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.     

中国主要化工矿产矿床类型划分方案

矿产是地球经历几十亿年贮存起来的自然资源,属于地球组成的一部分。这些资源是有限的,不可再生的,无论贮藏量有多丰富的矿藏,最终总有开采枯竭、使用完了的时候。例如,氟化工产品大多都来自称为萤石的化工矿石,萤石由氟化钙构成,地球的贮量是有限的。萤石首先制成氟化氢,一旦加工成氟化工产品,消耗了,就不可能再恢复为萤石。因此一旦地球上萤石消耗完,就要寻求其他氟来源,或使用其他制冷剂及橡胶产品。 化工矿产还具有不可替代性,特别是作为粮食的食粮的钾肥和磷肥。俗话说,“粮食一枝花,全靠肥当家”。中国的粮食生产十连增,化肥的贡献不可小觑。氮、磷、钾是化肥的主要元素,而磷、钾主要来源于自然界的矿物资源——钾盐和磷矿。     

1960-2014年湖南省极端气温事件变化特征分析

利用1960-2014年湖南省88个地面气象站日最高和最低气温的均一化资料,运用百分位阈值法统计暖日、暖夜、冷日和冷夜数,采用线性回归、M-K突变检验、Morlet小波分析等方法,研究湖南省55a以来极端气温事件的时空变化特征。结果表明：(1)湖南省暖日和暖夜数呈上升趋势,其年际变化倾向率分别为0.68d.(10a)-1、2.73 d.(10a)-1,冷日和冷夜数呈下降趋势,其年际变化倾向率分别为-0.45d.(10a)-1、-2.46d.(10a)-1,夜间增暖幅度大于白天增暖幅度;(2)湖南省大部分地区的暖日、暖夜数呈上升趋势,冷日数、冷夜数呈下降趋势,其中湘北、湘南部分地区变化趋势明显;(3)暖日、暖夜、冷夜数有明显的阶段性变化,其突变检验特征较明显,暖日、暖夜分别在2008、2003年突变增加,冷夜在1986年突变减少;(4)湖南省极端气温日数在不同的时间段存在着长短不同的振荡周期。