Bedload Transport in Mountain Streams Model Development, Numeric Simulation and Time Series Analysis
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Research Collection Doctoral Thesis Bedload transport in mountain streams Model development, numeric simulation and time series analysis Author(s): Heimann, Florian U.M. Publication Date: 2015 Permanent Link: https://doi.org/10.3929/ethz-a-010406973 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library DISS. ETH NO. 22530 Bedload transport in mountain streams: Model development, numeric simulation and time series analysis A thesis submitted to attain the degree of DOCTOR OF SCIENCES of ETH ZURICH (Dr. sc. ETH Zurich) presented by FLORIAN ULRICH MAXIMILIAN HEIMANN M.Sc., Ludwig-Maximilians-Universität München and Technische Universität München born on 09.01.1985 citizen of Germany accepted on the recommendation of Prof. Dr. James W. Kirchner Dr. Dieter Rickenmann Dr. Jens M. Turowski Prof. Dr. Stuart N. Lane 2015 Contents Abstract . .6 Kurzfassung . .8 1 Introduction 10 1.1 Motivation . 10 1.2 Research gaps . 11 1.3 Objectives and structure of the thesis . 13 Study 1 . 13 Study 2 . 13 Study 3 . 14 Study 4 . 15 2 sedFlow – a tool for simulating fractional bedload transport and longitudinal profile evolution in mountain streams 19 2.1 Introduction . 20 2.2 Implementation of the sedFlow model . 24 2.2.1 Hydraulic calculation . 24 Flow routing . 24 Flow resistance . 26 2.2.2 Bedload transport calculation . 27 Bedload transport rate . 27 Evolution of channel bed elevation and slope . 30 2.2.3 Grain-size distribution changes . 32 2.3 Discussion . 34 2.3.1 Comparison of sedFlow implementations with similar mod- els ............................. 34 Fractional transport and grain-size distributions . 34 Adverse channel slopes . 36 Simulation speed . 37 Flexibility . 37 2.3.2 Advantages and limits of the sedFlow modelling approach . 38 2.4 Conclusions . 39 2 CONTENTS 3 Appendix of chapter 2 43 2.A1 Supplementary methods . 43 2.A1.1 Explicit hydraulics . 43 2.A1.2 Bedload capacity estimation according to Wilcock and Crowe (2003) . 43 2.A1.3 Bedload capacity estimation according to Recking (2010) 44 2.A1.4 Bedload capacity estimation according to Rickenmann (2001) based on θ .............. 44 2.A1.5 Bedload capacity estimation according to Rickenmann (2001) based on q ..................... 44 2.A1.6 Fractional bedload capacity estimation according to Rick- enmann (2001) based on θ ................ 45 3 Calculation of bedload transport in Swiss mountain rivers using the model sedFlow: proof of concept 59 3.1 Introduction . 60 3.2 Material and methods . 62 3.2.1 General catchment characteristics . 63 3.2.2 Hydrology . 66 3.2.3 Channel morphology and bedload observations . 66 Rectangular channels . 66 Reference data . 67 Accumulated bedload transport . 69 3.2.4 The model sedFlow . 71 3.2.5 Model calibration and sensitivity calculations . 74 3.3 Results . 77 3.3.1 Simulations for the calibration period . 77 3.3.2 Sensitivity analyses . 78 3.4 Discussion . 79 3.4.1 Simulations for the calibration period . 79 3.4.2 Sensitivity analyses . 82 3.5 Conclusions . 83 Appendix of chapter 3 92 4 Assessing the impact of climate change on brown trout (Salmo trutta fario) recruitment 100 4.1 Introduction . 101 4.2 Materials and methods . 103 4.2.1 Study area . 103 4.2.2 Catchment scale: Impact of future climate change scenarios on discharge . 103 4.2.3 Reach scale: Climate change impacts on bedload trans- port and channel morphodynamics . 105 CONTENTS 4 4.2.4 Local scale: Climate change impacts on habitat stability and distribution . 107 Terrestrial survey / DTM generation . 107 Hydrodynamic-numerical modelling . 108 Classification and stability testing of spawning ground and mesohabitats . 109 Sensitivity testing and distribution of mesohabitats under differing discharges . 110 Mesohabitat suitability for different brown trout age classes110 4.3 Results . 111 4.3.1 Catchment scale . 111 4.3.2 Reach scale . 112 Bedload transport and morphodynamics . 112 4.3.3 Local scale . 114 Stability of spawning ground . 114 Sensitivity testing of flow variation . 115 Mesohabitat distribution under summer low flow condi- tions in the near and far future . 