Variability in Canadian Seasonal Streamflow Information and Its Implication for Hydrometric Network Design

AbstractHydrologic extremes such as severe storms, floods, and droughts are inherently seasonal in nature and remain the main concern in designing hydrometric networks. In general, hydrometric networks have been designed without paying particular attention to the effect of seasonal streamflow information (SSI) at gauging stations on the efficiency of the hydrometric networks. This paper evaluates the effect of SSI on streamflow networks based on nonparametric implementation of entropy theory using the kernel density approach for estimating the mutual information between gauging stations on a seasonal basis. Overall, it is shown that the SSI of individual stations is season dependent and the efficiency of the streamflow network is also season dependent, therefore the effect of seasonality should be incorporated in future hydrometric network design. This methodology was applied at five river basins in Canada and its role for network design is discussed.

[1]  Richard M. Vogel,et al.  Impact of Streamflow Persistence on Hydrologic Design , 2002 .

[2]  G. Tasker,et al.  Entropy and generalized least square methods in assessment of the regional value of streamgages , 2003 .

[3]  V. Singh,et al.  THE USE OF ENTROPY IN HYDROLOGY AND WATER RESOURCES , 1997 .

[4]  M H Nour,et al.  Geostatistical mapping of precipitation: implications for rain gauge network design. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[5]  Jurgen D. Garbrecht,et al.  Trends in Precipitation, Streamflow, and Evapotranspiration in the Great Plains of the United States , 2004 .

[6]  Sanjiv Kumar,et al.  Streamflow trends in Indiana: Effects of long term persistence, precipitation and subsurface drains , 2009 .

[7]  A. Lobbrecht,et al.  Information theory–based approach for location of monitoring water level gauges in polders , 2010 .

[8]  George Ostrouchov,et al.  Nonlinear statistics reveals stronger ties between ENSO and the tropical hydrological cycle , 2006 .

[9]  Paulin Coulibaly,et al.  Hydrometric network evaluation for Canadian watersheds , 2010 .

[10]  Moon,et al.  Estimation of mutual information using kernel density estimators. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[11]  New Approach to Identify Trend Pattern of Streamflows , 2010 .

[12]  V. Singh,et al.  Changes in extreme precipitation in Texas , 2010 .

[13]  Z. Şen.  Innovative Trend Analysis Methodology , 2012 .

[14]  Mehmet Özger,et al.  Autorun Persistence of Hydrologic Design , 2003 .

[15]  Vijay P. Singh,et al.  Seasonal streamflow extremes in Texas river basins: Uncertainty, trends, and teleconnections , 2011 .

[16]  Paulin Coulibaly,et al.  Developments in hydrometric network design: A review , 2009 .

[17]  Paulin Coulibaly,et al.  Comparison of Interpolation, Statistical, and Data-Driven Methods for Imputation of Missing Values in a Distributed Soil Moisture Dataset , 2014 .

[18]  Paulin Coulibaly,et al.  Spatial and Temporal Variability of Canadian Seasonal Streamflows , 2005 .

[19]  Vijay P. Singh,et al.  Evaluation of rainfall networks using entropy: I. Theoretical development , 1992 .

[20]  I. Rodríguez‐Iturbe,et al.  The design of rainfall networks in time and space , 1974 .

[21]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[22]  J. Stedinger,et al.  Regional Hydrologic Analysis: 1. Ordinary, Weighted, and Generalized Least Squares Compared , 1985 .

[23]  Cedric Laize,et al.  Integration of spatial datasets to support the review of hydrometric networks and the identification of representative catchments , 2004 .

[24]  Leonardo Alfonso,et al.  Information theory applied to evaluate the discharge monitoring network of the Magdalena River , 2013 .

[25]  David W. Scott,et al.  Multivariate Density Estimation: Theory, Practice, and Visualization , 1992, Wiley Series in Probability and Statistics.

[26]  P. Mulholland,et al.  Hurst Analysis of Hydrologic and Water Quality Time Series , 2011 .

[27]  Bellie Sivakumar,et al.  Nonlinear dynamics and chaos in hydrologic systems: latest developments and a look forward , 2009 .

[28]  V. Singh,et al.  Trend and persistence of precipitation under climate change scenarios for Kansabati basin, India , 2009, Hydrological Processes.

[29]  Ashish Sharma,et al.  Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 1 — A strategy for system predictor identification , 2000 .

[30]  Vijay P. Singh,et al.  Variability and Trend in Seasonal Precipitation in the Continental United States , 2013 .

[31]  A. Allen Bradley,et al.  RAINGAGE NETWORK DESIGN USING NEXRAD PRECIPITATION ESTIMATES 1 , 2002 .