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<p>Research on land use and land cover (LULC) dynamics, and understanding the factors driving these changes, is essential for interpreting land use data and developing sustainable Land &amp; Water Resources (LWR) management strategies. This study evaluates and quantifies LULC dynamics in the upper Oum Er Rbia watershed (Up-OER) from 1985 to 2022 using a combination of remote sensing-based diachronic analysis and surveys with stakeholders, associations, and farmers. Classification accuracy, based on the “Random Forest” algorithm, showed satisfactory results, with overall accuracy and Kappa coefficients exceeding 87% and 0.81, respectively. The findings revealed declines in forest and urban/bare soil areas by −24.6% and −22.6%, respectively, while cultivated land and pastures increased by 30.7%. Survey analysis aligned with these findings, indicating that key drivers include climate change, agricultural expansion, and socio-economic changes such as the transition from transhumance to sedentarization, and the adoption of new crops and agricultural practices. This research provides insights to support policymakers in formulating effective LWR strategies in a region of ecological, hydrological, and economic significance in Morocco, including the UNESCO-designated Cedars of the Atlas Biosphere Reserve, the Oum Er Rbia River, and the Ahmed El Hansali Dam, crucial for regional irrigation.</p>

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Land and water resources changes and their driving forces in the south part of the Middle Atlas Mountains, Morocco

  • 期刊论文

  • 发表日期：

    2025年5月12日

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  • Tarik El Orfi,
  • Mohamed El Ghachi,
  • Sébastien Lebaut,
  • Ionel Haidu,
  • Miloud Ouchala

摘要

Research on land use and land cover (LULC) dynamics, and understanding the factors driving these changes, is essential for interpreting land use data and developing sustainable Land & Water Resources (LWR) management strategies. This study evaluates and quantifies LULC dynamics in the upper Oum Er Rbia watershed (Up-OER) from 1985 to 2022 using a combination of remote sensing-based diachronic analysis and surveys with stakeholders, associations, and farmers. Classification accuracy, based on the “Random Forest” algorithm, showed satisfactory results, with overall accuracy and Kappa coefficients exceeding 87% and 0.81, respectively. The findings revealed declines in forest and urban/bare soil areas by −24.6% and −22.6%, respectively, while cultivated land and pastures increased by 30.7%. Survey analysis aligned with these findings, indicating that key drivers include climate change, agricultural expansion, and socio-economic changes such as the transition from transhumance to sedentarization, and the adoption of new crops and agricultural practices. This research provides insights to support policymakers in formulating effective LWR strategies in a region of ecological, hydrological, and economic significance in Morocco, including the UNESCO-designated Cedars of the Atlas Biosphere Reserve, the Oum Er Rbia River, and the Ahmed El Hansali Dam, crucial for regional irrigation.