Lake Jordan

CCEE Researchers create tools to protect our water quality

With support from the NC Policy Collaboratory and Water Resources Research Institute, a team of CCEE researchers is involved in a multi-year study to help clean up the Falls and Jordan Lake watersheds. Led by Dan Obenour, the team includes Jonathan Miller, Kimia Karimi, and Sankar Arumugam.  Their multi-disciplinary approach combines hydrology and pollutant transport processes with multi-decadal geospatial data and computer modeling.     

Nutrient loading is a major cause of water quality problems in lakes and reservoirs across the globe, including in central North Carolina.  Elevated nutrient loading (both nitrogen and phosphorus) stimulates excessive algal production, and some of these algae (cyanobacteria, in particular) can produce dangerous toxins, as well as compounds that negatively impact the taste and odor of water.  Excessive algae can also lead to discolored and turbid waters that affect the aesthetic appeal of our lakes, while diminishing light penetration and altering ecosystem function.  Furthermore, as algae decompose, oxygen is depleted in portions of the reservoir, reducing fish habitat and releasing chemicals from the bottom sediment (e.g., manganese).  These water quality problems diminish the value of reservoirs as recreational attractions and wildlife habitats, and can greatly increase the cost of treating water for human consumption.

In the Triangle region of North Carolina, Falls and Jordan Lakes serve as major water supplies and recreational attractions.  However, since their construction in the early 1980s, these reservoirs have suffered from high levels of nutrient loading. Excessive algal concentrations typically occur in summer and fall, especially where nutrient-laden streams enter the reservoirs.  To protect these reservoirs, the state of North Carolina and local stakeholders have focused on reducing watershed nutrient loading.  However, over the last three decades, few of the reservoirs’ tributary streams have exhibited consistent decreases in nutrient loading.  Instead, nutrient loading appears to be increasing in some streams.

“We are advancing a ‘hybrid’ approach for watershed modeling and nutrient source characterization.  The model combines simple mechanistic nutrient loading and transport relationships with an advanced statistical (Bayesian) framework for data-driven discovery and uncertainty quantification.  The approach leverages 35 years (1982-2017) of USGS streamflow records and NCDEQ nutrient sampling to quantify source-specific export rates.  Moreover, we’re exploring the year-to-year variability in nutrient export to reservoirs due to changes in precipitation, while also accounting for nutrient losses, including sedimentation and denitrification in streams and large impoundments.”         Dan Obenour

 Data-driven watershed modeling to assess nutrient export and retention in central NC

To manage nutrient pollution, it is critical to understand how loading varies over space, time, and among different source types.  It is well known that natural lands release nutrients at lower rates than developed (agricultural and urban) lands due to fertilizer use, pet and livestock waste, and sometimes leaking sewage infrastructure.  However, considering the heterogeneity of developed landscapes, there is considerable uncertainty and variability in nutrient export.

Urban lands developed since 1980 have nutrient export rates that are about the same as agricultural lands, but still much higher than natural lands. Thus, conversion of agricultural land to urban land will have a much smaller impact on overall nutrient loading than urban development of natural lands. Because a majority of lands in the Falls and Jordan Lake watersheds remain forested with little or no development, conversion of this land to either urban or agricultural land will dramatically increase nutrient loading to the reservoirs.  Additionally, wastewater treatment plant effluent accounts for a large portion of nutrient release to the lakes (e.g., 50% of nitrogen and 25% of phosphorus to Jordan lake; less for Falls Lake).  Finally, streams and small reservoirs were found to remove (or retain) a small but significant portion of the nutrient source loading within the watershed.

“Our results show that urban land is the greatest exporter of nutrients per unit area. Urban lands export about 10 times more nutrients per year than natural lands.  However, not all urban lands are created equal. We find that urban lands constructed before 1980 export twice the nitrogen and phosphorus of more recent development. This is likely due to improved watershed development practices, such as the installation of stormwater detention ponds.”     Jonathan Miller 

Many questions remain. What are our next steps?

While these results provide data-driven estimates of nutrient export rates from key sources over time, many questions remain.  What aspects of older urban development result in such high nutrient export rates, relative to newer development?  Why does the model tend to over- or under-predict nutrient loading in particular sub-watersheds?  To help answer these questions and provide more detailed management guidance, the researchers (with assistance from the Center for Geospatial Analytics) are looking to create new and better information on stream buffers, urban density, stormwater control measures, and other landscape features that may influence nutrient loading throughout the study area.  These new data will be incorporated into the hybrid model to evaluate which factors best explain the variability observed in both time and space, leading to improved predictive capabilities.  Overall, the researchers expect these modeling results to provide a data-driven foundation for developing efficient and cost-effective watershed management strategies that will help protect our region’s critical water supply reservoirs.

This study is part of a larger effort to develop a “New Comprehensive Nutrient Management Regulatory Framework” with a focus on Jordan Lake and Falls Lake.  The study also includes modeling of in-lake water quality conditions by Dr. Obenour’s team and others.  This modeling shows how nutrient loads from particular streams (e.g., Morgan and New Hope Creek) exert a disproportionately large influence on reservoir water quality, and also how nutrient storage in reservoir bottom sediments make water quality improvement a long-term (multi-decadal) proposition.  For more on this and other aspects of the study, see