Research on the Method of Extracting Water Body Information in Central Asia Based on Google Earth Engine

This study evaluates water body changes in Central Asia (2000–2019) using Landsat 7 data on Google Earth Engine, comparing the Modified Normalized Difference Water Index (MNDWI), OTSU algorithm, and random forest (RF). The random forest algorithm demonstrated the best overall performance in water body extraction and was selected as the analysis tool. The results reveal a significant 11.25% decline in Central Asia’s total water area over two decades, with the Aral Sea shrinking by 72.13% (2000–2019) and southern Kyrgyzstan’s glaciers decreasing by 39.23%. Pearson correlations indicate strong links between water loss and rising temperatures (−0.5583) and declining precipitation (0.6872). Seasonal fluctuations and permanent degradation (e.g., dry riverbeds) highlight climate-driven vulnerabilities, exacerbated by anthropogenic impacts. These trends threaten regional water security and ecological stability, underscoring the urgent need for adaptive resource management. The RF-GEE framework proves effective for large-scale, long-term hydrological monitoring in arid regions, offering critical insights for climate resilience strategies.