A STOCHASTIC DYNAMIC PROGRAMMING MODEL FOR THE OPTIMUM OPERATION OF A MULTI-PURPOSE RESERVOIR1

ABSTRACT: The main objective of this paper is to present a stockastic dynamic programming model useful in determining the optimal operating policy of a single multipurpose surface reservoir. It is the unreliability of forecasting the amount of future streamflow which makes the problem of a reservoir operation a stochastic process. In this paper the stochastic nature of the streamflow is taken into account by considering the correlation between the streamflows of each pair of consecutive time intervals. This interdependence is used to calculate the probability of transition from a given state and stage to its succeeding ones. A dynamic programming model with a physical equation and a stochastic recursive equation is developed to find the optimum operational policy. For illustrative purposes, the model is applied to a real surface water reservoir system.     

马尔柯夫法在耕地质量动态评价中的应用

根据随机过程原理,构建了新的转移矩阵,建立了一个马尔柯夫链综合耕地质量评价模型.通过实例的应用,分析证明了其模型的可靠性,从而为耕地质量动态评价的科学化提供了依据.     

Carbonaceous aerosols in PM10 and pollution gases in winter in Beijing

An intensive observation of organic carbon (OC) and element carbon (EC) in PM10 and gaseous materials (SO2, CO, and O3,) was conducted continuously to assess the characteristics of wintertime carbonaceous aerosols in an urban area of Beijing, China. Results showed that the averaged total carbon (TC) and PM10 concentrations in observation period are 30.2±120.4 and 172.6±198.3 μ/m3, respectively. Average OC concentration in nighttime (24.9±19.6 μ/m3) was 40% higher than that in daytime (17.7±10.9 μ/m3). Average EC concentrations in daytime (8.8±15.2 μ/m3) was close to that in nighttime (8.9±15.1 μ/m3). The OC/EC ratios in nighttime ranging from 2.4 to 2.7 are higher than that in daytime ranging from 1.9 to 2.0. The concentrations of OC, EC, PM10 were low with strong winds and high with weak winds. The OC and EC were well correlated with PM10, CO and SO2, which implies they have similar sources. OC and EC were not well correlated with O3. By considering variation of OC/EC ratios in daytime and night time, correlations between OC and O3, and meteorological condition, we speculated that OC and EC in Beijing PM10 were emitted as the primary particulate form. Emission of motor vehicle with low OC/EC ratio and coal combustion sources with high OC/EC ratio are probably the dominant sources for carbonaceous aerosols in Beijing in winter. A simple method was used to estimate the relative contribution of sources to carbonaceous aerosols in Beijing PM10. Motor vehicle source accounts for 80% and 68%, while coal combustion accounts for 20% and 32% in daytime and nighttime, respectively in Beijing. Averagely, the motor vehicle and coal combustion accounted for 74% and 26%, respectively, for carbonaceous aerosols during the observation period. It points to the motor vehicle is dominant emission for carbonaceous aerosols in Beijing PM10 in winter period, which should be paid attention to control high level of PM10 in Beijing effectively.     

Rapid determination of phenolic compounds in water samples by alternating-current oscillopolarographic titration

A rapid, simple and sensitive method was demonstrated for the determination of phenolic compounds in water samples by alternating-current oscillopolarographic titration. With the presence of sulfuric acid, phenol could be transferred into a nitroso-compound by reacting with NaNO2. The titration end-point was obtained by the formation of a sharp cut in the oscillopolarographic with infinitesimal NaNO2 on double platinum electrodes. The results showed that phenol concentration had an excellent linear relationship over the range of 4.82×10-6-9.65×10-3 mol/L, the RSD of the proposed method was lower than 1.5%, and the spiked recoveries of three real water samples were in the range of 95.6%-106.9%.     

Metal Contamination of the Natural Environment in Norway from Long Range Atmospheric Transport

Long range atmospheric transport is the most important sourceof contamination to the natural environment in Norway with manyheavy metals. Investigations based on aerosol studies, bulkdeposition measurements and moss analysis show that airborne transport from other parts of Europe is the major mode for supplyof vanadium, zinc, arsenic, selenium, molybdenum, cadmium, tin,antimony, tellurium, thallium, lead, and bismuth, whereas metalssuch as chromium, nickel, and copper are mainly derived from point sources within Norway and in northwestern Russia close tothe Norwegian border. Elements associated with long range transport show substantial enrichment in the humus horizon of natural soils in southern Norway, sometimes to levels suspected to cause effects on soil microbial processes. E.g. lead concentration values of 150–200 ppm are observed in the mostcontaminated areas in the south as compared to about 5 ppm inthe far north. Elements such as lead and cadmium also show enrichment in some terrestrial food chains. These elements alsoshow considerably elevated levels over background concentrationsin the water and sediment of small lakes in the southern part ofthe country. Retrospective studies based on ombrogenous peatcores indicate that long range transport has been a significantsource of heavy metal contamination in southern Norway for thelast couple of centuries. The deposition of most heavy metals inNorway has been considerably reduced over the last 20 yr, withthe exception of contributions in the north from Russian smelters.     

