Changdang Lake is located in the upper reaches of the Taihu Basin and has typical significance for studying the Taihu ecosystem. This study examines how intensive pond aquaculture and restoration projects jointly shape the spatio-temporal evolution of water quality in Changdang Lake. A multi-strategy sparrow search algorithm is proposed to optimize machine learning-based retrieval of water quality, and Sentinel-1 SAR time series map upstream pond dynamics. By coupling long-term TSM–Chla distributions with pond expansion/retreat and lake management measures, the lake’s trophic trajectory is characterized as being primarily driven by external pollution. During 2016–2023, Changdang Lake’s peak values of TSM and Chla occurred in May 2019 (TSM >140 mg/L) and August 2022 (Chla >40 µg/L). Ecological dredging in the northeastern source-protection zone temporarily reduced local TSM, but subsequent rebounds in nutrients show such projects tend to address the symptoms rather than the root cause of eutrophication. Object-based SAR mapping indicates that upstream pond expanded from 36.3 to 42.7 km² and then decreased to 36.8 km² by 2023, closely tracking mean lake Chla (R 2 = 0.85). Load estimates suggest that the direct annual inputs of TN and TP into Changdang Lake from ponds are about 250.01 and 52.18 t, which can raise TN and TP by ∼1.95 and 0.41 mg /L, substantially aggravating eutrophication in the lake. • Proposed MISSA improves water quality inversion accuracy for TSM and Chla. • Aquaculture ponds' spatiotemporal impact on Changdang Lake eutrophication. • Ecological dredging improves water quality but ponds still pose a major threat.
Wang et al. (Fri,) studied this question.