Geomorphic signatures on Brutsaert base flow recession analysis

This paper addresses the signatures of catchment geomorphology on base flow recession curves. Its relevance relates to the implied predictability of base flow features, which are central to catchment-scale transport processes and to ecohydrological function. Moving from the classical recession curve analysis method, originally applied in the Finger Lakes Region of New York, a large set of recession curves has been analyzed from Swiss streamflow data. For these catchments, digital elevation models have been precisely analyzed and a method aimed at the geomorphic origins of recession curves has been applied to the Swiss data set. The method links river network morphology, epitomized by time-varying distribution of contributing channel sites, with the classic parameterization of recession events. This is done by assimilating two scaling exponents, β and bG, with |dQ/dt| â̂ Q β where Q is at-a-station gauged flow rate and N(l) â̂ N(l)â̂G(l)bG where l is the downstream distance from the channel heads receding in time, N(l) is the number of draining channel reaches located at distance l from their heads, and G(l) is the total drainage network length at a distance greater or equal to l, the active drainage network. We find that the method provides good results in catchments where drainage density can be regarded as spatially constant. A correction to the method is proposed which accounts for arbitrary local drainage densities affecting the local drainage inflow per unit channel length. Such corrections properly vanish when the drainage density become spatially constant. Overall, definite geomorphic signatures are recognizable for recession curves, with notable theoretical and practical implications. Key Points signatures of catchment geomorphology on base flow recession curves Analysis of streamflow data and DEM for 27 catchments in Switzerland New conceptual model accounting for uneven drainage densit

The geomorphic origin of recession curves

An important study domain in hydrology is dedicated to understand how the spatial organization of river networks is reflected in the hydrologic response to rainfall inputs (Biswal and Marani, 2010). Base flow (or recession flow) is the discharge rate in a river that results from the natural release of the water stored in the upstream river channels and adjoining riparian aquifers in the absence of precipitation, snowmelt or other inputs (Brutsaert W. , 2005). Biswal and Marani (2010) sustain that the recession flow is dominated by aquifer drainage and they find a link between recession flows and network morphology. Since geomorphologic characteristics can be readily obtained from maps and air photos, a relationship between the groundwater outflow rate and the geomorphologic parameters of the basin would permit to extract the characteristics of recession hydrographs solely from Digital Terrain Models (DTMs). The practical importance of base flow prediction stems mainly from the fact that it is the rate of flow that a given catchment can sustain in the absence of precipitation and in the absence of artificial storage works (Brutsaert & Nieber, 1977). In the first chapter is presented the theoretical background dedicated to the study of the processes controlling recession flows with a particular attention to the aquifer drainage process. A method to describe the behaviour of the base flow rate at the outlet of the basin is presented, introducing the concept of recession slope analysis. The same method is used to define aquifer hydraulic parameters using Boussinesq equations, which are shortly described. Finally the relationship with geomorphic parameters found by Biswal and Marani (2010) is presented. In the second chapter the data and methods used to analyse the recession flows of the Chamberonne river are explained. In the last part of the report the results of the analysis are showed, followed by some propositions for the future work

I2. On the Brutsaert Baseflow Recessions and Their Geomorphic Origins

Once downloaded, these high definition QuickTime videos may be played using a computer video player with H.264 codec, 1280x720 pixels, millions of colors, AAC audio at 44100Hz and 29.97 frames per second. The data rate is 5Mbps. File sizes are on the order of 600-900 MB. (Other formats may be added later.) Free QuickTime players for Macintosh and Window computers may be located using a Google search on QuickTime. The DVD was produced by J. Robert Cooke.Moving from a classic study on the base flow characteristics of six basins in the Finger Lakes region [1], a set of Brutsaert recession curves (the lower envelope of available records of |dQ/dt| as a function of Q, where Q is at-a-station gauged flow rate) has been constructed from Swiss streamflow data relatively unaffected by snowmelt. The Lecture builds on the functional dependences found in [1] (chiefly through Boussinesq’ nonlinear solution of free-surface groundwater flow, yielding a specific relation to local drainage area and total stream length) and on the expedient avoidance of proper time references, to apply and generalize recent results aimed at the geomorphic origins of recession curves [2], that is, fully integrating sizable geometric and topologic complexity. In particular, such results propose a link between river network morphology and the parametrization in [1], in particular by assimilating the basic scaling exponent a (i.e. |dQ/dt|µQa) to that characterizing the empirical relation N(x) µ G(x)a (where x is the downstream distance from the channel heads, N(x) is the number of channel reaches exactly located at distance x from their heads, and G(x) is the total drainage network length at a distance greater or equal to x down to the gauging station where Q is recorded [2]). Application of the method, originally tested on DTMs and daily discharge observations in 67 US basins, suggests a definite linkage of active drainage and source functions with the basic features of the Brutsaert envelopes. The possible morphological predictability of base flow features is central to transport processes at catchment scales, not least for its implications on our understanding of the geomorphic structure of the hydrologic response [3] and of the stationarity of the ensuing travel time distributions leading to the so-called old water paradox [4]. These issues are briefly discussed in the Lecture. Here, through a broad survey of Swiss field data, we go on suggest that the method [2] provides excellent results only in catchments where drainage density (roughly defined as the ratio of total channel network length to its drainage area [L-1], defined at a station) can be regarded as spatially constant. When uneven drainage densities are observed, chiefly in our test cases for high mountainous areas where drainage density varies significantly owing to complex cryosphere dynamics and geologic or pedologic constraints, the method’s assumptions do not hold. In the Lecture a detailed reexamination of the premises of the approaches [1,2] is proposed. A revision is then proposed, which includes geomorphic corrections based on a proper description of the drainage density seen as a random space function [5]. Such corrections properly vanish should drainage density become spatially constant. Overall, it is recognized a definite geomorphic origin for Brutsaert recessions, with notable implications. REFERENCES [1] W. Brutsaert & J.L. Nieber, Regionalized drought flow hydrograph from a mature glaciated plateau, Water Resources Research, 13(3), 637-643, 1977 [2] B. Basudev & M. Marani, Geomorphological origin of recession curves, Geophysical Research Letters, 37, L24403, 2010 [3] I. Rodriguez-Iturbe and J.B. Valdes, The geomorphologic structure of the hydrologic response, Water Resources Research, 15(6), 1409-1420, 1979 [4] G. Botter, E. Bertuzzo, A. Rinaldo, Transport in the hydrologic response: Travel time distributions, soil moisture dynamics, and the old water paradox, Water Resources Research, 46, W03514, 2010 [5] G. Tucker, F. Catani and R.L. Bras, Statistical analysis of drainage density from digital terrain data, Geomorphology, 36, 187-202, 20011_9anufe8