Evaluation of Dairy Effluent Management Options Using Multiple Criteria Analysis

This article describes how options for managing dairy effluent on the Lower Murray River in South Australia were evaluated using multiple criteria analysis (MCA). Multiple criteria analysis is a framework for combining multiple environmental, social, and economic objectives in policy decisions. At the time of the study, dairy irrigation in the region was based on flood irrigation which involved returning effluent to the river. The returned water contained nutrients, salts, and microbial contaminants leading to environmental, human health, and tourism impacts. In this study MCA was used to evaluate 11 options against 6 criteria for managing dairy effluent problems. Of the 11 options, the MCA model selected partial rehabilitation of dairy paddocks with the conversion of remaining land to other agriculture. Soon after, the South Australian Government adopted this course of action and is now providing incentives for dairy farmers in the region to upgrade irrigation infrastructure and/or enter alternative industries.     

Cutting the cake: Supporting environmental fund allocation decisions

This paper describes a decision support model for allocating financial resources amongst multiple user groups in environmental management problems. The model is based on the multiple criteria analysis (MCA) method of compromise programming. It was used to inform the allocation of Natural Heritage Trust funds across 14 regions in Queensland, Australia. The model targets funding to those regions with greater natural resource management needs. Need is determined by 19 weighted criteria relating to natural resource assets and threats. The model was accepted by the Australian Government, Queensland Government and regional groups as an appropriate means for allocating program funds; first in 2005 and then again, with improvements, in 2007. This paper shows that an MCA model can improve the transparency, auditability and acceptance of allocation decisions which would otherwise be heavily politicised.     

Evaluating water quality investments using cost utility analysis

This study borrows concepts from healthcare economics and uses cost utility analysis (CUA) to select an optimum portfolio of water quality enhancement projects in Perth, Western Australia. In CUA, costs are handled via standard discounted cash flow analysis, but the benefits, being intangible, are measured with a utility score. Our novel methodology combines CUA with a binary combinatorial optimisation solver, known as a 'knapsack algorithm', to identify the optimum portfolio of projects. We show how water quality projects can be selected to maximise an aggregate utility score while not exceeding a budget constraint. Our CUA model applies compromise programming (CP) to measure utility over multiple attributes in different units. CUA is shown to provide a transparent and analytically robust method to maximise benefits from water quality remediation investments under a constrained budget.     

东北玉米热量指数预测方法研究(Ⅱ)——逐步回归预测方法

利用1960-2005年74类大气环流资料,从玉米播种期的5月开始到8月,逐月滚动建立了东北3省典型站玉米热量指数的逐步回归模型.各月模型都能较好地预测该区玉米生长季内的热量状况.检验结果表明,通过运用滚动预报的方法,可以有效地提高预测玉米生长季内热量指数的准确率.     

近50a人工灌排技术进步对玛纳斯河流域耕地格局变化的影响

分析绿洲人工灌排技术发展和耕地格局变化之间的关系,对研究干旱区灌溉农业发展具有重要的意义。论文选取玛纳斯河流域为研究区,利用RS和GIS技术,对玛纳斯河流域1960年地形图,1976、1989、1997、2006、2013年Landsat遥感影像和历史水利工程建设分布图等原始数据进行处理,获得5期人工灌排渠系矢量图和6期土地利用分类矢量图,并计算人工灌排渠系长度指数和表征耕地格局的绿洲垦殖率、净耕地系数、周长面积比;利用多元逐步回归法,分析干旱区绿洲人工灌排技术对耕地格局变化的影响。结果表明:滴灌技术应用前,玛纳斯河流域耕地分布格局由灌排渠系的空间分布决定,尤其是农渠的分布格局和长度,其与耕地面积的回归方程为y=0.43x+7.38(R~2=0.90,n=33,P=0);滴灌技术应用后,耕地分布格局的变化取决于滴灌系统管网的空间分布,尤其是干管和支管的分布格局与长度,导致流域灌溉水利用系数从1960年的0.38增长到2010年的0.65。     

A model supported by GIS for locating and quantifying PM2.5 emission originated from residential wood burning

A research method was presented for spatially quantifying and allocating the potential activity of a fine particle matter emission （ PM2.5 ）, which originated from residential wood burning （RWB） in this study. Demographic, hypsographic, climatic and topographic data were compiled and processed within a geographic information system（GIS）, and as independent variables put into a linear regression model for describing spatial distribution of the potential activity of residential wood burning as primary heating source. In order to improve the estimation, the classifications of urban, suburban and rural were redefined to meet the specifications of this application. Also, several definitions of forest accessibility were tested for estimation. The results suggested that the potential activity of RWB was mostly determined by elevation of a location, forest accessibility, urban/non-urban position, climatic conditions and several demographic variables. The linear regression model could explain approximately 86% of the variation of surveyed potential activity of RWB. The analysis results were validated by employing survey data collected mainly from a WebGIS based phone interview over the study area in central California. Based on lots free public GIS data, the model provided an easy and ideal tool for geographic researchers, environmental planners and administrators to understand where and how much PM2.5 emission from RWB was contributed to air quality. With this knowledge they could identify regions of concern, and better plan mitigation strategies to improve air quality. Furthermore, it allows for future adjustment on some parameters as the spatial analysis method is implemented in the different regions or various eco-social models.     

