Application of fuzzy sets and cognitive maps to incorporate social science scenarios in integrated assessment modelsA case study of urbanization in Ujung Pandang, Indonesia

Decision–support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the coastal city of Ujung Pandang, Indonesia. The results indicate that both techniques are useful tools for the design of integrated models based on a combination of concepts from the natural and social sciences. This revised version was published online in July 2006 with corrections to the Cover Date.     

INASUD project findings on integrated assessment of climate policies

This communication summarizes the main findings of INASUD, an European-wide research project on integrated assessment of climate policies. The project aimed at improving the framing of climate policy analysis through the parallel use of various existing integrated assessment models. It provides a comprehensive examination of the link between uncertainty regarding damages and inertia in economic systems. Results show that the Kyoto targets and timing are consistent with the precautionary principle but offers little insurance for longer-term climate protection. Flexibility mechanisms offer potentials for cooperation with developing countries, and are necessary to tap the environmental and economic benefits of joint carbon and sulfur emissions abatement.     

A Framework for Comprehensive,Integrated, Watershed Monitoring in New York City

The International Life SciencesInstitute (ILSI) Risk Science Institute (RSI) convenedan expert panel of scientists to developrecommendations for a comprehensive monitoring programfor the Croton and Catskill/Delaware watersheds, whichprovide drinking water to New York City's residents. This effort was conducted as part of efforts topreserve and enhance the quality of New York City'sreservoir system through a watershed protectionprogram. The panel developed recommendations for astrategic framework on which to construct a monitoringprogram. As part of this activity, the paneldetermined whether existing monitoring activities weredeficient and, where activities were deficient, thepanel developed recommendations for additionalinformation that should be collected.The panel recommended the development and use of anintegrated approach to watershed monitoring, whichdraws on modeling, risk-based planning and analysis,statistical sampling and design, and basic compliancemonitoring. The approach should be designed toprovide an assessment of natural and anthropogenicsources of stress to the system as well as anassessment of water quality trends in response tostresses acting in concert, both over the long termand over the five-year New York City Memorandum ofAgreement (MOA) assessment time frame. It should alsoprovide an assessment of the human health andenvironmental risks posed by a variety of stressors,and the impact of management actions implemented toameliorate stressors.     

The Need for Scale Sensitive Approaches in Spatially Explicit Land Use Change Modeling

This paper introduces some of the issues that are relevant to the spatially explicit modeling of land use systems. A short overview is given of the ways and means in which a number of different land use change models describe the land use system. Specific attention is given to the empirical modeling approach used in the CLUE (Conversion of Land Use and its Effects) modeling framework. This approach is demonstrated for three case studies in China, Ecuador and the Atlantic Zone of Costa Rica. These case-studies illustrate the methodology for multi-scale analysis of land use driving factors and their application in spatially explicit modeling exercises. Model functioning, performance and limitations are discussed. The presented case-studies indicate that empirical modeling results can contribute to a better theoretic imbedding of land use change research in scale sensitive and integrated theories.     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.     

基于灰建模的瓦斯含量多变量预测模型研究

研究了GM(1,N)、GM(0,N)瓦斯含量预测模型的数学原理,收集郑煤集团告成矿地质勘探期间及生产期间的瓦斯含量实测资料,获得16个可靠点,选取基岩厚度、新生界厚度、煤层厚度、煤层水分、煤层灰分、50m顶板含砂率6个因素作灰色建模预测的指标,分别建立了GM(1,6)和GM(0,6)瓦斯含量多变量预测模型。根据计算和评价结果,GM(1,6)和GM(0,6)瓦斯含量预测模型精度均能够满足工程精度的要求,说明利用灰色模型来预测瓦斯含量是可行的。由于前者精度略高于后者,故建议告成矿采用GM(1,6)模型来进行未知地区煤层瓦斯含量的预测。需要注意,由于模型没有考虑构造的影响,在实际预测时,还应根据构造对待预测区的影响关系和影响程度对模型的预测结果进行修正。     

Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques

Information on distribution and relative abundance of species is integral to sustainable management, especially if they are to be harvested for subsistence or commerce. In northern Australia, natural landscapes are vast, centers of population few, access is difficult, and Aboriginal resource centers and communities have limited funds and infrastructure. Consequently defining distribution and relative abundance by comprehensive ground survey is difficult and expensive. This highlights the need for simple, cheap, automated methodologies to predict the distribution of species in use, or having potential for use, in commercial enterprise. The technique applied here uses a Geographic Information System (GIS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem. The study area is in the Maningrida region, central Arnhem Land, in the Northern Territory, Australia. The species examined, Cycas arnhemica and Brachychiton diversifolius, are currently being 'wild harvested' in commercial trials, involving sale of decorative plants and use as carving wood, respectively. This study involved limited and relatively simple ground surveys requiring approximately 7 days of effort for each species. The overall model performance was evaluated using Cohen's kappa statistics. The predictive ability of the model for C. arnhemica was classified as moderate and for B. diversifolius as fair. The difference in model performance can be attributed to the pattern of distribution of these species. C. arnhemica tends to occur in a clumped distribution due to relatively short distance dispersal of its large seeds and vegetative growth from long-lived rhizomes, while B. diversifolius seeds are smaller and more widely dispersed across the landscape. The output from analysis predicts trends in species distribution that are consistent with independent on-site sampling for each species and therefore should prove useful in gauging the extent of resource availability. However, some caution needs to be applied as the models tend to over predict presence which is a function of distribution patterns and of other variables operating in the landscape such as fire histories which were not included in the model due to limited availability of data.     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.     

Kinetic extractions to assess mobilization of Zn, Pb, Cu, and Cd in a metal-contaminated soil: EDTA vs. citrate

Kinetic EDTA and citrate extractions were used to mimic metal mobilization in a soil contaminated by metallurgical fallout. Modeling of metal removal rates vs. time distinguished two metal pools: readily labile (QM1) and less labile (QM2). In citrate extractions, total extractability (QM1+QM2) of Zn and Cd was proportionally higher than for Pb and Cu. Proportions of Pb and Cu extracted with EDTA were three times higher than when using citrate. We observed similar QM1/QM2 ratios for Zn and Cu regardless of the extractant, suggesting comparable binding energies to soil constituents. However, for Pb and Cd, more heterogeneous binding energies were hypothesized to explain different kinetic extraction behaviors. Proportions of citrate-labile metals were found consistent with their short-term, in-situ mobility assessed in the studied soil, i.e., metal amount released in the soil solution or extracted by cultivated plants. Kinetic EDTA extractions were hypothesized to be more predictive for long-term metal migration with depth.     

Leaching behavior of heavy metals from municipal solid waste incineration bottom ash and its geochemical modeling

With the increase in the number of municipal solid waste incineration (MSWI) plants constructed in China recently, great attention has been paid to the heavy metal leaching toxicity of MSWI residues. In this study, the effects of various parameters, including extractant, leaching time, liquid-to-solid ratio, leachate pH, and heavy metal content, on the release properties of Cd, Cr, Cu, Ni, Pb, and Zn from MSWI bottom ash were investigated. Partial least-squares analysis was employed to highlight the interrelationships between the factors and response variables. Both experimental research and geochemical modeling using Visual MINTEQ software were conducted to study the pH-dependent leaching behavior of these metals in fresh and weathered bottom ash, considering precipitation/dissolution and surface complexation reactions (adsorption by hydrous ferric oxide and amorphous aluminum oxide/hydroxide). The results showed that leachate pH was the predominant factor influencing heavy metal leachability. The leaching of Cu, Pb, and Zn was mainly controlled by precipitation/dissolution reactions, whereas surface complexation had some effect on the leaching of Cr, Cd, and Ni for certain pH ranges. The modeling results aggreed well with the experimental results. Part of this work was presented at the Fourth International Conference on Combustion, Incineration/Pyrolysis and Emission Control (i-CIPEC)