Abstract
Previous research in agricultural catchments showed that past inputs of nitrate continue to influence present observations and future characteristics of nitrate concentrations in stream water for a long period of time. This persistence manifests itself as a “memory effect” with a prolonged response of stream water nitrate levels to reductions of nitrate inputs on the catchment scale. The question we attempt to resolve is whether such a memory effect also exists in mountainous catchments with a snowmelt-dominated runoff regime. We analyzed long-term records (∼20 years) of nitrate-nitrogen concentrations measured in stream at three stations on the upper Váh River (Slovakia). Applying spectral analysis and detrended fluctuation analysis, we found a varying degree of persistence between the three analyzed sites. With increasing catchment area, the fluctuation scaling exponents generally increased from 0.77 to 0.93 (fluctuation exponents above 0.5 are usually considered as a proof of persistence while values close to 0.5 indicate “white” uncorrelated noise). The nitrate-nitrogen signals temporally scaled as a power-low function of frequency (1/f noise) with a strong annual seasonality. This increase in persistence might be attributable to the catchment areas upstream the sampling sites. These results have important implications for water quality management. In areas where reduction of nitrate in surface waters is imposed by legislation and regulatory measures, two catchments with different persistence properties may not respond to the same reduction of sources of nitrogen at the same rate.
Similar content being viewed by others
References
Bashan, A., Bartch, R., Kantelhardt, J. W., & Havlin, S. (2008). Comparison of detrending methods for fluctuation analysis. Physica A, 387, 5080–5090.
Burt, T. P., Howden, N. J. K., Worrall, F., & Whelan, M. J. (2008). Importance of long-term monitoring for detecting environmental change: lessons from a lowland river in south east England. Biogeosciences Discussions, 5, 2369–2379.
Burt, T. P., Howden, N. J. K., Worrall, F., & McDonnell, J. J. (2010). On the value of long-term, low-frequency water quality sampling: avoiding throwing the baby out with the bathwater. Hydrological Processes. doi:10.1002/hyp.7961.
de Wit, H. A., Hindar, A., & Hole, L. (2008). Winter climate affects long-term trends in stream water nitrate in acid-sensitive catchments in southern Norway. Hydrology and Earth System Sciences, 12, 393–403.
Fleming, S. W., Lavenue, A. M., Aly, A. H., & Adams, A. (2002). Practical applications of spectral analysis to hydrological time series. Hydrological Processes, 16, 565–574.
Ganse A (2006) Applied Physics Laboratory, University of Washington, Seattle. Two-phase straight-line regression code. Available at: http://staff.washington.edu/aganse
Godsey, S. E., Aas, W., Clair, T. A., de Wit, H. A., Fernandez, I. F., et al. (2010). Generality of fractal 1/f scaling in catchment tracer time series, and its implications for catchment travel time distributions. Hydrological Processes, 24, 1660–1671.
Haag, D., & Kaupenjohann, M. (2000). Landscape fate of nitrate fluxes and emissions in Central Europe—a critical review of concepts, data, and models for transport and retention. Agriculture, Ecosystems and Environment, 86, 1–21.
Holko, L. (1995). Stable environmental isotopes of 18O and 2H in hydrological research of mountainous catchments. Journal of Hydrology and Hydromechanics, 43, 249–274.
Holko, L., Kostka, Z., Lichner, L., & Píš, V. (2006). Variation of nitrates in runoff from mountain and rural areas. Biologia, 61(19), 270–274.
Hurst, H. E. (1951). Long-term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers, 116, 770–799.
Jones, A. L., & Smart, P. L. (2005). Spatial and temporal changes in the structure of groundwater nitrate concentration time series (1935–1999) as demonstrated by autoregressive modeling. Journal of Hydrology, 310, 201–215.
Kantelhardt, J. W., Zschiegner, S. A., Koscielny-Bunde, E., Bunde, A., Havlin, S., & Stanley, H. E. (2002). Multifractal detrended fluctuation analysis of nonstationary time series. Physica A, 316. doi:10.1016/S0378-4371(02), 01383-3.
