Elevated phosphorus (P) loading of freshwater lakes and reservoirs often results in poor water quality and negative ecological effects. Critical source areas (CSA) of P in the watershed can be difficult to identify and control. A useful concept for identification of a CSA is the P risk index (P Index) that evaluates the P risk associated with distinct source and transport pathways. The objectives of this study were to create a GIS model that adapts the Minnesota (MN) P Index for use at the watershed scale in a mixed-use, mountain environment, and to evaluate its effectiveness relative to field-based assessment. A GIS-based model of the MN P Index, adapted for montane environments and relying primarily on publicly available geospatial data, was created and applied in the Wallsburg watershed, located in the mountains of Central Utah. One necessary data input, P found in plant residue of common Utah ecosystems, was found lacking after literature review. We experimentally determined a range of observed values from multiple ecosystems to adapt and validate the GIS model. The GIS P Index was evaluated against the results of 58 field scale applications of the MN P Index conducted throughout the watershed. The field-scale analysis resulted in about 14% of the sites sampled being identified as high or very high risk for P transport to surface water. Spatially, these high risk areas were determined to be a geographic cluster of fields near the lower middle agricultural section of the watershed. The GIS model visually and spatially identified the same cluster of fields as high risk areas. Various soil test P scenarios were explored and compared to the known 58 site values. Soil test phosphorus had little effect on the GIS model's ability to accurately predict P risk in this watershed suggesting that high volume soil sampling is not always necessary to identify CSAs of P. Variable hypothetical livestock density scenarios were also simulated. The GIS model proved sensitive to variable P inputs and highlighted the necessity of accurate applied P source data. On average the model under-predicted the known field-site values by a risk score of 1.3, which suggests reasonable success in P assessment based on the categorical risk scores of the MN P Index and some potential for improvement. The GIS model has great potential to give land managers the ability to quickly locate potential CSAs and prioritizing remediation efforts to sites with greatest risk.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-7559 |
| Date | 01 June 2017 |
| Creators | Johns, Josiah A. |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Theses and Dissertations |
| Rights | http://lib.byu.edu/about/copyright/ |
Page generated in 0.004 seconds