【摘要】 【目的】本文研究了鄱阳湖水质的监测与管理。【方法】对2015年8月实测3种水质参数与TN、TP浓度空间变化趋势进行分析。【结果】TN、TP的变化趋势受水环境和采砂活动影响较大,呈现采砂区下游和南北采样区TN、TP浓度较高、湖心浓度较低的趋势。以与TN、TP浓度相关性最高的悬浮泥沙作为TN、TP反演模型的间接反演因子,R₄/R₂、一阶微分R₄分别作为TN、TP直接反演模型敏感波段,构建鄱阳湖TN、TP浓度的间接、直接遥感估算模型。【结论】TN、TP间接反演模型平均相对误差分别为32.3%,16.3%;直接反演模型平均相对误差分别为25.8%、18.4%;造成该现象的原因是自然界中氮磷循环形式复杂、浅水区域湖底反射等,可依据湖泊水环境特征建立模型以提高反演精度。更多还原

【Abstract】 【Objective】The present paper aimed to study the monitoring and management of Poyang lake water quality.【Method】The changing trends of three water quality parameters and TN and TP concentrations in August 2015 were analyzed. 【Result】The trends of TN and TP were greatly affected by water environment and sand mining activities, the trends of higher TN and TP concentration and lower lake core concentration in the downstream and north-south sampling areas of the sand mining area were presented. The TN and TP inversion models were established by suspended sediment as the indirect inversion factor. The TN and TP direct inversion models were established by R₄/R₂ and the first-order differential R₄ as TN and TP remote sensing factors. 【Conclusion】The mean relative errors of TN and TP indirect inversion models were 32.3 % and 16.3 %, respectively. The mean relative errors of direct inversion models were 25.8 % and 18.4 %, respectively. The reason for this phenomenon was that the circulation form of TP and TN was complex in nature and the lake bottom reflection in shallow water area. Model could be established according to the characteristics of lake water environment to improve the accuracy of model inversion.更多还原