New Brunswick hydrometric network analysis and rationalization

The availability of hydrometric data, as well as its spatial distribution, is important for water resources management. An overly dense network or an under developed network can cause inaccurate hydrological regional estimates. This study's objective is to propose a methodology for rationalizing a network, specifically the New Brunswick Hydrometric Network. A hierarchical clustering analysis allowed dividing the province into two regions (North and South), based on latitude and high flow timing. These groups were subsequently split separately into three homogeneous subgroups, based on the generalized extreme value (GEV) distribution shape parameter of each station for annual maximum flow series. An entropy method was then applied to compute the amount of information shared between stations, ranking each station's importance. A station with a lot of shared information is redundant (less important), whereas one with little shared information is unique (very important). The entropy method appears to be a use...

[1]  Ian C. Goulter,et al.  An approach to the rationalization of streamflow data collection networks , 1991 .

[2]  P. Coulibaly,et al.  Evaluation of Canadian National Hydrometric Network density based on WMO 2008 standards , 2013 .

[3]  B. Bobée,et al.  Generalized Extreme Value versus Halphen System: Exploratory Study , 2010 .

[4]  D. Beveridge,et al.  Multivariate analysis of the low-flow regimes in eastern Canadian rivers , 2011 .

[5]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[6]  Jean-Pierre Fortin,et al.  Use of principal component analysis to identify homogeneous precipitation stations for optimal interpolation , 1979 .

[7]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

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

[9]  Donald H. Burn,et al.  Hydrological information for sustainable development , 1997 .

[10]  Hui-Chung Yeh,et al.  Entropy and kriging approach to rainfall network design , 2011, Paddy and Water Environment.

[11]  B Khalil,et al.  Statistical approaches used to assess and redesign surface water-quality-monitoring networks. , 2009, Journal of environmental monitoring : JEM.

[12]  Upmanu Lall,et al.  Modeling multivariable hydrological series: Principal component analysis or independent component analysis? , 2007 .

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

[14]  D. Hannah,et al.  Large‐scale river flow archives: importance, current status and future needs , 2011 .

[15]  P. J. Pilon,et al.  CHALLENGES FACING SURFACE WATER MONITORING IN CANADA , 1996 .

[16]  B Khalil,et al.  A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations. , 2011, Journal of environmental monitoring : JEM.

[17]  R. Fisher,et al.  Limiting forms of the frequency distribution of the largest or smallest member of a sample , 1928, Mathematical Proceedings of the Cambridge Philosophical Society.

[18]  H. V. Groenewoud The climatic regions of New Brunswick: a multivariate analysis of meteorological data , 1984 .

[19]  Zal K. Davar,et al.  Hydrometric Network Evaluation: Audit Approach , 1990 .

[20]  Tahir Husain,et al.  HYDROLOGIC UNCERTAINTY MEASURE AND NETWORK DESIGN1 , 1989 .

[21]  Chao Li,et al.  Entropy theory‐based criterion for hydrometric network evaluation and design: Maximum information minimum redundancy , 2012 .

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

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

[24]  J. Stedinger,et al.  Generalized maximum‐likelihood generalized extreme‐value quantile estimators for hydrologic data , 2000 .

[25]  Tahir Husain Hydrologic Network Design Formulation , 1987 .