Factsheet – Estimating watershed residence times in artificially-drained landscapes and relation to nutrient concentrations.
A research project funded by the Indiana Water Resources Research Center through the U.S. Geological Survey’s 104B annual base grants (section 104 of the Water Resources Research Act of 1984, as amended).
Start Date: 2018-03-01
End Date: 2019-02-28
Total Federal Funds: $15,000
Total Non-Federal Funds: $30,014
Nutrient runoff from agricultural lands leads to Harmful Algae Blooms and eutrophication in freshwater ecosystems including the Great Lakes and the Gulf of Mexico. Best Management Practices (BMPs) implemented over the last few decades aim to reduce nutrient transport to streams and rivers. Evaluations of their effectiveness have found mixed results in reducing nutrient concentrations. This could indicate that BMPs are ineffective in certain areas, or simply that the residence time of water and nutrients in the watersheds are long and the effect of BMPs won’t be seen for decades.
This project investigated the relationship between nitrate concentrations and a proxy of watershed travel times derived from water stable isotope ratio variability in the Wabash Sampling Blitz study area (Region of the Great Bend of the Wabash River watershed) . This study did not directly test BMP effectiveness, but provided a new context to examine the role of water age on nutrient dynamics.
Research Objectives
1. Classify watersheds into short and long residence times of stream water using stable isotope variability from Wabash Sampling Blitz collections. Streams that show low stable isotope variability over repeat sampling are assumed to have longer watershed travel times.
2. Confirm strong ground water influence in select watersheds in which we suspect long residence times from stable isotopes using additional sampling for isotopes and radon concentrations. Preliminary radon measurements were conducted, but Covid-19 research protocols greatly reduced the sampling that could be completed.
3. Investigate differences in nutrient concentrations of common land cover types and surface water residence times. Statistical analysis was used to explore relationships in the dataset.