Spectral analysis of surface water pollution using spectral indices NDWI, WQI, and WPI (Case study: Meyghan wetland, Markazi province)
Subject Areas : Water resources management
Hadi Lotfi
1
,
Amirhossein Mohammadi
2
*
,
Mehdi Feizollahpour
3
1 - Bachelor's student in Geography, Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan, Iran.
2 - Bachelor's student in Geography, Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan, Iran.
3 - Associate Professor, Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan, Iran.
Keywords: Remote Sensing, Meyghan Wetland, Environmental Monitoring, Water Pollution, Water Quality,
Abstract :
Background and Aim: Wetlands, as sensitive and dynamic ecosystems, play a fundamental role in environmental sustainability, regulating ecological cycles, moderating local climates, and providing vital water resources. These ecosystems not only preserve biodiversity but also contribute to floods control, groundwater recharge, and air quality improvement. The present study aims to monitor and evaluate changes in the water surface and environmental quality of the Meyghan Wetland during the period from 2000 to 2024. In this research, remote sensing data and spectral indices related to water and surface cover were employed to analyze the spatial and temporal variations of the wetland, in order to identify and assess potential trends of degradation or improvement in its environmental conditions of this water body.
Method: In this study, time-series satellite data from Landsat 7, 8, and 9 covering the period 2000 to 2024 were used to examine changes in the surface and quality of the wetland’s water. The satellite images were first geometrically and radiometrically corrected and then processed in ArcGIS Pro software. For more accurate analysis, the spectral indices NDWI, WQI, and WPI were extracted, and their values were calculated using standard formulas based on spectral reflectance. Subsequently, the spatial and temporal variations of each index were analyzed to determine trends in water level fluctuations and environmental quality changes throughout the study period. Finally, the results were presented as classified maps and analytical charts, allowing for a clear and precise visualization of the quantitative and qualitative changes in the wetland over time.
Results:The findings of this study revealed that three spectral indices—NDWI, WQI, and WPI—were analyzed to assess changes in the water level and quality of Miqan Wetland from 2000 to 2024. NDWI results showed a continuous decline in the wetland’s surface water area, from 3.7 km² in 2000 to approximately 0.7 km² in 2024, reflecting gradual drying and reduced water inflows. The WQI, which evaluates water quality, indicated a shift from “excellent” and “good” conditions in the early years to “moderate” and “poor” conditions in the later years; areas of high water quality decreased to less than 1 km² by 2024. WPI results confirmed an increasing trend of pollution, rising from about 0.9 in 2000 to over 1 in 2024, indicating the expansion of polluted areas and a significant decline in water quality. Comparison of WQI and WPI demonstrated an inverse relationship, where increased pollution (higher WPI) corresponded to reduced water quality (lower WQI). These results suggest that the wetland is significantly affected by anthropogenic and climatic pressures, underscoring the urgent need for conservation and management interventions.
Conclusion: The results obtained from the analysis of spectral indices indicated a significant decline in the water surface area of the Meyghan Wetland between 2000 and 2024, decreasing from approximately 3.7 square kilometers to less than 0.8 square kilometers. Simultaneously, water quality also deteriorated considerably. The WQI index revealed a shift from "good" and "excellent" quality to "moderate" and "poor" conditions across various parts of the wetland. The WPI index further confirmed increased pollution levels and the expansion of critically affected zones in the later years. These findings suggest that the wetland has been impacted by a combination of reduced water inflows, climate change, and increased discharge of human-induced pollutants. The application of remote sensing indices, particularly within the ArcGIS Pro environment, enabled accurate and cost-effective monitoring of water resources. Overall, the study underscores the urgent need for immediate management strategies to protect and restore this valuable ecosystem.
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