Spatial modelling of socioeconomic data to understand patterns of human-caused wildfire ignition risk in the SW of Madrid (central Spain)

The majority of wildfires in the Mediterranean Basin are caused directly or indirectly by human activity. Many biophysical and socioeconomic factors have been used in quantitative analyses of wildfire risk. However, the importance and effects of socioeconomic factors in spatial modelling have been given inadequate attention. In this paper, we use different approaches to spatially model our data to examine the influence of human activity on wildfire ignition in the south west of the Madrid region, central Spain. We examine the utility of choropleth and dasymetric mapping with both Euclidean and functional distance surfaces for two differently defined wildfire seasons. We use a method from Bayesian statistics, the Weights of Evidence model, and produce ten predictive maps of wildfire risk: (1) five maps for a two-month fire season combining datasets of evidence variables and (2) five maps for the four-month fire season using the same dataset combinations. We find that the models produced from a choropleth mapping approach with spatial variables using Euclidian and functional distance surfaces are the best of the ten models. Results indicate that spatial patterns of wildfire ignition are strongly associated with human access to the natural landscape. We suggest the methods and results presented will be useful to optimize wildfire prevention resources in areas where human activity and the urban-forest interface are important factors for wildfire ignition.     

不同排污收费情景下的发电企业减排模型研究

考虑未来多种污染物排污收费情景及区域电力需求的固有随机特性,建立了2阶段电源规划优化模型,分析了不同排污收费情景、不同电力需求水平下的区域电力结构变化以及污染物和CO2减排策略.在同时征收SO2排污费和CO2排放费的情景(情景3)下,清洁能源发电在发电系统中的比重增加,以煤电为主的火电比重下降;系统减排CO2 8.438′106t,同时协同减排SO2 5202t、NOx 7854t、颗粒物17.42t,但系统费用会显著增加.在同时征收SO2、NOx排污费和CO2排放费的情景下,系统减排SO2 8515t、NOx 13878t、颗粒物23.52t、CO2 12.988′106t,同时系统费用也会进一步增加.在目前征收SO2排污费的基础上征收CO2排放费或同时征收NOx排放费和CO2排放费,可以提高清洁发电方式在发电系统中的比重,降低SO2、NOx和CO2的排放量.     

Effects of tour boats on dolphin activity examined with sensitivity analysis of Markov chains

In Patagonia, Argentina, watching dolphins, especially dusky dolphins (Lagenorhynchus obscurus), is a new tourist activity. Feeding time decreases and time to return to feeding after feeding is abandoned and time it takes a group of dolphins to feed increase in the presence of boats. Such effects on feeding behavior may exert energetic costs on dolphins and thus reduce an individual's survival and reproductive capacity or maybe associated with shifts in distribution. We sought to predict which behavioral changes modify the activity pattern of dolphins the most. We modeled behavioral sequences of dusky dolphins with Markov chains. We calculated transition probabilities from one activity to another and arranged them in a stochastic matrix model. The proportion of time dolphins dedicated to a given activity (activity budget) and the time it took a dolphin to resume that activity after it had been abandoned (recurrence time) were calculated. We used a sensitivity analysis of Markov chains to calculate the sensitivity of the time budget and the activity-resumption time to changes in behavioral transition probabilities. Feeding-time budget was most sensitive to changes in the probability of dolphins switching from traveling to feeding behavior and of maintaining feeding behavior. Thus, an increase in these probabilities would be associated with the largest reduction in the time dedicated to feeding. A reduction in the probability of changing from traveling to feeding would also be associated with the largest increases in the time it takes dolphins to resume feeding. To approach dolphins when they are traveling would not affect behavior less because presence of the boat may keep dolphins from returning to feeding. Our results may help operators of dolphin-watching vessels minimize negative effects on dolphins.     

农业灌溉用水效率及其影响因素实证分析——基于随机前沿生产函数和新疆棉农调研数据

水资源是21 世纪的战略资源,提高农业部门水资源利用效率是水资源严重短缺的中国可持续发展的必然要求。论文利用“一步法”随机前沿生产函数模型评估了新疆地区806 户棉农的棉花生产技术效率及其影响因素,在此基础上采用单要素效率测算方法,借助Tobit 模型,考察棉花灌溉用水效率分布及其影响因素。研究结果表明：①新疆地区棉花技术效率与灌溉用水效率分别为0.85 和0.74,并且两种效率之间具有较高的相关性;②汉族农户以及采用滴灌技术和兵团经营方式的农户具有更高的技术效率与灌溉用水效率,而采用套种方式的农户两种效率较低;③棉花技术培训、每块土地规模的扩大有利于农户技术效率与灌溉用水效率的提高;④灌溉用水价格的提高有利于灌溉用水效率的提高。     

