Quantifying Landscape Nutrient Inputs With Spatially Explicit Nutrient Source Estimate Maps. Issue 2 (7th February 2020)

• Record Type: Journal Article
• Authors: Hamlin, Q. F.; Kendall, A. D.; Martin, S. L.; Whitenack, H. D.; Roush, J. A.; Hannah, B. A.; Hyndman, D. W.
• Is Part Of: Journal of geophysical research. Volume 125:Issue 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-02-07
• Subjects: Nutrients -- eutrophication -- spatially explicit model -- great lakes -- nitrogen -- phosphorus; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2019JG005134
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Nutrient management is an essential part of watershed planning worldwide to protect water resources from both widespread landscape inputs of nutrients (N and P) and point source emissions. To provide information to regional watershed planners and better understand nutrient sources, we developed the Spatially Explicit Nutrient Source Estimate Map (SENSEmap) to quantify individual sources of N and P at their entry points in the landscape. We modeled seven sources of N and six sources of P across the U.S. Great Lakes Basin at 30‐m resolution: atmospheric deposition, septic systems, chemical nonagricultural fertilizer, chemical agricultural fertilizer, manure, nitrogen fixation, and point sources. By modeling these sources, we provide a more detailed view of nutrient inputs to the landscape beyond what would be possible from land use alone. We found that 71% and 88% of N and P, respectively, came from agricultural sources. The nature of agricultural nutrient inputs varied significantly across the basin, as relative contributions of chemical agricultural fertilizers, manure, and N fixation changed according to diverse land use practices regionally. We then applied k‐means cluster analysis and identified nine Nutrient Input Landscapes (NILs) with N and P source characteristics, grouped into intensive agricultural, urban, and rural landscapes. These NILs can offer insights into landscape variability that land use data alone cannot; within agricultural NILs, application of chemical fertilizer and manure varied greatly, but land uses were similar. These NILs can provide a framework for broadly categorizing watersheds that may prove useful to both ecological and management practices. Plain Language Summary: Although plants need nutrients (nitrogen and phosphorus) for growth, the widespread use of nutrients to boost crop growth has led to serious water quality problems worldwide. Excess nutrients in water bodies disrupt ecosystem balance, allowing intense algae growth, sometimes creating harmful algal blooms that pose threats to human and aquatic life. In addition to using nutrients for crops in the form of chemical fertilizers and manure, other important sources include wastewater treatment plants, septic tanks, lawn fertilizers, and nutrients dissolved in rainfall or bound to settling dust. In order for managers and conservationists to better manage excess nutrients, nutrient "budgets" are often developed for nutrient inflows and outflows to provide a foundation for decision making. In this study, we developed high‐resolution maps of nutrient sources across the U.S. Great Lakes Basin as a tool for managers and scientists. These maps, collectively named SENSEmap (Spatially Explicit Nutrient Source Estimate map), integrate data from public databases, scientific publications, and satellite imagery to estimate inputs from seven nutrient sources across portions of eight states. We have analyzed these maps, summing nutrients across small‐to‐medium watersheds commonly used for management decisions, to gain a broader understanding of nutrient dynamics across the Great Lakes Basin. Key Points: We modeled seven sources of N and P inputs at 30‐m resolution across the U.S. Great Lakes Basin We identified nine distinct Nutrient Input Landscapes with unique nutrient source characteristics Land use among Nutrient Input Landscapes was similar, suggesting that land use alone does not capture nutrient source dynamics