Response of soil aggregate disintegration to the different content of organic carbon and its fractions during splash erosion

Aggregate disintegration is a critical process in soil splash erosion. However, the effect of soil organic carbon (SOC) and its fractions on soil aggregates disintegration is still not clear. In this study, five soils with similar clay contents and different contents of SOC have been used. The effects of slaking and mechanical striking on splash erosion were distinguished by using deionized water and 95% ethanol as raindrops. The simulated rainfall experiments were carried out in four heights (0.5, 1.0, 1.5 and 2.0 m). The result indicated that the soil aggregate stability increased with the increases of SOC and light fraction organic carbon (LFOC). The relative slaking and the mechanical striking index increased with the decreases of SOC and LFOC. The reduction of macroaggregates in eroded soil gradually decreased with the increase of SOC and LFOC, especially in alcohol test. The amount of macroaggregates (>0.25 mm) in deionized water tests were significantly less than that in alcohol tests under the same rainfall heights. The contribution of slaking to splash erosion increased with the decrease of heavy fractions organic carbon. The contribution of mechanical striking was dominant when the rainfall kinetic energy increased to a range of threshold between 9 J m⁻² mm⁻¹ and 12 m⁻² mm⁻¹. This study could provide the scientific basis for deeply understanding the mechanism of soil aggregates disintegration and splash erosion.     

Size and spatial distribution of loess slides on the Chinese Loess Plateau

ABSTRACT

The size and spatial distribution of loess slides are important for estimating the yield of eroded materials and determining the landslide risk. While previous studies have investigated landslide size distributions, the spatial distribution pattern of landslides at different spatial scales is poorly understood. The results indicate that the loess slide distribution exhibits a power-law scaling across a range of the size distribution. The mean landslide size and size distribution in the different geomorphic types are different. The double Pareto and inverse gamma functions can coincide well with the empirical probability distribution of the loess slide areas and can quantitatively reveal the rollover location, maximum probability, and scaling exponents. The frequency of loess slides increases with mean monthly precipitation. Moreover, point distance analysis showed that > 80% of landslides are located < 3 km from other loess slides. We found that the loess slides at the two study sites (Zhidan and Luochuan County) in northern Shaanxi Province, China show a significant clustered distribution. Furthermore, analysis results of the correlated fractal dimension show that the landslides exhibit a dispersed distribution at smaller spatial scales and a clustered distribution at larger spatial scales.     

Frequency analysis of nonstationary annual maximum flood series using the time‐varying two‐component mixture distributions

The most popular practice for analysing nonstationarity of flood series is to use a fixed single‐type probability distribution incorporated with the time‐varying moments. However, the type of probability distribution could be both complex because of distinct flood populations and time‐varying under changing environments. To allow the investigation of this complex nature, the time‐varying two‐component mixture distributions (TTMD) method is proposed in this study by considering the time variations of not only the moments of its component distributions but also the weighting coefficients. Having identified the existence of mixed flood populations based on circular statistics, the proposed TTMD was applied to model the annual maximum flood series of two stations in the Weihe River basin, with the model parameters calibrated by the meta‐heuristic maximum likelihood method. The performance of TTMD was evaluated by different diagnostic plots and indexes and compared with stationary single‐type distributions, stationary mixture distributions and time‐varying single‐type distributions. The results highlighted the advantages of TTMD with physically‐based covariates for both stations. Besides, the optimal TTMD models were considered to be capable of settling the issue of nonstationarity and capturing the mixed flood populations satisfactorily. Copyright © 2016 John Wiley & Sons, Ltd.     

Carboniferous eclogite and garnet–omphacite granulite from northeastern Hainan Island,South China: Implications for the evolution of the eastern Palaeo‐Tethys

High‐P (HP) eclogite and associated garnet–omphacite granulite have recently been discovered in the Mulantou area, northeastern Hainan Island, South China. These rocks consist mainly of garnet, omphacite, hornblende, quartz and rutile/ilmenite, with or without zoisite and plagioclase. Textural relationships, mineral compositions and thermobarometric calculations demonstrate that the eclogite and garnet–omphacite granulite share the same three‐stage metamorphic evolution, with prograde, peak and retrograde P?T conditions of 620–680°C and 8.7–11.1 kbar, 820–860°C and 17.0–18.2 kbar, and 700–730°C and 7.1–8.5 kbar respectively. Sensitive high‐resolution ion microprobe U–Pb zircon dating, coupled with the identification of mineral inclusions in zircon, reveals the formation of mafic protoliths before 355 Ma, prograde metamorphism at c. 340–330 Ma, peak to retrograde metamorphism at c. 310–300 Ma, and subsequent pegmatite intrusion at 295 Ma. Trace element geochemistry shows that most of the rocks have a MORB affinity, with initial ε_Nd values of +2.4 to +6.7. As with similar transitional eclogite–HP granulite facies rocks in the thickened root in the European Variscan orogen, the occurrence of relatively high P?T metamorphic rocks of oceanic origin in northeastern Hainan Island suggests Carboniferous oceanic subduction leading to collision of the Hainan continental block, or at least part of it, with the South China Block in the eastern Palaeo‐Tethyan tectonic domain.     

