Decision support system monitoring and modelling platform to inform policy and management strategies to reduce environmental impacts of traffic

2012 ◽  
Author(s):  
M. Bell ◽  
P. James ◽  
F. Galatioto ◽  
G. Hill
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Environmental Impacts ◽  
Support System ◽  
Management Strategies ◽  
System Monitoring

Optimised management strategies for the Biosphere reserve Lobau, Austria - based on a multi criteria decision support system

2006 ◽  
Vol 6 (1-4) ◽  
pp. 25-36 ◽  
Author(s):  
Thomas Hein ◽  
Alfred P. Blaschke ◽  
Gertrud Haidvogl ◽  
Severin Hohensinner ◽  
Verena Kucera-Hirzinger ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Management Strategies ◽  
Biosphere Reserve

Water Decision Support System for Urban Water Security under Uncertain Future: A Case Study of Upper Yamuna River Basin, India

2021 ◽  
Author(s):  
Dinesh Kumar ◽  
Chandrika Thulaseedharan Dhanya ◽  
Ashvani Gosain
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
River Basin ◽  
Support System ◽  
Management Strategies ◽  
Water Security ◽  
Urban Water ◽  
Future Scenarios ◽  
Yamuna River ◽  
Management Options

<p>Ensuring water security considering the near- and far-future climatic and socio-economic uncertainties, is one of the grand global challenges. In developing countries, supply-side management like the construction of new dams, rehabilitation and augmentation of the existing water resources and supply infrastructure are the widely adopted solutions. Often, the importance of the requirement of water for environmental well-being is neglected. Here, we develop a modelling framework using Water Evaluation and Planning and Qual2K models, considering ‘environment’ also as a stakeholder. This water decision support system is demonstrated on the Upper Yamuna River Basin, a complex and polluted river system in India. Further, to raise risk awareness among stakeholders about the extreme plausible future conditions, the storyline-based approach is adopted to develop future scenarios. The developed framework is deployed to explore the National Capital Territory of Delhi's urban water security for different plausible future scenarios. Based on this, reliability of different policy management options and strategies are explored. The simulated results show that the localized (urban level) management strategies are more reliable than the basin level management strategies, especially under a prolonged plausible warmer climate and better standard of living based socio-economic development conditions. The model building, scenario development, and analysis demonstrate the importance of incorporating the local system knowledge to build an effective decision support system for physically and legally complex river basins.</p>

scholarly journals Forest management strategies to reduce spruce budworm damage in the Fundy Model Forest

1996 ◽  
Vol 72 (4) ◽  
pp. 399-405 ◽  
Author(s):  
David A. MacLean
Keyword(s):  
Decision Support ◽  
Forest Management ◽  
Decision Support System ◽  
Support System ◽  
Tree Mortality ◽  
Choristoneura Fumiferana ◽  
Management Strategies ◽  
Spruce Budworm ◽  
Stand Age ◽  
Timber Supply

Spruce budworm (Choristoneura fumiferana) outbreaks cannot be prevented, but the amount of damage that occurs can be managed. Tree species, stand age, hardwood content, and drainage class, as well as the outbreak severity and length, determine the amount of tree mortality during budworm outbreaks. Silviculture and forest management can be used to reduce the incidence of the most damaged stand types across the landscape. The amount of defoliation in mixed balsam fir-hardwood stands is strongly negatively related to hardwood content, especially with hardwoods > 40%. The Spruce Budworm Decision Support System (DSS) links models of stand and forest response to budworm outbreaks and inventory interpretation to a GIS, and can be used to evaluate effects of outbreaks and management on forest structure and timber supply. An example using the Spruce Budworm DSS for a portion of the Fundy Model Forest indicated that losses from a future budworm outbreak could be reduced 34% by directing harvesting and silviculture towards conversion of one-half of the most vulnerable stand types into low susceptibility or non-susceptible species. Key words: decision support system, vulnerability, silviculture, insect damage

scholarly journals A Decision Support System for Integrated Tourism Development: Rethinking Tourism Policies and Management Strategies

2007 ◽  
Vol 9 (4) ◽  
pp. 387-404 ◽  
Author(s):  
Jean-Paul Bousset ◽  
Dimitris Skuras ◽  
Jan Těšitel ◽  
Jean-Bernard Marsat ◽  
Anastasia Petrou ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Management Strategies ◽  
Tourism Development

scholarly journals A Decision Support System for Sustainable Forest Management and Ecosystem Service Provisioning at the Enterprise Scale

2020 ◽  
Vol 3 (1) ◽  
pp. 83
Author(s):  
Timothy Thrippleton ◽  
Clemens Blattert ◽  
Reinhard Mey ◽  
Jürgen Zell ◽  
Esther Thürig ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Forest Management ◽  
Decision Support System ◽  
Support System ◽  
Ecosystem Service ◽  
Sustainable Forest Management ◽  
Management Strategies ◽  
Future Climate Change ◽  
Service Provisioning

Forest management is becoming increasingly complex due to increasing demands in ecosystem service provisioning and future climate change impacts. For a sustainable forest management, scientifically well-founded decision support is therefore urgently required. Within the project SessFor, a decision support system for strategic planning at the forest enterprise level is being developed, based on the climate sensitive forest model SwissStandSim and initialized from forest inventory data. The system is currently applied to the forest enterprise Wagenrain (440 ha), located in the Swiss Plateau region. Indicators for biodiversity and ecosystem service provisioning (timber production, recreation value and carbon sequestration) are calculated for different management strategies and evaluated using a multi-criteria decision analysis. Preliminary results demonstrate the suitability of the system to evaluate ecosystem service provisioning under different management strategies and to identify the best management strategy, based on criteria defined by the forest manager. Furthermore, results show how the system can be used to assess developments for time-scales of 50–100 years under different climate change scenarios. In the ongoing project, the system will be applied to other case study regions, including mountain forests, which are of key importance in Switzerland and other alpine areas.

WeedSOFT®: a weed management decision support system

Weed Science ◽  
2004 ◽  
Vol 52 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Christophe Neeser ◽  
J. Anita Dille ◽  
Gopal Krishnan ◽  
David A. Mortensen ◽  
Jeffery T. Rawlinson ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Weed Management ◽  
Management Strategies ◽  
Maximum Yield ◽  
Management Decision ◽  
Weed Species ◽  
Line Drawings ◽  
Selection Of

WeedSOFT® is a decision support system that was developed to help farmers and consultants in Nebraska with the selection of optimal weed management strategies. WeedSOFT® evolved from HERB, a bioeconomic model for soybean that was developed in North Carolina. The program is composed of four independent modules, namely, ADVISOR, EnviroFX, MapVIEW, and WeedVIEW. ADVISOR helps the user select a treatment based on maximum yield or maximum net gain. EnviroFX and MapVIEW provide environmentally relevant herbicide information and county soil maps that indicate vulnerability to groundwater contamination. WeedVIEW is a visual library of color images and line drawings of 46 common weed species. Over 500 farmers and consultants in Nebraska and adjacent states use WeedSOFT®. As a result of the current regionalization effort, the user base is expected to increase rapidly during the next 2 or 3 yr. This article explains the algorithms implemented in the current version of WeedSOFT®.

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