新建水库初期磷氮变化的动态模拟研究

本文首先建立磷氮时空分布模型并确定模型参数的率定方法。文章模拟了新建清平水库建库初期磷氮变化情况,得出由不稳定到稳定的过程。水库磷氮时空变化的模拟结果表明,空间分布是从库尾到大坝浓度逐渐递砬,时间分布是一年中Ｐ,Ｎ浓度七月份最高,年初年末最低,其分布央线类似高斯分布。     

Water Supply Planning Considering Uncertainties in Future Water Demand and Climate: A Case Study in an Illinois Watershed

Ensuring an adequate, reliable, clean, and affordable water supply for citizens and industries requires informed, long-range water supply planning, which is critically important for water security. A balance between water supply and demand must be considered for a long-term plan. However, water demand projections are often highly uncertain. Climate change could impact the hydrologic processes, and consequently, threaten water supply. Thus, understanding the uncertainties in future water demand and climate is critical for developing a sound water supply plan. In Illinois, regional water supply planning attempts to explore the impacts of future water demand and climate on water supply using scenario analyses and hydrologic modeling. This study is aimed at developing a water supply planning framework that considers both future water demand and climate change impacts. This framework is based on the Soil and Water Assessment Tool to simulate the watershed hydrology and conduct scenario analyses that consider the uncertainties in both future water demand and climate as well as their impacts on water supply. The framework was applied to water supply planning efforts in the Kankakee River watershed. The Kankakee River watershed model was calibrated and validated to observed streamflow records at four long-term United States Geological Survey streamflow gages. Because of the many model parameters involved, the calibration process was automated and was followed by a manual refinement, resulting in good model performance. Long-range water demand projections were prepared by the Illinois State Water Survey. Six future water demand scenarios were established based on a suite of assumptions. Climate scenarios were obtained from the Coupled Model Intercomparison Projection Phase 5 datasets. Three representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, are used in the study. The scenario simulation results demonstrated that climate change appears to have a greater impact on water availability in the study area than water demand. The framework developed in this study can also be used to explore the impacts of uncertainties of water demand and climate on water supply and can be extended to other regions and watersheds.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

A MODELING APPROACH FOR OPTIMUM SEDIMENT DETENTION POND DESIGN1

ABSTRACT: A design procedure to determine optimum size for a sediment detention pond is presented. The procedure is based on simulating the sediment removal efficiency of the pond in conjunction with temporal variations in rainfall and potential land use and/or management options. The simulation procedure is based on a combined probabilistic-deterministic modeling approach. The probabilistic model generates daily rainfall with hourly increments for a selected site. The deterministic model simulates sediment yield and concentration for drainage area (pond inflow) and sediment trapping efficiency of the pond. The sediment yield and concentration in pond effluent is estimated from the difference between sediment inflow to the pond and sediment trapped by the pond. As an example, the procedure is applied to determine optimum design for a sediment detention pond in a surface mined area using several pond design options and alternative mining operation/land reclamation strategies.     

Is “No-Threshold” a “Non-Concept”?

A controversy prominent in scientific literature that has carried over to newspapers, magazines, and popular books is having serious social and political expressions today: “Is there, or is there not, a threshold below which exposure to a carcinogen will not induce cancer?” The distinction between establishing the existence of this threshold (which is a theoretical question) and its value (which is an experimental one) gets lost in the scientific arguments. Establishing the existence of this threshold has now become a philosophical question (and an emotional one). In this paper I qualitatively outline theoretical reasons why a threshold must exist, discuss experiments which measure thresholds on two chemicals, and describe and apply a statistical method for estimating the threshold value from exposure-response data.     

Using Multimedia Modeling to Expedite Site Characterization

GOAL, SCOPE AND BACKGROUND: This paper uses two case studies of U.S. Department of Energy nuclear weapons complex installations to illustrate the integration of expedited site characterization (ESC) and multimedia modeling in the remedial action decision making process. CONCEPTUAL SITE MODELS, MULTIMEDIA MODELS, AND EXPEDITED SITE CHARACTERIZATION: Conceptual site models outline assumptions about contaminates and the spatial/temporal distribution of potential receptors. Multimedia models simulate contaminant transport and fate through multiple environmental media, estimate potential human exposure via specific exposure pathways, and estimate the risk of cancer and non-cancer health outcomes. ESC relies on using monitoring data to quantify the key components of an initial conceptual site model that is modified iteratively using the multimedia model. CASE STUDIES: Two case studies are presented that used the ESC approach: Los Alamos National Laboratory (LANL) and Pantex. LANL released radionuclides, metals, and organic compounds, into canyons surrounding the facility. The Pantex Plant has past waste management operations which included burning chemical wastes in unlined pits, burying wastes in unlined landfills, and discharging plant wastewaters into on-site surface waters. CONCLUSIONS: The case studies indicate that using multimedia models with the ESC approach can inform assessors about what, where, and how much site characterization data needs to be collected to reduce the uncertainty associated with risk assessment. Lowering the degree of uncertainty reduces the time and cost associated with assessing potential risk and increases the confidence that decision makers have in the assessments performed.     

