Assessment on irrigation system performance of sugarcane farm using remote sensing at lower Omo basin, Ethiopia

Abstract

This study was aimed at assessing the irrigation system performance at Omo Kuraz Sugar Cane Development Project using data from remote sensing and meteorological stations. To analyze the distribution of evapotranspiration over the treatment area, the SEBAL (Surface Energy Balance Algorithm) model was used to evaluate the evapotranspiration (ET) rate for sugarcane at the lower Omo River Basin. Surface energy balance algorithm input like NDVI, Land surface temperature, TOA albedo and emissivity was calculated from Land Lat 8 image using the ENVI software. The data were collected from the farm site meteorology station, and the calculated evapotranspiration rate was one of the inputs into irrigation system performance indicators model, along with actual field data gathered from irrigation delivery schedule, root depth of crop at each growth stage, soil moisture before and after irrigation, and water diverted to the field. The four pillars of irrigation system performance are over all consumed ratio, depleted fraction, evaporative fraction, and relative evapotranspiration. This study also examined system performance using four standard indicators; namely, adequacy, efficiency, reliability, and equity. These indicators were calculated using the SEBAL algorithm and data were classified based on satellite and irrigation application. The findings of this study revealed that the irrigation system performed poorly with all treatment fields being below the target performance indicator values (overall water consumption ratio, ep; depleted fraction, DF; evaporative fraction, ᴧ and relative evapotranspiration, RET). The calculated crop water requirements using the SEBAL model and satellite data were not consistent with applied water. The findings from this study also showed that irrigation system performance indicator parameters were limited due to excessive water applied to the field. The study also revealed an acceptable range of RET (0.8, 0.9); however, the irrigation system's reliability was poor according to the results of field observations at the experimental site. This observation was due to the field receiving an excessive amount of water. These results and observations suggest that the irrigation agronomist should schedule irrigation water application based on crop water requirements to manage poor irrigation system performance. Key words: Irrigation system performance, SEBAL model, Remote sensing, Landsat 8, lower Omo Basin