Semiarid Tunisia is characterized by agricultural production that is delimited by water availability and degraded soil. This situation is exacerbated by human pressure and the negative effects of climate change. To improve the knowledge of long-term (1980 to 2020) drivers for Land Use and Land Cover (LULC) changes, we investigated the semiarid Rihana region in central Tunisia. A new approach involving Google Earth Engine (GEE) was used to map LULC using Landsat imagery and vegetative indices (NDVI, MSAVI, and EVI) by applying a Random Forest (RF) classifier. A Rapid Participatory Systemic Diagnosis (RPSD) was used to consider the relation between LULC changes and their key drivers. The methodology relied on interviews with the local population and experts. Focus groups were conducted with practicians of the Regueb Agricultural Extension Services, followed by semi-structured interviews with 52 households. Results showed the following: (1) the RF classifier in Google Earth Engine had strong performance across diverse Landsat image types resulting in overall classification accuracy of ≥0.96 and a kappa coefficient ≥0.93; (2) rainfed olive land increased four times during the study period while irrigated agriculture increased substantially during the last decade; rangeland and rainfed annual crops decreased by 58 and 88%, respectively, between 1980 and 2021; (3) drivers of LULC changes are predominately local in nature, including topography, local climate, hydrology, strategies of household, effects of the 2010 revolution, associated increasing demand for natural resources, agricultural policy, population growth, high cost of agricultural input, and economic opportunities. To summarize, changes in LULC in Rihana are an adaptive response to these various factors. The findings are important to better understand ways towards sustainable management of natural resources in arid and semiarid regions as well as efficient methods to study these processes.

Climate change represents today one of the most pressing environmental and socio-economic challenges facing humanity. However, its effect is uneven across regions, affecting most severely those whose populations depend directly on natural resources for their livelihood. Many studies have assessed climate vulnerability at national and regional levels, but there remains a lack of detailed analysis of how vulnerability manifests in rural areas and how it varies across local contexts, particularly in rural territories such as those in Tunisia. To address this gap, we investigate the vulnerability of local population to climate change in Rihana, a small rural territory in Sidi Bouzid governorate (Central Tunisia), through two complementary approaches. The first is a qualitative approach based on a participatory territorial diagnosis to assess the perception of climate change, current and future vulnerability; while the second is a quantitative approach based on the Climate Change vulnerability index_Intergovernmental Panel on Climate Change (LVI-IPCC). This methodology involves a comparative study of two Homogeneous Territorial Units (HTU) located upstream (HTU2) and downstream (HTU1) of the study area. The use of both qualitative and quantitative approaches provides a more comprehensive understanding of vulnerability, unlike other studies that limit themselves to a single approach and may therefore overlook certain crucial aspects. The results reveal that the local population in the study area perceives climate change as a threat to its main resources, particularly changes in rainfall and temperature patterns, drought and floods. Moreover, vulnerability levels vary significantly between the two areas, mainly due to differences in geographical position. The upstream part is more vulnerable (LVI-IPCC = 0.14), being more sensitive, more exposed and with a lower capacity to adapt, while the downstream part is less vulnerable (LVI-IPCC = 0.03). The results also show that households anticipate an increase in future vulnerability, with intensified soil erosion, declining rain-fed crops, growing water scarcity, and a heightened risk of rural exodus. Finally, this study confirms that even at small local scale vulnerability levels vary significantly so it’s important to integrate local knowledge with scientific tools when analyzing vulnerability at the local level. Based on these findings, the study emphasizes the use of a territorial approach and the active involvement of local communities. Such engagement enhances the resilience of rural populations and facilitates the development of effective adaptation strategies, while providing valuable insights for future research on climate.

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