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91.
为在我国开展城市O3污染预报,新近发展了一个O3污染数值预报模式系统.它由物理、生态过程模式(包括污染源模型,下垫面参数化模型,中尺度-α气象模式,中尺度-β气象模式,湍流统计量参数化模式和干湿沉积模式)和高分辨O3化学模式(HROM)组成.用该系统对重庆、广州和济南市的O3污染作了24 h实际预报试验,结果表明:预报与实测O3质量浓度之间有相当好的一致性,API指数平均预报准确率超过85%;城市O3质量浓度表现出明显的日变化、空间分布的非均匀性和地区差异;NO2是O3的一个重要前体污染物,它们之间呈好的负相关. 相似文献
92.
Use of structured expert judgment to forecast invasions by bighead and silver carp in Lake Erie
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Marion E. Wittmann Roger M. Cooke John D. Rothlisberger Edward S. Rutherford Hongyan Zhang Doran M. Mason David M. Lodge 《Conservation biology》2015,29(1):187-197
Identifying which nonindigenous species will become invasive and forecasting the damage they will cause is difficult and presents a significant problem for natural resource management. Often, the data or resources necessary for ecological risk assessment are incomplete or absent, leaving environmental decision makers ill equipped to effectively manage valuable natural resources. Structured expert judgment (SEJ) is a mathematical and performance‐based method of eliciting, weighting, and aggregating expert judgments. In contrast to other methods of eliciting and aggregating expert judgments (where, for example, equal weights may be assigned to experts), SEJ weights each expert on the basis of his or her statistical accuracy and informativeness through performance measurement on a set of calibration variables. We used SEJ to forecast impacts of nonindigenous Asian carp (Hypophthalmichthys spp.) in Lake Erie, where it is believed not to be established. Experts quantified Asian carp biomass, production, and consumption and their impact on 4 fish species if Asian carp were to become established. According to experts, in Lake Erie Asian carp have the potential to achieve biomass levels that are similar to the sum of biomasses for several fishes that are harvested commercially or recreationally. However, the impact of Asian carp on the biomass of these fishes was estimated by experts to be small, relative to long term average biomasses, with little uncertainty. Impacts of Asian carp in tributaries and on recreational activities, water quality, or other species were not addressed. SEJ can be used to quantify key uncertainties of invasion biology and also provide a decision‐support tool when the necessary information for natural resource management and policy is not available. El Uso de Juicio Experto Estructurado para Predecir Invasiones de Carpas Asiáticas en el Lago Erie 相似文献
93.
Brian J. Harshburger Von P. Walden Karen S. Humes Brandon C. Moore Troy R. Blandford Albert Rango 《Journal of the American Water Resources Association》2012,48(4):643-655
Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.x Abstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R2), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R2 value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West. 相似文献
94.
Kaifeng Rao Li Tang Xin Zhang Heyu Xiang Liang Tang Yong Liu Wei Wang Jie Jiang Mei M Yiping Xu Zijian Wang 《环境科学学报(英文版)》2021,33(12):150-159
Environmental impact of pollutants can be analyzed effectively by acquiring fish behavioral signals in water with biological behavior sensors. However, a variety of factors, such as the complexity of biological organisms themselves, the device error and the environmental noise, may compromise the accuracy and timeliness of model predictions. The current methods lack prior knowledge about the fish behavioral signals corresponding to characteristic pollutants, and in the event of a pollutant invasion, the fish behavioral signals are poorly discriminated. Therefore, we propose a novel method based on Bayesian sequential, which utilizes multi-channel prior knowledge to calculate the outlier sequence based on wavelet feature followed by calculating the anomaly probability of observed values. Furthermore, the relationship between the anomaly probability and toxicity is analyzed in order to achieve forewarning effectively. At last, our algorithm for fish toxicity detection is verified by integrating the data on laboratory acceptance of characteristic pollutants. The results show that only one false positive occurred in the six experiments, the present algorithm is effective in suppressing false positives and negatives, which increases the reliability of toxicity detections, and thereby has certain applicability and universality in engineering applications. 相似文献
95.
Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO4 and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction. 相似文献
96.
基于wavelet-SVM的PM10浓度时序数据预测 总被引:1,自引:0,他引:1
太原是以煤炭为主要能源的重工业城市,PM_(10)(particulate matter)是太原市的主要大气污染物,因此研究其变化趋势,并给出污染物浓度预测结果,为相关部门进行大气污染防治,为突发污染事件应急提供理论支持是一项非常重要的工作.支持向量机(support vector machine,SVM)应用于PM_(10)污染物浓度时序数据预测时,表现出良好的泛化能力.在预测模型建立过程中通常选择历史数据作为学习模型的输入特征,然而这样的数据表示形式,结构单一,信息表达不完备,在很大程度上将影响预测模型的泛化能力.本文以山西省太原市城区4个监测站点的PM_(10)日浓度数据为研究数据,通过小波变换(wavelet transform)将一维输入数据转化为由低频信息和高频信息构成的高维数据,并以该数据为输入数据建立wavelet-SVM预测模型.结果表明,相较于传统SVM模型预测,wavelet-SVM模型预测结果具有更高的精度,尤其能更加准确捕捉到PM_(10)浓度突变点,为大气污染预警提供有效信息支持,并且wavelet-SVM模型对于PM_(10)浓度时序数据变化趋势的预测精度有明显提升,能更好地预测PM_(10)浓度变化趋势,揭示PM_(10)浓度时序数据内在规律. 相似文献
97.
98.
Sungwon Kim Vijay P. Singh 《Journal of the American Water Resources Association》2013,49(6):1421-1435
Various neural networks models are developed and applied for flood forecasting at Sangye station (no. 1) of the Bocheong Stream catchment, which is one of the International Hydrological Program's representative catchments, Republic of Korea. The neural networks models (NNMs) are multilayer perceptron‐neural networks model (MLP‐NNM), generalized regression neural networks model (GRNNM), and Kohonen self‐organizing feature maps neural networks model (KSOFM‐NNM). Data used for model training and testing are divided into two groups: such as floods and typhoon events. Single conventional application and class segregation implementation are applied to evaluate the neural networks models. KSOFM‐NNM forecasts flood discharge more accurately than do MLP‐NNM and GRNNM for the testing data of Methods I and II for single conventional application and class segregation implementation. This study shows that class segregation can capture the dynamics of different physical processes and overcome the difficulties using single conventional application of neural networks models. 相似文献
99.
本文介绍了江西地质灾害气象预报模型的建立、计算方法,以及预警预报在地质灾害防治工作中获得的成功,对类似条件地区的地质灾害防治工作,具有一定的借鉴作用. 相似文献
100.
民航运输中燃油消耗量的精确预测对能源需求的科学规划和决策具有重要参考价值,针对民航燃油消耗量历史数据少的特点,通过灰色系统建模、关联度分析以及残差辨识,建立了民航燃油消耗量的灰色预测模型,以均方差比值和小误差概率两项评级指标,将预测结果与精度检验等级的对比分析表明灰色预测民航燃油消耗量的拟合精度高,预测结果较为可靠。 相似文献