On the use of data and models in geosciences for assessing the vulnerability of rainfed agriculture in Ethiopia

Data and models in geosciences can provide a fundamental contribution to sustainable land use, especially where current and future climate stress is an issue. Here we focus on rainfed agriculture as a concrete example where geoscientific knowledge about climate and soils can inform sustainable development. Questions such as when does the rainfall season start, how much rain and crop yield can we expect, how will this change in the future, become critical for subsistence farmers under rainfed agriculture. Here we argue that new large scale climate datasets combined with soil-plant-atmosphere models can provide answers that can be translated into local recommendations and actions. We illustrate the first part of this chain on an example of key cereal crops (teff, maize, sorghum, wheat) in Ethiopia, where more than 90% of production is rainfed – by using publicly-available gridded global datasets of precipitation and air temperature, soil and landcover, by employing hydrological modelling of soil moisture and rainwater productivity, and exploiting climate change projections into the future. This geoscience data-modelling toolbox is used among others to estimate the potential crop losses sustained by a delay in the onset of the rainy season, and to map out the suitable production areas for the key crops today and in the future. The next challenge is to translate such information for stakeholders into actions that can reduce their vulnerability. We believe that current data and models in geosciences open up yet underutilized opportunities to achieve this goal.

The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)