocks were observed on VG30, whereas the CV area had the highest values. The TN stocks were similar across treatments. The levels of labile C decreased with cultivation time. Increases and reductions in carbohydrate and lignin ratios in POM and MOM occurred in VG15 and VG20, respectively, with POM being more sensitive to changes in land use. There was greater similarity between VG15 and VG20, but differences between CV and VG30. There was a correlation between higher labile reserves (labile C and carbohydrates) and areas with shorter land use and between Cmic and agricultural use for 30 years. There was also a negative correlation between soil nutrients and the total and MOM C and N contents as well as the MOM carbohydrate levels, and there was also a negative correlation between Cmic and TC. The intensive use of Oxisols promoted a reduction in soil organic matter stocks and altered their quality.

The sediment transport capacity (Tc) is an important parameter for analysing and controlling soil erosion processes. However, few studies have investigated the Tc of soils containing gravel (grain sizes of >2 mm) on steep slopes. Colluvial deposits on steep slopes in benggang are composed of loose materials with large amounts of gravel. This study aimed to investigate the effects of gravel content on the Tc of overland flow using colluvial deposits with a range of slope gradients and flow discharges in a nonerodible flume (4 m long, 0.12 m wide and 0.1 m high). The experiments were carried out using six gravel mass contents (0, 10, 20, 30, 40, and 50%), four slope gradients (18, 36, 57, and 84%), and four flow discharges (0. 56, 1.11, 2.22, and 4.44 × 10-3 m2 s−1). The experimental results revealed that the measured Tc increased linearly as the gravel content increased. The effects of the slope gradient, flow discharge and gravel content on Tc were significant (p < 0.01). Tc increased following power functions either with slope gradient, flow discharge and gravel content (coefficient of model determination (r2) = 0.96 and Nash-Sutcliffe model efficiency (NSE) = 0.96), or with slope gradient, flow discharge and sediment median grain size (d50) (r2 = 0.98 and NSE = 0.98). The two established power functions facilitated the prediction of the Tc of colluvial deposits in this study. However, the power functions overestimated the predicted Tc values when the measured Tc was less than 1 kg m−1 s−1 and underestimated the values when the measured Tc ranged from 2 to 4 kg m−1 s−1. These findings are helpful for improving the simulation of erosion processes in colluvial deposits and deepening the understanding of erosion mechanisms in soil and rock mixtures. Moreover, the relationship of hydrodynamic variables with Tc on colluvial deposits remains to be investigated in additional in-depth studies.

Hematite (Hm) and goethite (Gt) in tropical and subtropical soils stand out as indicators of different pedogenic and geochemical environments. The objective of this work was to characterize the geochemical and crystallographic changes of Hm and Gt in profiles of bichromic soils as a tool to interpret the xanthization process (yellowing) in the superficial horizons, which were higher in organic matter. Soil profiles from three sedimentary rocks (claystone, sandstone and varvite) were selected. The clay fractions of the soil horizons and the Fe-concentrated rock samples (varvite and sandstone were ground in a disc mill, sieved with a 325 mesh, and treated with 20% HF) were subjected to modified and less-aggressive citrate-bicarbonate-dithionite (CBD) extractions (Fe-release kinetics) and X-ray diffraction (XRD) analysis. The parent rocks released lithogenic Hm and Gt into the soils and in the superficial horizons, and most of the Hm was dissolved and the Fe recrystallized as Gt. The yellow superficial horizons contained two Gt populations: Gt with fewer isomorphic substitutions of Fe by Al (lithogenic) and Gt with more isomorphic substitutions and with smaller mean crystal diameters (pedogenic). The isomorphic substitutions conferred greater stability to the minerals, so Gt had greater resistance than Hm to the CBD extractions. After successive extractions with CBD, Hm tended toward an isodimensional form. Our data confirmed that the lower stability of Hm and the high electron concentrations due to high organic matter contents resulted on yellowing of the superficial horizons.

The surface soil of newly cut slopes used in ecological protection engineering has a loose structure, low strength, and an inadequate water amount and moisture conservation capacity. This results in weak vegetation growth, negative long-term effects, and high maintenance costs. For this reason, a novel type of polymer composite, namely, an aqua-dispersing-nano-binder (ADNB), optimised using different ratios of polymer adhesive and resin, was used to carry out water retention, erosion, and plant growth tests on weathered silty clay in the red beds of southern China. In addition, ADNB soil treatments were compared with untreated soil, and the occurrence and mechanism of water retention and erosion resistance in ADNB-modified soil were determined. The results show that with an increase in the amount of resin, the dry density of the soil decreased, and the void ratio, field capacity, and water holding capacity increased. With an increase in the amount of applied polymer adhesive, the dry density of the soil increased, and the void ratio, field capacity, and water holding capacity decreased, but were higher than those of the untreated soil. The mechanism of the ADNB modifying soil structure and improvements in its ecological self-repair were analysed. The adsorption and storage of free water by resin in the soil was observed through NMR imaging. Adding ADNB material at an appropriate proportion to the soil not only enhances the soil strength and erosion resistance, but also increases the soil water holding capacity and promotes plant growth. Thus, the ecological self-repair of the soil and the ecological protection of the slope can be significantly improved.

East Taihu Lake (the south-eastern portion of Taihu Lake in China) suffers from eutrophication. The study of lacustrine subfossil zooplankton assemblages can be used to reconstruct the long-term evolution of lake water environments. In particular, the analysis of subfossil Cladocera can indicate historical changes in aquatic plants, water level, trophic states, and human disturbance in lakes. In this study, we correlated downcores changes in cladoceran assemblages with several geochemical proxies to identify the response of Cladocera to environmental change in East Taihu Lake over the past one hundred years. Redundancy analysis (RDA) and Pearson correlation analysis identified significant correlations between total phosphorus (TP) and Bosmina spp. (total), B. (E.) longispina, and Chydorus cf. sphaericus (correlation coefficients: −0.720 (P < 0.01), −0.646, and 0.667 (P < 0.05), respectively). We observed decreasing abundances of subfossil Bosminidae and increases in littoral cladoceran species and TP after the 1960s, coinciding with the introduction of land reclamation for fish and crab farming. These anthropogenic pressures exacerbated eutrophication, which led to the rapid growth of submerged vegetation and subsequently altered the zooplankton assemblage.

