Influence of a coarse interlayer on seawater intrusion and contaminant migration in coastal aquifers

Vertical 2D slice laboratory experiments were carried out in homogenous and layered sand tanks to elucidate the effects of a highly permeable (coarse‐grained sand) interlayer on seawater intrusion and transport of contaminants to a coastal sea. Tidal fluctuations produced oscillations in the seawater–freshwater transition zone, fluctuations of the contaminant infiltration rate and a zigzag contaminant plume outline. The seawater wedge became discontinuous at the (vertical) edges of the interlayer because of increased lateral movement of the seawater–freshwater interface within the interlayer. The contaminant plume formed a tail within the interlayer depending on the tidal stage, and similar to the wedge, its movement was accentuated. A simple analytical model that neglected vertical flow reliably predicted steady‐state seawater intrusion into the coastal aquifer. Numerical modeling was used to gain insight into the groundwater hydrodynamics and contaminant migration. The numerical results confirmed the experimental findings, i.e. that a highly permeable interlayer can provide a rapid transit path for contaminants to reach the seaward boundary and that the interlayer amplifies the effects of tidal fluctuations, resulting in wider transition zones for the seawater wedge and contaminant plume. Numerical simulations further showed that, with increasing interlayer hydraulic conductivity, the maximum seawater intrusion distance inside the interlayer increases approximately linearly. For the fixed‐head contaminant injection condition used, the model showed that contaminant infiltration increases approximately logarithmically with increasing interlayer hydraulic conductivity (other factors held fixed). Copyright © 2013 John Wiley & Sons, Ltd.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

桂林毛村不同植被类型土壤微生物数量与碳酸酐酶活性比较

以非岩溶区林地为对比,分析了桂林毛村岩溶区4种不同植被类型土壤微生物数量及碳酸酐酶(CA)活性的季度动态变化规律,发现以下主要结果:1随着植被的正向演替,岩溶区弃耕地、草地、灌丛及林地微生物数量及CA活性逐渐升高,微生物总数从64.07×10~4cfu/g上升到178.23×10~4cfu/g,CA活性从0.77 U/g上升到1.82 U/g,岩溶区林地大于非岩溶区林地。2在岩溶区不同植被类型,微生物组成均表现为细菌最多(平均值95.14%),放线菌次之(平均值2.79%),真菌数量最少(平均值1.75%)。而在非岩溶区表现为细菌最多(平均值90.95%),真菌次之(平均值5.32%),放线菌最少(平均值3.73%)。3微生物数量季节动态整体表现为春季至夏季逐渐上升,至秋季达到最高,冬季下降,微生物总数的增长依赖于细菌的倍数增长,真菌和放线菌影响较小。CA活性整体表现为夏季和冬季低于春季和秋季,秋季达到最大值。4 CA活性与细菌及微生物总数呈极显著的正相关,表明土壤CA主要来源于细菌的分泌。     

Energy budgets on the interactions between the mean and eddy flows during a persistent heavy rainfall event over the Yangtze River valley in summer 2010

In this study,a persistent heavy rainfall event(PHRE) that lasted for around 9 days(from 0000 UTC 17 to0000 UTC 26 June 2010) and caused accumulated precipitation above 600 mm over the Yangtze River valley,was reasonably reproduced by the advanced research WRF model.Based on the simulation,a set of energy budget equations that divided the real meteorological field into the mean and eddy flows were calculated so as to understand the interactions between the precipitation-related eddy flows and their background circulations(BCs).The results indicated that the precipitation-related eddy flows interacted with their BCs intensely during the PHRE.At different layers,the energy cycles showed distinct characteristics.In the upper troposphere,downscaled energy cascade processes appeared,which favored the maintenance of upper-level eddy flows;whereas,a baroclinic energy conversion,which reduced the upper-level jet,also occurred.In the middle troposphere,significant upscaled energy cascade processes,which reflect the eddy flows’ reactionary effects on their BCs,appeared.These effects cannot be ignored with respect to the BCs’ evolution,and the reactionary effects were stronger in the dynamical field than in the thermodynamical field.In the lower troposphere,a long-lived quasi-stationary lower-level shear line was the direct trigger for the PHRE.The corresponding eddy flows were sustained mainly through the baroclinic energy conversion associated with convection activities.Alongside this,the downscaled energy cascade processes of kinetic energy,which reflect the direct influences of BCs on the precipitation-related eddy flows,were also favorable.A downscaled energy cascade of exergy also appeared in the lower troposphere,which favored the precipitation-related eddy flow indirectly via the baroclinic energy conversion.     

A timescale decomposed threshold regression downscaling approach to forecasting South China early summer rainfall

A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.     

Changes in the boreal summer intraseasonal oscillation projected by the CNRM-CM5 model under the RCP 8.5 scenario

Climate Dynamics - The 30–60-day boreal summer intraseasonal oscillation (BSISO) is the predominant intraseasonal variability in the Asian summer monsoon (ASM) region, representing the...