Agricultural Resilience and the Shift to Solar Power

In this perspective, we examine the transition toward Solar-Powered Irrigation Systems (SPIS) as a critical strategy for intensifying and diversifying agriculture in Baringo County, Kenya. Agriculture remains the backbone of the local economy, employing over 40% of the population and contributing 33% to the national GDP. However, the sector is highly vulnerable to erratic rainfall and recurrent droughts that characterize the region's Arid and Semi-Arid Lands (ASALs). The sources argue that building resilience requires a shift away from traditional, rain-fed practices toward sustainable, clean-energy solutions like SPIS to reduce the reliance on expensive and environmentally costly fuel-based pumping.

Advanced Geospatial Frameworks for Site Selection

To address the complexity of identifying optimal locations for such infrastructure, researchers utilized an integrated GIS and Multi-Criteria Decision Analysis (MCDA) approach. The study combined five key thematic layers: solar radiation, precipitation, slope, proximity to rivers, and existing irrigation areas. These variables were processed using Saaty’s Analytical Hierarchy Process (AHP) to assign relative weights based on their importance to irrigation success. A key component of this methodology was the use of Weighted Linear Combination (WLC) to derive suitability classes at a high spatial resolution, accounting for both the local topography and the availability of natural resources.

Spatial Patterns of SPIS Suitability in Baringo

The modeling results show that SPIS suitability follows distinct ecological and climatic gradients across the county. Approximately 58% of the land area is classified as moderately suitable, while 24% demonstrates high suitability. High-potential “hotspots” were identified in the southern and western regions, particularly along the stretch from Eldama Ravine to the Kerio Valley fringe. These areas benefit from optimal solar radiation and closer proximity to reliable water sources. Conversely, the arid northeastern Tiaty region showed very low suitability, as it lacks both the water resources and the agricultural history necessary for SPIS adoption.

Multidimensional Vulnerability and Adoption Barriers

The study highlights that physical hazard or potential must be distinguished from a population’s actual capacity to adopt new technology. Suitability is conceptualized as a multidimensional condition: socioeconomic barriers are determined by a lack of technical know-how for installation and maintenance, as well as low financial resources among smallholder farmers. In contrast, physical constraints are defined by functional territorial factors such as steep slopes and excessive distances from water sources. The research indicates that while large sections of the county are biophysically suitable, actual resilience depends on overcoming these combined structural and social constraints.

A Research-Driven Path Toward Sustainable Intensification

Ultimately, the study concludes that strengthening resilience in Baringo County requires policy measures that prioritize investments in clean energy, protect water infrastructure, and align agricultural growth with data-driven adaptation strategies. This research showcases the academic contributions of the Centre for Climate Resilience at the University of Augsburg, where researchers like Harison Kipkulei apply advanced geospatial tools to address overwhelming climate risks. Their involvement underscores a commitment to developing practical, data-driven solutions that improve food security and the survival chances of the world's most vulnerable populations.

Source: Kipkulei, H. K., Boitt, M., Ahmed, A., Lameck, A. S., Uckert, G., Moisa, M. B., & Rotich, B. (2026): Mapping suitability for solar-powered irrigation systems using GIS–AHP in Baringo County, Kenya. Discover Geoscience 4, 161.