Predicting organic matter, nitrogen, and phosphorus concentrations in runoff from peat extraction sites using partial least squares regression

Organic matter and nutrient export from drained peatlands is affected by complex hydrological and biogeochemical interactions. Here partial least squares regression (PLSR) was used to relate various soil and catchment characteristics to variations in chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) concentrations in runoff. Peat core samples and water quality data were collected from 15 peat extraction sites in Finland. PLSR models constructed by cross-validation and variable selection routines predicted 92, 88, and 95% of the variation in mean COD, TN, and TP concentration in runoff, respectively. The results showed that variations in COD were mainly related to net production (temperature and water-extractable dissolved organic carbon (DOC)), hydrology (topographical relief), and solubility of dissolved organic matter (peat sulfur (S) and calcium (Ca) concentrations). Negative correlations for peat S and runoff COD indicated that acidity from oxidation of organic S stored in peat may be an important mechanism suppressing organic matter leaching. Moreover, runoff COD was associated with peat aluminum (Al), P, and sodium (Na) concentrations. Hydrological controls on TN and COD were similar (i.e., related to topography), whereas degree of humification, bulk density, and water-extractable COD and Al provided additional explanations for TN concentration. Variations in runoff TP concentration were attributed to erosion of particulate P, as indicated by a positive correlation with suspended sediment concentration (SSC), and factors associated with metal-humic complexation and P adsorption (peat Al, water-extractable P, and water-extractable iron (Fe)).