ISLAMABAD: The Green Climate Fund (GCF) during its 14th board meeting, held in Republic of Korea on Friday, approved Pakistan’s $36 million Climate Change Adaptation project responding to glacial outburst in northern Pakistan.
The Ministry of Climate Change together with the UNDP had submitted this project for the board’s approval. An Indian board member attempted to reject Pakistan’s proposal, citing unsubstantiated technical reasons. However, the other 23 members, who considered the project fit for approval, rejected these claims and approved the project.
At the meeting, Pakistan was also able to effectively mitigate false perceptions that were being propagated by the Indian member.
The approved project will impact the lives of thousands of people who are living in constant danger of periodic glacial outbursts in the northern Pakistan.
The main project outputs include strengthened sub-national institutional capacities to plan and implement climate change-resilient development pathways, community-based early warning system (EWS) and long-term measures to increase communities’ adaptive capacity.
The project will address climate change impacts and Glacial Lake Outbursts Floods (GLOF) risks by preventing loss of lives and community infrastructure based on a holistic approach in all seven districts of Gilgit-Baltistan and five districts in Khyber Pakhtunkhwa (KP), thus contributing to a climate-resilient sustainable development.
The proposed project will benefit approximately 700,000 people on an average with 30 million indirect beneficiaries, of whom half are women and girls. The project thus will benefit about 15pc of the total population of Pakistan.
The project outcome will strengthen adaptive capacity and reduce exposure to climate risks posed by climate change impacts and the GLOF risks through increased technical capacity of provincial and line departments to integrate CC and GLOF risks into development plans, tools and budgets and by expanding the Pakistan Meteorological Department (PMD)’s Early Warning System (EWS) based on hydrological modelling and flood scenarios.
