Root‐zone moisture replenishment in a native vegetated catchment under Mediterranean climate

The root‐zone moisture replenishment mechanisms are key unknowns required to understand soil hydrological processes and water sources used by plants. Temporal patterns of root‐zone moisture replenishment reflect wetting events that contribute to plant growth and survival and to catchment water yield. In this study, stable oxygen and hydrogen isotopes of twigs and throughfall were continuously monitored to characterize the seasonal variations of the root‐zone moisture replenishment in a native vegetated catchment under Mediterranean climate in South Australia. The two studied hillslopes (the north‐facing slope [NFS] and the south‐facing slope [SFS]) had different environmental conditions with opposite aspects. The twig and throughfall samples were collected every ~20 days over 1 year on both hillslopes. The root‐zone moisture replenishment, defined as percentage of newly replenished root‐zone moisture as a complement to antecedent moisture for plant use, calculated by an isotope balance model, was about zero (±25% for the NFS and ± 15% for the SFS) at the end of the wet season (October), increased to almost 100% (±26% for the NFS and ± 29% for the SFS) after the dry season (April and May), then decreased close to zero (±24% for the NFS and ± 28% for the SFS) in the middle of the following wet season (August). This seasonal pattern of root‐zone moisture replenishment suggests that the very first rainfall events of the wet season were significant for soil moisture replenishment and supported the plants over wet and subsequent dry seasons, and that NFS completed replenishment over a longer time than SFS in the wet season and depleted the root zone moisture quicker in the dry season. The stable oxygen isotope composition of the intraevent samples and twigs further confirms that rain water in the late wet season contributed little to root‐zone moisture. This study highlights the significant role of the very first rain events in the early wet season for ecosystem and provides insights to understanding ecohydrological separation, catchment water yield, and vegetation response to climate changes.     

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.     

Generation of continuous surface soil moisture dataset using combined optical and thermal infrared images

Surface soil moisture (SSM) is a critical variable for understanding water and energy flux between the atmosphere and the Earth's surface. An easy to apply algorithm for deriving SSM time series that primarily uses temporal parameters derived from simulated and in situ datasets has recently been reported. This algorithm must be assessed for different biophysical and atmospheric conditions by using actual geostationary satellite images. In this study, two currently available coarse‐scale SSM datasets (microwave and reanalysis product) and aggregated in situ SSM measurements were implemented to calibrate the time‐invariable coefficients of the SSM retrieval algorithm for conditions in which conventional observations are rare. These coefficients were subsequently used to obtain SSM time series directly from Meteosat Second Generation (MSG) images over the study area of a well‐organized soil moisture network named REMEDHUS in Spain. The results show a high degree of consistency between the estimated and actual SSM time series values when using the three SSM dataset‐calibrated time‐invariable coefficients to retrieve SSM, with coefficients of determination (R²) varying from 0.304 to 0.534 and root mean square errors ranging from 0.020 m³/m³ to 0.029 m³/m³. Further evaluation with different land use types results in acceptable debiased root mean square errors between 0.021 m³/m³ and 0.048 m³/m³ when comparing the estimated MSG pixel‐scale SSM with in situ measurements. These results indicate that the investigated method is practical for deriving time‐invariable coefficients when using publicly accessed coarse‐scale SSM datasets, which is beneficial for generating continuous SSM dataset at the MSG pixel scale.     

Reevaluating suitability estimates based on dynamics of cropland expansion in the Brazilian Amazon

Agricultural suitability maps are a key input for land use zoning and projections of cropland expansion. Suitability assessments typically consider edaphic conditions, climate, crop characteristics, and sometimes incorporate accessibility to transportation and market infrastructure. However, correct weighting among these disparate factors is challenging, given rapid development of new crop varieties, irrigation, and road networks, as well as changing global demand for agricultural commodities. Here, we compared three independent assessments of cropland suitability to spatial and temporal dynamics of agricultural expansion in the Brazilian state of Mato Grosso during 2001–2012. We found that areas of recent cropland expansion identified using satellite data were generally designated as low to moderate suitability for rainfed crop production. Our analysis highlighted the abrupt nature of suitability boundaries, rather than smooth gradients of agricultural potential, with little additional cropland expansion beyond the extent of the flattest areas (0–2% slope). Satellite-based estimates of the interannual variability in the use of existing crop areas also provided an alternate means to assess suitability. On average, cropland areas in the Cerrado biome had higher utilization (84%) than croplands in the Amazon region of northern Mato Grosso (74%). Areas of more recent expansion had lower utilization than croplands established before 2002, providing empirical evidence for lower suitability or alternative management strategies (e.g., pasture–soya rotations) for lands undergoing more recent land use transitions. This unplanted reserve constitutes a large area of potentially available cropland (PAC) without further expansion, within the management limits imposed for pest management and fallow cycles. Using two key constraints on future cropland expansion, slope and restrictions on further deforestation of Amazon or Cerrado vegetation, we found little available flat land for further legal expansion of crop production in Mato Grosso. Dynamics of cropland expansion from more than a decade of satellite observations indicated narrow ranges of suitability criteria, restricting PAC under current policy conditions, and emphasizing the advantages of field-scale information to assess suitability and utilization.     

