Sustainable Asset Valuation of Climate-Resilient Landscapes in Ghana

The Nature-Based Infrastructure Global Resource Centre is collaborating with the United Nations Environment Programme (UNEP) and local stakeholders in Ghana to analyze potential nature-based infrastructure (NBI) and hybrid scenarios totalling 12,000 hectares across four districts: Lambussie, Wa West, Lawra, and Jirapa. The performance of these options is analyzed under three climate scenarios (Shared Socioeconomic Pathways [SSP] SSP1, SSP3, and SSP5).

In this report, we assess the following scenarios:

• Reference scenario, representing the baseline of no action taken to address challenges related to extreme weather events. In this scenario, increased encroachment of riverbanks, higher occurrences of flash floods, significant loss of crops, and damage to infrastructure due to inadequate preparedness are expected.
• NBI scenario, consisting of reforestation, restoration of riparian buffer zones, agroforestry, and climate-smart agriculture to restore natural ecosystems, improve land management practices, and enhance the resilience of agricultural systems to a changing climate.
• Hybrid infrastructure scenario, consisting of the above nature-based solutions, plus implementation of irrigation systems and traditional “grey” water storage systems, to address water scarcity and improve agricultural water management.

Our assessment found that NBI and hybrid interventions are effective investments for mitigating the impacts of extreme weather events in Ghana. Under all climate scenarios, NBI and hybrid interventions have synergies in tackling both floods and droughts effectively, offering risk mitigation options to communities impacted by climate change. Interestingly, our assessment shows that for avoided costs from floods, an SSP5 scenario is not as damaging as SSP3, demonstrating the nuances of climate change and identifying the most effective NBI solution for the problem. For example, expanding this ambition to a 3,500-hectare area for reforestation in one modelled district resulted in a substantial 46.7% reduction in flood risk.