Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/11/2018
Publication Date: 3/15/2018
Citation: Bolster, C.H., Vadas, P.A. 2018. Comparison of two methods for calculating the P sorption capacity parameter in soils. Soil Science Society of America Journal. 82(2):493-501. https://doi.org/10.2136/sssaj2017.09.0317.
DOI: https://doi.org/10.2136/sssaj2017.09.0317 Interpretive Summary: Phosphorus (P) is commonly applied to agricultural fields in the form of inorganic fertilizer, animal manure, or biosolids to maintain or increase crop yields and improve soil quality. To assess the impact of agricultural activities on water quality, computer simulation models are often employed to help planners better manage nutrients at the field and farm scale. Several P transport models have been developed to help identify and quantify the impact that various nutrient management practices have on reducing P loss from agricultural fields. An important component of all P loss models is how P cycling in soils is described. The P cycling routines in most models are based on the routines developed for the EPIC model over 30 years ago. An important parameter required for this model is the P sorption capacity parameter (PSP). In this study we compare two distinct methods for estimating PSP. We found a very poor correlation between PSP values calculated using these two methods indicating that these two approaches are not measuring the same parameter. It is not clear whether these differences are due to limitations with the experimental method for measuring PSP or limitations with the P cycling routines. Our results highlight the need for additional research to improve methods for estimating PSP from soil P data and soil incubation studies.
Technical Abstract: Phosphorus (P) cycling in soils is an important process affecting P movement through the landscape. The P cycling routines in many computer models are based on the relationships developed for the EPIC model. An important parameter required for this model is the P sorption capacity parameter (PSP). In this study we compare two distinct methods for estimating PSP using data collected to develop the EPIC model. Specifically, we compare PSP values measured from changes in soil P concentrations in 6-month laboratory soil incubation experiments with PSP values obtained from fitting the model to soil P data. We found a very poor correlation between PSP values calculated using these two methods indicating that these two approaches are not measuring the same parameter. We also found that PSP values calculated from soil incubation studies resulted in significant underpredictions of total P. It is not clear whether this is due to limitations in the experimental approach for measuring PSP, or whether it is a result of limitations with the model itself. An advantage of calibrating PSP on measured soil P data is that it is less costly and time consuming than the soil incubation studies. Furthermore, any limitations with the model are accounted for in the fitted PSP data. However, this means that the fitted values should be viewed strictly as a calibration parameter and not representative of an independently-measurable physically-based parameter. Our results highlight the need for additional research to improve methods for estimating PSP from soil P data and soil incubation studies.