Privacy Policy Disclaimer
  Advanced SearchBrowse





Climate risk analysis for adaptation planning in Uganda's agricultural sector: An assessment of maize and coffee value chains


von Loeben,  Sophie Charlotte
Potsdam Institute for Climate Impact Research;


Gornott,  Christoph
Potsdam Institute for Climate Impact Research;


Abigaba,  David
Potsdam Institute for Climate Impact Research;

Adriko,  John
External Organizations;

Awori,  Eres
External Organizations;

Cartsburg,  Matti
External Organizations;


Chemura,  Abel
Potsdam Institute for Climate Impact Research;


Cronauer,  Carla Catarina
Potsdam Institute for Climate Impact Research;

Lipka,  Naima
External Organizations;


Murken,  Lisa
Potsdam Institute for Climate Impact Research;


Muzafarova,  Albina
Potsdam Institute for Climate Impact Research;

Noleppa,  Steffen
External Organizations;


Romanovska,  Paula
Potsdam Institute for Climate Impact Research;


Tomalka,  Julia
Potsdam Institute for Climate Impact Research;


Weituschat,  Chiara Sophia
Potsdam Institute for Climate Impact Research;


Zvolsky,  Antonia
Potsdam Institute for Climate Impact Research;

External Ressource
No external resources are shared
Fulltext (public)

(Publisher version), 26MB

Supplementary Material (public)
There is no public supplementary material available

von Loeben, S. C., Gornott, C., Abigaba, D., Adriko, J., Awori, E., Cartsburg, M., Chemura, A., Cronauer, C. C., Lipka, N., Murken, L., Muzafarova, A., Noleppa, S., Romanovska, P., Tomalka, J., Weituschat, C. S., Zvolsky, A. (2023): Climate risk analysis for adaptation planning in Uganda's agricultural sector: An assessment of maize and coffee value chains, Potsdam : A report prepared by the Potsdam Institute for Climate Impact Research (PIK) in cooperation with the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ), 73 p.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_28791
Climate change increasingly affects the productivity of Uganda’s agricultural sector, with droughts and precipitation variability challenging livelihoods as well as the economic prospects of entire value chains. The country’s national policies and plans on climate change and agriculture recognise that investing in effective adaptation is key to mitigating climate risks. Yet, limited information on current and projected climate impacts on the different steps of agricultural value chains is available on which sound adaptation decisions can be based. This study aims to address this gap by providing a comprehensive climate risk analysis for two selected agricultural value chains: maize, a major food crop, and coffee (Robusta and Arabica), a major export crop. Based on ten global climate models (GCMs), we project how temperature and precipitation is expected to change under two greenhouse gas (GHG) emissions scenarios (SSP1- RCP2.6 low emissions scenario and SSP3-RCP7.0 high emissions scenario) and how these impacts might affect maize and coffee production. In addition, interviews with key actors involved in post-harvest activities (including aggregation, processing, marketing and distribution) have been conducted, to better understand how climate change affects later stages of the value chains. Based on the projected impact analysis as well as on a participatory process with various stakeholders in Uganda, four adaptation strategies were selected for our analysis: improved maize varieties, improved maize storage, agroforestry systems for coffee production and improved coffee storage. As part of our adaptation analysis, we consider aspects of risk mitigation potential, cost-effectiveness and gender. The results have been complemented and cross-checked by expert- and literature-based assessments and two stakeholder workshops. The results of this climate risk analysis show that, in response to increasing GHG concentrations, temperatures in Uganda will increase by 1.1 °C under the low emissions scenario (SSP1-RCP2.6) and by 1.5 °C under the high emissions scenario (SSP3-RCP7.0) by 2050, compared to 2004. The number of hot days and hot nights are projected to steadily increase, with severe temperature extremes especially in the north of Uganda. The majority of models project slight future increases of annual precipitation, but precipitation projections are subjected to high model uncertainties. Climatic conditions also substantially affect crop production in Uganda. The projected changes translate into modelled maize yield losses of up to 26.8 % by the end of the century, especially in high maize potential areas such as parts of the Central and Eastern regions, as well as in shifts and reductions in suitability of land to grow coffee. Arabica coffee is particularly affected with projected suitability losses of up to 20 % until 2050. Robusta suitability will only slightly, but progressively, reduce with time with higher losses expected under the high emissions scenario (SSP3-RCP7.0) of up to 5 %. Climate impacts are also felt at later stages of the value chain, significantly affecting post-harvest products, activities and finances, as well as the overall composition of the value chain. The analyses of the four adaptation strategies show that improved maize varieties and agroforestry for coffee production are examples of promising agricultural practices, both in terms of their potential to buffer projected losses due to climate change, but also in terms of cost efficiency. Beyond that, improved storage is a cost-efficient approach for both, maize and coffee, to reduce post-harvest losses and secure the products’ quality. Implementation of these strategies should take farmer types and their local context into consideration and be seen as part of broader resilience-building strategies. Aspects of inequality, such as gender and land tenure, should feed into the design of adaptation strategies. Generally, taking dynamics of the broader value chain into consideration will help to ensure the feasibility and long-term successful uptake of adaptation strategies.