Health risk assessment of PCDD/F emissions from a hazardous and medical waste incinerator in Turkey

A multimedia risk assessment procedure was conducted to determine the fate and transport of polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran (PCDD/F) emissions from the Izmit Hazardous and Medical Waste Incinerator (IZAYDAS) in Turkey and their potential health risks. Congener concentrations in ambient air and their deposition rates were determined by an air dispersion model (ISCST3). Their transfer to some plant groups and animal tissues was predicted by food chain modeling. Exposure scenarios were produced based on three receptor groups (urban, semiurban, and rural) and five subgroups determined according to ages. Daily intakes of PCDD/Fs via exposure pathways were determined based on three different emission scenarios for each group and subgroup. Estimated incremental PCDD/F doses caused by the incinerator emissions in central-tendency scenario were computed as between 2.31 x 10(-6) and 0.008 pg TEQ kg(-1) bodyweight (bw) day(-1) on average for all the receptors other than infants in all the settings, while the range was 3.01 x 10(-5)-0.081 pg TEQ kg(-1) bw day(-1) for infants. Sensitivity analysis showed that the consumption of vegetal products and their locally grown fractions are the most significant parameters in the exposure to PCDD/Fs in the area.     

Modeling the Suitability of Potential Wetland Mitigation Sites with a Geographic Information System

Wetland mitigation is frequently required to compensate for unavoidable impacts to wetlands. Site conditions and landscape context are critical factors influencing the functions that created wetlands perform. We developed a spatial model and used a geographic information system (GIS) to identify suitable locations for wetland mitigation sites. The model used six variables to characterize site conditions: hydrology, soils, historic condition, vegetation cover, adjacent vegetation, and land use. For each variable, a set of suitability scores was developed that indicated the wetland establishment potential for different variable states. Composite suitability scores for individual points on the landscape were determined from the weighted geometric mean of suitability scores for each variable at each point. These composite scores were grouped into five classes and mapped as a wetland mitigation suitability surface with a GIS. Sites with high suitability scores were further evaluated using information on the feasibility of site modification and project cost. This modeling approach could be adapted by planners for use in identifying the suitability of locations as wetland mitigation sites at any site or region.     

煤矸石山自然发火数学模型在红阳三矿新矸石山自燃防治中的应用

煤矿矸石山自燃现象普遍存在 ,对环境污染及危害极大 ,防治矸石山自燃是矿区环境修复的重点研究内容。笔者利用宏观的连续介质研究方法 ,以多孔介质流体动力学理论为指导 ,建立了煤矿矸石山自然发火数学模型 ,从数学上揭示了矸石山自燃的动态演变过程。通过分析矸石山内的渗流场明确了自然发火的影响因素及内在联系 ,针对红阳三矿新矸石山的自燃预防问题 ,提出了碾压、覆盖和边界注浆相结合的综合防治施工方案。该技术在红阳三矿新矸石山的现场应用表明 ,治理方案科学、经济、合理 ,实施效果良好。研究结果对预防矸石山自燃具有理论指导意义与实际应用价值。     

Predicting mass rapid transit noise levels on an elevated station

This study developed a noise prediction model for elevated mass rapid transit (MRT) platforms. Relevant physical and operational parameters (e.g. cruise speed, acceleration and deceleration rates for trains, building fa?ade setbacks and so on) were collected from the Bangkok mass transit system (BTS), the first elevated MRT system operated in Bangkok, Thailand. The equivalent continuous sound pressure levels (L(Aeq)) were collected from both sides of the MRT stations at the center of each platform. The relevant parameters were collected on both platforms and ground level, on both sides of MRT stations. These parameters were statistically tested to determine their correlation with MRT noise. The final model was built from highly correlated parameters using multiple regression analysis with a stepwise regression technique. Statistical evaluation showed a high degree of goodness-of-fit test for the model to the observed data. Therefore, it can be efficiently used for the projection of MRT noise in the affected areas.