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Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia

Author

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  • Selamawit Haftu Gebresellase

    (College of Hydrology and Water Resources Engineering, Hohai University, Nanjing 210098, China)

  • Zhiyong Wu

    (College of Hydrology and Water Resources Engineering, Hohai University, Nanjing 210098, China)

  • Huating Xu

    (College of Hydrology and Water Resources Engineering, Hohai University, Nanjing 210098, China
    Shanghai Investigation, Design & Institute Co., Ltd., Shanghai 200434, China)

  • Wada Idris Muhammad

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China)

Abstract

Understanding the spatiotemporal changes in land use and land cover (LULC) in the watershed is crucial for maintaining the sustainability of land resources. This study intents to understand the historical (1972–2015) and future (2030–2060) spatiotemporal distribution of LULC changes in the Upper Awash Basin (UAB). The supervised Maximum Likelihood Classifier technique (MLC) was implemented for historical LULC classification. The Cellular Automata-Markov (CA–Markov) model was employed to project two scenarios of LULC, ‘business-as-usual’ (BAU) and ‘governance’ (Gov). Results from the historical LULC of the study area show that urban and cropland areas increased from 52.53 km 2 (0.45%) to 354.14 km 2 (3.01%) and 6040.75 km 2 (51.25%) to 8472.45 km 2 (71.97%), respectively. Whereas grassland, shrubland, and water bodies shrunk from 2052.08 km 2 (17.41%) to 447.63 km 2 (3.80%), 2462.99 km 2 (20.89%) to 1399.49 km 2 (11.89%) and 204.87 km 2 (1.74%) to 152.44 km 2 (1.29%), respectively, from 1972 to 2015. The historical LULC results indicated that the forest area was highly vulnerable and occupied by urban and cropland areas. The projected LULC under the BAU scenario shows substantial cropland and urban area expansion, increasing from 8472.45 km 2 (71.97%) in 2015 to 9159.21 km 2 (77.71%) in 2060 and 354.14 km 2 (3.1%) in 2015, 1196.78 km 2 (10.15%) in 2060, respectively, at the expense of vegetation cover. These results provide insight intothe LULC changes in the area, thus requiring urgent attention by watershed managers, policymakers, and stakeholders to provide sustainable practices for the UAB. Meanwhile, the Gov scenario indicates an increase in vegetable covers and a decrease in cropland, encouraging sustainable development compared to the BAU scenario.

Suggested Citation

  • Selamawit Haftu Gebresellase & Zhiyong Wu & Huating Xu & Wada Idris Muhammad, 2023. "Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1683-:d:1036947
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    1. Nij Tontisirin & Sutee Anantsuksomsri, 2021. "Economic Development Policies and Land Use Changes in Thailand: From the Eastern Seaboard to the Eastern Economic Corridor," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    2. Yang, Xin & Zheng, Xin-Qi & Lv, Li-Na, 2012. "A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata," Ecological Modelling, Elsevier, vol. 233(C), pages 11-19.
    3. Mansour, Shawky & Al-Belushi, Mohammed & Al-Awadhi, Talal, 2020. "Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques," Land Use Policy, Elsevier, vol. 91(C).
    4. Girum Ayalneh Tiruye & Abreham Tesfaye Besha & Yedilfana Setarge Mekonnen & Natei Ermias Benti & Gebrehiwet Abrham Gebreslase & Ramato Ashu Tufa, 2021. "Opportunities and Challenges of Renewable Energy Production in Ethiopia," Sustainability, MDPI, vol. 13(18), pages 1-25, September.
    5. Liu, Xiaoping & Ou, Jinpei & Li, Xia & Ai, Bin, 2013. "Combining system dynamics and hybrid particle swarm optimization for land use allocation," Ecological Modelling, Elsevier, vol. 257(C), pages 11-24.
    6. Abera Assefa Biratu & Bobe Bedadi & Solomon Gebreyohannis Gebrehiwot & Assefa M. Melesse & Tilahun Hordofa Nebi & Wuletawu Abera & Lulseged Tamene & Anthony Egeru, 2022. "Impact of Landscape Management Scenarios on Ecosystem Service Values in Central Ethiopia," Land, MDPI, vol. 11(8), pages 1-16, August.
    7. Motuma Shiferaw Regasa & Michael Nones & Dereje Adeba, 2021. "A Review on Land Use and Land Cover Change in Ethiopian Basins," Land, MDPI, vol. 10(6), pages 1-18, June.
    8. Ruci Wang & Hao Hou & Yuji Murayama, 2018. "Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    9. Markos Mathewos & Semaria Moga Lencha & Misgena Tsegaye, 2022. "Land Use and Land Cover Change Assessment and Future Predictions in the Matenchose Watershed, Rift Valley Basin, Using CA-Markov Simulation," Land, MDPI, vol. 11(10), pages 1-28, September.
    10. Zhipeng Lai & Chengjing Chen & Jianguo Chen & Zhuo Wu & Fang Wang & Shaoying Li, 2022. "Multi-Scenario Simulation of Land-Use Change and Delineation of Urban Growth Boundaries in County Area: A Case Study of Xinxing County, Guangdong Province," Land, MDPI, vol. 11(9), pages 1-18, September.
    11. Rahel Hamad & Heiko Balzter & Kamal Kolo, 2018. "Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    12. Maryam Mehmood & Ahsan Shahzad & Bushra Zafar & Amsa Shabbir & Nouman Ali & Afaq Ahmad, 2022. "Remote Sensing Image Classification: A Comprehensive Review and Applications," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-24, August.
    13. Ge Shi & Nan Jiang & Lianqiu Yao, 2018. "Land Use and Cover Change during the Rapid Economic Growth Period from 1990 to 2010: A Case Study of Shanghai," Sustainability, MDPI, vol. 10(2), pages 1-15, February.
    14. Guan, DongJie & Li, HaiFeng & Inohae, Takuro & Su, Weici & Nagaie, Tadashi & Hokao, Kazunori, 2011. "Modeling urban land use change by the integration of cellular automaton and Markov model," Ecological Modelling, Elsevier, vol. 222(20), pages 3761-3772.
    15. Parviz Azizi & Ali Soltani & Farokh Bagheri & Shahrzad Sharifi & Mehdi Mikaeili, 2022. "An Integrated Modelling Approach to Urban Growth and Land Use/Cover Change," Land, MDPI, vol. 11(10), pages 1-26, October.
    16. Mekonnen H. Daba & Songcai You, 2022. "Quantitatively Assessing the Future Land-Use/Land-Cover Changes and Their Driving Factors in the Upper Stream of the Awash River Based on the CA–Markov Model and Their Implications for Water Resources," Sustainability, MDPI, vol. 14(3), pages 1-29, January.
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