Determination of trace and rare-earth elements in Chinese soil and clay reference materials by ICP-MS

Inductively coupled plasma mass spectrometry(ICP-MS) has become a powerful tool for providing reliable analytical results in many laboratories around the word. In this study, the mixture of HF and HNO3 acids in high-temperature and high-pressure closed-vessel digestion technique were used to decompose some Chinese reference materials, and thirty seven elements were determined by ICP-MS. Most of the results for Chinese soil reference materials were found to be in reasonable agreement with the reference values, except Cs, Ta, Li, Ge, Zn, Nd, Tb and Ta whose values need to be revised. Their precisions were typically lower than 5% RSD. However, the Precisions of Chinese clay reference materials, especially for GBW03102 and GBW03102a, were significantly different with reference values, probably reflecting the existence of a coarser-grained fraction(70 μm) in samples, and the formation of fluorides in Al-rich samples during sample decomposition by using the mixture of HF and HNO3 acids. Moreover, thirty-seven trace elements covering the mass range from Li to U in four Chinese clay reference materials were firstly provided with good precision and accuracy in this study.     

基于遥感影像的黄河内蒙古段冰-水分类研究

及时获取凌汛期河冰和水体的空间分布特征,对于预测冰凌灾害、提高防凌信息化管理水平有重要意义。遥感技术是当前获取河冰和水体空间分布的最主要手段之一。但是,黄河水体有大量悬浮泥沙,这给基于遥感技术的高精度冰-水分类带来了挑战。以黄河内蒙古段为例,基于Landsat 8 OLI遥感影像数据,在利用归一化积雪指数（NDSI）及河道矢量数据排除无关地物的基础上,对比了近红外波段反射率值、归一化差异水体指数（NDWI）、归一化积雪指数（NDSI）、改进的归一化积雪指数（MNDSI）以及归一化差异未封冻水体指数（NDUWI）在黄河内蒙古段典型河道河冰、水体分类中的表现,计算各指标总体分类精度及Kappa系数并进行阈值稳定性分析。结果表明：在利用NDSI和高清历史影像排除河道外无关地物后,NDUWI在各子段影像中的总体分类精度和Kappa系数均达到90.00%及0.90以上,其河冰、水体最优区分阈值大体分布于阈值中值附近。研究结果可为凌汛期黄河冰凌监测方法的选取以及冰上爆破位置的拟定提供依据。     

Impacts of uncertain river flow data on rainfall‐runoff model calibration and discharge predictions

In order to quantify total error affecting hydrological models and predictions, we must explicitly recognize errors in input data, model structure, model parameters and validation data. This paper tackles the last of these: errors in discharge measurements used to calibrate a rainfall‐runoff model, caused by stage–discharge rating‐curve uncertainty. This uncertainty may be due to several combined sources, including errors in stage and velocity measurements during individual gaugings, assumptions regarding a particular form of stage–discharge relationship, extrapolation of the stage–discharge relationship beyond the maximum gauging, and cross‐section change due to vegetation growth and/or bed movement. A methodology is presented to systematically assess and quantify the uncertainty in discharge measurements due to all of these sources. For a given stage measurement, a complete PDF of true discharge is estimated. Consequently, new model calibration techniques can be introduced to explicitly account for the discharge error distribution. The method is demonstrated for a gravel‐bed river in New Zealand, where all the above uncertainty sources can be identified, including significant uncertainty in cross‐section form due to scour and re‐deposition of sediment. Results show that rigorous consideration of uncertainty in flow data results in significant improvement of the model's ability to predict the observed flow. Copyright © 2010 John Wiley & Sons, Ltd.     

