Estimation of Soil Base Cation Weathering Rates with the PROFILE Model to Determine Critical Loads of Acidity for Forested Ecosystems in Pennsylvania, USA: Pilot Application of a Potential National Methodology
Phelan, J., Belyazid, S., Kurz, D., Guthrie, S., Cajka, J., Sverdrup, H., & Waite, R. (2014). Estimation of Soil Base Cation Weathering Rates with the PROFILE Model to Determine Critical Loads of Acidity for Forested Ecosystems in Pennsylvania, USA: Pilot Application of a Potential National Methodology. Water Air and Soil Pollution, 225(9), Article No. 2109. https://doi.org/10.1007/s11270-014-2109-4
Base cation weathering (BCw) rate is one of the most influential yet difficult to estimate parameters in the calculation of critical acid loads of nitrogen (N) and sulfur (S) deposition for terrestrial systems. Only the clay correlation-substrate method, a simple empirical model, has been used for estimating BCw rates for forest ecosystems in the conterminous USA and may not be suitable for application at all sites without calibration or revision. An alternate model, PROFILE, may offer an improved method to estimate BCw rates. It is a transferable, process-based model that simulates the weathering rates of groups of minerals. The objective of this study was to evaluate PROFILE using national datasets as a method to estimate BCw rates for forests in the USA, focusing on Pennsylvania (PA) as the first test state. The model paired with national datasets was successfully applied at 51 forested sites across PA. Weathering rates ranged from 119 to 9,245 eq ha(-1) year(-1) and were consistent with soil properties and regional geology. Comparisons of terrestrial critical acid loads with 2002 N and S deposition showed critical load exceedances at 53 % of the sites. This trial evaluation of PROFILE paired with national datasets in PA establishes that there are sufficient data to support the estimation of BCw rates and determination of critical acid loads for forests in the USA. However, the paired method should be applied in other locations to further evaluate the performance of the model in different regions of the country.