In order to accurately estimate the carbon (C) balance in arid and semi-arid grasslands, it is necessary to first understand how the demands of photosynthates and root carbon (C) are allocated in response to drought. To accomplish this goal, we used a 13C pulse labeling technique to assess correlations between root morphology and the amount of 13C in the root, which is a measure of respiration. We compared respiration changes via the excised root 13C of Bothriochloa ischaemum at various root excision times (i.e., 0, 6, 24, 48, 216, and 360 h after labeling). Our results showed that 13C and root respiration continued to increase until 216 h after labeling, and then they decreased after 360 h. Root respiration correlated significantly with the carbon labeled as being from the fine roots that were undergoing drought stress treatments. This indicates that later-photosynthates are the primary C source for root respiration. Fine root 13C positively correlated with fine root biomass and specific root length under serious drought conditions. This suggests that fine root growth is based primarily on recently derived photosynthates. Serious drought was shown to inflate the root/shoot ratio by increasing both the 13C and the biomass, which led to greater C allocation in the root system. Finally, the fine/coarse root ratios of 13C and biomass were greatest in the serious drought treatment. This suggests that fine roots have a higher C demand than coarse roots under drought stress. Fine root respiration was also found to stimulate new C demand in roots because the amount of 13C created during root respiration was positively correlated with tissue N concentration of fine roots.

Three pairs of small, fourth- to sixth-order catchments (approximately 5–80 km2), draining the margin of the Darjeeling Himalayas into the piedmont, were selected for a comparison of the land-use impact on the morphology and sedimentology of their stream channels. Each pair experienced similar annual rainfall and comprised similar metamorphic bedrock, steep topography, and brown soils; the members of each pair contrast with respect to their land-use structure as they comprise large forest cover (forest >90%) and a significant contribution of agricultural land with tea plantations (forest <63%), respectively. A set of rainfall, cross-sectional, and sediment data were collected for the characterization of the stream channels. The obtained results revealed that, under extreme rainfall and high denudation rates as well as frequent flash floods, the geomorphic response to land-use changes involving agricultural expansion at the expense of forest cover was less pronounced in the mountain channels than in the piedmont. Significant differences between the studied pairs of mountain streams draining forested and agricultural catchments were observed only at bankfull width and baseflow depth in fourth-order streams and baseflow depth in fifth-order streams. Local environmental factors such as bedrock channel boundaries, steep topography, high material supply to river networks, and selective sediment mobilization during extreme rainfall and floods override the effects of land use and exert dominant control over stream channels in mountain catchments. However, the effects of agricultural activity in mountains are propagated downstream. In the agricultural catchment in the piedmont, a local rapid decrease in river slope and an increase in water infiltration into alluvia facilitates the deposition of eroded material. In addition, the stream in the agricultural catchment exhibited a rise in the riverbed with the expansion of a braided channel over a dozen kilometers below the Himalayan front in the piedmont, while the streams in the forested catchment revealed a distinct tendency towards incision. The present-day channel morphologies and sediment patterns observed in forested catchments are most likely similar to those that existed in the studied rivers prior to the development of tea plantations and settlements in the mid-19th century.

The morphology of the failure scar has been a long-debated issue concerning the Loess Plateau of China, and the lack of normative data has hampered vital research in this area. In this study, a series of laboratory experiments were conducted to observe failure geometries and volumes under rainfall simulations. The following six failure-scar types occurred: The sequence of the types described here may be same to that of the following text, namely Tf, Cd, Cu, Ia, Ps, and Co. The number of failure masses in the experiment for scar types Tf, Cd, Cu, Ia, Ps, and Co amounted to 45, 26, 23, 3, 2, and 1% of the total, and the corresponding volumes were 58, 16, 20, 2, 3, and 1% of the total, respectively. This implies that Tf, Cd, and Cu were the three major types of failure scars during the process of gravity erosion on a steep loess slope, and the scar Tf was the most significant. The sensitivity coefficient – the degree of variation in the target value caused by a change in a crucial factor when other conditions remain unchanged – of the slope gradient and rainfall intensity for the total volume of the Tf scar were 4.5 and 3.7, respectively. In other words, a relatively dangerous failure scar (Tf) might appear if the slope became steeper, or if the rainfall became more intensive. In addition, the sensitivity coefficients of the rainfall duration for the total volume of the Cu scar was significant, being 12.4. This shows that a long-duration storm could easily induce a large-volume failure with a Cu scar. The experimental results obtained here provide a morphogenic insight into the gravity-erosion control on a loess gully sidewall.

Fire-vegetation relationships are critical to understand transient mountain ecosystems and their long-term landscape dynamics, which is essential for alpine forest conservation. In this paper we aim to (1) reconstruct the Holocene fire history at high altitudes of the southern Central Pyrenees, (2) add evidence to the debate on fire origin, naturally or anthropogenically produced, (3) determine the importance of fire as a disturbance agent for sub-alpine and alpine vegetation, in comparison with the plant community internal dynamics applying conditional inference trees. We present and compare microcharcoal and pollen data series, from two lacustrine sedimentary sequences in the Central Pyrenees: Basa de la Mora (BSM), within the treeline ecotone at the sub-alpine belt (1914 m a.s.l.) and Marboré Lake, above the treeline at the alpine belt (2612 m a.s.l.). We evidence that, fire activity was not the most important factor in driving vegetation dynamics regionally. Our results suggest that spatially, the fire signal might be site-dependent while over time, climate exerted a strong influence on fire activity during the early-to-mid Holocene, showing more fires during the Holocene Thermal Maximum (HTM) (ca. 7000–6000 cal yr BP) whereas fire activity decreased with the cold Neoglacial period. At ca. 3700 cal yr BP, fire activity increased coinciding with a regional landscape opening, suggesting that human activities may have strengthened the importance of fire. Fire activity remained low over the last two millennia but a remarkable Holocene maximum for the last centuries in both sequences is observed, likely related to increasing human pressure.

Understanding the process of soil organic carbon (SOC) sequestration and mineralization in aggregates is pertinent to mitigate climate change and minimize risks of soil degradation. Thus, soil samples were obtained after a 10-year field experiment to identify the influences of tillage on aggregate-associated SOC sequestration and mineralization in the North China Plain (NCP). Four tillage practices investigated were as follows: no-till with straw retention (NTS, conservation tillage), rotary tillage with straw incorporation (RTS), conventional tillage with straw incorporation (CTS), and conventional tillage with straw removal (CT). Significantly negative correlations were observed between SOC concentration and potentially mineralized carbon in aggregates under different treatments for the 0–10 cm soil layer. The large macro-aggregates (>2 mm) with the highest proportion of size distribution represented the major pool of SOC stock (47.3–51.2%) and mineralization amount (38.2–43.6%) in the 0–30 cm layer, followed by that in the small macro-aggregates (0.25–2 mm), regardless of tillage practices. However, the mineralization quotient (mineralization per unit SOC concentration) of macro-aggregates (>0.25 mm) was lower than that for the other size classes. The NTS enhanced the macro-aggregate formation in the 0–20 cm layer and associated SOC concentration in the 0–10 cm layer. Furthermore, NTS decreased total potential mineralization in the 0–30 cm layer compared with the other tillage practices, attributed to decrease in the large macro-aggregates (30.0–51.4%) with low particulate organic carbon (POC) concentration. The NTS with low straw inputs had higher incremental efficiency with straw incorporation than that in the RTS and CTS by 45.0% and 13.5%, respectively (P < 0.05). Overall, the higher proportion of macro-aggregates recorded under NTS decreased carbon mineralization, and consequently, increased incremental efficiency with straw incorporation, and improved SOC sequestration in the surface soil layer in the NCP.

