Temporal variation of soil erosion resistance on sloping farmland during the growth stages of maize (Zea mays L.)

Maize growth has great effects on soil properties and thus likely induces the changes in soil erosion resistance on sloping farmland. However, temporal variation of soil erosion resistance during the growth stages of maize is still unclear in the mountainous yellow soil area where maize is the dominant crop. In this study, four maize plots (MP) and four bare land plots (CK) were conducted to investigate soil erosion resistance, and multiple indicators of soil erosion resistance were measured including the total soil anti-scourability (TAS), mean weight diameter (MWD), soil erodibility K factor and soil shear strength (SH). A comprehensive soil erosion resistance index (CSERI) was employed to quantify the temporal variation of soil erosion resistance during the growth stages of maize (seedling stage, SS; jointing stage, JS; tasselling stage, TS; maturing stage, MS). The results showed that TAS, MWD, SH increased significantly with maize growth and SH decreased when at MS. But K factor decreased significantly over time. CSERI increased significantly during the growth stages of maize and the CSERI of JS, TS, MS increased on average by 74.72, 180.68 and 234.57% than that of SS. Compared to CK, CSERI of MP increased by 49.90, 66.82, 55.60 and 38.61% during the growth stages of maize. The temporal variation of soil erosion resistance was closely related to the changes in maize cover, maize roots and soil organic carbon. The findings demonstrated that it is necessary to consider the temporal variation of soil erosion resistance in the mountainous yellow soil area.     

Damage and Acoustic Emission Characteristics of Combined Rock Mass with Anchor Under Different Inclination Angles and Combination Modes

Geotechnical and Geological Engineering - Soft and hard rock assemblages and anchor solids have important effects on rock mechanics properties under different inclinations and assemblages, so it is...     

Variability in the vertical hyporheic water exchange affected by hydraulic conductivity and river morphology at a natural confluent meander bend

River confluences and their associated tributaries are key morphodynamic nodes that play important roles in controlling hydraulic geometry and hyporheic water exchange in fluvial networks. However, the existing knowledge regarding hyporheic water exchange associated with river confluence morphology is relatively scarce. On January 14 and 15, 2016, the general hydraulic and morphological characteristics of the confluent meander bend (CMB) between the Juehe River and the Haohe River in the southern region of Xi'an City, Shaanxi Province, China, were investigated. The patterns and magnitudes of vertical hyporheic water exchange (VHWE) were estimated based on a one‐dimensional heat steady‐state model, whereas the sediment vertical hydraulic conductivity (K_v) was calculated via in situ permeameter tests. The results demonstrated that 6 hydrodynamic zones and their extensions were observed at the CMB during the test period. These zones were likely controlled by the obtuse junction angle and low momentum flux ratio, influencing the sediment grain size distribution of the CMB. The VHWE patterns at the test site during the test period mostly showed upwelling flow dominated by regional groundwater discharging into the river. The occurrence of longitudinal downwelling and upwelling patterns along the meander bend at the CMB was likely subjected to the comprehensive influences of the local sinuosity of the meander bend and regional groundwater discharge and finally formed regional and local flow paths. Additionally, in dominated upwelling areas, the change in VHWE magnitudes was nearly consistent with that in K_v values, and higher values of both variables generally occurred in erosional zones near the thalweg paths of the CMB, which were mostly made up of sand and gravel. This was potentially caused by the erosional and depositional processes subjected to confluence morphology. Furthermore, lower K_v values observed in downwelling areas at the CMB were attributed to sediment clogging caused by local downwelling flow. The confluence morphology and sediment K_v are thus likely the driving factors that cause local variations in the VHWE of fluvial systems.     