Keener, V. W., Feyereisen, G. W., Lall, U., Jones, J. W., Bosch, D. D., & Lowrance, R. (2010). El-Nino/Southern Oscillation (ENSO) influences on monthly NO3 load and concentration, stream flow and precipitation in the Little River Watershed, Tifton, Georgia (GA). Journal of Hydrology, 381, 352–363.
Király, A., Bartos, I., & Jánosi, I. M. (2006). Correlation properties of daily temperature anomalies over land. Tellus, 58, 593–600.
Kirchner, J. W., Feng, X., & Neal, C. (2000). Fractal stream chemistry and its implications for contaminant transport in catchments. Nature, 403, 524–527.
Kirchner, J. W., Feng, X., & Neal, C. (2001). Catchment-scale advection and dispersion as a mechanism for fractal scaling in stream tracer concentrations. Journal of Hydrology, 254, 82–101.
Koirala, S., Gentry, R. W., Perfect, E., Schwartz, J. S., & Sayler, G. S. (2008). Temporal variation and persistence of bacteria in streams. Journal of Environmental Quality, 37, 1559–1566.
Koirala, S., Gentry, R. W., Mulholland, P. J., Perfect, E., & Schwartz, J. S. (2010). Time and frequency domain analysis of high-frequency hydrologic and chloride data in an east Tennessee watershed. Journal of Hydrology, 387, 256–264.
Kopáček, J., Veselý, J., & Stuchlík, E. (2001). Sulphur and nitrogen fluxes and budgets in the Bohemian Forest and Tatra Mountains during the Industrial Revolution (1850–2000). Hydrology and Earth System Sciences, 5, 391–405.
Koscielny-Bunde, E., Kantelhardt, J. W., Braun, P., Bunde, A., & Havlin, S. (2006). Long-term persistence and multifractality of river runoff records: detrended fluctuation analysis. Journal of Hydrology, 322, 120–137.
Kovács, J., Hatvani, I. G., Korponai, J., & Kovácsné, S. I. (2010). Morlet wavelet and autocorrelaiton analysis of long term data series of the Kis-Balaton Water Protection System (KBWPS). Ecological Engineering, 36, 1469–1477.
Lomb, N. R. (1976). Least-squares frequency analysis of unequally spaced data. Astrophysics Space Science, 39, 447–462.
Matsoukas, C., Islam, S., & Rodriguez-Iturbe, I. (2000). Detrended fluctuation analysis of rainfall and stremflow time series. Journal of Geophysical Research-Atmosphere, 105(D23), 29165–29172.
McGuire, K. J., & McDonnell, J. J. (2006). A review and evaluation of catchment transit time modeling. Journal of Hydrology, 330, 543–563.
McGuire, K. J., DeWalle, D. R., & Gburek, W. J. (2002). Evaluation of mean residence time in subsurface waters using oxygen-18 fluctuations during drought conditions in the mid-Appalachians. Journal of Hydrology, 261, 132–149.
Onderka, M., Pekárová, P., Miklánek, P., Halmová, D., & Pekár, J. (2009). Examination of the dissolved inorganic nitrogen budget in three experimental microbasins with contrasting land cover—a mass balance approach. Water, Air, and Soil Pollution, 210, 221–230.
Paonita, A. (2010). Long-range correlations and nonlinearity in geochemical time series of gas discharges from Mt. Etna, and changes with, and 2002–2003 eruptions. Nonlinear Processes in Geophysics, 17, 733–751.
Pekárová, P., Szolgay, J., et al. (2005). Changing hydrosphere and biosphere in the Hron and Váh Rivers in response to climate change (pp. 17–48). Bratislava: VEDA. in Slovak. ISBN 80-224-0884-0.
Peng, C. K., Havlin, S., Stanley, H. E., & Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos, 5(1), 82–87.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1992). Numerical recipes in C: The art of scientific computing (Secondth ed., pp. 577–579). Cambridge: Cambridge University Press.
