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The purpose of this paper is to investigate the patterns and trends of drought incidence in north east highlands of Ethiopia using monthly rainfall record for the period 1984-2014.

Standard precipitation index and Mann – Kendal test were used to analyze drought incident and trends of drought occurrences, respectively. The spatial extent of droughts in the study area has been interpolated by inverse distance weighted method using the spatial analyst tool of ArcGIS.

Most of the studied stations experienced drought episodes in 1984, 1987/1988, 1992/1993, 1999, 2003/2004 and 2007/2008 which were among the worst drought years in the history of Ethiopia. The year 1984 was the most drastic and distinct-wide extreme drought episode in all studied stations. The Mann–Kendal test shows an increasing tendencies of drought at three-month (spring) timescale at all stations though significant (p < 0.05) only at Mekaneselam and decreasing tendencies at three-month (summer) and 12-month timescales at all stations. The frequency of total drought was the highest in central and north parts of the region in all study seasons.

This detail drought characterization can be used as bench mark to take comprehensive drought management measures such as early warning system, preparation and contingency planning, climate change adaptation programs.

The recently released fifth IPCC report indicates a high agreement among global actors on the need to integrate climate change adaptation (CCA) and disaster risk reduction (DRR). However, there remains little local level evidence on how DRR and CCA could be linked, the sorts of adjustments that are required for the two concepts to be integrated and the challenges ahead. This paper aims to provide an empirical insight on the possible links and departures between DRR and CCA.

The study used a qualitative case study approach to excavate lessons from an existing DRR intervention for CCA using a local-level adaptive capacity assessment framework as a normative criteria. Data was collected both from primary and secondary sources. The primary data collection involved the use of participatory rural appraisal techniques with village communities in Chifra District, Afar Regional State, Ethiopia.

The findings showed that the DRR interventions studied addressed parts of the elements of adaptive capacity at the local level. The findings also showed the limitation of the DRR intervention, which could be attributed to both the nature of the DRR interventions in general and implementation problems of the case study intervention in particular. The limitations show cases where full integration of DRR with CCA could be challenging.

The paper argues why the two approaches may not be integrated fully and also shows the need to focus on the design of DRR interventions in achieving both short-term (reducing disaster risks) and long-term objectives (enhancing adaptive capacity).

The purpose of this study is to examine the biophysical and socioeconomic impacts of climate change on maize production and food security in sub-Saharan Africa (SSA) using adapted improved maize varieties and well-calibrated and validated bioeconomic models.

Using the past climate (1950-2000) as a baseline, the study estimated the biophysical impacts of climate change in 2050 (2040-2069) and 2080 (2070-2099) under the A1B emission scenario and three nitrogen levels, and the socioeconomic impacts in 2050.

Climate change will affect maize yields across SSA in 2050 and 2080, and the extent of the impact at a given period will vary considerably between input levels, regions and maize mega environments (MMEs). Greater relative yield reductions may occur under medium and high-input intensification than under low intensification, in Western and Southern Africa than in Eastern and Central Africa and in lowland and dry mid-altitude than in highland and wet mid-altitude MMEs. Climate change may worsen food insecurity in SSA in 2050 through its negative impact on maize consumption and reduction in daily calorie intake. However, international trade has the potential to offset some of the negative impacts.

The study calibrated and applied bioeconomic models to estimate the biophysical and socioeconomic impact of climate change on maize production at fine resolution. The results could be used as a baseline to evaluate measures that will be applied to adapt maize to the future climate in SSA.