Analytical modeling on consolidation of stiffened deep mixed column-reinforced soft soil under embankment

Stiffened deep mixed (SDM) column is a new ground improvement technique to improve soft soil, which can be used to increase bearing capacity, reduce deformation, and enhance stability of soft soil. This technique has been successfully adopted to support the highway and railway embankments over soft soils in China and other countries. However, there have been limited investigations on its consolidation under embankment loading. This paper developed an analytical solution for the consolidation of embankment over soft soil with SDM column in which core pile is equal to or shorter than outer DM column. The consolidation problem was simplified as a consolidation of composite soil considering the load shear effect of core pile. The developed solution was verified by a comparison with the results computed by three-dimensional (3-D) finite element analysis. A parametric study based on the derived solution was conducted to investigate influence factors—length of core pile, diameter of core pile, diameter of SDM column, modulus of DM column, and permeability coefficient of DM column—on the consolidation behavior of SDM column-supported embankment over soft soil. The developed solution was applied to a case history of SDM column-supported embankment, and a good agreement was found between the predictions and the field measurements.     

Efficient estimation of flood forecast prediction intervals via single‐ and multi‐objective versions of the LUBE method

Prediction intervals (PIs) are commonly used to quantify the accuracy and precision of a forecast. However, traditional ways to construct PIs typically require strong assumptions about data distribution and involve a large computational burden. Here, we improve upon the recent proposed Lower Upper Bound Estimation method and extend it to a multi‐objective framework. The proposed methods are demonstrated using a real‐world flood forecasting case study for the upper Yangtze River Watershed. Results indicate that the proposed methods are able to efficiently construct appropriate PIs, while outperforming other methods including the widely used Generalized Likelihood Uncertainty Estimation approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatial and temporal variations of albedo on nine glaciers in western China from 2000 to 2011

This research demonstrates the spatiotemporal variations of albedo on nine glaciers in western China during 2000–2011, by the albedo derived from two types of datasets: Landsat TM/ETM + images and MOD10A1 product. Then, the influence factors of glacier albedo and its relationship with glacier mass balance are also analyzed by the correlation approach, which is frequently used in geostatistics. The paper finds that there are different spatiotemporal variations over the glaciers in western China: (1) For a single glacier, the albedo varies gently with altitude on its tongue and increases fast in the middle part, while in the accumulation zones, the albedo value appears in the form of fluctuation. This could provide a quantitative method to retrieve the snowline by determining the threshold albedo value of snowpack and bare ice. (2) For the glaciers in western China, the albedo decreases with distance to the center of Tibetan Plateau (TP). This may relate to the elevation of glacier, for the speed of glacier retreat highly depends on air temperature. (3) In the summer period, albedo on most glaciers declines over the last 12 years, and it decreases much faster in southeastern TP than other regions, for which air temperature overwhelms the black carbon concentration. In addition, the trend of glacier albedo in summer is greatly correlated with that of measured glacier mass balance, which implies that the long‐term albedo datasets by remote sensing technology could be used to monitor and predict the change of glacier mass balance in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Integrative propositions for adapting conservation policy to the impacts of climate change

Conservation policies have changed over time in response to changes in human and ecological drivers. The impacts of climate (and other) concurrent changes prompt consideration of further iterations for both conservation means and objectives. In this paper we bring together previous disparate literatures and apply them to the question of how to adapt conservation polices to suit an era of climate change impacts. Our approach is based on two assertions: (i) that the integration of specific natural and social science insights is essential for understanding and effectively responding to this challenge, and (ii) that in addition to adaptive conservation means (strategies), attention needs to be given to considering adaptive conservation objectives. Specifically, we convert a core set of natural and social science insights into analytical tools known as heuristics or rules of thumb. We then use the heuristics as a basis to offer a list of preliminary propositions that can help inform the development of new means and objectives. The propositions address key considerations including recalibrating management objectives, the role of disturbance in facilitating ecological transitions, and overarching topics relating to governance. The propositions are speculative, and so intended only to outline potential avenues for further empirical research and subsequent refinement. In the spirit of adaptation, we expect and welcome their revision.