摘要
为及时对汉江下游水华做出预警、探究汉江水华的驱动因素及保护水质,构建长短期记忆神经网络模型模拟汉江下游仙桃水文站附近水体的叶绿素a浓度变化过程,通过情境分析评估水华发生期间氨氮、总磷、水温、流量、气温变化对水体中叶绿素a浓度的影响。结果表明:长短期记忆神经网络模型可较好地模拟叶绿素a浓度变化;水体中氨氮、总磷浓度与叶绿素a浓度呈显著正相关关系,流量与叶绿素a浓度呈显著负相关关系,叶绿素a浓度随水温升高呈先增后减的单峰变化趋势,而随气温升高则表现为先增强促进、后影响减弱、最终再次促进的非线性响应关系;情境分析中,气温、水温和流量变化对水体中叶绿素a浓度变化的影响相对较大。研究成果可为汉江下游水华预警与防治工作提供参考。
In order to timely warn of algal blooms in the lower reaches of Hanjiang River and explore the preventive measures for algal blooms in the Hanjiang River,a long short-term memory neural network model was constructed to simulate the change process of Chl-a concentration in the water body near the Xiantao Hydrological Station in the lower reaches of Hanjiang River.The contribution of ammonia nitrogen,total phosphorus,water temperature,flow and temperature changes to Chl-a concentration in the water body during the algal bloom were evaluated through scenario analysis.The results showed that the LSTM neural network model could simulate the change of Chl-a concentration well.The concentrations of ammonia nitrogen and total phosphorus in water bodies show a significantly positive correlation with Chl-a concentration,while flow rate exhibits a significantly negative correlation with Chl-a concentration.Chl-a concentration demonstrates a unimodal variation pattern with water temperature,which isinitially increasing then decreasing as temperature rises.In contrast,it exhibits a nonlinear response to temperature changes,initially enhancing and promoting the effect,then weakening it,and finally promoting it again as temperatures rise.The change of water temperature and flow has a relatively large impact on the change of Chl-a concentration in the water body.The research results can provide a reference for the early warning and prevention of algal blooms in relevant departments.
作者
王浩轩
魏猛
罗春艳
钱宝
WANG Haoxuan;WEI Meng;LUO Chunyan;QIAN Bao(Middle Changjiang River Bureau of Hydrology and Water Resources Survey,Bureau of Hydrology of Changjiang Water Resources Commission,Wuhan 430010,China;Bureau of Hydrology,Changjiang Water Resources Commission,Wuhan 430010,China)
出处
《水利水电快报》
2026年第2期99-104,共6页
Express Water Resources & Hydropower Information
基金
武汉市自然科学基金项目(2024040801020272)。
关键词
水华预测
叶绿素A
长短期记忆神经网络
汉江下游
algal bloom prediction
Chl-a
long-short term memory neural network
lower reaches of Hanjiang River
