Variation in low food access areas due to data source inaccuracies

Several spatial measures of community food access identifying so called “food deserts” have been developed based on geospatial information and commercially-available, secondary data listings of food retail outlets. It is not known how data inaccuracies influence the designation of Census tracts as areas of low access. This study replicated the U.S. Department of Agriculture Economic Research Service (USDA ERS) food desert measure and the Centers for Disease Control and Prevention (CDC) non-healthier food retail tract measure in two secondary data sources (InfoUSA and Dun & Bradstreet) and reference data from an eight-county field census covering 169 Census tracts in South Carolina. For the USDA ERS food deserts measure accuracy statistics for secondary data sources were 94% concordance, 50–65% sensitivity, and 60–64% positive predictive value (PPV). Based on the CDC non-healthier food retail tracts both secondary data demonstrated 88–91% concordance, 80–86% sensitivity and 78–82% PPV. While inaccuracies in secondary data sources used to identify low food access areas may be acceptable for large-scale surveillance, verification with field work is advisable for local community efforts aimed at identifying and improving food access.     

40m天线预测控制算法的研究

将预测控制的思想用于大口径天线跟踪系统的控制,提出了位置控制器的一种设计方案。并对天线的直流驱动系统进行建模和仿真实验。     

三电平逆变器驱动的IPMSM模型预测电流控制系统研究

三电平逆变器拓扑结构简单、所用器件较少且每个功率管所承受的电压应力小,适用于高电压、大容量的场合.相比于传统两电平逆变器,三电平逆变器输出电平的数量从2变成3,输出的电压电流谐波含量低,波形正弦度更好.本文提出内置式永磁同步电机模型预测电流控制算法,以提高控制系统电流动态响应速度,并针对该算法在控制系统中产生的时间延迟,引入二阶延迟补偿策略.对以上内容建立系统仿真模型,仿真结果表明：三电平逆变器相比两电平逆变器输出电流波形谐波含量更小、电机的动态及稳态性能更好.     

Inverse modelling for freshwater lens in small islands: Kish Island,Persian Gulf

A number of challenges including instability, nonconvergence, nonuniqueness, nonoptimality, and lack of a general guideline for inverse modelling have limited the application of automatic calibration by generic inversion codes in solving the saltwater intrusion problem in real‐world cases. A systematic parameter selection procedure for the selection of a small number of independent parameters is applied to a real case of saltwater intrusion in a small island aquifer system in the semiarid region of the Persian Gulf. The methodology aims at reducing parameter nonuniqueness and uncertainty and the time spent on inverse modelling computations. Subsequent to the automatic calibration of the numerical model, uncertainty is analysed by constrained nonlinear optimization of the inverse model. The results define the percentage of uncertainty in the parameter estimation that will maintain the model inside a user‐defined neighbourhood of the best possible calibrated model. Sensitivity maps of both pressure and concentration for the small island aquifer system are also developed. These sensitivity maps indicate higher sensitivity of pressure to model parameters compared with concentration. These sensitivity maps serve as a benchmark for correlation analysis and also assist in the selection of observations points of pressure and concentration in the calibration process. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling future lahars controlled by different volcanic eruption scenarios at Cotopaxi (Ecuador) calibrated with the massively destructive 1877 lahar

Lahars are among the most hazardous mass flow processes on earth and have caused up to 23 000 casualties in single events in the recent past. The Cotopaxi volcano, 60 km southeast of Quito, has a well-documented history of massively destructive lahars and is a hotspot for future lahars due to (i) its ~10 km² glacier cap, (ii) its 117–147-year return period of (Sub)-Plinian eruptions, and (iii) the densely populated potential inundation zones (300 000 inhabitants). Previous mechanical lahar models often do not (i) capture the steep initial lahar trajectory, (ii) reproduce multiple flow paths including bifurcation and confluence, and (iii) generate appropriate key parameters like flow speed and pressure at the base as a measure of erosion capacity. Here, we back-calculate the well-documented 1877 lahar using the RAMMS debris flow model with an implemented entrainment algorithm, covering the entire lahar path from the volcano edifice to an extent of ~70 km from the source. To evaluate the sensitivity and to constrain the model input range, we systematically explore input parameter values, especially the Voellmy–Salm friction coefficients μ and ξ. Objective selection of the most likely parameter combinations enables a realistic and robust lahar hazard representation. Detailed historic records for flow height, flow velocity, peak discharge, travel time and inundation limits match best with a very low Coulomb-type friction μ (0.0025–0.005) and a high turbulent friction ξ (1000–1400 m/s²). Finally, we apply the calibrated model to future eruption scenarios (Volcanic Explosivity Index = 2–3, 3–4, >4) at Cotopaxi and accordingly scaled lahars. For the first time, we anticipate a potential volume growth of 50–400% due to lahar erosivity on steep volcano flanks. Here we develop a generic Voellmy–Salm approach across different scales of high-magnitude lahars and show how it can be used to anticipate future syneruptive lahars.     

