Characterizing the spatial correlation of daily streamflows. Issue 2 (25th February 2017)

• Record Type: Journal Article
• Authors: Betterle, A.; Schirmer, M.; Botter, G.
• Is Part Of: Water resources research. Volume 53:Issue 2(2017)
• Page Start: 1646
• Page End: 1663
• Publication Date: 2017-02-25
• Subjects: hydrology -- streamflows correlation -- flows spatial variability -- flows seasonal variability -- stochastic hydrology -- water resources; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2016WR019195
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: In this study we propose an analytical framework to estimate the spatial correlation of daily flows at two arbitrary locations within a given hydrologic district or river basin. The method builds on the description of the coupled streamflow dynamics at the outlet of two catchments, which are represented as correlated shot noises forced by Poisson rainfall. Novel analytical expressions for the spatial correlation of discharge are derived using a limited number of parameters that encapsulate effective precipitation regime and catchment drainage rates. The method is suited to describe how heterogeneity of climate and landscape features impact the spatial and temporal variability of flow regimes along river systems. The analysis suggests that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, unless the drainage rates of the two catchments differ by almost one order of magnitude. The method also portrays how the topological arrangement of the two outlets along the river network influences the underlying streamflow correlation and shows how nested catchments tend to maximize the spatial correlation of flow regimes. To demonstrate the potential of the tool, the model is tested on a set of 16 catchments belonging to a 120, 000 km 2 region of the United States. The application evidences satisfactory performance in reproducing the observed spatial correlation of daily streamflows among the study sites ( RMSE < 0.1). The approach provides a clue for the characterization of water availability in space at seasonal time scale, with implications for water resources assessment, risk prevention, and ecological studies. Plain Language Summary: The importance of freshwater is not limited to drinking water. Water is crucial to produce sustainable energy, to support recreational activities along rivers, agriculture and industry, as well as to supply adequate transportation networks. Freshwater environments represent the elective habitat of many plants and fishes, and they contribute significantly to global‐scale biodiversity. The understanding of the water cycle, namely: when, where and how much water is available in rivers ‐ is therefore a crucial issue for a sustainable use of water resources. In this study we develop an analytical method to quantify similarities between the daily flows in two arbitrary locations belonging to one or more rivers. This requires to quantify what are the major climatic and landscape characteristics that control rivers flows. Second, it has to be quantified how these features affect similarity (i.e. synchronicity) of flow records at two arbitrary locations. This work represents a tool to improve our ability to quantify water resources in space and time, providing a theoretical basis to develop strategies for a wiser use of water in the era of climate change. Key Points: Novel analytical expressions for the spatial correlation of discharge are derived using a process‐based stochastic formulation The method describes how heterogeneity of climate and landscape impact the spatial variability of flow regimes The method shows how nested catchments tend to maximize the spatial correlation of flow regimes