Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/92311
Type of publication: Tezės kituose recenzuojamuose leidiniuose / Theses in other peer-reviewed publications (T1e)
Field of Science: Aplinkos inžinerija / Environmental engineering (T004)
Author(s): Vyčienė, Gitana;Grybauskienė, Vilda;Miseckaitė, Otilija
Title: Kriging methods as a tool to estimate spring flood peak discharge in ungauged watersheds in Lithuania
Is part of: Agrosym 2018 [elektroninis išteklius] : IX International Scientific Agriculture Symposium, Jahorina, 4-7 October 2018, Bosnia and Herzegovina: book of abstracts / University of East Sarajevo [et al.]. East Sarajevo : Faculty of Agriculture, 2018
Extent: p. 885-885
Date: 2018
Keywords: Ordinary Kriging;spring flood peak discharge;water gauging stations
ISBN: 9789997671851
Abstract: Responsible and efficient management of water resources relies on accurate hydrological data, but changing economic situation results inthe fact that natural researches are becoming more and more expensive. Decrease in network of water gauging stations leave many small watersheds ungagged and with no ability to assess and understand local hydrology. Ordinary Kriging might be used in order to assess the values between measuring points and to connect the hydrologic data with the other types of regional spatial information. Kriging algorithms use various mathematical functions for the spatial modeling of the variability of z values between known points. The parameters of these functions are then optimized for the best fit of the experimental semivariogram. The interpolated surface is then constructed using statistical conditions of unbiasedness and minimum variance. The objective of this study was to investigate the suitability and accuracy of ordinary kriging to predicted spring flood peak discharge 1% probability in ungagged watersheds. The study used data of 74 water gauging stations (WGS) on 55 rivers almost totally covering the area of Lithuania. It is concluded that ordinary kriging was useful for prediction of spring flood peak discharge data in ungauged watersheds in Lithuania. Applying the Ordinary Kriging selected all parameters with probability p=0.95.The model describedabout74 % of all investigated values
Internet: https://hdl.handle.net/20.500.12259/92311
Affiliation(s): Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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