Application of an Environmental Decision Support System to a Water Quality Trading Program Affected by Surface Water Diversions

Environmental decision support systems (EDSSs) are an emerging tool used to integrate the evaluation of highly complex and interrelated physicochemical, biological, hydrological, social, and economic aspects of environmental problems. An EDSS approach is developed to address hot-spot concerns for a water quality trading program intended to implement the total maximum daily load (TMDL) for phosphorus in the Non-Tidal Passaic River Basin of New Jersey. Twenty-two wastewater treatment plants (WWTPs) spread throughout the watershed are considered the major sources of phosphorus loading to the river system. Periodic surface water diversions to a major reservoir from the confluence of two key tributaries alter the natural hydrology of the watershed and must be considered in the development of a trading framework that ensures protection of water quality. An EDSS is applied that enables the selection of a water quality trading framework that protects the watershed from phosphorus-induced hot spots. The EDSS employs Simon’s (1960) three stages of the decision-making process: intelligence, design, and choice. The identification of two potential hot spots and three diversion scenarios enables the delineation of three management areas for buying and selling of phosphorus credits among WWTPs. The result shows that the most conservative option entails consideration of two possible diversion scenarios, and trading between management areas is restricted accordingly. The method described here is believed to be the first application of an EDSS to a water quality trading program that explicitly accounts for surface water diversions.     

Perceived Collective Efficacy and Trust in Government Influence Public Engagement with Climate Change-Related Water Conservation Policies

Water insecurity, induced or intensified due to climate change, has emerged as a key policy challenge in poor and developing countries such as India. Drawing on social cognitive theory, this paper examines the role of perceived collective efficacy—people's shared beliefs about their group's capabilities to accomplish collective tasks—and trust in government as factors influencing Indians' engagement with government water conservation policies. Using a national survey of Indians (N = 4031), we found that individuals with high levels of perceived collective efficacy and trust in government are more likely to support government water conservation policies. Moreover, for individuals with low trust in government, higher collective efficacy is associated with greater policy support. Perceived collective efficacy is also associated with activist behaviours, while distrust is not. Increasing collective efficacy beliefs, for example through mass media channels and targeted campaigns, could help increase citizens' engagement with climate change adaptation policies.     

Estimation of daily sunshine duration using support vector machines

Although sunshine duration (SD) is one of the most frequently measured meteorological parameters, there is a lack of measurements in some parts of the world. Hence, it should be estimated accurately for areas where no reliable measurement is possible. The main objective of this study is to evaluate the potential of support vector machine (SVM) approach for estimating daily SD. For this purpose, three different kernels of SVM, such as linear, polynomial, and radial basis function (RBF), were used. Different combinations of five related meteorological parameters, namely cloud cover, maximum temperature (T_max), minimum temperature (T_min), relative humidity (RH), and wind speed (WS), and one astronomic parameter, day length, were considered as the inputs of the models, and the output was obtained as daily SD. Simulated values of the models were compared with ground measured values, and concluded that the usage of the SVM-RBF estimator with combination of all input attributes produced the best results. The coefficient of determination, root mean square error, and mean absolute error were found to be 0.8435, 1.5105 h, and 1.0771 h, respectively, for the pooled four-year daily data set of 14 stations in Turkey. It was also deduced that accuracy increased as the number of attributes increased and the major contribution to this came from RH as compared with T_max, T_min, and WS. This study has shown that the SVM methodology can be a good alternative for conventional and artificial neural network methods for estimating daily SD.     

Impacts of Human Behavioral Heterogeneity on the Benefits of Probabilistic Flood Warnings: An Agent‐Based Modeling Framework

Flood forecasts and warnings are intended to reduce flood‐related property damages and loss of human life. Considerable research has improved flood forecasting accuracy (e.g., more accurate prediction of the occurrence of flood events) and lead time. However, the delivery of improved forecast information alone is not necessarily sufficient to reduce flood damage and loss of life, as people have varying responses and reactions to flood warnings. This study develops an agent‐based modeling framework that evaluates the impacts of heterogeneity in human behaviors (i.e., variation in behaviors in response to flood warnings), as well as residential density, on the benefits of flood warnings. The framework is coupled with a traffic model to simulate evacuation processes within a road network under various flood warning scenarios. The results show the marginal benefit associated with providing better flood warnings is significantly constrained if people behave in a more risk‐tolerant manner, especially in high‐density residential areas. The results also show significant impacts of human behavioral heterogeneity on the benefits of flood warnings, and thus stress the importance of considering human behavioral heterogeneity in simulating flood warning‐response systems. Further study is suggested to more accurately model human responses and behavioral heterogeneity, as well as to include more attributes of residential areas to estimate and improve the benefits of flood warnings.     

