Spatial and temporal analysis in land and water productivity using WaPOR data. A case study of the sugarcane plantations of Metahara, Ethiopia

Abstract

The Ethiopian government faces a challenge in which they aim to increase the yields of the sugarcane fields of Metahara, while decreasing the water consumption. Hence, this research analyzed the spatial and temporal distribution of land and biomass water productivity in Metahara. WaPOR data covering 2009-2021 was used to analyze five irrigation scheme performance indicators: i) land and water productivity, ii) productivity gaps, iii) water consumption, iv) uniformity, and v) adequacy. The WaPOR data was compared to ground-level data for validation. Stakeholders were consulted to understand the results and the results of the WaPOR data were compared to two other variables: soil texture and the influence of the saltwater of Lake Basaka.

The temporal results from this research revealed that water productivity decreased over time, and that droughts explained partly for temporal variations. Furthermore, biomass did not increase, and water consumption ncreased instead of decreased over time. Due to soil compaction and the related decreased infiltration capacity, more water is applied while not more water reaches the crops. Spatial variation in land and water productivity was related to the influence of Lake Basaka. Fields closer to Lake Basaka had lower productivity. More compacted and finer soil textures had a higher water consumption, better uniformity, and higher adequacy. Soil texture did not explain for spatial land and water productivity variation but did explain for temporal variations. Also, fields with a higher water consumption had an overall higher biomass production. Concluding, spatial and temporal distribution in water productivity related to the influence of Lake Basaka, soil texture, and droughts.

This research contributes to the wider scope of knowledge in remote sensing-based data because it has proven that on-the-ground knowledge is needed to explain for varieties in time and space shown by remote sensing data. Some findings in spatial land and water productivity could only be declared with stakeholder knowledge. Nevertheless, the remote sensing-based research is valuable, and the future potential is high.