CONTINENTAL SCALE SIMULATION OF THE HYDROLOGIC BALANCE1

This paper describes the application of a continuous daily water balance model called SWAT (Soil and Water Assessment Tool) for the conterminous U.S. The local water balance is represented by four control volumes; (1) snow, (2) soil profile, (3) shallow aquifer, and (4) deep aquifer. The components of the water balance are simulated using “storage” models and readily available input parameters. All the required databases (soils, landuse, and topography) were assembled for the conterminous U.S. at 1:250,000 scale. A GIS interface was utilized to automate the assembly of the model input files from map layers and relational databases. The hydrologic balance for each soil association polygon (78,863 nationwide) was simulated without calibration for 20 years using dominant soil and land use properties. The model was validated by comparing simulated average annual runoff with long term average annual runoff from USGS stream gage records. Results indicate over 45 percent of the modeled U.S. are within 50 mm of measured, and 18 percent are within 10 mm without calibration. The model tended to under predict runoff in mountain areas due to lack of climate stations at high elevations. Given the limitations of the study, (i.e., spatial resolution of the data bases and model simplicity), the results show that the large scale hydrologic balance can be realistically simulated using a continuous water balance model.     

Weighted Regressions on Time,Discharge, and Season (WRTDS), with an Application to Chesapeake Bay River Inputs1

Hirsch, Robert M., Douglas L. Moyer, and Stacey A. Archfield, 2010. Weighted Regressions on Time, Discharge, and Season (WRTDS), With an Application to Chesapeake Bay River Inputs. Journal of the American Water Resources Association (JAWRA) 46(5):857-880. DOI: 10.1111/j.1752-1688.2010.00482.x Abstract: A new approach to the analysis of long-term surface water-quality data is proposed and implemented. The goal of this approach is to increase the amount of information that is extracted from the types of rich water-quality datasets that now exist. The method is formulated to allow for maximum flexibility in representations of the long-term trend, seasonal components, and discharge-related components of the behavior of the water-quality variable of interest. It is designed to provide internally consistent estimates of the actual history of concentrations and fluxes as well as histories that eliminate the influence of year-to-year variations in streamflow. The method employs the use of weighted regressions of concentrations on time, discharge, and season. Finally, the method is designed to be useful as a diagnostic tool regarding the kinds of changes that are taking place in the watershed related to point sources, groundwater sources, and surface-water nonpoint sources. The method is applied to datasets for the nine large tributaries of Chesapeake Bay from 1978 to 2008. The results show a wide range of patterns of change in total phosphorus and in dissolved nitrate plus nitrite. These results should prove useful in further examination of the causes of changes, or lack of changes, and may help inform decisions about future actions to reduce nutrient enrichment in the Chesapeake Bay and its watershed.     

APPLICABILITY OF THE t-TEST FOR DETECTING TRENDS IN WATER QUALITY VARIABLES1

ABSTRACT: A major concern in managing water resources is whether or not water quality variables have changed over time or space. The two-sample Student's t-test is probably the most commonly used statistical test for this purpose. Given that the underlying assumptions of the test may often be violated by water quality variables, a major concern regarding applicability of the test arises. This paper reviews and synthesizes available information in order to examine the effects of non-normality, unequal variances, serial dependence, and seasonality on the performance of the two-sample t-test. The results suggest the t-test is robust for non-normal distributions if the distributions have the same shape (either symmetric or skewed) and sample sizes are equal. The t-test is also robust for unequal variances if the sample sizes are equal. The t-test appears not to be robust when: 1) samples come from two distributions of different shape, 2) samples have unequal variances and unequal sample sizes, 3) serial dependence in observations is present, or 4) seasonal changes, in concentration are present and not removed.     

流域景观格局对土壤保持服务的影响

以子流域为空间单元,应用生态系统服务和交易的综合评估模型（InVEST）进行土壤保持服务评估,并借助景观指数计算软件（FRAGSTATS）表征景观格局特征,综合运用空间自相关探讨土壤保持量与景观格局指数的空间关联关系,同时从景观格局角度出发,开展土壤保持量与景观格局指数的空间回归分析.结果表明：2014年土壤保持服务较高的子流域具有景观类型组成相对单一、景观各类型间非均匀分布、存在优势斑块、景观分离度低的格局特征; 2014年甘肃白龙江14个子流域表现出土壤保持服务与景观格局显著的空间相关关系,占子流域总数量的37.84%;模型对比方面,空间滞后模型（SLM）优于非空间线性模型（OLS）,表明甘肃白龙江各子流域的土壤保持量在空间上具有实质性的空间依赖.景观类型多样性及其均匀程度是影响甘肃白龙江子流域土壤保持量的重要景观指标.     

Electric Accidents in the Production,Transmission, and Distribution of Electric Energy: A Review of the Literature

Many work related electric accidents occurred in electric energy industries and they were very often fatal. The situation of electric accidents in electric companies worldwide is investigated by reviewing the scientific literature, to offer perspectives on the types and kinds of statistics available, the factors regarded as influencing their occurrence, their consequences, and also methodological shortcomings.

