Inversion and Interpretability Analysis of Bottom-Water Dissolved Oxygen in the Bohai Sea Using Multi-Source Remote Sensing Data
文献类型：期刊论文
| 作者 | Li, Tao3,4; Guo, Jie2,4; Liu, Shanwei3; Jin, Yong3; Ji, Diansheng1; Hou, Chawei1; Tang, Haitian1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2026-03-09 |
| 卷号 | 18期号:5页码:20 |
| 关键词 | dissolved oxygen (DO) hypoxia Bohai Sea geostationary ocean color imager (GOCI) geostationary ocean color imager II (GOCI-II) XGBoost remote sensing |
| DOI | 10.3390/rs18050838 |
| 通讯作者 | Guo, Jie(jguo@yic.ac.cn) |
| 英文摘要 | Highlights What are the main findings? DO is a non-optically active parameter, but it can be indirectly estimated using satellite-derived optical variables. A temporal lag exists between satellite-derived surface optical variables and bottom-water DO response; explicitly accounting for this delay significantly improves the accuracy of bottom DO retrieval. The inversion framework successfully reproduced the spatiotemporal variation in bottom-water DO in the Bohai Sea, revealing two main hypoxic zones in summer. What are the implications of the main findings? The delayed response of bottom-water DO to surface bio-optical signals indicates that biogeochemical processes linked to organic matter sinking and oxygen-consuming decomposition in bottom waters influence DO variability. The inversion framework reveals the feasibility of monitoring coastal bottom-water hypoxia using multi-source satellite remote sensing, providing a scalable and cost-effective approach to long-term ecological assessment, marine management, and early warning for hypoxia events.Highlights What are the main findings? DO is a non-optically active parameter, but it can be indirectly estimated using satellite-derived optical variables. A temporal lag exists between satellite-derived surface optical variables and bottom-water DO response; explicitly accounting for this delay significantly improves the accuracy of bottom DO retrieval. The inversion framework successfully reproduced the spatiotemporal variation in bottom-water DO in the Bohai Sea, revealing two main hypoxic zones in summer. What are the implications of the main findings? The delayed response of bottom-water DO to surface bio-optical signals indicates that biogeochemical processes linked to organic matter sinking and oxygen-consuming decomposition in bottom waters influence DO variability. The inversion framework reveals the feasibility of monitoring coastal bottom-water hypoxia using multi-source satellite remote sensing, providing a scalable and cost-effective approach to long-term ecological assessment, marine management, and early warning for hypoxia events.Abstract Seasonal hypoxia in bottom waters of the Bohai Sea poses an escalating threat to marine ecosystems, yet monitoring it via satellite remote sensing continues to be challenging due to the inaccessibility of bottom layers. However, surface bio-optical signals do not instantaneously reflect variation in bottom-water dissolved oxygen (DO); instead, a distinct temporal lag exists between surface biological activity and its influence on bottom DO. Leveraging this insight, an inversion framework was established, integrating multi-source remote sensing data with decision tree-based machine learning models to estimate bottom-water DO concentration. We evaluated multiple lag intervals for satellite-derived bio-optical variables and adopted a 14-day lag as representative of the delayed impact of surface processes on bottom DO. An optimized feature set selected via a genetic algorithm (GA) was used to train the XGBoost model, which achieved high predictive performance (R2 = 0.86, RMSE = 0.79 mg/L, MAPE = 8.89%). Interpretability analysis identified the sea surface temperature as the dominant driver of bottom-water DO variation in the Bohai Sea. The framework successfully reproduced the spatiotemporal variability in bottom DO from 2022 to 2024 in the Bohai Sea and captured the locations of summer hypoxic zones. Further analysis demonstrated that incorporating physically based bottom-layer variables substantially enhances model accuracy (R2 = 0. 89, RMSE = 0.68 mg/L, MAPE = 7.85%), underscoring their critical role in regulating bottom-water DO concentrations. Building on the established inversion framework and integrating extended in situ and satellite observations, we reconstruct the long-term temporal distribution of bottom DO in the Bohai Sea from 2014 to 2025, revealing the considerable potential of satellite data for monitoring bottom-water DO conditions in coastal seas. |
| WOS关键词 | SUMMER HYPOXIA ; CHLOROPHYLL-A ; GOCI |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001713931500001 |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.yic.ac.cn/handle/133337/42287]  |
| 专题 | 烟台海岸带研究所_海岸带信息集成与综合管理实验室 |
| 通讯作者 | Guo, Jie |
| 作者单位 | 1.Minist Nat Resources, Yantai Marine Ctr, Yantai 264006, Peoples R China 2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Shandong Key Lab Coastal Zone Environm Proc & Ecol, Yantai 264003, Peoples R China 3.China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R China 4.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Tao,Guo, Jie,Liu, Shanwei,et al. Inversion and Interpretability Analysis of Bottom-Water Dissolved Oxygen in the Bohai Sea Using Multi-Source Remote Sensing Data[J]. REMOTE SENSING,2026,18(5):20. |
| APA | Li, Tao.,Guo, Jie.,Liu, Shanwei.,Jin, Yong.,Ji, Diansheng.,...&Tang, Haitian.(2026).Inversion and Interpretability Analysis of Bottom-Water Dissolved Oxygen in the Bohai Sea Using Multi-Source Remote Sensing Data.REMOTE SENSING,18(5),20. |
| MLA | Li, Tao,et al."Inversion and Interpretability Analysis of Bottom-Water Dissolved Oxygen in the Bohai Sea Using Multi-Source Remote Sensing Data".REMOTE SENSING 18.5(2026):20. |
入库方式： OAI收割
来源：烟台海岸带研究所
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