Reddy, M. M., Schuster, P., Kendall, C., & Reddy, M. B. (2006). Characterization of surface and ground water d18O seasonal variations and its use for estimating groundwater residence times. Hydrological Processes, 20, 1753–1772.
Scargle, J. D. (1982). Studies in astronomical time series analysis. II—statistical aspects of spectral analysis of unevenly spaced data. The Astrophysical Journal, 263, 835–853.
Scher, H., Margolin, G., Metzler, R., Klafter, J., & Berkowitz, B. (2002). The dynamical foundation of fractal stream chemistry: the origin of extremely long retention times. Geophysical Research Letters, 29(5). doi:10.1029/2001GL014123.
Schilling, K., Yhank, Y-K., Hill, D. R., Jones, C. S., Wolter, C. F. (2009). Journal of Hydrology, 365, 79–85.
Shi, K., Liu, C. Q., Ai, N. S., & Zhang, X. H. (2008). Using three methods to investigate time-scaling properties in air pollution indexes time series. Nonlinear Analysis: Real World Applications, 9(2), 693–707.
Shi, K., Liu, C. Q., Huang, Z. W., Zhang, B., & Su, Y. (2010). Comparative analysis of time-scaling properties about water pH in Poyang Lake Inlet and Outlet on the basis of fractal methods. Water Science and Technology, 618, 2113–2118.
Tessier, Y., Lovejoy, S., Hubert, P., Schertzer, D., & Pecknold, S. (1996). Multifractal analysis and modeling of rainfall and river flows and scaling, causal transfer functions. Journal of Geophysical Research, 101, 427–440.
Tetzlaff, D., Malcolm, I. A., & Soulby, C. (2007). Influcence of forestry, environmental change and climatic variability on the hydrology, hydrochemistry and residence times of upland catchments. Journal of Hydrology, 346, 93–111.
Veselý, J., Majer, V., & Norton, S. A. (2002). Heterogeneous response of central European streams to decreased acidic atmospheric deposition. Environmental Pollution, 120, 275–281.
Wang, G., Jiang, T., Blender, R., & Fraedrich, K. (2008). Yangtze 1/f discharge variability and the interacting river-lake system. Journal of Hydrology, 351, 230–237.
Wolock, D. M., Fan, J., & Lawrence, G. B. (1997). Effects of basin size on low-flow stream chemistry and subsurface contact time in the Neversink River watershed, New York. Hydrological Processes, 11, 1273–1286.
Worrall, F., & Burt, T. P. (1998). A univariate model of river water nitrate time series. Journal of Hydrology, 214, 74–90.
Worrall, F., & Burt, T. P. (1999). A univariate model of river water nitrate time series. Journal of Hydrology, 214, 74–90.
Worrall, F., Swank, W. T., & Burt, T. P. (2003). Changes in stream nitrate concentrations due to land management practices, ecological succsession, and climate: developing a systems approach to integrated catchment response. Water Resources Research, 39(7), 1177.
Zhang, Y.-K., & Schilling, K. (2005). Temporal variations and scaling of streamflow and baseflow and their nitrate-nitrogen concentrations and loads. Advances in Water Resources, 28, 701–710.
Zhang, Q., Xu, C. Y., Chen, Y. D., & Yu, Z. (2008). Multifractal detrended fluctuation analysis of streamflow series of the Yangtze River, China. Hydrological Processes, 22, 4997–5003.
Acknowledgments
This study was supported by the National Research Fund, Luxembourg (PDR-09-057), and co-funded under the Marie Curie Actions of the European Commission (FP7-COFUND). All empirical data were kindly provided by the Slovak Hydrometeorological Institute.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Onderka, M., Mrafková, L., Krein, A. et al. Long-term Persistence of Stream Nitrate Concentrations (Memory Effect) Inferred from Spectral Analysis and Detrended Fluctuation Analysis. Water Air Soil Pollut 223, 241–252 (2012). https://doi.org/10.1007/s11270-011-0854-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11270-011-0854-1