An Integrated Decision-Making Framework Towards Improved Water Management in Coastal Areas of Mountainous Watersheds

Abstract

The coastal zone is vital to littoral countries, as its natural resources provide life support and economic development opportunities. Land conservation goals and the preservation of coastal assets is achieved through the sustainability of land use planning and ecological integrity of these zones. In the context of agricultural lands and landscape conservation, the management and planning is dictated by farmers’ perception, response and decisions about adaptation facing the ongoing changes in the conditions of the watershed especially in the context of climate change. Understanding farmers’ behaviour is therefore indispensable for land conservation and sustainability. Despite advances in farmer’s behavior research, it remains challenging to understand, predict and manage. Given the complexity of farmers’ behavioral processes, agricultural lands are in need of a tool that models farmers’ perception, response and decisions with special consideration of the complexity of the systems incorporating socio-economic and ecological facets.

This research targets the Eastern Mediterranean coastal agricultural areas, highly vulnerable to climate change. It examines the main drivers of farmers’ behavioral and decision making processes, assessing the impacts of local anthropogenic activities and projected global climate change. The research appraises the spatial and temporal dynamics of farmers’ behavior integrating socio-psychological, economic and empirical modules, as the basis for understanding farmers’ decision making in response to climate change. It develops spatio-temporal Agent Based Models covering the three modules for farmers’ behaviour future predictions. This research further develops a hybrid Morkov Chain- Cellular Automata modelto evaluate the projected future landcover landuse, as well as a hydrologic model able to quantify the impacts of climate change on water resources availability in small mountanious mediterranean watersheds.

Results of the projected future water availability spatial distribution indicated a decrease in water availability with a mean of 24% between 2008 and 2032. The 2032 LCLU projection showed a significant increase in urban areas of reaching a 93% rate. Agricultural lands were also predicted to increase by an average of 11%. Agricultural and urban areas will be growing at the expense of forest and grasslands. Forests and grass lands will be reduced by 5 and 73%, respectively while barren lands will increase slightly (0.4%).

Results of the decisional models highlighted the significance of the integration of empirical, socio-psychological and economic modules with site-specific socio-cultural features on behavioral evaluation. Empirical-economic based ABM returned a 35% compatibility with the true response of farmers. The compatibility increased to 69% upon considering an exclusive socio-psychological model which when combined with socio-economic rules, conformity with the true response of the farmers reached 83%. By means of generating a stable representation of the drivers and logic lying behind farmers’ decisions, the constructed framework acts as an effective decision support tool to aid decision makers in land conservation planning and management.