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Lookup NU author(s): Professor Claire Walsh
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023, The Author(s).Evaluation of the hydrological impact of urbanization-induced land use land cover (LULC) changes for medium to large catchments is still an important research topic due to the lack of evidence to conclude about how local changes translate to impacts across scales. This study aims to provide evidence on the effects of LULC change on the streamflow of the Akaki catchment that hosts Addis Ababa, the capital city of Ethiopia. Since the comparative performance of classification algorithms is poorly understood, we compared the performance of one parametric and five non-parametric machine learning methods for LULC mapping using Landsat imageries. To investigate the effect of LULC changes on streamflow, a semi-distributed HEC-HMS model was calibrated and validated using daily discharge data at multiple sites. Findings of this study showed that: (i) the accuracy of classification and regression tree (CART) was superior to the other classifiers, (ii) from 1990 to 2020, urban and forest cover increased at the expense of agricultural and bare land, (iii) the performance of the HEC-HMS model was acceptable at all stations during both the calibration and validation periods, and (iv) the mean annual and main rainy seasonal streamflow of the catchment experienced significant increases due to LULC change but the simulated streamflow changes highly varied with the type of LULC classifier. This study contributes to the limited evidence on how catchments, with rapidly developing cities are prone to hydrological regime changes that need to be recognized, understood and quantified, and incorporated into urban planning and development.
Author(s): Negash ED, Asfaw W, Walsh CL, Mengistie GK, Haile AT
Publication type: Article
Publication status: Published
Journal: Sustainable Water Resources Management
Year: 2023
Volume: 9
Issue: 3
Print publication date: 01/06/2023
Online publication date: 25/04/2023
Acceptance date: 28/02/2023
Date deposited: 16/05/2023
ISSN (print): 2363-5037
ISSN (electronic): 2363-5045
Publisher: Springer Science and Business Media Deutschland GmbH
URL: https://doi.org/10.1007/s40899-023-00831-4
DOI: 10.1007/s40899-023-00831-4
Data Access Statement: Data cannot be made publicly available; however the readers can contact the corresponding author for details.
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