Biological assessment of rivers in the Manawatu‐Wanganui region of New Zealand using a predictive macroinvertebrate model

This study presents a river invertebrate and classification system (RIVPACS) type bioassessment methodology for the Manawatu‐Wanganui region of New Zealand. Aquatic macroinvertebrates and related physico‐chemical data were collected at 127 sites, with minimal human impacts (reference sites) in 2000. The reference sites were classified into five groups based on their macroinvertebrate data using TWINSPAN. These biotic groupings were then applied to their corresponding physico‐chemical data and discriminant functions were obtained to assign sites into the biotic groups using the physico‐chemical data. The discriminant functions correctly allocated 72% of the sites to the correct classification group using a jack‐knife validation. The probabilities from the discriminant functions were used to predict macroinvertebrate assemblages and these were compared with observed macroinvertebrate assemblages. The model was then used to assess the health of 29 test sites with known impacts. All test sites were assessed as impacted based on the 10th percentile of the reference data. To evaluate the temporal reliability of the model, data available for 11 sites sampled in 1997 and 2000 were run through the model. The results of this comparison showed little variation in O/E ratios over time and the two sites classed as impacted in 1997 were also classed as impacted in 2000.     

Rain-fall modeling: An Application of Bayesian forecasting

The rainfall-runoff modeling is very useful for forecasting purposes. A good methodology for forecasting the future stream flow is a key requirement for designers and operators of water resources systems. A compromise between conceptual and classical time series modeling is applied to model the relationship between rainfall and runoff. The dynamic nonlinear model is composed of a probability distribution describing the observation, a link function relating its mean to the so called state parameters and a system of equations defining the evolution of these parameters. Its Bayesian nature permits to take into account subjective information, making forward intervention, defining monitoring schemes and introducing smoothing facilities. An application using the data of Fartura river's basin is reported. The assessment of the prior distribution is discussed and the predictive performance of the linear and the non-linear models is reported.     

Prediction of fish yield and potential productivity from limnological data in Lake Borollus, Egypt

Four limnological models (lake shoreline development (D_L), Morphoedaphic Index (MEI), primary production and total nutrient input) have been applied to Lake Borollus to estimate existing fish yield and future potential productivity. The estimated existing fish yield from the lake is about 1260 kg/ha (i.e. 53,000 tons/annum), which is at or near its existing potential and is considered in the ultra enriched category. From 1931 to 1935, the estimated fish production of Lake Borollus was about 68 kg/ha, which is considered low enriched category, while from1960 to 1970, the lake belonged to the moderately enriched category, where the estimated fish production was about 155 kg/ha, and then tremendously increased to about 580 kg/ha during the 1980's.Thisincrease in fish yield is mainly attributed to the nutrient loading of the southern and eastern drains to the lake. In the long term, and based on existing nutrient input to fish yield relationships, it is estimated that increased nutrient loading from drainage water may elevate its yield by 24, 580 tons by the year 2005 (i.e. total fish yield could be increased to 77,500 tons/annum). This revised version was published online in July 2006 with corrections to the Cover Date.     

1991年江淮流域梅雨结束预报的分析与讨论

1991年江淮梅雨结束，在预报上具有相当难度。由于ECMWF数值预报出现重大偏差，曾一度造成业务预报的重大分歧，增加了预报决策的困难。作者客观地反映当时预报的实况，其目的在于剖析预报分歧中的症结，并由此提出预报员的经验可以弥补单一预报工具的不足，修正数值预报产品的误差，从而提高预报准确率。     

Models to predict Secchi depth in small glacial lakes

This study quantifies and ranks variables of significance to predict mean values of Secchi depth in small glacial lakes. The work is based on a new, extensive set of data from 88 Swedish lakes and their catchments. Several empirical models based on catchment and lake morphometric parameters are presented. These empirical models can only be used to predict Secchi depth for lakes of the same type, and the models based on geological map parameters can evidently not be used for time-dependent and site typical predictions of Secchi depth. However, many of the principles behind the results ought to be valid for lakes in general. Various hypotheses concerning the factors regulating the variability in mean Secchi depth among lakes are formulated and tested. The most important variables are: Lake colour (expressing allogenic input of different types of humic materials), total-P and lake temperature (measures of production of autogenic materials). The most important map parameters are: The mean depth (linked to resuspension and lake morphometry) and the ratio between the drainage area and lake area (expressing the linkage between catchment and lake). The predictability of some of the models cannot be markedly improved by accounting for the distribution of the characteristics in the drainage area (using the drainage area zonation technique). The variability in mean Secchi depth from other factors, such as precipitation and anthropogenic load, may then be quantitatively differentiated from the impact of these geological factors, which can statistically explain 68% of the variability in Secchi depth among these lakes. The model based on map parameters can also be used to estimate natural, preindustrial reference values of Secchi depth.