WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.     

蓄热式加热炉安全技术操作规程优化初探

唐钢中型厂2#加热炉技术改造后，在加热炉设备检修、维修、维护过程中，如何在保证操作安全的同时，保证操作的准确到位，为安全管理工作提出了研究课题。     

粉煤灰静电脱炭技术研究

本文介绍粉煤灰静电脱炭资源化利用技术的试验研究.利用YNDF-I型立式电场粉煤灰脱炭装置进行优化试验,提出电压、极板间距、摩擦分散器材料、粉尘浓度及气体流量等运行工艺特性参数与静电脱炭率的相关关系.试验结果表明,该立式电场脱炭装置在最优工艺参数条件下运行时,可使粉煤灰脱炭后的精灰含炭量降低到1.20%,脱炭率达86.74%,能够直接代替水泥用作建筑材料或修筑公路路面,具有较高的经济效益、社会效益和环境效益,为粉煤灰资源化利用提供了一种新的途径.     

A grey multi-objective programming approach for sustainable land-use in the Miyun Reservoir basin, China

Miyun Reservoir is the most important water source to Beijing City. Land-use of the basin plays a great role in the protection of water resources. Hence a sustainable land-use planning is required to optimize land-use structure and protect water resources in the basin. Based on the complete land-use system analysis in Miyun, a grey multi-objective programming to basin land-use(GMOPBLU)model was developed and applied to land-use planning. Two alternatives were produced and analyzed by means of interactive adjustment and scenano analysis. The results showed the GMOPBLU model is a valuable approach for basin land-use planning.     

电力供应系统地震安全性优化控制研究

在深入研究电力供应系统潮流分布特性、发电机出力和成本曲线特性、电力系统地震安全性分析与控制的基础上,将安全约束最优化控制算法运用于电力供应系统地震安全性控制中。通过对算法的网络线性分析模型、发电机出力约束条件、线路潮流约束条件和目标函数的深入研究,得出该算法的实施过程;而后,结合供电系统潮流分析的快速解耦法、安全性分析的灵敏度安全性分析法和本文的安全约束最优化控制算法,编写了相应的Fortran和Matlab计算程序,该程序能在较短的时间内计算出调度控制措施和调度费用;最后,通过一个实际算例的分析与计算,验证了该算法的实用性和优越性。本文工作可为震后供电系统功能快速恢复,减少供电系统经济损失,使系统功能得到最大发挥提供理论分析依据,具有很大的现实意义。     

基于PSO-AHP的大坝致灾因子权重计算

提出了一种基于改进粒子群优化-层次分析法(SELPSO-AHP)的致灾因子权重计算模型,该模型依据大坝现场检测、原型监测和安全定期检查等成果,由层次分析法构建大坝风险分析的层次结构体系。为保证判断矩阵的一致性,引入改进粒子群算法和罚函数法用于层次分析法的权值计算,取得了比遗传算法更精确、更稳定的结果。将所建立的模型用于某混凝土重力坝的运行风险分析,得到了影响该坝运行风险的主要因素,为保障大坝安全提供了依据。     

基于灾变的人群疏散避灾路径优化及应用

突发事件条件下的应急疏散是一个复杂的过程,不仅要考虑时间因素,而且要考虑疏散网络中各路段的受灾风险水平。因此,对于人群快速转移避灾路径的解算结果,不仅要求快速,还要求避灾。基于灾害预测的疏散路径优化理论模型,在求解时变灾害条件下,集成考虑实时与未来灾害影响的转移避灾路径优化算法。采用C#程序设计语言和Visual studio 2013平台,开发了进行模型算法实现的原型系统,并通过算例进行了说明。结果表明:在预先设置的灾害情景中,提出的模型算法可以提前规划出避开灾害且疏散时间较短的路径,为制定应急预案提供参考依据。     

Valuing environmental amenities through inverse optimization: Theory and case study

Amenity values of private forests are implicit but play a critical role in decision and policy making. This study presents an innovative valuation approach integrating techniques of operations research and economic theory of pricing environmental goods. A forest planning problem was inversed through altering its reward function of timber values so that the observed harvesting behavior became optimal. The discrepancy between the original and new rewards uncovered amenities values which were linked to forest attributes via hedonic models. This method was applied to a case study of the U.S. southern pine region. Depending on forest conditions, total economic values of amenities varied from zero to just under one thousand dollar per ha. At a discount rate of 3%, a typically managed forest generated on average $243 ha⁻¹ of amenities values per annum, more than twice of harvested timber values. Structural diversity and density of large pine trees were the key determinants to preserving forests for environmental amenities.     

PRISM vs. CFSR Precipitation Data Effects on Calibration and Validation of SWAT Models

Precipitation is one of the most important drivers in watershed models. Our objective was to compare two sources of interpolated precipitation data in terms of their effect on calibration and validation of two Soil and Water Assessment Tool (SWAT) models. One model was a suburban watershed in metropolitan Atlanta, Georgia. The precipitation sources were Parameter‐elevation Relationships on Independent Slopes Model (PRISM) data on a 4‐km grid and climate forecast system reanalysis (CFSR) data on a 38‐km grid. The PRISM data resulted in a better fit to the calibration data (Nash Sutcliffe efficiency [NSE] = 0.64, Kling‐Gupta efficiency [KGE] = 0.74, p‐factor = 0.84, and r‐factor = 0.43) than the CFSR data (NSE = 0.47, KGE = 0.53, p‐factor = 0.67, and r‐factor = 0.39). Validation results were similar. Sensitive parameters were similar in both the PRISM and CFSR models, but fitted values indicated more rapid groundwater flow to the streams with the PRISM data. The same comparison was made in the Big Creek watershed located approximately 1,000 km away, in central Louisiana. Results were similar with a more responsive groundwater system indicating PRISM data may produce better predictions of streamflow because of a more accurate estimate of rainfall within a watershed or because of a denser grid. Our study implies PRISM is providing a better estimate than CFSR of precipitation within a watershed when rain gauge data are not available, resulting in more accurate simulations of streamflows at the watershed outlet. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Optimization of thermal performance of the parabolic trough solar collector systems based on GA-BP neural network model

The aim of this paper is to optimize the thermal performance (system output energy, thermal efficiency, and heat loss of cavity absorber) of parabolic trough solar collector (PTC) systems in order to improve its thermal performance, based on the genetic algorithm-back propagation (GA-BP) neural network model. There are a number of undefined problems, fuzzy or incomplete information and a complex thermal performance of the PTC systems. Therefore, the thermal performance prediction of the PTC systems based on GA-BP neural network model was developed. Subsequently, the metrics performances have been adopted to comprehensively understand the algorithm and evaluate the prediction accuracy. Results revealed that the GA-BP neural network model can be successfully used to predict the complex nonlinear relationship between the input variables and thermal performance of the PTC systems. The cosine effect has a great influence on the thermal performance; thereby the geometrical structure of the PTC systems was optimized. It was found that the optimized geometrical structure was beneficial to improve the thermal performance of the PTC system. In conclusion, the GA-BP neural network model has higher prediction accuracy than the other algorithm and it can be feasible and reliable.