Streamflow estimation using optimal regional dependency function |
| |
| Authors: | Abdüsselam Altunkaynak |
| |
| Institution: | Civil Engineering Department, Hydraulics Division, Istanbul Technical University, 34469 Istanbul, Turkey |
| |
| Abstract: | The determination of spatial dependency of regionalized variable (ReV) is important in engineering studies. Regional dependency function that leads to calculation of weighting coefficients is required in order to make regional or point‐wise estimations. After obtaining this dependency function, it is possible to complete missing records in the time series and locate new measurement station. Also determination of regional dependency function is also useful to understand the regional variation of ReV. Point Cumulative Semi‐Variogram (PCSV) is another methodology to understand the regional dependency of ReV related to the magnitude and the location. However, this methodology is not useful to determine the weighting coefficient, which is required to make regional and point‐wise estimations. However, in Point Semi‐Variogram (PSV) proposed here, weighting coefficient depends on both magnitude and location. Although the regional dependency function has a fluctuating structure in PSV approach, this function gradually increases with distance in PCSV. The study area is selected in Mississippi river basin with 38 streamflow stations used for PCSV application before. It is aimed to compare two different geostatistical models for the same data set. PSV method has an ability to determine the value of variable along with optimum number of neighbour stations and influence radius. PSV and slope PSV approaches are compared with the PCSV. It was shown that slope slope point semi‐variogram (SPSV) approaches had relative error below 5%, and PSV and PCSV methods revealed relative errors below 10%. Copyright © 2009 John Wiley & Sons, Ltd. |
| |
| Keywords: | streamflow point‐wise estimation geostatistical analysis optimal regional dependency function point semi‐variogram |
|
|
