<p>Freshwater dam reservoirs are increasingly threatened by land use/land cover changes, leading to eutrophication and degraded water quality. This study presents an integrated remote sensing and object-based image analysis approach to assess the impacts of land-use/land-cover change on eutrophication dynamics in the Sattarkhan dam reservoir, East Azerbaijan, Iran. Multi-temporal Landsat imagery (1994–2024) was employed to classify land-use/land-cover changes and estimate chlorophyll-a concentrations. In-situ chlorophyll-a measurements from seasonal sampling (2023–2024) were used to calibrate empirical models, with the blue/green band ratio power model yielding the best performance (4.44 ± 0.30 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\mu \text{g}/\text{L}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>μ</mi> <mtext>g</mtext> <mo stretchy="false">/</mo> <mtext>L</mtext> </mrow> </math></EquationSource> </InlineEquation> (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">$RMSE$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="italic">RMSE</mi> </mrow> </math></EquationSource> </InlineEquation>), 3.22 ± 0.21 <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$\mu \text{g}/\text{L}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>μ</mi> <mtext>g</mtext> <mo stretchy="false">/</mo> <mtext>L</mtext> </mrow> </math></EquationSource> </InlineEquation> (<InlineEquation ID="IEq4"> <EquationSource Format="TEX">$MAE$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="italic">MAE</mi> </mrow> </math></EquationSource> </InlineEquation>), 36.95% ± 2.80 (<InlineEquation ID="IEq5"> <EquationSource Format="TEX">$sMPAE$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="italic">sMPAE</mi> </mrow> </math></EquationSource> </InlineEquation>), and 0.70 ± 0.04 (<InlineEquation ID="IEq6"> <EquationSource Format="TEX">$R^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>R</mi> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation>)). The findings suggest a potential rise in eutrophication between 2004 and 2024, though long-term trends are subject to uncertainties from temporal extrapolation of the 2023–2024 calibrated model. Gray relational analysis was employed to investigate the relationship between landcover changes and trophic status, revealing a potential role for increasing built-up land in nutrient loading. These findings highlight the framework’s utility for sustainable watershed management in semi-arid regions. Future work should incorporate advanced modeling for broader applicability.</p>

Integrated remote sensing approach to assess impact of landcover change on eutrophication in a semi-arid dam reservoir

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发表日期：

2026年1月12日

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S. F. Shohadie,
N. Habibzadeh,
H. Ahmadzadeh,
E. Atazadeh

摘要

Freshwater dam reservoirs are increasingly threatened by land use/land cover changes, leading to eutrophication and degraded water quality. This study presents an integrated remote sensing and object-based image analysis approach to assess the impacts of land-use/land-cover change on eutrophication dynamics in the Sattarkhan dam reservoir, East Azerbaijan, Iran. Multi-temporal Landsat imagery (1994–2024) was employed to classify land-use/land-cover changes and estimate chlorophyll-a concentrations. In-situ chlorophyll-a measurements from seasonal sampling (2023–2024) were used to calibrate empirical models, with the blue/green band ratio power model yielding the best performance (4.44 ± 0.30 $\mu \text{g}/\text{L}$ $μ g / L$ ( $RMSE$ $RMSE$ ), 3.22 ± 0.21 $\mu \text{g}/\text{L}$ $μ g / L$ ( $MAE$ $MAE$ ), 36.95% ± 2.80 ( $sMPAE$ $sMPAE$ ), and 0.70 ± 0.04 ( $R^{2}$ $R^{2}$ )). The findings suggest a potential rise in eutrophication between 2004 and 2024, though long-term trends are subject to uncertainties from temporal extrapolation of the 2023–2024 calibrated model. Gray relational analysis was employed to investigate the relationship between landcover changes and trophic status, revealing a potential role for increasing built-up land in nutrient loading. These findings highlight the framework’s utility for sustainable watershed management in semi-arid regions. Future work should incorporate advanced modeling for broader applicability.