Soil erosion prediction and conservation planning require detailed soil data under different environmental conditions. When such data are needed at the field scale, aspatial and spatial models could be used to predict soil erosion processes. This study was conducted to develop spatial models including geostatistical models (i.e. ordinary kriging (OK) and cokriging (CK)) and hybrid geostatistical models (i.e. multiple linear regression-kriging (MLRK) and artificial neural network-kriging (ANNK)) for estimating WEPP baseline soil sensitivity to erosion parameters for calcareous agricultural soils in northwest Iran. Inter-rill and rill erosion simulation experiments were carried out at 100 locations at the field scale with 3 replications. At each location, the soil properties (organic matter, calcium carbonate equivalent, sand, silt, clay, base infiltration rate) were measured and auxiliary data obtained from attributes derived from digital elevation models (elevation, slope, stream power index, wetness index and sediment transport index) and remote sensing data (three visible bands, NIR, SWIR (5 and 7 bands), NDVI indices). The MLR and ANN models were used to estimate baseline inter-rill soil sensitivity to erosion (Kib) and rill soil sensitivity to erosion (Krb and τcb) using two types of input data. For the first type of prediction models (type I), the measured soil properties and auxiliary data were used, whereas for the second type of models (type II), principal components (PCs) based on the soil and auxiliary data were used. In comparison to the models that were developed here, the WEPP inter-rill and rill soil sensitivity to erosion models showed a relatively poor performance. The ANN models developed here predicted Kib, Krb and τcb parameters better than the MLR models using both types of data (type I and II). Moreover, the results indicated that the ANNK model was the most appropriate spatial or hybrid model for predicting soil sensitivity to erosion parameters.

Quaternary calcretes are widespread in soils of many regions of the world especially in semi arid and arid areas. Their development has been studied worldwide for more than a century involving various disciplines and resulting in large amounts of data concerning their evolution. In this article, the geographical distribution of calcrete has been studied by combining Geographical Information Systems (GIS) and statistical analysis. In this paper, we present a qualitative approach that incorporates topographic, geological, hydrogeological and climatic data as well as field observations. After getting all four parameters, they were divided into classes and an index value has been assigned to each of them according to influence degree on calcrete development. Finally, all the parameters are superimposed to prepare the final map of calcrete distribution. The multivariate statistical analysis techniques used were principal component analysis and cluster analysis. Both methods were performed to discuss the potential relations among the investigated parametres (CaCO3 (%), Palygorskite (%), slope (%)) and calcrete evolution. The qualitative approach adopted provided a distribution map predicting the possible areas where different calcrete forms might occur and allowed to elucidate the degree of influence of environmental factors on the evolution of calcrete. The accuracy of this method has been estimated by comparing it with 52 cross-section data from the field. This approach proved to be successful in this study. The results of statistical analysis confirm the results obtained using GIS method and highlight the influence of the studied environmental factors on the spatial distribution of different types of calcrete.

Peak sediment transport during flood events is very important to the sustainability of the Three Gorges Reservoir (TGR), and thus, in-depth research on peak sediment transport must be performed for the refined regulation of this reservoir. The variation in peak sediment transport and its corresponding causes following the completion of the cascade reservoirs in the lower Jinsha River in the TGR are still unclear. In this study, based on daily discharge and suspended sediment concentration time series, hysteresis patterns and peak sediment transport times were used to determine the peak sediment transport variations. The temporal peak sediment transport variations and their origins were revealed based on wave theory and a one-dimensional hydraulic model. The results show that peak sediment hysteresis has become more obvious recently, and the greatest influencing factor is the construction of cascade reservoirs. Rising water levels in the TGR contributed to slowing SSC, doubling the proportion of anti-clockwise patterns, and increasing the peak sediment transport time by approximately 31% after 2003. The cascade reservoirs in the lower Jinsha River reduced the peak discharge by approximately 15%, which had a relatively large influence on the SSC peak, increasing the SSC peak transport time by approximately 22% and increasing the proportion of the anti-clockwise pattern at the inflow reach. These results can provide references for reservoir regulation during flood events; more significant sediment hysteresis means the regulation timing should be changed. The lag between the peak sediment and peak discharge is affected by the flow process and water level and can be used to help develop a reservoir regulation model.

This study investigates the ostracod assemblages obtained from a sediment core from a paleolake in the Sağlık plain in south-central Anatolia (Turkey). In addition to ostracods, oxygen and. carbon stable isotopes of ostracod shells were analysed and pollen analysis of the core undertaken. The sediments comprise the Late Glacial and early Holocene interval with an approximate 14C age from 18,000 to 6700 14C years ago, after applying a correction for reservoir effects. Eight podocopid ostracod species were recorded, among them Cyprideis torosa and Candona sp. which were used for stable oxygen and carbon isotope analyses. C. torosa dominated during the Late Glacial while Candona sp. dominated most of the early Holocene assemblages. Both forms of C. torosa disappear abruptly close to the onset of the Holocene. Around this time, ostracod preservation was dominated by many black coloured valves and carapaces. Based on ostracod assemblage data and isotope analyses, relatively wet phases were identified for the Older Dryas, Younger Dryas, and during the mid-Holocene at around 7500 14C years ago. Relatively dry phases were identified during the Allerød interstadial, at the end of YD, and at about 6700 14C years ago. An oligotrophic and brackish lake persisted until shortly before the end of the YD, when, according to the δ 13C values, conditions gradually became more eutrophic. The sudden disappearance of C. torosa at the end of the YD seems the consequence of anoxic bottom water conditions and/or eutrophication. Alternating wet and dry phases characterize the early Holocene, with a longer period of wet and oligotrophic conditions around 7500 14C years ago (ca. 8300 calBP). Ostracod assemblages and isotope records indicate a dry and more productive lake around 6700 14C years ago (ca. 7550 calBP).

Time stability of soil water storage (SWS) is the similarity of spatial patterns of soil water storage over time and is scale and location dependent due to multivariate effects of controlling factors. However, our understanding of scale and location dependency of the time stability of SWS and its seasonally dependent controls in cropped fields is inadequate. This study examined the scale and location dependent time stability of SWS at multiple depths, over different seasons in a cropped field in western Quebec, Canada. Soil water content was measured at 0.05, 0.10 and 0.20 m depths along six transects (128 locations per transect) using the actively heated fiber optic (AHFO) technique. Wavelet coherency analysis was used to examine the scale and location dependent time stability of SWS over different seasons. Results showed strong intra-seasonal time stability across all scales, locations and depths during the dry period in the summer due to a dominant control of evapotranspiration (ET). The weak inter-seasonal time stability of SWS showed the change in the dominant processes controlling the spatial patterns of SWS in different seasons. While the intra-seasonal time stability was also strong during the wet period of autumn, correlations were not significant across all scales, locations and depths, likely due to the dominant effects of smaller to medium scale processes. The results of the study clearly showed that the dominant hydrological processes controlling the time stability of SWS at different depths during a dry period in summer were different than that of a wet period in autumn. The change in the dominant hydrological processes affected the spatial scales and the locations of the similarity of the spatial patterns of SWS in the field. Therefore, the analysis outcome can be used to identify the change in the sampling domain as controlled by the hydrological processes operating at different scales and locations delivering the maximum information with minimum sampling effort.

