- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
The role of forests in regulating landslide risks is well established but estimates of the economic value of this ecosystem service are limited. In order to incorporate the role of forests for landslide risk mitigation in spatial planning and other decision-making contexts, there is a need for spatially explicit information regarding the value of this service. We develop a methodological framework to combine bio-physical modelling of natural hazard risk and socio-economic exposure in a predictive model to estimate and map of the economic value of forest regulation of landslides. This method is applied in a case study of Adjara Autonomous Republic of Georgia to examine alternative scenarios for forest management and associated land cover change. The approach produces credible spatially explicit results to inform policy decisions regarding investment in forest management; and has the potential for replication in other data scarce regions.
In this paper we develop and apply a method for estimating spatially explicit economic values for the role of forests in regulating the occurrence of landslides. The approach combines available data and models on land cover, sediment export, population, landslide frequency and compensation payments to predict how the value of landslide damage is likely to change under alternative future scenarios for forest management. The approach is illustrated in a case study of Adjara Autonomous Republic of Georgia and shown to produce somewhat conservative estimates of historic landslide damage. The case study results were presented at a workshop in Batumi, Adjara, for stakeholders including the Directorate for Environmental Protection and Natural Resources, Adjara Forest Agency, other ministries of Adjara, representatives of the NGO sector and individual experts. The workshop provided an opportunity to validate the results and begin the process of applying the information to support decision making. The workshop participants judged the scenarios, predicted changes in landslide risk and associated changes in damage costs to be credible and highly useful for developing investments in forest management.