Abstract

Background: The water hyacinth (Eichhornia crassipes) is often regarded as the world’s most notorious invasive species. In Southern Eastern Ethiopia, lake Koka has serious problems related to the alien water hyacinth invasive weed. This study aimed to examine the spatial-temporal pattern of water hyacinth and it’s dynamic with seasonal variability and the nutrient (nitrogen and phosphorus) content of lake Koka. The area of water hyacinth and surface area of the lake were mapped using Landsat 7 ETM+ and Landsat 8O LI image data from the years 2013, 2017 and 2021 and Sentinel-2 MS I image data of 2017-2021. The amount total nitrogen was determined by TNT persulfate digestion method and total phosphorus by molybdovanadate method.

Result: The annual coverage areas of water hyacinth increased by 328.89% from 45.74 ha in 2013 to 21.23 ha in 2021 over the last nine years. The annual maximum lake surface area was 164.63 km2 occurred in 2017 and the minimum was 77.38 in 2021 km2. Seasonal spatial-temporal dynamics of water hyacinth in lake Koka exhibit a periodic cyclical pattern, the mean percentage seasonal land uses of water hyacinth are the maximum on spring 2.99%, followed by summer 2.10%, then 1.25 % in winter and the list is on the autumn 0.57%. Total Nitrogen was average ranging from 5.6 mg/L-16.5 mg/L However, the concentration varied from site to site with the highest concentration site of draining the wet season average value of 13 mg/L-19 mg/L. Total phosphorus was average ranged from <.001 mg/L-0.85 mg/L. However, the concentration varied from site to site with the highest concentration site of draining the wet season with average value of 1 mg/L-1.3 mg/L.

Conclusion: In general, the significantly increasing spatial coverage of water hyacinth on lake Koka in the last 9 years and impearled with water quality degradation, however, the management and control almost nil wards to the weed infestation. Therefore, a holistic approach, effective and sustainable management strategy and action must be implemented to stop the spread of water hyacinth on Lake Koka.

Keywords: Water hyacinth; Lake Koka; Remote sensing; GIS; Image classification