Rice is one of the most important crops in the world. It provides food for 40% of the world’s population and 60% of China’s population. Soil nutrients have a significant impact on both agriculture and the environment, particularly with regards to soil fertility, soil quality, and rice production. However, minimal research has been conducted to address spatial patterns of soil nutrients at a large scale within paddy fields. This information is crucial for improving not only soil nutrient management, but also rice yields. Soil surface samples (0–20 cm of plough depth, totalling 8890) were collected from paddy fields to determine the spatial variability of eight soil chemical properties (soil organic carbon (SOC), total nitrogen (TN), available N (AN), total phosphorus (TP), available P (AP), total potassium (TK), rapidly available K (RAK), and slowly available K (SAK)). Inverse distance weighting (IDW) and ordinary kriging methods were applied to produce a continuous soil nutrient surface. Results indicated that soil chemical properties vary substantially. Paddy fields were characterized by high mean concentrations of SOC (19.7 g kg−1), TN (1.91 g kg−1), and AN (164.7 mg kg−1), implying that no additional C and N fertilizer was needed in regions with high SOC and N. SAK and AP demonstrated moderate (36.9%) and weak (96.2%) spatial dependence, respectively, while strong spatial dependence (10.1–13.5%) was observed across the remaining six soil chemical properties. Regional distribution maps of soil chemical properties were produced and ordinary kriging methods interpolated more accurately than the IDW method.

Over the last three decades, both the crop yields and population in China have steadily increased due to continued agricultural investments. K fertilizer and the return of straw have played vital roles in the yield and quality of crops. However, the effects of long-term fertilization on soil K to a soil depth of 1 m have received little focus, and unbalanced K fertilization frequently occurs because local farmers lack sufficient information about soil K. In this study, the spatial distribution of available potassium (AK) in East China was predicted using kriging with external drift (KED) and random forest (RF) techniques. A comparison of the trends in the 1980s and 2010s showed that the mean AK values in East China generally increased. The mean AK values at soil depths of 0–20 cm, 20–50 cm and 50–100 cm increased by 17%, 12% and 23%, respectively, and the AK stocks increased from 0.14 Pg to 0.17 Pg. However, the spatial patterns of AK at the regional scale suggested that approximately 68.12% of the study area lacked AK. AK deficiency was found in Northeast and South China. The ratios of AK concentrations in the subsoil to those in the topsoil suggested that less K was stored in the subsoil than in the topsoil. Relatively more AK was found in the subsoil (20–50 cm) of paddy fields in the middle of East China than in the other areas. The maps produced in this study could be used to support the decisions of regional agriculture management, and our study demonstrates that effective K fertilizer application in East China should be taken into consideration.

Demand for accurate soil information is increasing for various applications. This paper investigates the history of soil survey in Iran, particularly more recent developments in the use of digital soil mapping (DSM) approaches rather than conventional soil mapping (CSM) methods. A 2000–2019 literature search of articles on DSM of areas of Iran in international journals found 40 studies. These showed an increase in frequency over time, and most were completed in the arid and semi-arid regions of central Iran. Artificial Neural Networks (ANN), Random Forests (RF), and Multinomial Logistic Regression (MnLR) were the most commonly applied models for predicting soil classes and properties and ANN performed best in most comparative studies. Given the scale of inquiry of most studies (local or regional), quantitative environmental variables such as terrain attributes and remote sensing data were frequently used whereas qualitative variables such as geomorphology, geology, land use, and legacy soil maps were rarely used. The literature review of CSM showed that this method is incapable of defining the spatial distribution of soils and also provides a lower accuracy than DSM method. This review has identified research gaps that need filling. In Iran, coherent national scale DSM with consistent methodology is needed to update legacy soil maps, and to apply DSM in forestlands, hillslopes, deserts, and mountainous regions which have largely been ignored in recent DSM studies. This review should also be useful for producing more local and regional digital soil maps more rapidly as it helps show which covariates and mathematical methods have been best suited to this scale of DSM in Iran.

We present a remote sensing-based methodology for the Land Productivity (LP) rapid assessment and monitoring of status and trends at national and sub-national scales. This methodology aims at supporting national and international policies to achieve the Land Degradation Neutrality (LDN) target in the framework of the UN Agenda 2030 and the Sustainable Development Goals (SDG 15.3). The work was performed using the NASA-MODIS Normalized Difference Vegetation Index (NDVI) as proxy indicator of LP status and trends in Italy for 16 years (2000–2015). The assessment of the LP status was based on the pixel mean and standard deviation values of yearly LP values. The LP trends of the yearly time series were computed using Mann-Kendall (MK) and Contextual MK (CMK) tests providing a monitoring indicator for land productivity change. The amount of land with valid increasing and decreasing trends is estimated assuming the 95% significance level of trends in the areas with “good” NDVI pixel reliability. The area of increasing and decreasing LP are estimated for the national territory and for different land covers. The widespread observed increasing LP variations were correlated to the progressive renaturalization of lands subsequent to the decrease of agricultural activities and increasing precipitation trends in the winter season. Decreasing LP affected very limited areas and hot spots were correlated to changes of seasonal precipitation and anthropic activities. The areas and municipalities most affected by LP changes are identified and may support, in the framework of SDG 15.3 and LDN, the identification of policy initiatives.

