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<p>Hydrological ecosystem services (HES), particularly stormwater regulation, are increasingly threatened by intensifying land use change and climate pressures in rapidly growing urban centres. In response to this emerging risk, this study integrates geospatial techniques with biophysical models to assess the impact of land use on stormwater retention capacity in cities of the rainforest (Akure and Owerri) and Guinea savanna (Makurdi and Minna) ecological regions of Nigeria, West Africa, for 2002 and 2022. Landsat images were acquired and processed in the Google Earth Engine (GEE) environment, and classified using the random forest (RF) machine learning classifier to derive land use and land cover (LULC) patterns. The normalised difference vegetation index (NDVI) was also derived. Land use pattern for 2042 was simulated using the Modules of Land Use Change Evaluation (MOLUSCE). Topographic, pedological and meteorological datasets were integrated with land use data on the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) platform to model stormwater runoff and retention capacity. Results revealed that urban and agricultural expansion influenced runoff volume, particularly within a 5–10&#xa0;km radius of the urban core, resulting in a 1.55–14.83% decline in stormwater retention capacity across cities. Geographically weighted regression revealed a stronger spatial relationship between NDVI change and stormwater retention capacity in the rainforest (<i>R</i><sup>2</sup> = 59.52–82.73%) than in the Guinea savanna (<i>R</i><sup>2</sup> = 23.79–46.87%). Stormwater retention capacity is expected to decline by 0.15% (Akure), 3.76% (Owerri), 0.35% (Makurdi) and 3.72% (Minna) between 2022 and 2042 if the current pattern of land use transformation persists, and this may exacerbate flood risk. These findings emphasise the need for ecologically sensitive land management strategies to sustain HES and reduce future flood vulnerability across urbanising regions.</p>

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Land use change as a driver of hydrological ecosystem services in the rainforest and Guinea savanna ecological regions of West Africa

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Rotimi Oluseyi Obateru

摘要

Hydrological ecosystem services (HES), particularly stormwater regulation, are increasingly threatened by intensifying land use change and climate pressures in rapidly growing urban centres. In response to this emerging risk, this study integrates geospatial techniques with biophysical models to assess the impact of land use on stormwater retention capacity in cities of the rainforest (Akure and Owerri) and Guinea savanna (Makurdi and Minna) ecological regions of Nigeria, West Africa, for 2002 and 2022. Landsat images were acquired and processed in the Google Earth Engine (GEE) environment, and classified using the random forest (RF) machine learning classifier to derive land use and land cover (LULC) patterns. The normalised difference vegetation index (NDVI) was also derived. Land use pattern for 2042 was simulated using the Modules of Land Use Change Evaluation (MOLUSCE). Topographic, pedological and meteorological datasets were integrated with land use data on the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) platform to model stormwater runoff and retention capacity. Results revealed that urban and agricultural expansion influenced runoff volume, particularly within a 5–10 km radius of the urban core, resulting in a 1.55–14.83% decline in stormwater retention capacity across cities. Geographically weighted regression revealed a stronger spatial relationship between NDVI change and stormwater retention capacity in the rainforest (R2 = 59.52–82.73%) than in the Guinea savanna (R2 = 23.79–46.87%). Stormwater retention capacity is expected to decline by 0.15% (Akure), 3.76% (Owerri), 0.35% (Makurdi) and 3.72% (Minna) between 2022 and 2042 if the current pattern of land use transformation persists, and this may exacerbate flood risk. These findings emphasise the need for ecologically sensitive land management strategies to sustain HES and reduce future flood vulnerability across urbanising regions.