Stage‐discharge uncertainty derived with a non‐stationary rating curve in the Choluteca River,Honduras

Uncertainty in discharge data must be critically assessed before data can be used in, e.g. water resources estimation or hydrological modelling. In the alluvial Choluteca River in Honduras, the river‐bed characteristics change over time as fill, scour and other processes occur in the channel, leading to a non‐stationary stage‐discharge relationship and difficulties in deriving consistent rating curves. Few studies have investigated the uncertainties related to non‐stationarity in the stage‐discharge relationship. We calculated discharge and the associated uncertainty with a weighted fuzzy regression of rating curves applied within a moving time window, based on estimated uncertainties in the observed rating data. An 18‐year‐long dataset with unusually frequent ratings (1268 in total) was the basis of this study. A large temporal variability in the stage‐discharge relationship was found especially for low flows. The time‐variable rating curve resulted in discharge estimate differences of ? 60 to + 90% for low flows and ± 20% for medium to high flows when compared to a constant rating curve. The final estimated uncertainty in discharge was substantial and the uncertainty limits varied between ? 43 to + 73% of the best discharge estimate. Copyright © 2010 John Wiley & Sons, Ltd.     

Recharge estimation using remotely sensed evapotranspiration in an irrigated catchment in southeast Australia

Reliable estimates of groundwater recharge are required for the sustainable management of surface and ground water resources in semi‐arid regions particularly in irrigated regions. In this study, groundwater recharge was estimated for an irrigated catchment in southeast Australia using a semi‐distributed hydrological model (SWAT). The model was calibrated under the dry climatic conditions for the period from August 2002 to July 2003 using flow and remotely sensed evapotranspiration (ET). The model was able to simulate observed monthly drain flow and spatially distributed remotely sensed ET. Recharge tended to be higher for irrigated land covers, such as perennial pasture, than for non‐irrigated land. On average, the estimated annual catchment recharge ranged between 147 and 289 mm which represented about 40% of the total rainfall and irrigation inputs. The optimized soil parameters indirectly reflected flow bypassing the soil matrix that could be responsible for this substantial amount of recharge. Overall, the estimated recharge was much more than that previously estimated for the wetter years. Copyright © 2011 John Wiley & Sons, Ltd.     

Input data resolution‐induced uncertainty in watershed modelling

The temporal‐spatial resolution of input data‐induced uncertainty in a watershed‐based water quality model, Hydrologic Simulation Program‐FORTRAN (HSPF), is investigated in this study. The temporal resolution‐induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log‐normal relation with time interval for temperature data while it exhibits a power‐law relation for rainfall data. The temporal‐scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash‐Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate‐nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log‐normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal‐scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non‐symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.     

Climate change and fluvial flood risk in the UK: more of the same?

The potential impact of climate change on fluvial flooding is receiving considerable scientific and political interest thanks to evidence from climate model projections and a widely held belief that flood risk may be increasing at European levels. This review compares published work on historical trends in UK rainfall and river flow records with high‐resolution regional climate change projections, and attempts to reconcile apparent differences between the two. Attention is focused on the techniques used for climate change detection and attribution, as well as the potential confounding effects of land‐use change. International and domestic efforts to build adaptive capacity rest on improved quantification of uncertainty in flood risk at very local, catchment and regional scales. This will involve further research to better integrate climate and land‐management interactions, to understand changes in the dependence between different flood generating mechanisms, and to improve the characterization and communication of uncertainty at all stages of analysis. Resources are also needed to ensure that latest, but still uncertain, science is presented in an appropriate form to underpin policy development and is translated into sensible guidance for practitioners. Copyright © 2007 John Wiley & Sons, Ltd.     

数字矿山的数据组织及其不确定性分析

数字矿山是数字地球的重要组成部分,数据是数字矿山的核心,这些数据的精确与否将关系到矿山的安全生产、合理决策等方面的问题。数字矿山的数据来源广泛,数据极其复杂,因此,采用空间数据仓库技术来处理矿山数据是必要的。本文在分析矿山数据内容、特征的基础上,论述了数字矿山数据的组织,针对矿山数据源、数据入库、数据动态性及数据处理引起的不确定性问题作了分析,并归纳了相应的处理方法。     

考虑参数误差的3维空间直线不确定性模型

由于线元上任一点坐标的误差不仅受端点误差的影响,还会受到长度误差的影响,故不确定性模型要考虑各种影响位置精度的参数误差,对3维空间直线不确定性模型作了进一步研究.不但考虑了端点误差的影响,还顾及了长度误差的影响,使模型在理论上更为严密.理论和实验研究表明,长度误差影响了直线方向的精度.