Beech and hornbeam are two of the most common species in old-growth temperate forests. However, how these two species affect soil carbon (C), soil nitrogen (N) and soil microbial and enzymatic activities is still not well understood. Thus, the aim of the present study was to quantify the effects of beech and hornbeam on soil chemical, biochemical and biological features at Makarod forest, Northern Iran, by sampling either forest floor or mineral soil (30 × 30 × 15 cm) under individual trees of both species. Based on our data, hornbeam showed higher concentrations of N, phosphorous (P), potassium (K), calcium (Ca) and magnesium (Mg), but lower total thickness, C and C: N ratio in the forest floor. Top mineral soil under hornbeam had alkaline condition (pH > 7), higher electrical conductivity (EC), total N, N in micro- and macro-aggregates, N sequestration, available P, K, Ca, Mg, humic acid, fine root biomass, total earthworm (i.e. epigeic, anecic and endogeic) density and biomass, total nematode, acarina and protozoa densities. Hornbeam trees increased soil basal respiration and substrate induced respiration (0.50 and 1.47 mg CO2 g−1) compared to beech. The two studied species did not show any significant difference in soil microbial biomass C, metabolic quotient, microbial ratio, C availability index, particulate organic C and dissolved organic C, whereas, higher values of soil microbial biomass N, particulate organic N and dissolved organic N (66.97 mg kg−1, 0.52 g kg−1 and 38.53 mg kg−1, respectively) were again found under hornbeam. Except for arylsulfatase, all the other soil enzyme activities (i.e. urease, acid phosphatase and invertase) were almost two-fold higher under hornbeam (24.55 μg NH4+–Ng−1 2 h−1, 498.30 μg PNP g−1h−1 and 296.2 μg Glucose g−1 3 h−1, respectively). As well, higher values of ammonification rate were measured under hornbeam (0.38 mg kg−1 d−1), whereas beech significantly increased the nitrification rate (−0.16 mg kg−1 d−1). Net N mineralization rate was about three-fold higher under hornbeam (0.14 mg kg−1 d−1) than under beech. Our results indicate that differences in functional traits between beech and hornbeam caused changes in microbial community and in its activity, underlying a higher forest floor quality, higher soil fertility and more active microbial populations under the latter.

Landslides are a common type of natural disaster that brings great threats to the human lives and economic development around the world, especially in the Chinese Loess Plateau. Longxian County (Shaanxi Province, China), a landslide-prone area located in the southwest part of the Loess Plateau, was selected as the study area. The main purpose of this paper is to map landslide susceptibility using Alternating decision tree (ADTree) as well as GIS-based new ensemble techniques involving ADTree with bootstrap aggregation (Bagging) and ADTree with adaptive boosting (AdaBoost). Initially, a landslide inventory map was prepared with 171 determined historical landslides events in the study area, 120 landslides (70%) were randomly selected for training dataset and the remaining 51 landslides (30%) were used for validation dataset. Subsequently, eleven landslide conditioning factors were considered in the landslide susceptibility mapping. Then, an optimization operation on selection of landslide conditioning factors was performed using correlation attribute evaluation method and Spearman’s rank correlation coefficient. Afterwards, landslide susceptibility maps were generated with the three models. Finally, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) and statistical measures were applied to evaluate and validate the performance of the models. The results show success rates of the ADTree model, the ADTree with Bagging (ADTree-Bagging) model and the ADTree with AdaBoost (ADTree-AdaBoost) model were 0.872, 0.917, and 0.984, respectively, while prediction rates of the three models were 0.696, 0.752 and 0.787, respectively. In sum, the two ensemble models proposed prohibited better performance than the ADTree model did, and the ADTree-AdaBoost model was selected as the best model in the study. Hence, ensemble techniques can provide new and promising methods for spatial prediction and zonation of landslide susceptibility.

The paper focuses on the weathering processes affecting gneissic rocks of the western Sila Grande Massif (Calabria, Italy) through the development of an interdisciplinary research based on field studies and investigations, minero-petrographical analyses and geochemical modeling. Both physical and chemical weathering affect gneissic rocks of the study area, where the combination of tectonic and past climatic conditions played an important key role in the development of complex and deep weathering profiles. Field surveys and cut slope analyses highlight articulated and complex geometric relationships between various classes of weathering (i.e., out-of-sequence weathering horizons giving rise to a partial, or even complete inversion of the “normal” weathering profile). The weathering profile has turned out particularly intense, as classes IV, V and VI are widespread. Among the class VI, the colluvial soils are prominent in comparison whit the residual soils. Borehole logs, that confirm the intensity and complexity of weathering profiles in deep, allow to estimate the presence of weathered rocks to be at least 70 m in thicknesses. The main mineralogical modifications linked to weathering processes concern the partial transformation of biotite and the partial destruction of feldspars (mainly plagioclases), associated with the neoformation of secondary mineralogical phases (clay minerals and Fe-oxides). Neoformed clay minerals (such as sericite, illite and mixed layer phases) and ferruginous products replaced feldspars and biotite during the most advanced weathering stage. Results of XRD analyses and geochemical modelling provide a good indication on the secondary mineral assemblage due to the increase of the weathering intensity (form class III to class VI) that reflects the different contributions of chemical elements provided by dissolution of silicate minerals into the surrounding groundwater system. The chemical composition of the studied rock samples and the oxides variations suggest a removal of some alkali (Na and K) and alkaline earth (Ca and Mg) into solution as a consequence of weathering reactions. The chemical analysis and the weathering indices (CIA, PIA, CIW and CIW’) show a marked alteration process, with ferromagnesian minerals and feldspars probably dissolved and leached into the surrounding groundwater system. The CO2-controlled dissolution of plagioclase appears to be the most important reaction during chemical weathering. The progressive dissolution results then dominated by biotite, followed by a minor amounts K-feldspar, chlorite and garnet; whereas the sillimanite shows a neglectable amounts. The secondary solid phases observed during the geochemical modeling (illite, followed by vermiculite, ferrihydrite and saponite) are similar to those found in this natural system. The proposed approach could be used to characterize weathered crystalline rocks and related weathering profiles in similar geological setting, and the obtained results represent a key point for the evaluation of the control exerted by weathering on landscape evolution under current environmental settings in terms of sediment generation, soil erosion rates, and mass movements, and for the mechanical characterization of weathering profiles for engineering geological purposes.

Arid environments are fragile and the associated soils are subject to serious threats like water deficiency, erosion, salt accumulation, and loss of fertility. In this context, understanding the processes involved in soil genesis may contribute toward protecting land from degradation. This study highlights the interconnection between geomorphic and pedogenetic processes in soil formation of the Jeffara Plain, a pre-Saharan area of southern Tunisia. To reach this goal, one coastal oasis (Chenini Nahel) and two inland environments (Matmata Nouvelle and Menzel Habib) were studied. After geomorphological and pedological surveys, the soils were sampled by genetic horizons and characterized by physical, mineralogical, and chemical analyses, and by microscope observation. Field observations and laboratory data suggest that soil formation in the Jeffara Plain was a combination of additions and losses controlled by climate changes. At Chenini Nahel, the soils developed by accumulation of wind-blown sediments coming from a close area dominated by gypsum-bearing rocks. At Matmata Nouvelle, the soils mainly formed from sedimentation of repeated mudflows during a rainy period between 9000 and 5000 years before present, followed by drought periods. Finally, the soils of Menzel Habib developed from an early gypsum formation in the presence of a salt-rich water table and repeated cycles of sedimentation/deflation of wind-blown materials. The different genesis of these pre-desert soils produced characteristic B horizons: Byy horizons with poorly developed soil structure at Chenini Nahel, Bw horizons with a hard rupture-resistance at Matmata Nouvelle, and Bk horizons at depth due to intense sedimentation with CA + BC horizons at the surface due to the accretion of wind-blown materials at Menzel Habib.

