Hydrological modeling of mountain catchments in Central Asia
type: CreativeWork
description: Water resources from Central Asia’s mountain regions have a high relevance for the water supply of the water scarce lowlands. A good understanding of the water cycle in these mountain regions is therefore needed to develop water management strategies. Hydrological modeling helps to improve our knowledge of the regional water cycle, and it can be used to gain a better understanding of past changes or estimate future hydrologic changes in view of projected changes in climate. However, due to the scarcity of hydrometeorological data, hydrological modeling for mountain regions in Central Asia involves large uncertainties. Addressing this problem, the first aim of this thesis was to develop hydrological modeling approaches that can increase the credibility of hydrological models in data sparse mountain regions. This was achieved by using additional data from remote sensing and atmospheric modeling. It was investigated whether spatial patterns from downscaled reanalysis data can be used for the interpolation of station-based precipitation data. This approach was compared to other precipitation estimates using a hydrologic evaluation based on hydrological modeling and a comparison of simulated and observed discharge, which demonstrated a generally good performance of this method. The study further investigated the value of satellite-derived snow cover data for model calibration. Trade-offs of good model performance in terms of discharge and snow cover were explicitly evaluated using a multiobjective optimization algorithm, and the results were contrasted with single-objective calibration and Monte Carlo simulations. The study clearly shows that the additional use of snow cover data improved the internal consistency of the hydrological model. In this context, it was further investigated for the first time how many snow cover scenes were required for hydrological model calibration. The second aim of this thesis was the application of the hydrological model in order to invest…
abstract: Water resources from Central Asia’s mountain regions have a high relevance for the water supply of the water scarce lowlands. A good understanding of the water cycle in these mountain regions is therefore needed to develop water management strategies. Hydrological modeling helps to improve our knowledge of the regional water cycle, and it can be used to gain a better understanding of past changes or estimate future hydrologic changes in view of projected changes in climate. However, due to the scarcity of hydrometeorological data, hydrological modeling for mountain regions in Central Asia involves large uncertainties. Addressing this problem, the first aim of this thesis was to develop hydrological modeling approaches that can increase the credibility of hydrological models in data sparse mountain regions. This was achieved by using additional data from remote sensing and atmospheric modeling. It was investigated whether spatial patterns from downscaled reanalysis data can be used for the interpolation of station-based precipitation data. This approach was compared to other precipitation estimates using a hydrologic evaluation based on hydrological modeling and a comparison of simulated and observed discharge, which demonstrated a generally good performance of this method. The study further investigated the value of satellite-derived snow cover data for model calibration. Trade-offs of good model performance in terms of discharge and snow cover were explicitly evaluated using a multiobjective optimization algorithm, and the results were contrasted with single-objective calibration and Monte Carlo simulations. The study clearly shows that the additional use of snow cover data improved the internal consistency of the hydrological model. In this context, it was further investigated for the first time how many snow cover scenes were required for hydrological model calibration. The second aim of this thesis was the application of the hydrological model in order to invest…
author: Düthmann, Doris
keywords: hydrological modeling, mountain hydrology, precipitation interpolation, multiobjective calibration, remote sensing data, trend attribution, hydrologische Modellierung, Gebirgshydrologie, Niederschlagsinterpolation, multiobjektive Kalibrierung, Fernerkundungsdaten, Trendattributierung
date published: 2015-06-16
date modified: 2026-07-24T03:51:50Z
provider: Universität Potsdam - Diss
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Universität Potsdam