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.     

Multiple overpressure systems and their relationship with hydrocarbon accumulation in the Qikou Depression of the Bohai Bay Basin,China

Pressure measurements using drill stem tests and estimates from log data calculation indicate that three vertically stacked regional pressure compartments exist in the Qikou Depression of Bohai Bay Basin, N. China. The compartments comprise hydrostatic, upper weak, and lower overpressure systems. Laterally, overpressure (pressure coefficient > 1.2) occurs in the deeper areas and weakens gradually from the centre to the margin of the depression. The accumulation of oil and gas exhibits the interesting characteristics of oil‐bearing layers above gas‐bearing layers in the Qikou Depression. The pattern can be accounted for by the evolution of overpressure system, the maturity process of the source rock and the main fault activity. In the late Dongying Formation (Ed, 30 Ma), the lower overpressure system began to form shape, and the hydrocarbon sources generated a large volume of oil. However, because there was no migration pathway, the oil only accumulated in the original strata. In the late Guantao Formation (Ng, 12 Ma), the gas was generated, the upper overpressure system formed gradually, and the activity of the main fault gradually increased. Then, the overpressure pushed the early gathered oil to flow from the lower overpressure system into the upper overpressure system. Afterwards, the activity of the main fault decreased again and remains weak until now. Thus, later generated natural gas cannot keep migrating along the main fault and can only accumulate in the lower overpressure system. Copyright © 2014 John Wiley & Sons, Ltd.     

An asynchronous Geoprocessing Workflow and its application to an Antarctic ozone monitoring and mapping service

The integration of Sensor Web Enablement services with other Open Geospatial Consortium (OGC) Web Services as Geospatial Processing Workflows (GPW) is essential for future Sensor Web application scenarios. With the help of GPW technology, distributed and heterogeneous OGC Web Services can be organized and integrated as compound Web Service applications that can direct complicated earth observation tasks. Under the Sensor Web environment, asynchronous communications between Sensor Web Services are common. We have proposed an asynchronous GPW architecture for the integration of Sensor Web Services into a Web Service Business Process Execution Language workflow technology. We designed a Sensor Information Accessing and Processing workflow, an asynchronous GPW instance, to take an experiment of observing and mapping ozone over Antarctica. Based on our results, our proposed asynchronous workflow method shows the advantages of taking environmental monitoring and mapping tasks.     

Precipitation variability assessment of northeast China: Songhua River basin

Variability in precipitation is critical for the management of water resources. In this study, the research entropy base concept was applied to investigate spatial and temporal variability of the precipitation during 1964–2013 in the Songhua River basin of Heilongjiang Province in China. Sample entropy was applied on precipitation data on a monthly, seasonally, annually, decade scale and the number of rainy days for each selected station. Intensity entropy and apportionment entropy were used to calculate the variability over individual year and decade, respectively. Subsequently, Spearman’s Rho and Mann–Kendall tests were applied to observe for trends in the precipitation time series. The statistics of sample disorder index showed that the precipitation during February (mean 1.09, max. 1.26 and min. 0.80), April (mean 1.12, max. 1.29 and min. 0.99) and July (mean 1.10, max. 1.20 and min. 0.98) contributed significantly higher than those of other months. Overall, the contribution of the winter season was considerably high with a standard deviation of 0.10. The precipitation variability on decade basis was observed to increase from decade 1964–1973 and 1994–2003 with a mean value of decadal apportionment disorder index 0.023 and 0.053, respectively. In addition, the Mann–Kendall test value (1.90) showed a significant positive trend only at the Shangzhi station.     

Thermal equation of state of natural tourmaline at high pressure and temperature

Synchrotron-based in situ angle-dispersive X-ray diffraction experiments were conducted on a natural uvite-dominated tourmaline sample by using an external-heating diamond anvil cell at simultaneously high pressures and temperatures up to 18 GPa and 723 K, respectively. The angle-dispersive X-ray diffraction data reveal no indication of a structural phase transition over the P–T range of the current experiment in this study. The pressure–volume–temperature data were fitted by the high-temperature Birch–Murnaghan equation of state. Isothermal bulk modulus of K ₀ = 96.6 (9) GPa, pressure derivative of the bulk modulus of \(K_{0}^{\prime } = 12.5 \;(4)\), thermal expansion coefficient of α ₀ = 4.39 (27) × 10^?5 K^?1 and temperature derivative of the bulk modulus (?K/?T) _P  = ?0.009 (6) GPa K^?1 were obtained. The axial thermoelastic properties were also obtained with K _a0 = 139 (2) GPa, \(K_{a0}^{\prime }\) = 11.5 (7) and α _a0 = 1.00 (11) × 10^?5 K^?1 for the a-axis, and K _c0 = 59 (1) GPa, \(K_{c0}^{\prime }\) = 11.4 (5) and α _c0 = 2.41 (24) × 10^?5 K^?1 for the c-axis. Both of axial compression and thermal expansion exhibit large anisotropic behavior. Thermoelastic parameters of tourmaline in this study were also compared with that of the other two ring silicates of beryl and cordierite.