Soil organic carbon (SOC) associated with iron (Fe-OC) can be recognized as an important component of the stabilized carbon pool. In permafrost regions, slump deformation can expose soil organic carbon and alter moisture conditions, which change the Fe-OC distribution. We measured the top 30 cm of soils in five slump deformation landscapes under three vegetation types on the middle and eastern Qinghai-Tibetan Plateau. Three stages of slump deformation were defined according to their microtopography. In the slump deformation areas, the SOC and total nitrogen (TN) contents in the surface 30 cm of soils were all lower than the soils without slump deformation in wet meadow (22% and 26%), meadow (16% and 29%), and steppe (14% and 20%) areas. The contents of Fe-OC in wet meadow were 4.1% and 12.5% in the soils without and with slump deformation, respectively, whereas these contents in the meadow and steppe soils were 25.6% and 17.2%, respectively. Slump deformation greatly changed the physiochemical soil variables and affected the Fe-OC% based on different vegetation types. Fe-OC was correlated with factors such as soil moisture, pH and C/Fe ratio. The study shows that slump deformation greatly affected the SOC and TN distribution and SOC stabilization processes in areas with slump deformation features.

The link between soil properties and forest restoration is not well understood in soils with a high proportion of bare rock outcrops (ROCs). This study compared the concentration of total potassium (TK) and available potassium (AK), soil organic matter (OM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), volumetric proportions of soil (VPS), pH, and bulk density in soil with ROC emergence under a sequence of grass, shrubs, young regenerated forest, and closed forest on karst landforms at Shilin, S.W. China. The aims were to determine the relationship between the changes in soil properties, biomass accumulation, and plant species under the context of ROCs, and to identify the most limiting factor for forest restoration on this specific geology. We found that (1) the concentration of TK and AK, pH, and bulk density decreased, and OM, TN, AN, and TP concentrations slightly increased in 0–20 cm, 21–40 cm, and 41–100 cm soil layers during vegetation restoration from grass to shrubs and then young regenerated forest. Only TP and AK in all soil layers, TN in the 0–20 cm layer, and TK and bulk density in the 0–20 cm and 21–40 cm layers were significantly different between the soils of grass areas and closed forest. (2) The biomass was negatively correlated with TK and AK stocks in the 0–20 cm soil layer and AK stock in the entire 1 m pedon, and positively with TN, TP, and AN stocks in the entire 1 m pedon. The optima of various species groups, which account for a small proportion, corresponded to stock of N, P, K in canonical correspondence analysis. In conclusion, biomass accumulation during forest recovery in the context of ROCs had depleted soil K stocks and caused the reduction of TK and AK concentrations, contrary to the slight enrichment of soil N, and P and improvement of OM, pH and bulk density. Any measure increasing soil K may benefit forest restoration in karst areas.

The availability and precision of topographic data determines the reliability of the calculated slope length and slope gradient (LS) factor, which limits the use of the universal soil loss equation (USLE) and its adapted versions in region-scale soil erosion risk assessment. One of the common complications is the effectiveness of topographic data with different resolutions or the compatibility of topographic data originated from different sources. In this study, the topographic data from five common sources, 5-m digital elevation model (DEM) based on 1:10,000 topographic maps (5-m topo DEM of 1:10,000), 25-m DEM derived from 1:50,000 topographic maps (25-m topo DEM of 1:50,000), 30-m ASTER GDEM, 30-m and 90-m SRTM DEMs, were individually applied to calculate the LS factors of five catchments with distinct terrain characteristics. Our results show that the computation accuracy of the LS factors in the five study catchments decreased with greater grid sizes derived from the five topographic data sources. Compared to the most precision 5-m topo DEM of 1:10,000, the relative computation error of the mean LS factors was less than 10% when calculated from the 25-m topo DEM of 1:50,000, and that was less than 25% from the 30-m ASTER and 30-m SRTM DEMs. For scenarios in gently rolling areas, the 90-m SRTM DEM with the relative computation error less than 15% could be recommended when there are noises on the open sources DEMs surface. Therefore, depending on the requirements of data accuracy, different data sources can be applied individually or in combined to obtain the optimal predictions of the LS factors. However, such recommendations on data sources proposed in this study appeared to be more applicable for regions with complex terrains. Further studies over a range of terrain features and spatial scales are required to validate the effectiveness of different topographic data sources in calculating the LS factor.

The North China Plain (NCP) is one of the most intensively farmed agricultural regions in China, and the annual double-cropping system of winter wheat and summer maize produces a large quantity of straw. A field experiment was carried out from 2010 to 2016 to assess the effects of straw and manure management on crop performance, soil physical and chemical characteristics. Four management practices were tested: (1) all the straw from the annual double-cropping system was returned to the soil directly (as a control, WMs); (2) maize straw was removed as yellow silage and winter wheat straw was maintained (Ws); (3) manure produced from dairy farms was added to Ws (Ws + M); (4) extra manure was added to WMs (WMs + M). The results showed that the soil bulk density and soil aggregates were not significantly different among the four treatments. The soil nutrient contents and organic matter (OM) increased continuously under the four treatments. The results indicated that with at least one season of straw returning to the field would maintain an improved soil nutrient contents. The increase rate for organic matter, P and K for the treatments with manure addition was higher than that for the treatments without manure application. Both biomass and grain yield of summer maize were improved with the continuous addition of manure. Although the biomass of winter wheat was improved with manure addition, the grain yield of winter wheat was not affected due to the reduction in the harvest index, which might be related to the shortened grain-filling duration. No significant difference in water use efficiency was found among the four treatments for winter wheat or maize. The improved soil nutrient and organic matter contents affected the production of the two crops differently in this annual double-cropping system. The larger increase in organic matter contents using maize straw changed manure through animal feeding would benefit the grain production of summer maize as well as the soil carbon sequestration.

In arid and semi-arid ecosystems, shortage of water can trigger changes in landscapes’ structures and function leading to degradation and desertification. Hydrological connectivity is a useful framework for understanding water redistribution and scaling issues associated with runoff and sediment production, since human and/or natural disturbances alter surface water availability and pathways increasing/decreasing connectivity. In this paper, we illustrate the use of the connectivity framework for several examples of dryland systems that are analysed at a variety of spatial and temporal scales. In doing so, we draw particular attention to the analysis of coevolution of system structures and function, and how they may drive threshold behaviour leading to desertification and degradation. We first analyse the case of semi-arid rangelands, where feedbacks between the decline in vegetation density and landscape erosion reinforces degradation processes driven by changes in connectivity until a threshold is crossed above which the return to a functional system is unlikely. We then focus on semi-arid wetlands, where decreases in water volumes promote terrestrial vegetation encroachment that changes drainage conditions and connectivity, potentially reinforcing redistribution of flow paths to other wetland areas. The analysis of dryland wetlands is based on a novel hydrologic connectivity index derived using inundation requirements for wetland vegetation associations. The examples presented highlight the need to incorporate a coevolutionary framework for the analysis of changing connectivity patterns and the emergence of thresholds in arid and semi-arid systems.

