Patterns of streamflow regimes along the river network: The case of the Thur river. (July 2017)

• Record Type: Journal Article
• Authors: Doulatyari, Behnam; Betterle, Andrea; Radny, Dirk; Celegon, Elisa Alessi; Fanton, Pietro; Schirmer, Mario; Botter, Gianluca
• Is Part Of: Environmental modelling & software. Volume 93(2017)
• Page Start: 42
• Page End: 58
• Publication Date: 2017-07
• Subjects: Geo-database -- Streamflow regime -- Stochastic model -- Flow duration curve -- Physically-based -- River network; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.03.002
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: A modeling framework for point-wise prediction of the probability density function and flow duration curve of streamflows along complex river networks is presented. The predictions are based on catchment-scale climatic and morphological features, without calibration on observed discharge time-series. The framework was applied to a test basin in north-eastern Switzerland, and relevant flow statistics were validated at six sub-catchment outlets with satisfactory results. Spatial patterns of flow regime exhibit a strong climatic signature, mostly driven by reduced rainfall depths and increasing effective rainfall frequency in the downstream areas. The increasing non-linearity of the catchment response with contributing area is reflected by the observed increase in the recession parameters along the main river channel. This framework offers a novel approach for assessing the spatial patterns of streamflows based on limited information, which is important for evaluation of human and ecological functions in riverine systems. Highlights: Process based framework for predicting basin-scale spatial variability of flow regimes. Flow regimes patterns are the by-product of climate gradients and network structure. Hydrologic response becomes more non-linear at larger spatial scales.