QUANTIFYING RELATIONSHIPS BETWEEN NEAR-INFRARED REFLECTANCE SPECTRA OF LAKE-SEDIMENTS AND WATER CHEMISTRY

One of the most useful approaches to long-term monitoring of aquatic s ystems is the analysis of lake sediments. Biological indicators, such as diatoms, preserved in the sediments are widely used. We suggest tha t use of near-infrared reflectance (NIR) spectroscopy of lake sediment s could become a rapid and cost-effective technique for environmental monitoring to follow long-term changes in water quality. NIR spectra o f surface sediments from Swedish lakes were used to establish relation ships between sediment properties and measured lake water chemistry. P redictive models for inferring total phosphorus (TP), pH, and total or ganic carbon (TOC) from sediment NIR data were developed using partial least squares regression. The model for inferring lake water TP (n = 33 lakes) captured 83% of the variance, while the explained variance f or pH (n = 52 lakes) and TOC (n = 25 lakes) was 85 and 68%, respective ly. We also used the TP model to evaluate the effect of inaccuracy in measured lake water chemistry for the model performance, i.e., the amo unt of explained variance. The inaccuracy in measured lake water chemi stry corresponds to 10.5% of the total variance in the model. The high est possible variance to model then being 89.5%. This evaluation indic ated that the obtained modeled variance almost equaled the variance po ssible to model, which suggests that further improvement of the models should be focused on enlargement of the calibration data set to inclu de more lake types.