Reliable drought monitoring is critical for evaluating drought risk and reducing potential agricultural losses. However, many existing drought indices developed by a single indicator may not properly describe the complex features of agricultural drought. Here, we propose a new drought index—the integrated agricultural drought index (IDI), which describes the relationship between multiple variables and agricultural drought conditions. The derivation of IDI is based on the remote sensing data and the back-propagation (BP) neural network, capable of identifying the non-stationary relationship of drought conditions. Development of IDI involves the following meteo-hydrological variables: precipitation, land surface temperature (LST), normalized difference vegetation index (NDVI), soil water capacity, and elevation. The lagging effect of NDVI with respect to precipitation and LST changes can also be captured by the proposed IDI. Our results indicate that the IDI based on a machine learning method can relax the assumption used in many existing indices that the input and output data are linearly correlated. Results also demonstrate that the IDI is close to SPI-3 and SPEI-3 in a case study of the North China Plain (NCP). Moreover, we found the drought condition in the NCP area is highly correlated with 10 cm depth soil moisture at 8 agrometeorological stations and the newly developed IDI can effectively monitor the drought in terms of onset, duration, extent, and intensity of a drought episode. Additionally, the IDI provides spatial information about root zone soil moisture that can facilitate agricultural drought monitoring. The proposed framework of IDI can also be applied in other regions of the world for agriculture management.

Both soil organic carbon (SOC) and inorganic carbon (SIC) are important components of soil carbon storage. However, few studies have attempted to estimate the magnitude and patterns of SIC in arid areas. We measured the concentrations of SOC and SIC in alpine steppe grasslands along a climate gradient in the Tibetan Plateau. At all sites, an opposing trend was found in the distribution of SOC compared with SIC. SOC increased with increasing precipitation, while SIC decreased. Within sites, SOC decreased with soil depth, while SIC increased. Among the variables considered, soil total nitrogen (TN) and soil water content explained the most variability in SOC (r2 = 0.95 for TN, r2 = 0.93 for soil water content), and soil pH had the highest correlation with SIC (r2 = 0.90). This finding indicates that SOC is closely related to biological processes, such as biomass input and litter accumulation, while SIC is determined by abiotic factors such as chemical and physical processes of soil formation. SOC and SIC densities showed that the SOC pool comprised 91% of total carbon (TC) storage in these alpine steppe soils. A decrease in SOC density occurred with depth, but this pattern was the opposite for SIC density in all soil profiles. These findings help to characterize the C cycle in the alpine steppe of the Tibetan Plateau.

It is the core task of geoscientists to gain insight into the complex systems of nature. Yet, complexity may be perceived very differently and a plethora of models with different degrees of complexity is available. How do we, geoscientists, decide what model complexity is warranted? Does this differ among disciplines? And, how do we even define model complexity? We developed a short questionnaire to investigate the geoscientific community’s views on complexity in models. The response was overwhelming, with 618 completed responses. The results show that the number of processes explicitly included and the number of interactions / feedbacks incorporated were seen as important determinants of complexity. Confidence was not per se higher in the simulations of a complex model compared to a simple one. Interestingly, neither gender, the discipline within the geosciences, nor career stage or work sector, explained the characterization of model complexity. The results of the questionnaire demonstrate that there is no general consensus on how model complexity is perceived or should be defined, and that formal definitions are not broadly or generally accepted. In an environment seeking greater collaboration and interdisciplinarity, these results indicate the need for conscious dialogue about this topic among different model users.

Two contiguous alluvial valleys (Maria and Guadalupe sectors) of the upper Guadalentín River (SE Spain) show distinct Holocene alluvial architecture (cut-and-fill, nested and stepped fill terraces), revealing a strong control of valley morphology and bedrock barriers on sediment delivery, storage and preservation. The headwater valley (Maria sector) preserves four morphosedimentary alluvial units corresponding to two palaeogeographic stages. Morphosedimentary unit (MSU1), the most extensive, is a major depositional valley infill dominated by sand and silt texture, showing three stratigraphic sets dated 9000–8500, 5300–4800, 4000–3000 cal BP. This vertically stacked alluvial accumulation occurs upstream of a narrow bedrock channel, that limited sediment connectivity with the downstream Guadalupe sector. Between 3000 and 2350 cal BP, a 15-m deep incision on MSU1 occurred, and subsequent cut-and-fill cycles generated three alluvial terraces dated at 2350–1900 cal BP (MSU2), 1800–700 cal BP (MSU3), and post-400 years (MSU4). In the downstream valley (Guadalupe sector), six flights of alluvial terraces (MSUg1 to MSUg6) were formed by episodic aggradation and quasi-continuous incision, in response to baselevel changes of the lower Guadalentín River during the Holocene. Alluvial chronologies in these two contiguous valleys show out-of-phase sedimentation periods under low connectivity conditions (9–3 ka), and in-phase cut-and-fill cycles after valley re-connection (post-3.0 ka). The late Holocene alluvial activity periods also coincide with morpho-stratigraphic data from the lower Guadalentín, indicating that fluvial connectivity throughout the catchment was only completed in the late Holocene.

We investigated the differences among two types of forest (pine and oak forests) and a meadow in soil water extractable organic carbon (WEOC), ammonium (NH4+) and nitrate (NO3−) concentrations in the Qinling Mountains, China. Our results showed that soil WEOC, NH4+ and NO3− concentrations were higher in the meadow than in the forests, and they were higher in the pine forest than in the oak forest. The soil surface temperature and soil water content were positively correlated with WEOC and inorganic nitrogen concentrations (P < 0.01). In addition, there was a significantly negative correlation between soil WEOC concentration and pH (P < 0.01). Moreover, soil WEOC concentration was positively correlated with the inorganic nitrogen concentration (P < 0.01). Generally, soil WEOC concentration decreased in the forests, and increased in the meadow under warming condition. The effects of warming on soil WEOC and dissolved inorganic nitrogen (DIN) concentrations varied with time. We elucidated that warming had a significant influence on soil WEOC concentration in the pine forest, whereas soil DIN concentration was affected significantly by warming only in the meadow. Our findings indicate that soil WEOC and DIN show different responses to warming in the mountain forest and meadow ecosystems. This study could provide useful insights for the prediction of soil carbon and nitrogen cycling and their responses to climate change in the complex mountain ecosystem.