用Markov模型预测长江水质

由于长江水质的污染程度日益严重,为了说明治理长江对长江水质进行了简单的评价,保护长江迫在眉睫,首先,根据长江流域的17个观测站近两年多的水质检测数据统计,说明了近两年多来长江的防污治理工作有一定的效果。然后,根据1995~2004年长江流域水质的数据报告,考虑各类水之间的相互转化,构造了马尔柯夫(Markov)转移矩阵,建立了马尔柯夫预测模型,通过已有的观测数据验证了该模型的正确性及有效性。运用该马尔柯夫模型预测未来10年水质的变化趋势,即Ⅰ、Ⅱ、Ⅲ、Ⅳ类水逐年减少,而Ⅴ、劣Ⅴ类水逐年增加。到2014年,长江的第Ⅰ类水只有0.4 059%,劣Ⅴ类水达到26.2 714%,不可饮用水（即第Ⅳ,Ⅴ,劣Ⅴ类水）将达到47.468%,为此应采取更加有效的治理措施,控制长江水质的恶化。最后,通过计算,得到了每年需要处理污水的最小百分比,才能杜绝劣Ⅴ类水,将第Ⅳ、Ⅴ类水控制在20%内,从而才能保证我们有足够的饮用水     

基于HMM和DT的无人机异常检测方法

为了实时检测无人机异常状态,提出基于隐马尔可夫模型(Hidden Markov Model,HMM)和决策树(Decision Tree,DT)的无人机异常检测方法(HMMDT).首先根据异常致因将无人机异常分为干扰异常和硬件异常;然后结合HMM和DT建立无人机异常检测模型,定义无人机异常度衡量异常状态的严重程度,确定...     

A multiscale hierarchical Markov transition matrix model for generating and analyzing thematic raster maps

A model is described for generating hierarchically scaled spatial pattern as represented in a thematic raster map. The model involves a series of Markov transition matrices, one for each level in the scaling hierarchy. In full generality, the model allows the transition matrices to be different at each level, potentially making available a large number of parameters for landscape characterization. The model is self-similar when the transition matrices are all equal. A method is presented for fitting the model to data that take the form of a single-resolution thematic raster map. Explicit analytic solutions are obtained for the fitted parameters. The fitting method is based on a relationship between the hierarchical transitions in the model and spatial transitions at varying distance scales in the data map, a categorical analogy of the geostatistical variogram.     

FORECAST UNCERTAINTY IN WATER SUPPLY RESERVOIR OPERATION1

ABSTRACT: This research investigates the benefits of forecasting in water supply systems. Questions relating operational losses to forecast period and accuracy are addressed. Some simple available forecasting techniques are assessed for their accuracy and applicability. These issues are addressed through the use of a simulation model of the Cedar and South Fork Tolt Rivers, where the system is modeled as a single purpose reservoir supplying municipal and industrial water to the Seattle metropolitan area. The following conclusions were made for this system: (1) reservoir operation deteriorates markedly with the loss of forecast accuracy; (2) the optimal length of forecasting period is five months; (3) reservoir operation may be improved by as much as 88 percent if perfect predictive abilities are available; (4) the mean of the historic data is not recommended to predict future flows because Markov methods are always superior; and (5) lag-one autoregressive Markov schemes exhibit about a 9 percent improvement in operation over no forecasting.     

基于马尔科夫模型的芜湖市景观格局演变研究

在遥感和地理信息系统的支持下，利用1996年和2003年2个时期的Landsat—TM假彩色合成影像作为信息源，获取芜湖市景观类型的转化数据，并结合国土局的土地详查数据，确定相应的转移概率矩阵，应用马尔科夫过程模拟土地类型景观的动态演变情况和未来演变的趋势。结果表明，随着城市化过程的发展，研究区内各种土地类型不断地向城市用地转化。