随机桁架结构可靠性分析的完全概率方法

提出了一种求解随机参数桁架结构在随机荷载作用下反应的概率密度函数和结构精确可靠度的方法.通过对随机参数桁架结构在随机荷载作用下的有限元分析方法的研究,考虑了结构的物理参数,构件的几何尺寸和作用荷载幅值等的随机性.应用随机向量函数的概率分布函数表达式,通过确定积分区间、变量替换、交换积分顺序等一系列数学上的处理,获得所求结构反应的概率密度函数.由干涉理论得到了结构位移和应力的可靠度.通过算例的结果与Monte-Carlo模拟法结果比较,表明该方法具有较高的精度及良好的实用性.     

基于Monte-Carlo随机有限元的火灾可靠性研究--以混凝土简支梁为例

通过对建筑火灾的背景分析和研究现状的回顾,指出了进行建筑火灾可靠性研究的必要性.介绍了蒙特卡罗随机有限元计算的基本原理、随机数的产生办法和模拟次数的确定,最后作者采用通用有限元程序ANSYS计算了混凝土简支梁在不同温度、保护层厚度和荷载下的火灾可靠性.     

INDEXED SEQUENTIAL HYDROLOGIC MODELING FOR HYDROPOWER CAPACITY ESTIMATION1

ABSTRACT: The indexed sequential hydrologic modeling (ISM) methodology is utilized by the Western Area Power Administration as the basis for risk-based estimation of project-dependable hydropower capacity for several federally owned/operated projects. ISM is a technique based on synthetic generation of a series of overlapping short-term inflow sequences obtained directly from the historical record. The validity of ISM is assessed through application to the complex multireservoir hydropower system of the Colorado River basin for providing risk estimates associated with determination of reliable hydrogeneration capacity. Performance of ISM is compared with results from stochastically generated streamflow input data to the Colorado River Simulation System (CRSS). Statistical analysis and comparison of results are based on monthly power capacity, energy generation, and downstream water deliveries. Results indicate that outputs generated from ISM synthetically generated sequences display an acceptable correspondence with those obtained from stochastically generated hydrologic data for the Colorado River Basin.     

SENSITWITY OF IRRIGATION DEMAND IN A HUMID-TEMPERATE REGION TO HYPOTHETICAL CLIMATIC CHANGE1

ABSTRACT: An irrigation model based on a modified Thornthwaite water balance was used to simulate the effects of various hypothetical climatic changes on annual irrigation demand in a humidtemperate climate. The climatic-change scenarios consisted of combinations of changes in temperature, precipitation, and stomatal resistance of plants to transpiration. The objectives were to (1) examine the effects of long-term changes in these components of climatic change on annual irrigation demand, and (2) identify which of these factors would cause the largest changes in annual irrigation demand. Hypothetical climatic changes that only included increases in temperature and changes in precipitation resulted in increased annual irrigation demand, even with a 20 percent increase in precipitation. The model results showed that, for the ranges of changes in temperature and precipitation used in this study, changes in irrigation demand were more sensitive to changes in temperature than to changes in precipitation. Model results also indicated that increased stomatal resistance to transpiration counteracted the effects of increases in temperature and decreases in precipitation on irrigation demand. Changes in irrigation demand were even more sensitive to changes in stomatal resistance than to changes in temperature. A large amount of uncertainty is associated with predictions of future climatic conditions; however, uncertainty associated with natural climatic variability may be larger and may mask the effects of climatic change on irrigation demand.     

AN OBJECTWE TEST FOR HYDROLOGIC SCALE1

ABSTRACT: Improving the reliability of parametric hydrologic models (sometimes called cenceptual rainfall-runoff models) in the continuous simulation of runoff from ungaged catchments has been frustrated by difficulties in estimating model parameters from catchment characteristics. An underlying problem is that these models use parameters to represent catchments as a whole, whereas data on catchment characteristics are collected at multiple field locations and are difficult to transform into one measure of collective impact. Subdividing the catchment and calibrating a stochastic parametric model to estimate distributions for the parameters that covered the range of observed streamflow values was found to improve the simulations. This paper presents an optimization of the amount of subdivision to use in simulation with a version of the Stanford Watershed Model using available climatological data. The calibration process assumes that catchment heterogeneity introduces errors that can be reduced by calibrating parameters as spatial distributions rather than single values. Calibrations for three diverse small gaged catchments located in California and in Virginia found the optimal number of subdivisions to range from 4 to 25 and the optimal scale to range from 0.3 to 2.1 mi².     

OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)1

ABSTRACT: Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a Stochastic Dynamic Programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons.