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• W3179033927 startingPage "113169" @default.
• W3179033927 abstract "To mitigate the negative effects of land use developments, the current study focused on the hydrological connectivity within the landscape ecological network of Gharesou watershed, Iran, using Graph theory. Thus, scenarios of the future land use arrangements were used for the objective assessment of the effects of patterns on the ecological structures and functions, the main target being runoff control. Hydrological connectivity was analyzed using runoff source network, stream network and its buffer zone. Also, functions like permeability and runoff production potential were analyzed for the future scenarios. Following the ranking of the connectivity significance of the hydrological graphs elements, the ecosystem services hotspots and incompatible land uses were demonstrated. Subsequent assessments of the elements of runoff source networks using Circuit Theory helped identify the future critical areas. Analyses of the hydrological graphs and the runoff source network represented the amount and location of critical areas in each development scenario as well as the imposed hydrological costs. The hydrological and ecological land use costs were used in the process of land use optimization through Simulating Annealing algorithm (SA). Using these costs in the land use planning process resulted in detecting areas which may experience disturbance later in future. Finally, the results of the optimization of scenarios showed how land use arrangements in each scenario can be optimized to simultaneously include the ecological suitability (vertical relationships) and the ecological network relationships (horizontal relationships)." @default.
• W3179033927 created "2021-07-19" @default.
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• W3179033927 date "2021-10-01" @default.
• W3179033927 modified "2023-10-17" @default.
• W3179033927 title "Hydrological connectivity assessment of landscape ecological network to mitigate development impacts" @default.
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• W3179033927 doi "https://doi.org/10.1016/j.jenvman.2021.113169" @default.
• W3179033927 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34256293" @default.
• W3179033927 hasPublicationYear "2021" @default.
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