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Special Issue "Advances in Environmental Modelling"

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).

Deadline for manuscript submissions: closed (31 January 2011)

Special Issue Editor

Guest Editor
Prof. Dr. Allan Brimicombe

Centre for Geo-Information Studies, University of East London, Docklands Campus, University Way, London, E16 2RD, UK
Website | E-Mail
Interests: GIS & environmental simulation modelling; spatial data analysis & data mining; modelling of spatial phenomena; modelling crime, deprivation and social exclusion; spatial data quality; fuzzy concepts in GIS; location-based services (LBS)

Special Issue Information

Dear Colleagues,

Environmental simulation models provide a solution exploration space for many of the key issues and problems we face in the custodianship of our planet. The turn of the decade is a good time to take stock of the state-of-the-art and the new or remaining challenges for the research agenda. This special issue on Advances in Environmental Modelling will include within its remit simulation modelling of physical, biological, economic and socio-cultural environments. The theme will incorporate not only advances in the approaches to environmental modelling per se, but a more broader view on the evolving contributions that these models make in decision-making and to the sustainability agenda.

Prof. Dr. Allan Brimicombe
Guest Editor

Keywords

  • agent-based and component-based approaches to environmental modelling
  • coupling environmental models with GIS and geocomputational toolsets
  • modelling economic, social and cultural impacts of climate change
  • modelling environmental justice
  • environmental modelling in strategic and environmental impact assessment
  • risk/cost analysis of hazards
  • data quality issues and modelling uncertainty in relation to predictive
  • performance
  • real-time systems
  • contingency planning and emergency response
  • visualisation and communication with stakeholders
  • participatory and mediated approaches
  • management and decision support, including underpinning sustainability
  • open source software

Published Papers (3 papers)

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Research

Open AccessArticle A Four-Step Method for Optimising the Normal Water Level of Reservoirs Based on a Mathematical Programming Model—A Case Study for the Songyuan Backwater Dam in Jilin Province, China
Int. J. Environ. Res. Public Health 2011, 8(4), 1049-1060; doi:10.3390/ijerph8041049
Received: 1 November 2010 / Revised: 31 December 2010 / Accepted: 26 March 2011 / Published: 7 April 2011
Cited by 2 | PDF Full-text (224 KB) | HTML Full-text | XML Full-text
Abstract
Determination of the optimal normal water level of reservoirs (RNWL) was investigated, incorporating environmental ecology as a primary consideration. RNWL constitutes a relatively significant eigenvalue of any water conservancy project. In the present study, a four-step method based on a mathematical programming model
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Determination of the optimal normal water level of reservoirs (RNWL) was investigated, incorporating environmental ecology as a primary consideration. RNWL constitutes a relatively significant eigenvalue of any water conservancy project. In the present study, a four-step method based on a mathematical programming model and suitable for RNWL decision making was developed and applied to the water conservancy project of the Songyuan backwater dam in China. System analysis, correlation analysis, significance testing, principal component analysis, sensitivity analysis, and system optimisation theory are used in the solution process. In this study, various factors that impact the economic viability, engineering characteristics, environmental and urban ecology are considered for holistic optimisation. The study shows that the proposed four-step method may provide a feasible quantitative form of support for RNWL decision making. Full article
(This article belongs to the Special Issue Advances in Environmental Modelling)
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Open AccessArticle Assessing the Impacts of Local Knowledge and Technology on Climate Change Vulnerability in Remote Communities
Int. J. Environ. Res. Public Health 2011, 8(3), 733-761; doi:10.3390/ijerph8030733
Received: 27 January 2011 / Revised: 8 February 2011 / Accepted: 25 February 2011 / Published: 4 March 2011
Cited by 15 | PDF Full-text (2307 KB) | HTML Full-text | XML Full-text
Abstract
The introduction of new technologies into small remote communities can alter how individuals acquire knowledge about their surrounding environment. This is especially true when technologies that satisfy basic needs, such as freshwater use, create a distance (i.e., diminishing exposure) between individuals
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The introduction of new technologies into small remote communities can alter how individuals acquire knowledge about their surrounding environment. This is especially true when technologies that satisfy basic needs, such as freshwater use, create a distance (i.e., diminishing exposure) between individuals and their environment. However, such distancing can potentially be countered by the transfer of local knowledge between community members and from one generation to the next. The objective of this study is to simulate by way of agent-based modeling the tensions between technology-induced distancing and local knowledge that are exerted on community vulnerability to climate change. A model is developed that simulates how a collection of individual perceptions about changes to climatic-related variables manifest into community perceptions, how perceptions are influenced by the movement away from traditional resource use, and how the transmission of knowledge mitigates the potentially adverse effects of technology-induced distancing. The model is implemented utilizing climate and social data for two remote communities located on the Seward Peninsula in western Alaska. The agent-based model simulates a set of scenarios that depict different ways in which these communities may potentially engage with their natural resources, utilize knowledge transfer, and develop perceptions of how the local climate is different from previous years. A loosely-coupled pan-arctic climate model simulates changes monthly changes to climatic variables. The discrepancy between the perceptions derived from the agent-based model and the projections simulated by the climate model represent community vulnerability. The results demonstrate how demographics, the communication of knowledge and the types of ‘knowledge-providers’ influence community perception about changes to their local climate. Full article
(This article belongs to the Special Issue Advances in Environmental Modelling)
Open AccessArticle A Simple Model of Tetracycline Antibiotic Resistance in the Aquatic Environment (with Application to the Poudre River)
Int. J. Environ. Res. Public Health 2011, 8(2), 480-497; doi:10.3390/ijerph8020480
Received: 1 January 2011 / Revised: 20 January 2011 / Accepted: 10 February 2011 / Published: 15 February 2011
Cited by 10 | PDF Full-text (376 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Antibiotic resistance is a major concern, yet it is unclear what causes the relatively high densities of resistant bacteria in the anthropogenically impacted environment. There are various possible scenarios (hypotheses): (A) Input of resistant bacteria from wastewater and agricultural sources is significant, but
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Antibiotic resistance is a major concern, yet it is unclear what causes the relatively high densities of resistant bacteria in the anthropogenically impacted environment. There are various possible scenarios (hypotheses): (A) Input of resistant bacteria from wastewater and agricultural sources is significant, but they do not grow in the environment; (B) Input of resistant bacteria is negligible, but the resistant bacteria (exogenous or endogenous) grow due to the selection pressure of the antibiotic; (C) Exogenous bacteria transfer the resistance to the endogenous bacteria and those grow. This paper presents a simple mechanistic model of tetracycline resistance in the aquatic environment. It includes state variables for tetracyclines, susceptible and resistant bacteria, and particulate and dissolved organic matter in the water column and sediment bed. The antibiotic partitions between freely dissolved, dissolved organic matter (DOM)-bound and solids-bound phases, and decays. Bacteria growth is limited by DOM, inhibited by the antibiotic (susceptible bacteria only) and lower due to the metabolic cost of carrying the resistance (resistant bacteria only). Resistant bacteria can transfer resistance to the susceptible bacteria (conjugation) and lose the resistance (segregation). The model is applied to the Poudre River and can reproduce the major observed (literature data) patterns of antibiotic concentration and resistance. The model suggests observed densities of resistant bacteria in the sediment bed cannot be explained by input (scenario A), but require growth (scenarios B or C). Full article
(This article belongs to the Special Issue Advances in Environmental Modelling)
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