Spatiotemporal Dynamics of Chlorophyll-a in a Small Inland Reservoir Using Field Sampling and Satellite Data

This study examines harmful algal bloom (HAB) dynamics in Shanzai Reservoir, Fujian Province, China, through integrated in-situ and satellite remote sensing techniques. Chlorophyll-a concentrations the primary indicator of algal biomass, were measured directly using the bbe-Moldaenke FluoroProbe II, while Sentinel-2 imagery processed via Google Earth Engine (GEE) was used to map spatiotemporal bloom patterns. Monthly field sampling was conducted from March to December in 2022 and 2023, with sites aligned to satellite acquisition points.Two spectral indices, the Normalized Difference Chlorophyll Index (NDCI) and the Normalized Difference Vegetation Index (NDVI), were applied to estimate chlorophyll-a distribution. Results showed peak algal concentrations in late spring and summer, especially in May, with highest values at reservoir edges and near Qili and Banling villages. Strong correlations (R² up to 0.93) between in-situ and satellite-derived chlorophyll-a confirmed the reliability of remote sensing for HAB monitoring. Seasonal analysis indicated cyanobacteria dominance in spring and summer, and increased diatom prevalence in autumn and winter. Findings demonstrate that combining high-frequency satellite data with targeted in-situ measurements enables effective, large-scale, and near real-time HAB monitoring in small inland reservoirs. NDCI outperformed NDVI in detecting and mapping bloom severity, supporting its use for routine water quality surveillance. Additional spectral band combinations (NIR, SWIR, red edge) further improved bloom detection.This integrative approach offers a cost-effective, scalable method for HAB assessment and supports sustainable freshwater management. While perfect temporal alignment of in-situ and satellite data is often constrained by logistics and bloom variability, coordinated monitoring enhances accuracy and reliability.