Identification of optimum afforestation areas considering sustainable management of natural resources, using geo-environmental criteria

Fereshteh Kordrostami, Pedram Attarod, Karim C. Abbaspour, Ralf Ludwig, Vahid Etemad, Hossein Alilou, Omid Bozorg-Haddad

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Conservation of natural resources is vital for sustainable management, especially in fragile semi-arid ecosystems. Forest plantations can provide a wide range of ecosystem services and deliver a measure of protection for soil and water resources. This study proposes a novel framework (Optimum Land Suitability Score, OLSS) to prioritize the most suitable areas with high priority for restoring degraded lands and protecting erosion-prone areas. We applied OLSS to the Latian watershed located in Tehran, Iran. The Latian watershed was divided into 56 sub-basins, where we studied the importance of each sub-basin for afforestation. We used a multicriteria analysis using the Fuzzy Analytical Network Process to bridge the gap between previous studies for determining suitable areas for afforestation in which 21 factors of environmental variables, morphometric characteristics, and topographical indices were considered. Finally, sub-basins were divided into four classes based on the fuzzy theory. The evaluated result indicated that 9 sub-basins showed the highest priority for afforestation. The identified sub-basins were mostly located in areas of depleted plant coverage due to overgrazing and human interventions. We proposed afforestation with proper species adapted to the environmental characteristics of prioritized sub-basins as ecological management. The measure should decrease erosion and flood risk and sustain the Latian reservoir storage capacity. OLSS offers valuable information for watershed managers and decision-makers to invest in soil conservations.

Original languageEnglish
Article number106259
JournalEcological Engineering
Volume168
DOIs
Publication statusPublished - 1 Oct 2021

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