Project

Community-based Integrated Natural Resources Management Project

Country

Country Flag Ethiopia

Sector

Agricultural Development

Approval Date

30 April 2009

Duration

2009 - 2018

Project ID

1100001424

The degradation of natural resources is a crucial issue in Ethiopia. The country loses some 2 billion tons of fertile soil annually as a result of land degradation. In particular, siltation of water bodies is a major threat to the development of irrigation.

The project targets the Lake Tana watershed in north-eastern Ethiopia. Its objectives are to enhance the access of poor rural people to natural resources such as land and water, and to introduce improved technologies for agricultural production, mainly through sustainable land management.

The project also establishes and strengthens community-based organizations, and promotes off-farm employment opportunities with the aim of relieving pressure on marginal lands. It is part of the Strategic Investment Programme for Sustainable Land Management in sub- Saharan Africa, coordinated by the Global Environment Facility (GEF).

Using participatory approaches, the project involves communities in decision-making processes so as to empower them, and builds on indigenous knowledge and institutions to promote sustainable land management. By improving farmers' land tenure security, it encourages them to invest in land improvement. Reduced siltation of water bodies creates opportunities for hydropower development. Conservation of biodiversity and improved ecosystem integrity are expected long-term benefits. Project activities are designed to:

Support implementation of about 650 watershed management plans;
Restore the productivity of a large area of degraded land;
Increase the productivity of agriculture, including forests and fisheries;
Improve food security and the incomes of people living within the Lake Tana watershed.

The project also aims to increase carbon sequestration, which should reduce greenhouse gas emissions and help mitigate climate change.

Additional Data