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Evaluating the impact of satellite soil moisture data as an additional component in the calibration of a conceptual hydrological model Cover

Evaluating the impact of satellite soil moisture data as an additional component in the calibration of a conceptual hydrological model

Open Access
|Nov 2024

Abstract

This study proposes a new method for dividing a catchment with the aim of testing it in the calibration process of a conceptual hydrological model. The new catchment division is reflected in having different land cover zones and the input data prepared in a semi-distributed way. This study also explores the impact of satellite soil moisture data when multi-objective calibration is used with the land cover zone divisions of a catchment while assigning different weights to runoff ranging from 0% to 100% (with a 0.05 step). The results indicate that using a weight range of 60% to 80% on a runoff provides optimal results, bettering both the runoff model’s efficiency and soil moisture correlation. For further validation of the internal parameters and processes, the field capacity and evapotranspiration of the catchment were monitored. In regions with specially limited in-situ soil moisture data, satellite-derived data can contribute as an scarce additional component of the land cover division that can point out areas of the most reliable soil moisture information.

DOI: https://doi.org/10.2478/johh-2024-0026 | Journal eISSN: 1338-4333 | Journal ISSN: 0042-790X
Language: English
Page range: 436 - 446
Submitted on: Sep 4, 2024
Accepted on: Oct 17, 2024
Published on: Nov 21, 2024
Published by: Slovak Academy of Sciences, Institute of Hydrology; Institute of Hydrodynamics, Czech Academy of Sciences, Prague
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Milica Aleksić, Juraj Parajka, Patrik Sleziak, Kamila Hlavčová, Michaela Danáčová, published by Slovak Academy of Sciences, Institute of Hydrology; Institute of Hydrodynamics, Czech Academy of Sciences, Prague
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.