1. Comparing Stream Discharge, Dissolved Organic Carbon, and Selected MODIS Indices in Freshwater Basins Wade Shaver and Dr. Wil Wollheim Research and Discover University of New Hampshire Summer 2009

2. Background Dissolved Organic Carbon (DOC) is an important water quality parameter because: It creates disinfection by-products in water treatment facilities, which are carcinogenic, and it is responsible for the transport and fate of toxic, heavy metals such as mercury. (Aiken and Reddy, 2002; Dittman et al., 2009; Singer, 1999) It can help explain anomalies in the terrestrial carbon budget, and provide insight into climate change phenomena. (Striegl et al. 2005, Worral and Burt 2007, Freeman et al. 2001, Fahey et al. 2005)

3. Background Proposal submitted to NASA with an objective to “Quantify DOC quantity and quality across season and flow conditions … by coupling terrestrial and aquatic remote sensing information, models, and field measurements.” Preliminary findings showed that the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) had a good relationship with temporal DOC variability in the Ipswich River Basin in Massachusetts.

4. Purpose To explore using remote sensing tools as a means for predicting temporal DOC variability in freshwater basins.

5. Methods Water quality data from the United States Geological Survey (USGS) National Water Quality Assessment (NAWQA) program was obtained. Site Selection Criteria: Small Receiving Basins (< 600km 2 ) Continuous, Long-term DOC and Discharge Data MODIS data was collected for each site’s receiving basin and evaluated along with the temporal variability in DOC and discharge. The MODIS indices were chosen based on their connections with terrestrial DOC and include: Normalized Difference Vegetation Index (NDVI) Enhanced Vegetation Index (EVI) Daily Photosynthesis (PSN) Leaf Area Index (LAI) Coefficients of determination (r 2 ) and correlation coefficients (r) were calculated for relationships between DOC vs. Discharge and DOC vs. MODIS.

6. Site Locations OH PA NY MA VT NH WV CT NJ ME VA NC MD DE RI Atlantic Ocean Lake Ontario N Ipswich Site Study Sites

7. Results Discharge Correlated SiteDischarge Poorly Correlated Site

8. Results As the DOC vs. Q correlation coefficient increases, the DOC vs. MODIS correlation coefficient decreases. (Significance < 1% for all indices)

9. Results Data UnalteredDOC Outlier Removed/MODIS Shifted Ahead One Month

10. Results (For All Sites: 30<n<160) SiteDOC vs QDOC vs Q rDOC vs NDVI rDOC vs EVI rDOC vs PSN rDOC vs LAI r 1119375no effect00.4310.370.3740.336 1124000diluting-0.2120.550.4710.4110.49 1125100diluting-0.3970.5150.4290.410.49 1184490concentrating0.4620.1410.1550.1260.118 1192500no effect-0.0770.4280.4840.3450.409 1196222concentrating0.5070.2470.10.2070.138 1203000concentrating0.3220.3780.350.2390.297 1208049diluting-0.4160.6470.6330.4730.643 1485500concentrating0.3740.4210.4850.4450.458 1487000concentrating0.8310.2320.1610.3220.205 1491000concentrating0.8010.10.1050.0890 2097464concentrating0.572-0.03200.032-0.071 Ipswichno effect0.10.4710.4690.4110.352 Correlation Coefficients between DOC vs. Discharge and DOC vs. MODIS

11. Conclusions MODIS indices used in this study were found to account for significant variations in DOC in some basins. As the DOC vs. discharge correlation increases the DOC vs. MODIS correlation decreases, but only if the discharge effect is concentrating. Sites with diluting discharge effects have the best MODIS correlations. When there is a good DOC vs. MODIS relationship, the MODIS index seems to rise and fall shortly before the DOC measurements, indicating a “lag time.” When MODIS indices have the best correlation coefficients with DOC variability they are the NDVI and EVI.

12. Future Work In order to better examine DOC vs. MODIS correlations regression trees should be developed (eg. Xiao et al., 2008) to account for things such as land cover, wetlands, discharge events, droughts, etc. Other sites outside of the USGS NAWQA program should be investigated in the same manner. (In progress) Field measurements in smaller headwater basins should be established to ensure a terrestrial signal is being obtained to compare to terrestrial MODIS products. (In progress) Other MODIS indices like Gross Primary Production (GPP) and Land Surface Water Index (LSWI) should be considered.

13. Acknowledgements UNH EOS Staff Ben Curran Stanley Glidden George Hurtt Richard Lammers Michael Routhier

14. References Water quality data obtained from USGS NAWQA web site: http://water.usgs.gov/nawqa/http://water.usgs.gov/nawqa/ MODIS data obtained from: http://daac.ornl.gov/MODIS/http://daac.ornl.gov/MODIS/ Aiken, G. and M. Reddy (2002). Interactions of mercury with dissolved organic carbon in the Florida Everglades. U.S. Dept. of Interior Fact Sheet. USGS. Dittman, J. A., J. B. Shanley, C. T. Driscoll, G. R. Aiken, A. T. Chalmers and J. E. Towse (2009). Ultraviolet absorbance as a proxy for total dissolved mercury in streams. Environmental Pollution, 157: 1953-1956. Fahey, T. J., T. G. Siccama, C. T. Driscoll, G. E. Likens, J. Campbell, C. E. Johnson, J. J. Battles, J. D. Aber, J. J. Cole, M. C. Fisk, P. M. Groffman, S. P. Hamburg, R. T. Holmes, P. A. Schwarz, and R. D. Yanai (2005), The biogeochemistry of carbon at Hubbard Brook, Biogeochemistry, 75, 109-176. Freeman C., C.D. Evans, D.T. Monteith, B. Reynolds, and N. Fenner (2001). Export of organic carbon from peat soils. Nature, 412: 785. Singer, P. C. (1999). Humic substances as precursors for potentially harmful disinfection by-products. Water Science Technology, 40: 25-30. Striegl, R., G.R. Aiken, M. Dornblaser, P. Raymond, and K. Wickland (2005). A decrease in discharge-normalized DOC export by the Yukon River during summer and autumn. Geophysical Research Letters, 32: L21413, doi:10.1029/2005GL024413. Worrall, F., and T. P. Burt (2007), Flux of dissolved organic carbon from UK rivers, Global Biogeochemical Cycles, 21. Xiao, J. et al. (2008), Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data. Agricultural and Forest Meteorology, 148, 1827-1847.