Spatial interpolation of mean monthly flow series by nonlinear correlation model applied in the Ibar river basin

Abstract

When providing hydrologic indicators needed for hydro power plant design, knowledge of mean monthly flows allows for estimation of majority of indicators. The paper deals with a problem of obtaining mean monthly flows at the location where flow observation data do not exist. The closest gauge station from the observation network is selected as an analogue location/basin. Since the selected gauge station observation period is rather short, the extension of the data set is achieved by generating synthetic mean monthly flow series by the nonlinear correlation method explained within the paper. Attention is paid to finding the best fit for correlation within the observation period. Four segmentation types of the correlation curve of transformed values are studied. Observed data are used for estimation of applied model quality i.e. spatial interpolation of surrounding gauge stations to the analogue station. At the selected hydro power plant location, synthetic series of mean monthly flow is calculated by scaling series from the analogue gauge station, using basin area ratio as scaling coefficient. Apart from mean annual flow and annual flow distribution, based on the synthetic mean monthly series, daily flow duration curve and maintenance flow were calculated.