2种有机磷农药联合胁迫下日本青鳉的逐级行为响应

采用水质安全在线生物预警系统(BEWs)记录行为强度数据,探讨了2种有机磷农药敌百虫和对硫磷联合胁迫下,不同暴露浓度、不同暴露时间日本青鳉的行为响应.在不同浓度比例的农药暴露中,20、10、5、1和0.1TU的暴露浓度下行为反应时间分别为:1.4、4.8、6.4、32.2和43.0h,并且每个浓度不同配比之间行为反应时间差异不明显.结果表明,在2种有机磷农药的暴露下,日本青鳉的逐级行为响应既受化合物浓度高低的影响,又受暴露时间的影响,但每个浓度的不同配比之间的行为响应时间差异不明显,而且每个浓度2种药物不同配比暴露下的青鳉鱼的逐级行为响应基本一致,即2种作用机制相似的有机磷农药对日本青鳉的行为毒性是简单的相加作用.     

社区水平森林景观格局的动态变化与未来情景模拟

论文以重庆市石柱县三星乡石星村为样区,基于2004年森林景观格局的相关数据,运用Logistic逐步回归方法筛选出了不同时期对石星村森林景观格局具有决定作用的影响因子,并采用CLUE-S模型对石星村2014年森林景观分布格局进行了模拟与验证。此基础上,分别基于历史发展趋势、“农二代”返乡潮以及工商资本介入3种情景模拟石星村2024年的森林景观格局,利用景观格局指数对2004-2024年间3种情景下的景观格局动态及破碎度进行研究。结果表明：1） 利用石星村2004年的森林景观格局分布图对2014年森林景观格局进行模拟,总体精度达到了85%,Kappa指数均值达到0.816,这表明CLUE-S模型对石星村森林景观的格局变化具有良好的模拟能力;2） 在预设的3种情景下,样区森林景观一直占据20 a间景观基质的主导地位,林区分析结果显示出林地总面积没有明显减少,且相较于2004年的林地总面积表现出增加的趋势。3种情景下退化林地面积均呈减少的趋势,其中,相较于历史发展趋势,“农二代”返乡潮情景下退化林地的减少均伴随着人工林和农用地面积的增加,而工商资本介入情景下退化林地的减少伴随着人工林面积的增加和农用地面积的减少;3） 在林地的空间分布上,各林地类型的分布存在一定的规律性,其中退化原始林主要集中分布在中东部低山、深丘区,次生林、退化林地和人工林呈镶嵌格局,分散于主要基质性景观中;4） 样区在3种情景模拟下,森林景观破碎化程度存在差异。总体来说,“农二代”返乡潮和工商资本介入两种情景下森林景观恢复较好。研究结论可为石星村未来森林景观管理、规划及政策的制定等提供参考依据和决策支持。     

A nonlinear model for assessing multiple probabilistic risks: a case study in South five-island of Changdao National Nature Reserve in China

Several methods for estimating the potential impacts caused by multiple probabilistic risks have been suggested. These existing methods mostly rely on the weight sum algorithm to address the need for integrated risk assessment. This paper develops a nonlinear model to perform such an assessment. The joint probability algorithm has been applied to the model development. An application of the developed model in South five-island of Changdao National Nature Reserve, China, combining remote sensing data and a GIS technique, provides a reasonable risk assessment. Based on the case study, we discuss the feasibility of the model. We propose that the model has the potential for use in identifying the regional primary stressor, investigating the most vulnerable habitat, and assessing the integrated impact of multiple stressors.     

江苏中部农业园小麦和土壤镉元素含量关系研究

为研究江苏中部农业园土壤和小麦镉元素含量［ω(Cd_soil)和ω（Cd_wheat）］关系,采集了土壤和小麦样品40组,采用多元线性回归分析方法建立ω(Cd_wheat)的预测模型。结果表明：（1）研究区表层土壤呈中性偏弱酸性,ω(Cd_soil)含量范围为0.083~0.239 mg/kg,平均值为0.152 mg/kg,均低于《土壤环境质量 农用地土壤污染风险管控标准（试行）》（GB 15618—2018）中农用地土壤污染风险筛选值,属于优先保护类土壤;（2）依据《食品安全国家标准 食品中污染物限量》（GB 2762—2017）中ω(Cd_wheat)限定值(0.1 mg/kg),小麦籽实Cd超标率为10%;（3）ω(Cd_wheat)主要受表层ω(Cd_soil)控制,同时受到土壤钼（Mo）、铅（Pb）、砷（As）、钙（Ca）和镉（Cd）等元素有效态影响,另外,还受土壤理化性质（pH值和有机质）的影响。