Prediction of global solar radiation using support vector machines

This article utilizes Support Vector Machines (SVM) for predicting global solar radiation (GSR) for Sharurha, a city in the southwest of Saudi Arabia. The SVM model was trained using measured air temperature and relative humidity. Measured data of 1812 values for the period from 1998–2002 were obtained. The measurement data of 1600 were used for training the SVM, and the remaining 212 were used for comparison between the measured and predicted values of GSR. The GSR values were predicted using the following four combinations of data sets: (i) Daily mean air temperature and day of the year as inputs, and global solar radiation as output; (ii) daily maximum air temperature and day of the year as inputs, and GSR as output; (iii) daily mean air temperature and relative humidity and day of the year as inputs, and GSR as output; and (iv) daily mean air temperature, day of the year, relative humidity, and previous day’s GSR as inputs, and GSR as output. The mean square error was found to be 0.0027, 0.0023, 0.0021, and 7.65 × 10^?4 for case (i), (ii,), (iii), and (iv) respectively, while the corresponding absolute mean percentage errors were 5.64, 5.08, 4.48, and 2.8%. Obtained results show that the SVM method is capable of predicting GSR from measured values of temperature and relative humidity.     

基于农业用地和地形约束的陇南山区适宜人口规模估算

陇南山区地形复杂,耕地不足,经济贫困,人口对资源环境的压力较大。研究适度人口容量对于地震灾后重建、缓解贫困以及保护长江上游的生态安全具有重要意义。以人均粮食和经济水平两个指标来估算温饱、宽裕和小康3个水平上的人口承载量,测度人口和农业资源的关系。并基于地形复杂度计算劳动用工及可抚养人口。结果表明：目前陇南10县(区)的人口在温饱生活水平下尚有超载。以小康生活为标准,适宜人口规模约为135万。经营现有的农耕地和林地需要100.81万劳动力,可抚养人口191.54万人,加上城镇人口总人口为 231.03万。这个人口规模实现温饱有余而宽裕不足,难达小康目标。“人口 农业用地 劳动力”之间形成了一个怪圈,决定了陇南山区农村实现小康目标的艰巨性和复杂性。为此,陇南山区的灾后重建和区域可持续发展需要创新思路,多方并举.     

动载下巷道围岩微震响应特征及支护研究

为探讨动载下深部巷道围岩变形特征,采用微震监测系统、顶板动态监测仪及FLAC3D 数值模拟软件研究深部工作面回采中微震活动特征及巷道变形破坏特征,模拟动载前后巷道围岩及支护体力学响应特性。研究结果表明:微震事件分布与累计损失能量均呈现出明显的3阶段特征,与工作面开采过程出现的初次来压、采空区初次见方和遇见断层现象相对应;微震事件的分布在时间和空间上具有一致性;动载下顶板破坏程度大于底板及两帮;动载扩大了巷道围岩塑性区范围,改变了围岩的受力状态,增大了围岩的变形量与支护体的受力;通过增加锚杆直径、长度、排距及提高预紧力对支护结构进行优化,现场监测数据表明,优化后支护方案保证了围岩的完整性,限制了围岩的变形,减小了锚杆受力,能够有效控制采动影响下巷道围岩的变形,对采动影响下深部巷道维护保证煤矿安全生产具有参考应用价值。     

基于三维GIS的火电厂应急救援决策支持系统研究

针对火电站事故灾害的应急救援工作、电厂应急预案制定的现状,提出基于三维GIS的火电厂应急救援决策支持系统,对火电厂区及周边环境进行虚拟现实仿真,实现对基础地图数据、应急资源数据、重大危险源及其相关属性数据的系统科学管理,以Web方式提供信息查询服务,实现重大危险源周边的三维仿真显示,预测事故影响及其后果,提供最佳路径及救援方案。该研究为火电站及有关部门实施远程应急救援决策提供科学依据。     

模糊支持向量机在滑坡危险性评价中的应用

为了将模糊支持向量机应用于滑坡灾害危险性评价工作,并进行验证,进行了研究区滑坡现状的调查,评价指标的选取,隶属函数的确定和基于FSVM的滑坡灾害危险性评价.选取了高程指标、坡度指标、岩土体指标、地表湿度指标及植被覆盖指标等5个指标作为滑坡灾害危险性评价指标,最后以莆田市为例,结合Rs和GIS技术,进行了滑坡危险性评价的研究.评价结果与实地验证和莆田市国土局提供的地质灾害现状图基本吻合.     

多点激励下拱桥竖向地震反应的简化计算方法

以某大跨公路拱桥为例,通过对拱桥在三种行波输入模式下地震反应的对比计算,提出了拱脚行波输入的简化输入方式;利用拱桥结构的对称性特点,提出了多点输入下半拱叠加的简化计算方法。经验证,这一计算方法具有良好的计算精度,可将较为复杂的拱桥多点输入地震反应计算问题,转化为工程技术人员熟悉的一致输入下地震反应计算问题。