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Kriging in the design of streamflow sampling networks
Author(s) -
Villeneuve JeanPierre,
Morin Guy,
Bobee Bernard,
Leblanc Denis,
Delhomme JeanPierre
Publication year - 1979
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr015i006p01833
Subject(s) - kriging , variance (accounting) , streamflow , sampling (signal processing) , statistics , mathematics , estimation , environmental science , hydrology (agriculture) , econometrics , computer science , geography , geology , engineering , cartography , drainage basin , accounting , filter (signal processing) , systems engineering , geotechnical engineering , business , computer vision
Kriging is of particular interest in network design because of its ability to estimate streamflow values using existing stations. Another possibility offered by kriging is the estimation of variance reduction gained by addition of fictitious stations in regions of high variance. In this article we give a brief description of kriging theory as developed at the Ecole des Mines de Paris. In order to improve and optimize the Quebec streamflow recording network design we kriged specific streamflows with a given return period over the Quebec province, using the data observed at existing stations. For the evaluation of the given return period flow and its sampling variance at each gauged site we use the log Pearson type 3 distribution model. Kriging is an optimal estimation technique, in terms of minimum variance, and contrary to other methods it gives an estimation variance for any point in the kriged domain, which is essential in network design.