Nature-based solutions (NBS) are actions that use natural processes in a resource efficient manner to solve societal challenges. The lack of supportive legislature, and financial, communication and social barriers complicate the process of NBS implementation. It is an urgent need to develop approaches to design and implement NBS that would act as drivers to overcome potential barriers and enhance the social acceptability of the project. The vision-based decision-making methodology and participatory process created in this study has been carried out in the Koiliaris Critical Zone Observatory in Crete to design erosion and flood protection NBS and restore the riparian forest. The methodology consists of four distinct steps as follows: i) develop a vision of the area, ii) conduct a baseline assessment study, iii) NBS design and co-design, and iv) procurement and implementation. The methodology overcame multiple barriers because of the effective stakeholder engagement and the vision “drove” the project and created the necessary consensus that is necessary to achieve the objective of converting privately owned prime agricultural land to riparian forest. It offers an exemplar of a functional ecosystem restoration project that protects the river in a sustainable way, improves its biodiversity and water quality and improves the quality of life and social cohesion.
Abstract. Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a statistical methodology is proposed to predict the probability of the presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the logistic regression methodology. It is developed in two forms, logistic regression and locally weighted logistic regression, which both deliver useful and accurate results. The second form, though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use and accurate and can be applied to any region and river.
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