Using stable isotopes to understand seasonal and interannual dynamics in moisture sources and atmospheric circulation in precipitation

Stable isotopes in precipitation are useful tracers to strengthen understanding of climate change and hydrological processes. In this study, the moisture sources of 190 precipitation events in Beijing were analysed using the Hybrid Single‐particle Lagrangian Integrated Trajectory model, based on which we studied the relation between variations in precipitation δ¹⁸O and dynamics in moisture sources and atmospheric circulation in seasonal and interannual timescales. Categorization of 7 groups of moisture sources was performed, among which oceanic moisture sources presented lower δ¹⁸O in precipitation than continental moisture sources. The results show that seasonal variations of precipitation δ¹⁸O were caused by changes of moisture sources. In summer, moisture from proximal oceans dominated vapour transport to Beijing due to increasing monsoon strength and resulted in a relatively small variation of precipitation δ¹⁸O. At the interannual timescale, the variations of δ¹⁸O in summer precipitation were related to dynamics in oceanic moistures, showing depleted values when the contribution of oceanic moistures, especially the proportion of long‐distance oceanic moisture, was high. Further analysis indicated that changes of oceanic moisture sources were controlled by the strength of summer monsoons. These findings address the complexity of moisture sources in midlatitude monsoon areas and suggest that isotopic signals in precipitation have the potential to deduce changes in moisture sources and atmospheric circulation and can therefore serve for palaeoclimate reconstruction.     

Temporal stability of soil moisture in an oasis of northwestern China

Temporal stability of soil moisture has been widely used in hydrological monitoring since it emerged. However, the spatial analysis of temporal stability at the landscape scale is often limited because of insufficient sampling numbers. This work made an effort to investigate the spatial variations of temporal stability of soil moisture in an oasis landscape. The specific objectives of the study were to explore the spatial patterns of temporal stability and to determine the controlling factors of temporal stability in the desert oasis. A time series of soil moisture measurements were gathered on 23 occasions at 118 locations over 3 years in a rectangular transect of approximately 100 km². The nonparametric Spearman's rank correlation coefficient, standard deviation of relative difference (SDRD), and mean absolute bias error (MABE) were used to quantify the temporal stability of soil moisture. Results showed that the temporal stability of soil moisture was depth dependent and season dependent. The spatial pattern of soil moisture in a deep soil layer and between two same seasons generally had a high temporal stability. SDRD and MABE were spatially autocorrelated and exhibited strong spatial structures in the geographic space. The concept of temporal stability can be extended to describe the time‐stable areas of soil moisture with geostatistics. There were great differences between SDRD and MABE in describing the temporal stability of soil moisture and in identifying the controlling factors of temporal stability. In this case, MABE was a better alternative to estimate the areal mean soil moisture using representative locations than SDRD. Land use type, soil moisture condition, and soil particle composition were the dominant controls of temporal stability in the oasis. These insights could help to better understand the essence of temporal stability of soil moisture in arid regions.     

Simulation of site-scale water fluxes in desert and natural oasis ecosystems of the arid region in Northwest China

The study of water fluxes is important to better understand hydrological cycles in arid regions. Data-driven machine learning models have been recently applied to water flux simulation. Previous studies have built site-scale simulation models of water fluxes for individual sites separately, requiring a large amount of data from each site and significant computation time. For arid areas, there is no consensus as to the optimal model and variable selection method to simulate water fluxes. Using data from seven flux observation sites in the arid region of Northwest China, this study compared the performance of random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and multiple linear regression (MLR) models in simulating water fluxes. Additionally, the study investigated inter-annual and seasonal variation in water fluxes and the dominant drivers of this variation at different sites. A universal simulation model for water flux was built using the RF approach and key variables as determined by MLR, incorporating data from all sites. Model performance of the SVM algorithm (R² = 0.25–0.90) was slightly worse than that of the RF algorithm (R² = 0.41–0.91); the BPNN algorithm performed poorly in most cases (R² = 0.15–0.88). Similarly, the MLR results were limited and unreliable (R² = 0.00–0.66). Using the universal RF model, annual water fluxes were found to be much higher than the precipitation received at each site, and natural oases showed higher fluxes than desert ecosystems. Water fluxes were highest during the growing season (May–September) and lowest during the non-growing season (October–April). Furthermore, the dominant drivers of water flux variation were various among different sites, but the normalized difference vegetation index (NDVI), soil moisture and soil temperature were important at most sites. This study provides useful insights for simulating water fluxes in desert and oasis ecosystems, understanding patterns of variation and the underlying mechanisms. Besides, these results can make a contribution as the decision-making basis to the water management in desert and oasis ecosystems.