Seagrass is crucial to ecosystems and economies worldwide. To address the current decline in seagrass populations and promote additional sources of blue carbon, restoration efforts have been implemented in Thailand. Seagrass conditions are influenced by both human activities and natural factors, making it essential to consider both when selecting restoration sites to increase success. In this study, we developed a GIS-based model called the "Suitable Seagrass Restoration Site Selection Model (2SR2SM)". The model combines satellite remote sensing data, in-situ measurements, and a 3D hydrodynamic model, and was applied to a study site in southwestern Thailand (lower Andaman), the country's most important seagrass habitat. The model also takes into account local hydrodynamic conditions affected by climate variability, including El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Preliminary results suggest that the newly developed 2SR2SM can effectively identify different classes of suitable areas for seagrass restoration, with suitability varying both spatially and temporally, and significantly influenced by water temperature and water levels. Therefore, the 2SR2SM offers an effective tool for dynamic planning and management of seagrass conservation and restoration. It can also pinpoint areas of seagrass that are less vulnerable to changes driven by ENSO and IOD, making it an effective resource site for sustainable restoration efforts.
 

Seagrass restoration,Suitable sit selection model,Climate variabilities,ENSO,IOD