Temporal inequality of nutrient and sediment transport: A decision-making framework for temporal targeting of load reduction goals

Authors: PREISENDANZ, HEATHER - Pennsylvania State University; Veith, Tameria - Tamie; ZHANG, QIAN - University Of Maryland Eastern Shore (UMES); SHORTLE, JAMES - Pennsylvania State University

Submitted to: Environmental Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/11/2020
Publication Date: 12/18/2020
Citation: Preisendanz, H.E., Veith, T.L., Zhang, Q., Shortle, J. 2020. Temporal inequality of nutrient and sediment transport: A decision-making framework for temporal targeting of load reduction goals. Environmental Research Letters. 16:1-18. https://doi.org/10.1088/1748-9326/abc997.
DOI: https://doi.org/10.1088/1748-9326/abc997

Interpretive Summary: Agricultural sources of excess nutrients and sediments continue to impair surface water bodies worldwide. Although significant efforts have been made to understand how to target appropriate best management practices across a landscape spatially, less effort has been made to understand how to temporally target specific events that transport most of the nutrient and sediment loads. We adopted a method for quantifying “temporal inequality” that is commonly utilized to quantify economic inequalities within a population. The results of the temporal inequality analysis can provide “windows of opportunity” during which load reductions can be temporally targeted to achieve desired load reduction goals within a specific watershed. We applied this new methodology to 108 gauging stations with the Chesapeake Bay watershed and provided examples of how to use the results to create a decision-making framework that will provide a flexible and convenient method for decision-makers to decide how to best achieve desired load reduction goals both over space and over time. The methods we present here can be applied to any contaminant and at any spatial scale, providing a platform that is easily transferrable beyond the Chesapeake Bay watershed.

Technical Abstract: Nutrient and sediment transport exhibit strong spatial and temporal inequality, with a small percentage of locations and events contributing to the vast majority of total annual loads. Although design and implementation of best management practices (BMPs) for reducing these loads at a watershed scale often target the spatial component of this inequality, the temporal component is rarely assessed. We introduce a framework using the Lorenz Inequality and corresponding Gini Coefficient to quantify the temporal inequality of nutrient and sediment transport across the Chesapeake Bay watershed. This long-impaired, 166,000 km2 watershed has been federally mandated since 2010 to continually reduce nutrient and sediment loads reaching the Bay. Data were obtained for 108 sites in the Chesapeake Bay’s Non-Tidal Network (NTN) database from 2010 through 2018. The Lorenz Inequality analysis was conducted using monthly-scale data for flow and loads of total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) at each gauging station and their Gini Coefficients were calculated. We leverage these results to create a “temporal targeting framework” that identifies periods of time and corresponding flow conditions that must be targeted to achieve desired or mandated load reduction goals across the watershed. Among the 108 sites, the degree of temporal inequality for TP and TSS (0.36 – 0.90) was much greater than for flow and TN (0.18 – 0.69), likely due to the importance of overland versus baseflow in the transport pathways of the respective constituents. These findings stress the importance of informed design and implementation of BMPs effective in “hot moments,” and not just “hot spots,” across impaired watersheds to achieve and maintain water quality restoration goals. The “temporal targeting framework” detailed in this manuscript provides a useful and convenient method for watershed planners to create low- and high-flow load targeting tables specific to a watershed and constituent.