为研究矿区沉陷水域重金属元素含量快速有效的监测方法，以淮南市潘一矿沉陷水域为研究区域;首先利用ASD FieldSpec 4地物光谱仪采集采样点的光谱数据并采集样本，其次，对取回的水样中Cu,Pb,Zn,As,Cd和Cr六种重金属元素含量采用原子吸收光谱仪和原子荧光光度计测定;然后，对光谱数据进行微分变换及倒数对数变换，将变换后的光谱数据与水体重金属含量进行相关性分析，并提取特征光谱;且根据相关性分析结果选择显著相关的波段进行建模。采用单波段分析、多元逐步回归(SMLR)分析及波段深度与偏最小二乘回归(PLSR)结合3种方法分别建立基于光谱反射率估算水体重金属含量的预测模型，并对预测模型进行精度评定，选取各重金属含量的最佳预测模型。结果表明，经过微分变换的光谱波段与重金属元素含量的相关系数有显著提高且达到了更高的相关度。微分变换后，Cu,Pb,Zn,As,Cd和Cr五种重金属元素的最大相关系数分别为0.874,-0.648,0.824,0.764,0.636 和-0.885;Cu,Cr元素含量与二阶微分变换光谱建立的单波段回归模型为最佳预测模型，验证R²分别为0.823,0.806。Pb元素、Zn元素、As元素和Cd元素含量与光谱数据的二阶微分建立的逐步回归模型为最佳预测模型，验证R²分别为0.774,0.724，0.564，0.767。该模型可用于潘一矿沉陷水域重金属含量的快速监测。

In order to study a rapid and effective monitoring method for the heavy metal elements in the subsidence wa- ters of a mining area,the subsidence water area of Panyi Mine in Huainan,China,was taken as a research area. First- ly,the spectral data of sampling points were collected by ASD FieldSpec 4 spectrometer and some samples were col- lected. The contents of six heavy metals including Cu,Pb,Zn,As,Cd and Cr in water samples were determined using atomic absorption spectrometer and atomic fluorescence spectrometer. Then,the spectral data was subjected to differen- tial transformation and reciprocal logarithmic transformation. The correlation analysis was carried out with the water content of the metal and the characteristic spectrum was extracted. The significant correlation bands were selected ac- cording to the correlation analysis results. Single-band analysis,multiple stepwise regression ( SMLR) analysis and band depth and partial least squares regression (PLSR) were combined to establish a prediction model for estimating heavy metal content in water based on spectral reflectance,and the accuracy of the prediction model was evaluated.The best prediction model for each heavy metal content was selected. The results show that the correlation coefficient between the spectral band of the differential transformation and the heavy metal element content of the water body is significantly improved and a higher correlation is achieved. After differential transformation,the maximum correlation coefficients of six heavy metal elements including Cu,Pb,Zn,As,Cd and Cr are 0. 874,-0. 648,0. 824,0. 764,0. 636 and -0. 885,respectively. Based on the Cu,Cr content and second-order differential transformation spectrum,the es- tablished single-band regression model is their best predictive model,and the R2 is verified to be 0. 823 and 0. 806,re- spectively. The stepwise regression model established by the second-order differential of Pb,Zn,As and Cd content and spectral data is their best prediction model. The verification R2 is 0. 774,0. 724,0. 564,and 0. 767,respectively. The models can be used for the rapid monitoring of heavy metal content in the subsided waters at Panyi Mine.