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Analytical modeling of reach-scale and network-scale dynamics of flow regimes
Auteur(s)
Doulatyari, Behnam
Date de parution
2015
Mots-clés
Résumé
Sustainable management of river networks is an important topic in hydrology today. Rivers and streams are a significant source of drinking water, as well as energy production and other human valued services. Spatial and temporal patterns of flow regimes have a significant impact on ecological and anthropogenic uses of fresh water within entire river basins. Developing tools for management of streamflows hinges on a deep understanding of the hydrologic form and function at the basin scale, and the interplay between the key driving processes. This study is centered on providing a process-based description of flow regimes and their spatial variability, with the purpose of developing tools for catchment-scale management of streamflows and studying ecologically relevant processes. Simple methods that allow a spatially explicit characterization of flow regimes with limited data and calibration requirements are extremely valuable for efficient management of water resources in data scars regions. <br> In order to meet these research goals, a modeling method was developed in this thesis for the prediction of streamflow regimes, based solely on catchment-scale climatic and morphological features. The method was tested in eleven test catchment distributed evenly in the United States, east of the rocky mountains. Considering the minimal data requirements (rainfall, potential evapotranspiration and digital elevation maps), the method was capable of capturing the patterns of observed streamflows reasonably well in all cases. This method was then expanded and applied point-wise along the river network of a test basin in north eastern Switzerland. A custom geo-database and a Web GIS platform were created for the management of data and model application. Predicted values of relevant flow statistics were validated at six subcatchment outlets, where discharge data was available, with satisfactory results. Strong seasonal signature of rainfall was identified as the dominant driving force of flow regimes. The seasonal variability of the streamflows showed a complex pattern, influenced by climatic gradients and by the increasing variability of hydrologic response observed at larger scales. The modeling method and data management framework presented here offer a novel and robust approach for assessing the spatial patterns of streamflows based on limited information.<br> The spatial and temporal variability of river flows bear important influence on ecological processes at the reach and basin scales. In this thesis, the effect of streamflow dynamics on riparian vegetation growth was studied using a lumped stochastic framework which explicitly incorporates the randomness of exposure and submersion periods implied by the streamflow variability, and links such a randomness to climatic and landscape properties. The framework was applied to the terminal reach of two catchments characterized by contrasting flow regimes. The results illustrated the role of vegetation specific traits and water availability as limiting factors, and flow regime variability as the driver for patterns of riparian vegetation biomass along the river reach.
Notes
Thèse de doctorat : Université de Neuchâtel, 2015
Identifiants
Type de publication
doctoral thesis
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