Article : Quantifying urbanization-associated changes in terrestrial hydrologic system memory
Authors : Domański, B.M.Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland, firstname.lastname@example.org, Gnyp, A.Carpathian Branch of Subbotin Institute of Geophysics, National Academy of Sciences of Ukraine, Lviv, Ukraine, email@example.com, Shanker, D.Department of Earthquake Engineering, Indian Institute of Technology Roorkee, Roorkee, India, firstname.lastname@example.org, Zheng, H.Geological Science Department, University of Saskatchewan, Saskatoon, Canada, email@example.com, Majewska, Z.AGH University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection, Kraków, Poland, firstname.lastname@example.org, Dooge, J.C.I.Centre for Water Resources Research, University College, Dublin, email@example.com, Fleming, S.W.Meteorological Service of Canada, Vancouver, Canada, firstname.lastname@example.org,
Abstract : A common feature of watershed urbanization is increased hydrograph ‘flashiness’, whereby river discharge fluctuations grow more erratic. Such changes might be intuitively interpreted as a decrease in watershed-scale hydrologic system memory. Here, I investigate this hypothesis through a paired-catchment experiment. The serial correlation coefficient, a common metric of short-term time series memory, is applied to daily winter streamflow data from urbanizing and rural watersheds in the Puget Sound lowland of Washington State, USA. Statistical comparisons confirm that this metric shows highly significant decreases over time in the catchment undergoing land use change, but not in the control watershed, which remains rural over the hydrometric record. Moreover, the mean serial correlation coefficients are statistically indistinguishable between the two catchments over the early period of record, when both watersheds are largely rural, whereas the system memory is far weaker in the urbanized stream relative to the rural stream over the late period, following land use change in the former. The results appear readily interpretable in terms of the physical hydrologic changes typically associated with urbanization. The serial correlation coefficient thus appears to be an instructive measure of urbanization impacts for small streams in this region.
Bibliography : Arnold, C.L., and C.J. Gibbons, 1996, Impervious surface coverage: the emergence of a key environmental indicator, J. Am. Plan. Assoc. 62, 243-258.
Astatkie, T., D.G. Watts and W.E. Watt, 1997, Nested threshold autoregressive (NeTAR) models, International Journal of Forecasting 13, 105-116.
Bras, R.L., and I. Rodríguez-Iturbe, 1993, Random Functions and Hydrology, Dover Publications, New York.
Chatfield, C., 1996, The Analysis of Time Series, 5th Ed., Chapman and Hall, London.
Chen, J., and P. Kumar, 2002, Role of terrestrial hydrologic memory in modulating ENSO impacts in North America, J. Climate 15, 3569-3585.
Chi, M., E. Neal and G.K. Young, 1973, Practical applications of fractional Brownian motion and noise in synthetic hydrology, Water Resour. Res. 9, 1523-1533.
Chiew, F.H.S., and T.A. McMahon, 2002, Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability, Hydrol. Sci. J. 47, 505-522.
Connor, J.T., R.D. Martin and L.E. Atlas, 1994, Recurrent neural networks and robust time series prediction, IEEE Trans. Neural Networks 5, 240-254.
Dingman, S.L., 1994, Physical Hydrology, Prentice-Hall, Englewood Cliffs.
Farahmand, T., S.W. Fleming and E.J. Quilty, 2007, Detection and visualization of storm hydrograph changes under urbanization: an impulse response approach, J. Environ. Manag. (in press).
Fiering, M.B., and B.B. Jackson, 1971, Synthetic Streamflows, Water Resources Monograph No. 1, American Geophysical Union, Washington DC.
Fleming, S.W., and G.K.C. Clarke, 2002, Autoregressive noise, deserialization, and trend detection and quantification in annual river discharge time series, Canad. Water Resour. J. 27, 335-354.
Galster, J.C., F.J. Pazzaglia, B.R. Hargreaves, D.P. Morris, S.C. Peters and R.N. Weisman, 2006, Effects of urbanization on watershed hydrology: the scaling of discharge with drainage area, Geology 34, 713-716.
Granger, C.W.J., and R. Joyeux, 1980, An introduction to long-memory time series models and fractional differencing, J. Time Series Analysis 1, 15-29.
