Wetland restoration prioritizing, a tool to reduce negative effects of drought; An application of multicriteria-spatial decision support system (MC-SDSS).

In recent years, large parts of arid and semi-arid areas in the world are dealing with water restrictions. In these areas, wetlands provide habitats for migratory birds and have a critical role in socio-ecological systems. Generally, in these areas, changing water-use patterns because of land-use change and water limitation because of climate change have led to the loss of wide areas of wetlands. Wetland restoration is suggested to restore the functions and values of wetlands that have been destroyed or affected by stresses. In this paper, a new application of wetland restoration prioritizing is introduced; restoration prioritizing to reduce the negative effects of drought. In this method, areas with the highest priority for restoration will be determined in a wetland destroyed because of water limitations. Multicriteria-spatial decision support system (MC-SDSS) was used to plan a scheme for Hamun wetlands restoration prioritizing in order to reduce the negative effects of drought and to restore the wetlands. This prioritization-determined areas that are valuable for Long-term water conservation, reduce the negative effects of dust storms and conserve water bird’s habitats. This method was used in a wetland that is the only water resource in the middle of a wide arid plain. Because of water limitation, it is not possible to restore the hole wetland; therefore, different parts of this wetland were prioritized for restoration. Based on the results, it is possible to produce a model to determine which priority can be restored in each amount of water volume. In this way, it becomes clear for decision-makers to select areas for restoration in different volumes of water. The result of this study shows that since MC-SDSS decreases conflicts between alternatives in a decision-making process and uses their spatial situation, it is a preferred method to balance among conflicting goals. Furthermore, because spatial data are the most important parts of MC-SDSS, this paper shows the ability of remote sensing to be used in MC-SDSS method. It seems that in the future; remote sensing will have the most important role in MC-SDSS. [ABSTRACT FROM AUTHOR]