Sustainable rangeland management using a multi-fuzzy model: how to deal with heterogeneous experts' knowledge

While fuzzy specialists commonly use homogeneous experts' knowledge to construct fuzzy models, it is much more difficult to deal with knowledge elicited from a heterogeneous group of experts. This issue is exemplified in the area of sustainable rangeland management (SRM). One way to deal with the diversity of opinions is to develop a fuzzy system for all experts and to combine all these, the so-called primary systems, into one multi-fuzzy model. To derive each of the primary fuzzy systems, several semi-structured interviews were held in three different areas of the Fars province in Southwest Iran using the knowledge of a group of administrative experts. To obtain the final output of the multi-fuzzy model, we applied different 'voting' methods. The first method simply uses the arithmetic average of the primary outputs as the final output of the multi-fuzzy model. This final output represents an estimation of the right rate of stocking (RRS). We also propose other (un)supervised voting methods. Most importantly, by harmonising the primary outputs such that outliers get less emphasis, we introduce an unsupervised voting method for calculating a weighted estimate of the RRS. This harmonising method is expected to provide a new useful tool for policymakers dealing with heterogenity in experts' opinions: it is especially useful where limited field data are available and one is forced to rely on experts' knowledge only. By constructing the three fuzzy models based on the elicitation of heterogeneous experts' knowledge, our study shows the multidimensional vaguenesses that exist in SRM. Finally, by comparing the final RRS with its common values, this study strongly points to the existence of overgrazing in pastures in the three regions of the Fars province in Southwest Iran.     

Sustainable multi-trip periodic redesign-routing model for municipal solid waste collection network: the case study of Tehran

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Estimation of greenhouse gas emission flux from agricultural lands of Khuzestan province in Iran

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开都河下游绿洲耕地土壤重金属污染及潜在生态风险

开都河下游绿洲采集98个耕地土壤样品,测定其中As、Cd、Cr、Cu、Mn、Ni、Pb和Zn等8种重金属元素的含量.基于地统计法,污染负荷指数法和潜在生态风险指数法研究耕地土壤重金属污染和潜在生态风险,并对重金属的来源进行讨论.结果表明:(1)研究区Cd含量平均值超出《国家土壤环境质量标准》中Ⅱ级标准的11.08倍.Cd、Cr、Ni、Pb和Zn含量的平均值分别超出新疆灌耕土背景值的55.42、1.32、1.36、3.40和5.14倍.重金属元素空间分布各不相同,部分区域出现高值区,表明人类活动对耕地土壤环境具有负面效应.(2)研究区耕地土壤Cd呈现重度污染,Pb呈现中度污染,Cr、Cu、Ni和Zn呈现轻度污染,As和Mn呈现无污染态势.Cd是污染面积最大,污染程度最高的元素.研究区污染负荷指数PLI的平均值为1.68,呈现轻度污染.(3)各重金属元素单项生态风险指数(E)的平均值从大到小依次为:Cd、Ni、As、Cu、Pb、Cr与Zn.研究区综合生态风险指数(RI)的平均值为355.31,属于较强生态风险.(4)研究区耕地土壤As、Cd、Pb和Zn主要受到人类活动的影响,Cr、Cu、Mn和Ni主要受到土壤地球化学特征的控制.Cd是研究区耕地土壤主要的污染因子,对PLI和RI的贡献很大,耕地土壤中Cd污染必须关注.