Worldwide, reliable comparable data exist and indicate a downward trend in fatal electric accidents. Difficulties were encountered in compiling international statistics because of differences in how accident data were defined and recorded, variations in mandatory practices, lack of suitable data and indices, accident insurance systems, and lack of correlation between technical, financial, and medical aspects.     

FORECASTING QUARTER-MONTHLY RIVERFLOW1

Recent developments with respect to transfer function-noise models are reviewed and used to model and forecast quarter-monthly (i.e., near-weekly) natural inflows to the Lac St-Jean reservoir in the Province of Quebec, Canada. The covariate series are rainfall and snowmelt, the latter being a novel derivation from daily rainfall, snowfall and temperature series. It is clearly demonstrated using the residual variance and the Akaike information criterion that modeling is improved as one starts with a deseasonalized ARMA model of the inflow series and successively adds transfer functions for the rainfall and snowmelt series. It is further demonstrated that the transfer function-noise model is better than a periodic autoregressive model of the inflow series. A split-sample experiment is used to compare one-step-ahead forecasts from this transfer function-noise model with forecasts from other stochastic models as well as with forecasts from a so-called conceptual hydrological model (i.e., a model which attempts to mathematically simulate the physical processes involved in the hydrological cycle). It is concluded that the transfer function-noise model is the preferred model for forecasting the quarter-monthly Lac St-Jean inflow series.     

排放废水综合合格率统计概念分析

在企业环境管理与环境统计中，排放废水综合合格率是一个常见的和重要的考核指标。本文运用多种辅助方法对其意义及内涵进行了多侧面的分析，同时给出了一些实例，并对其进行了统计运算和效果分析。     

Climatic Fluctuations and Forecasting of Streamflow in the Lower Colorado River Basin1

Abstract:  Water‐resource managers need to forecast streamflow in the Lower Colorado River Basin to plan for water‐resource projects and to operate reservoirs for water supply. Statistical forecasts of streamflow based on historical records of streamflow can be useful, but statistical assumptions, such as stationarity of flows, need to be evaluated. This study evaluated the relation between climatic fluctuations and stationarity and developed regression equations to forecast streamflow by using climatic fluctuations as explanatory variables. Climatic fluctuations were represented by the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and Southern Oscillation Index (SOI). Historical streamflow within the 25‐ to 30‐year positive or negative phases of AMO or PDO was generally stationary. Monotonic trends in annual mean flows were tested at the 21 sites evaluated in this study; 76% of the sites had no significant trends within phases of AMO and 86% of the sites had no significant trends within phases of PDO. As climatic phases shifted in signs, however, many sites had nonstationary flows; 67% of the sites had significant changes in annual mean flow as AMO shifted in signs. The regression equations developed in this study to forecast streamflow incorporate these shifts in climate and streamflow, thus that source of nonstationarity is accounted for. The R² value of regression equations that forecast individual years of annual flow for the central part of the study area ranged from 0.28 to 0.49 and averaged 0.39. AMO was the most significant variable, and a combination of indices from both the Atlantic and Pacific Oceans explained much more variation in flows than only the Pacific Ocean indices. The average R² value for equations with PDO and SOI was 0.15.     

交通事故损失的时间序列分析

为揭示交通事故经济损失的变化规律,笔者研究并利用时间序列的方法,建立了ARIMA模型,对1985—2005年全国交通事故经济损失的数据进行了分析和预测。根据原始数据的特点,选择随机时间序列分析方法。通过对模型的识别和参数的选择,得到2006—2008年的交通事故损失的预测值分别为2.9559,2.9707和3.0129亿元,置信区间为95%。通过对1985—2005年交通事故经济损失的预测结果与原始数据的比较表明,预测结果接近原始数据,该方法为交通事故的预防和控制提供了技术指导和有益参考。     

Indicators for sustainable energy development: An initiative by the International Atomic Energy Agency

Since 1999, the International Atomic Energy Agency (IAEA) has been leading a multinational, multi‐agency effort to develop a set of energy indicators useful for measuring progress on sustainable development at the national level. This effort has included the identification of major relevant energy indicators, the development of a framework for implementation and the testing of the applicability of this tool in a number of countries. To achieve these goals, the IAEA has worked closely with other international organizations, leaders in energy and environmental statistics and analysis including the United Nations Department of Economic and Social Affairs (DESA), the International Energy Agency (IEA), Eurostat and the European Environment Agency (EEA). Also, the IAEA completed a three‐year coordinated research project for the implementation and testing of the original set of indicators in seven countries — Brazil, Cuba, Lithuania, Mexico, the Russian Federation, the Slovak Republic and Thailand. This article provides an overview of the IAEA programme on Indicators for Sustainable Energy Development (ISED) and highlights its experiences and accomplishments.