Goonetilleke, A., E. Thomas, S. Ginn and D. Gilbert, 2005, Understanding the role of land use in urban stormwater quality management, Journal of Environmental Management 74, 31-42.
James, L.D., and W.O. Thompson, W.O., 1970, Least squares estimation of constants in a linear recession model, Water Resour. Res. 6, 1062-1069.
Konrad, C.P., and D.B. Booth, 2002, Hydrologic Trends Associated with Urban Development for Selected Streams in the Puget Sound Basin, Western Washington, USGS Water Resources Investigations Report 02-4040, US Geological Survey, Tacoma, Washington.
Konrad, C.P., D.B. Booth and S.J. Burges, 2005, Effects of urban development in the Puget Lowland, Washington, on interannual streamflow patterns: consequences for channel form and streambed disturbance, Water Resour. Res. 41, W07009, doi:10.1029/ 2005WR004097.
Leith, R.M., and P.H. Whitfield, 1996, Intervention modelling of effects of urbanization on a small watershed, Canad. Water Resour. J. 21, 387-392.
Leith, R.M., and P.H. Whitfield, 2000, Some effects of urbanization on streamflow records in a small watershed in the lower Fraser Valley, B.C., Northwest Science 74, 69-75.
Leopold, L.B., 1968, Hydrology for Urban Land Planning, USGS Circular 554, US Geological Survey, Reston, Virginia.
Maier, H.R., and G.C. Dandy, 2000, Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications, Environ. Modelling and Software 15, 101-124.
May, C.W., 1999, The cumulative effects of urbanization on small streams in the Puget Sound Lowland Ecoregion, 4th Puget Sound Research Conference, Seattle, Washington. Available online at: www.psat.wa.gov/Publications/ 98_proceedings/pdfs/1a_may.pdf.
OFM, 2006, Historical Data Set: Federal Census Decennial Population Counts for Washington State, Counties, and Cities, 1890 to 2000, Office of Financial Management, State of Washington, Olympia, Washington. Available online at: http://www.ofm.wa.gov/pop/decseries/default.asp.
Salas, J.D., and R.A. Pielke, 2003, Stochastic characteristics and modeling of hydroclimatic processes. In: T.D. Potter and B.R. Colman (eds.), “Handbook of Weather, Climate, and Water”, Wiley, New York.
Salas, J.D., J.W. Delleur, V. Yevjevich and W.L. Lane, 1980, Applied Modeling of Hydrologic Time Series, Water Resour. Publs., Littleton.
Skoien, J.O., and G. Blöschl, 2003, Characteristic space scales and timescales in hydrology, Water Resour. Res. 39, doi: 10.1029/2002WR001736.
Stahl, K., and R.D. Moore, 2006, Influence of watershed glacier coverage on summer stream flow in British Columbia, Canada, Water Resour. Res. 42, doi: 10.1029/2006WR 005022.
Tallaksen, L.M., 1995, A review of baseflow recession analysis, J. Hydrology 165, 349-370.
USGS, 2006, Daily Streamflow for Washington, Washington NWISWeb, US Geological Survey, Tacoma, Washington. Available online at: http://nwis.waterdata.usgs.gov/wa/nwis/discharge.
Varotsos, C., and D. Kirk-Davidoff, 2006, Long-memory processes in ozone and temperature variations at the region 60°S-60°N, Atmospheric Chemistry and Physics 6, 4093-4100.
von Storch, H., and F.W. Zwiers, 1999, Statistical Analysis in Climate Research, Cambridge University Press, Cambridge.
Whitfield, P.H., 1998, Reporting scale and the information content of streamflow data, Northwest Science 72, 42-51.
Whitfield, P.H., and A. Covic, 1998, Memory and the statistical independence of rainfall and runoff events, Canadian Water Resour. J. 23, 21-29.
Qute : Domański, B.M. ,Gnyp, A. ,Shanker, D. ,Zheng, H. ,Majewska, Z. ,Dooge, J.C.I. ,Fleming, S.W. ,Fleming, S.W. , Quantifying urbanization-associated changes in terrestrial hydrologic system memory. Acta Geophysica Vol. 55, no. 3/2007