艾比湖流域地表水水体悬浮物、总氮与总磷光谱诊断及空间分布特征

Spectral Diagnosis and Spatial Distribution of SS, TN and TP in Surface Water in Ebinur Lake Watershed

水体悬浮物(SS)、总氮(TN)和总磷(TP)是衡量水质的一个重要指标。选择新疆艾比湖流域为靶区,基于2015年10月实测光谱数据,采用微分法和反射率变换法以及偏最小二乘法估算水体中的SS、TN和TP的质量浓度。结果表明,(1)水体悬浮物的自然对数(ln SS)的显著性波段出现在350、410、520、570、655和940 nm处,基于偏最小二乘法的ln SS均方根一阶拟合效果最好,P<0.01水平下拟合系数r^2=0.3562。此外,ln SS与总氮、总磷存在显著性正相关,相关系数分别为0.506和0.505(P<0.01)。(2)水体TN的显著性波段出现在393~399 nm与674~678 nm范围内,水体TN的倒数一阶拟合效果最好,P<0.01水平下拟合系数r2=0.438 9;(3)水体TP的显著性波段出现在333、349、862、882和905 nm处,水体TP的倒数一阶拟合最优,P<0.01显著性水平下拟合系数r^2=0.634 8。从水体SS、TN和TP浓度的空间分布可知,水体SS、TN和TP含量高值点位于艾比湖的北岸,基于最优模型反演的SS、TN和TP的浓度整体偏高,且与原始数据的空间分布相差不明显。综上所述,利用光谱数据可以精准、快速的估算水体悬浮物、总氮和总磷,可为水质的评价提供科学依据,亦可为今后利用星载高光谱传感器对艾比湖流域水质参数进行大面积估算提供新思路。

SS,TN and TP are the important indexes for measuring water quality.Choosing Xinjiang Ebinur Lake Watershed as the target and based on the hyper spectral data collected in October2015,the author estimated the mass concentration of TN and TP in water sample by the differential method,the reflectivity transformation method and the partial least square analysis for inversion.It turned out that,(1)the significant bands of natural logarithm(lnSS)with water suspended matter appeared at350,410,520,570,655and940nm.Based on partial least squares,it is known that the best fit showed in first order of the lnSS with the root mean square in the water,and the fitting coefficient r2=0.3562,below the P<0.01level.There was significant correlation among lnSS with total nitrogen and total phosphorus with correlation coefficients being0.506and0.505(P<0.01level),respectively.(2)The significant bands of TN in water appeared in the range of393~399nm and674~678nm.Based on partial least square,it is known that the best fit showed at the reciprocal first order of the TN in the water,and the fitting coefficient r2=0.4389,below the P<0.01level.(3)The significant bands of TP appeared at333,349,862,882and905nm.The reciprocal first order of TP in water was the best,and the fitting coefficient r2=0.6348,below the P<0.01level.In addition,we found out from the spatial distribution of SS,TN and TP inwater that the high value of SS,TN and TP content were located on the north shore of the Ebinur Lake.The content of SS,TN and TP based on the optimal model inversion was all higher,and the differences in spatial distribution when compared to original data were not conspicuous.In summary,accurate and rapid estimation of TN and TP in water can provide data basis for the evaluation of water quality,and offer a new way of large-scale water quality evaluation using space-borne hyper-spectral sensors in Ebinur Lake Watershed in the future.