Sustainable Land Management II

Ethiopia
KfW, 2016 - 2019

As Ethiopia is undoubtedly one of the Sub-Saharan Africa countries most seriously affected by land degradation, which is a major cause of the country’s low and declining agricultural productivity, the project’s approach focuses on integrated and participatory watershed development and management at the grass root level. Under the umbrella of its Strategic Investment Framework (ESIF), the Ethiopian government has been operating the Sustainable Land Management Programme (SLMP) with various aspects covered by different donors and coordinated by the Ministry of Agriculture and Natural Resources (MoANR).

GFA is now implemented the KfW-financed Sustainable Land Management II with the ultimate objectives are to reduce land degradation and increase productivity in order to decrease food insecurity and increase economic benefits for the population. In 2011, the Ethiopian and the German governments signed an agreement to support the implementation in 23 woredas through financial and technical assistance.

GFA B.I.S. Services

GFA B.I.S. was commissioned by GFA Consulting Group to implement an suitable Monitoring & Evaluation System for the management of project outcomes, named DACOTA.

Monitoring data is regularly collected with Survey Solutions at project sites by field workers and later imported into a central monitoring database, including imports of attached binary data such as photos taken on-site. Imports happen automatically after a data set has been ultimately approved in Survey Solutions’ Headquarters application. After an import, project staff are notified by e-mail on the success or failure status of the operation. A web-based application allows direct access to the data, potentially including the ability to modify the data. This web-based application may also provide a map view and dashboard, depending on the needs of the project team. The user interface (UI) is built following Google’s Material Design specification.

Finally, a reporting application enables in-depth analyses of the data in the monitoring database. A limited number of standard reports will be defined that can be parametrized to enable different disaggregations and filtering of the data.