Increased pore-water pressure due to rainfall infiltration and cyclic loading is a major cause of slope instability. Many studies have been carried out to assess rainfall-induced landslide spatial probability based on physical models, combining hydrological models to analyze changes in pore-water pressure on slopes due to rainfall. However, the generation of pore-water pressure due to seismic loading is often disregarded during assessments of earthquake-induced landslide susceptibility. Hence, in this paper, we propose a model to assess landslide spatial probability that takes into account increased pore-water pressure during both rainfall and earthquakes. The procedure for the proposed method includes two main steps. In step 1, we analyze the change in the groundwater table due to rainfall infiltration and subsurface flow during rainfall. In step 2, the slope safety factor is calculated using an infinite slope model, considering the generation of excess pore-water pressure under cyclic loading during earthquakes. Landslide spatial probability is established based on the slope factor of safety. We validated the proposed model by analyzing rainfall-earthquake-induced landslide events occurring on September 6, 2018 in Atsuma town, Japan. According to our results, the area under the receiver operating characteristic curve of the Atsuma landslide data is 82.4% and the true-positive rate of unstable slope classification is 98.1%. The proposed model was then applied to Mt. Umyeon, Korea, to assess the spatial probability of rainfall-earthquake-induced landslide. Our model classifies the likelihood of landslide occurrence according to four susceptibility levels: high, moderate, low and very low. We also compared our results to those of previous models and show that the proposed approach may provide reasonably accurate predictions of landslide spatial probability during rainfall and earthquake events.

Biological soil crusts (BSCs) are vital components of desert ecosystems. Developments of BSCs enrich nutrients, create niche differentiation and drive the variations of soil microbiota. However, how BSC developments drive the dynamics of soil prokaryotic and fungal community similarities and community assemblages remain fully elusive. Here, we evaluated the variations of microbial taxonomic and phylogenetic similarities with the developmental stages of BSC. Results showed that prokaryotic communities tended to be convergent in later BSC stages, mainly driven by the environmental filtering through nutrient accumulation. Deterministic processes and stochastic processes dominated in prokaryotic and fungal community assemblages, respectively. Most prokaryotic generalists (e.g., Actinobacteria, Proteobacteria and Thaumarcaeota) and generalists of lichenized fungi were more abundant in later BSC stages. Some prokaryotic generalists (e.g., Bacteroids, Cyanobacteria, Deltaproteobacteria) showed possible symbiotic (positive) relationships with generalists of lichenized fungi. BSC development promoted the abundances of prokaryotic generalists, but reduced prokaryotic specialists and both fungal generalists and specialists through increasing primary productivity. Additionally, prokaryotic co-occurrence networks (Co-MENs) tended to be less complex and less connected. Overall, the increases of prokaryotic generalists and decreases of specialists and less complex Co-MENs supported that prokaryotic communities were more convergent in later BSC stages. Our results provided mechanistic understandings of the interactions among microbial community succession, niche specialization and BSC development.

Soil and water losses are major environmental problems throughout the world. Many soil and water conservation techniques have been developed to protect food production and maintain ecological security. However, the current evaluation methods focus mainly on certain aspect of soil and water conservation technique, such as evaluating the implementation effects, and thus they cannot fully assess the characteristics of the technique, and insufficient consideration is given to the suitability of the technique itself and the implementation area. Therefore, the purpose of the study was to develop and test an evaluation framework for comprehensively assessing soil and water conservation technique as well as its impact. This comprehensive evaluation method was developed by theoretical primary selection and expert screening to assess the attributes, suitability, application effects, and potential of a specific technique. The evaluation framework comprises two levels: the target layer and index layer. The target layer assesses the adaptation effect of the ecological management technique. The index layer includes 5 first-level indices, 14 s-level indices, and 29 third-level indices. The analytic hierarchy process method was used to determine the weight of each index and the weighted composite index method was employed to construct the evaluation model. Soil and water conservation techniques applied in five small watersheds on the Loess Plateau in China were evaluated successfully with the evaluation framework (Gaoxigou 4.59, Wangdonggou 4.14, Xiannangou 3.89, Zhifanggou 3.81 and Chengjiagou 3.69), all of which reflected the actual situation for these local soil and water conservation techniques. The proposed evaluation framework can provide a scientific basis and key technical support for assessments of soil and water conservation techniques, as well as facilitating the development of innovative soil and water conservation techniques.

The near-surface saturated hydraulic conductivity (Ksat) is an important hydrological characteristic because it determines surface infiltration rates and the vertical and lateral redistribution of water in the soil. However, there is comparatively little knowledge about the changes in Ksat during landscape development and how the co-evolution of biological, pedological and hydrological characteristics affect the movement of water through the soil. On the one hand, increasing vegetation cover is expected to increase macroporosity and thus Ksat. On the other hand, clay formation is expected to decrease Ksat. To investigate how hillslope aging affects Ksat, we used a space-for-time approach and conducted comprehensive measurements of vegetation, soil and topography on a chronosequence of moraines in a proglacial area of the Swiss Alps. On four moraines, ranging from about ten thousand to ~30 years in age, we measured for three plots the near-surface soil characteristics. Surface and near-surface Ksat were high and decreased with depth on all moraines. Surface Ksat was highest on the youngest moraine (median: 4320 mm hr−1) and lowest (540 mm hr−1) on the oldest moraine. Ksat was significantly positive correlated with soil texture and the gravel content in the surface soil layer. The correlation analyses and Structural Equation Model suggested that the larger fraction of small particles for the older moraines had a bigger effect on Ksat than the denser root network. Even though the variability in measured Ksat-values within the moraines was high and water movement is thus likely very heterogeneous, the measured Ksat values suggest that infiltration-excess overland flow is very unlikely on these hillslopes but (lateral) near surface flow likely increases with the age of the hillslope. This information is important for understanding differences in runoff generation mechanisms in alpine areas with moraines of different ages, as well as landscape evolution models.

Understanding the creeping behavior of loess is of great importance as large-scale loess landslides are closely related with creep behavior. At present, it is still challenging to predict and estimate the long-term stability of such landslides. This is in a large degree due to the poor understanding of moisture control on creep behavior of loess. The purpose of this study is to decipher the loess creep behavior under various moisture contents (MCs) using loess specimens obtained from Baqiao landslide, Xi’an of China, using multi-loading triaxial creep tests under different MCs of 9%, 12%, 15%, 18% and 21%. Based on the laboratory test results, a series of relationships between the creep rate at the steady-state creep stage and the initial strain and initial shear modulus are revealed. Meanwhile, a method for obtaining the long-term strength of loess specimens, namely, the Steady-state Creep Rate Slope Method (SCRSM), is proposed. SCRSM resolves the issue in several conventional methods such as the Isochronous Stress-Strain Curve Method, the Tangent Method of Steady Creep Rate when MCs are of concern. Such an improvement is primarily due to a better way of finding the inflection point of the steady-state rate. It is found that SCRSM is robust and accurate to determine the long-term strength of loess specimens. Furthermore, we propose a modified Burgers model with a newly introduced nonlinear parameter n to overcome deficiencies of conventional creep models. This modified Burgers model is flexible to fit the creep test curves of loess, and can describe the curves at the accelerated creep stage more accurately. Lastly, the main factors triggering the Baqiao landslide is analyzed considering stratum lithology, rainfall and excavation. In general, this study provides a basis for understanding the evolutional process of loess landslides as well as guidelines for prevention, controlling and prediction of loess landslides.