Modelling the flow of self‐compacting concrete

A Lagrangian particle‐based method, smooth particle hydrodynamics (SPH), is used in this paper to model the flow of self‐compacting concretes (SCC) with or without short steel fibres. An incompressible SPH method is presented to simulate the flow of such non‐Newtonian fluids whose behaviour is described by a Bingham‐type model, in which the kink in the shear stress vs shear strain rate diagram is first appropriately smoothed out. The viscosity of the SCC is predicted from the measured viscosity of the paste using micromechanical models in which the second phase aggregates are treated as rigid spheres and the short steel fibres as slender rigid bodies. The basic equations solved in the SPH are the incompressible mass conservation and Navier–Stokes equations. The solution procedure uses prediction–correction fractional steps with the temporal velocity field integrated forward in time without enforcing incompressibility in the prediction step. The resulting temporal velocity field is then implicitly projected on to a divergence‐free space to satisfy incompressibility through a pressure Poisson equation derived from an approximate pressure projection. The results of the numerical simulation are benchmarked against actual slump tests carried out in the laboratory. The numerical results are in excellent agreement with test results, thus demonstrating the capability of SPH and a proper rheological model to predict SCC flow and mould‐filling behaviour. Copyright © 2010 John Wiley & Sons, Ltd.     

基于NGM(1,1,k,c)模型和改进切线角的危岩变形预测

针对危岩变形预测问题,本文以非齐次指数序列的灰色模型(NGM)作为危岩变形预测的基本模型,通过对望霞危岩变形的分析结果显示,NGM(1,1,k,c)模型拟合效果明显优于GM(1,1)模型,说明危岩变形趋势更接近于非齐次指数序列。利用NGM(1,1,k,c)模型结合改进切线角可对危岩变形趋势进行分析预测,可作为危岩稳定性和发展趋势的评估依据。     

求解GM(1,1)模型新总体最小二乘算法

在GM(1,1)模型中系数矩阵和观测向量都是由原始序列组成的。系数矩阵中同样是有误差的,与观测向量中的误差一样,亦来源于原始序列,即它们误差同源。不同位置的相同元素应该有相同的改正数,采用传统总体最小二乘求解则不能达到此目的。针对这一缺陷,推导了一种新的总体最小二乘算法;并且通过算例验证了新方法的可行性和有效性。     

Flexible membranes anchored to the ground for slope stabilisation: Numerical modelling of soil slopes using SPH

An alternative modelling for flexible membranes anchored to the ground for soil slope stabilisation is presented using Smoothed-Particle Hydrodynamics to model the unstable ground mass in a soil slope, employing a dynamic solve engine. A regression model of pressure normal to the ground, q_sim, and also membrane deflection, f_sim, have been developed using Design of Experiment. Finally, a comparison between the pressure obtained from numerical simulation and from a limit equilibrium analysis considering infinite slope has been carried out, showing differences in the results, mainly due to the membrane stiffness.     

香港世界地质公园晚侏罗世荔枝庄组岩石组合及其成岩地质过程解析

中国东南大陆晚侏罗世地层普遍缺失,仅零星见于个别地区,香港新界东北的荔枝庄组即为其一。荔枝庄组出露于香港世界地质公园沉积岩园区的荔枝庄地区,自下往上由火山岩—沉积岩—火山岩组合而成,沉积岩中发育大型包卷层理和滑塌构造等典型沉积构造,是香港地区最具代表性的晚侏罗世火山—沉积岩系。通过实测地层剖面研究,确定其成岩过程大体上可划分为早期普林尼式火山爆发、中期破火山口湖相沉积和晚期普林尼式火山爆发三个阶段,以湖相沉积作用为主、火山喷发作用为辅;受晚期火山岩浆活动的影响,沉积岩层普遍发生硅化或炭化。荔枝庄组独特的岩石组合与形成的古地理环境,为探讨中国东南大陆中生代火山活动—沉积作用方式与成岩过程,提供了难得的研究实例。