116 Ecological relevance of mesohabitat modelling . 118 4.4 Discussion . 118 4.4.1 Bedload transport and morphodynamics . 118 4.4.2 Spawning and incubation phase . 120 4.4.3 Parr phase . 121 4.5 Conclusions and possible mitigation measures . 122 Appendix of chapter 4 128 5 Spectral characteristics of bedload transport 140 5.1 Introduction . 140 5.2 Material and methods . 144 5.2.1 Study site . 144 5.2.2 Bedload transport measurements . 145 5.2.3 Time series analysis . 146 5.3 Results . 148 5.3.1 Power spectral density . 148 Observations . 148 Reshuffled impulse counts benchmark test . 149 5.3.2 Coherence and phase shift of discharge and bedload . 149 5.4 Discussion . 150 5.4.1 The inter-event scale range . 151 5.4.2 The event scale range . 151 5.4.3 The phaseshift at the transition from the inter-event to the event scale range . 152 CONTENTS 5 5.4.4 The phaseshift at the transition from the event to the intra-event scale range . 153 5.4.5 Spectral slopes at the transition from the event to the intra-event scale range . 154 5.4.6 The intra-event scale range . 154 General characteristics of the intra-event scale range . 154 The systematic intra-event scale range . 155 The random intra-event scale range . 155 5.4.7 The periods of 20 to 40 minutes . 155 5.5 Conclusions . 156 Appendix of chapter 5 164 5.A1 Block randomisation . 165 5.A2 Distance to a sediment source based on phaseshift at the tran- sition from the event to the intra-event scale range . 166 5.A3 Artificial time series . 168 5.A3.1 Methods . 168 5.A3.2 Results . 169 Const.Size-NoMod. 169 Var.Size-NoMod. 169 Var.Size-Const.Mod. 170 Var.Size-Var.Mod. 170 Const.Size-Var.Mod. 170 5.A3.3 Discussion . 171 6 Synthesis and outlook 190 6.1 Synthesis . 190 6.2 Outlook . 193 Danksagung 195 Abstract Bedload transport has a wide range of implications for research studies and for civil engineering practice in mountain regions. Considering these implications, the thesis aims to improve the estimation and prediction of bedload transport. These improvements include the provision, assessment, and example application of the new modelling tool sedFlow and a more profound understanding of the temporal dynamics of natural bedload transport systems, which define the scale range of applicability for a deterministic model like the one presented in this thesis. The new one-dimensional model sedFlow is designed to realistically repro- duce the total transport volumes and overall morphodynamic changes resulting from sediment transport events such as major floods, and complements the range of existing tools for the simulation of bedload transport in steep moun- tain streams. It is intended for temporal scales from the individual event (several hours to a few days) up to longer-term evolution of stream channels (several years). The envisaged spatial scale covers complete catchments at a spatial discretisation of several tens of metres to a few hundreds of metres. sedFlow offers different options for bedload transport equations, flow-resistance relation- ships and other elements which can be selected to fit the current application in a particular catchment. The presented model is an appropriate tool if (I) grain size distributions need to be dynamically adjusted in the course of a simulation, if (II) the effects of ponding, e.g. due to massive sediment inputs through debris flows, might play a role in the study catchment or if (III) one simply needs a fast simulation of bedload transport in a mountain stream with quick and easy pre- and post-processing. We use the model sedFlow to calculate bedload transport observations in two Swiss mountain rivers. Observations from bedload transport events are suc- cessfully reproduced with plausible parameter settings, meaning that calibration parameters are only varied within ranges of uncertainty that have been pre- determined either by previous research or by field observations in the simulated study reaches. The influence of different parameters on simulation results is semi-quantitatively evaluated in a simple sensitivity study. Besides some other study results that help to interpret the model behaviour, the presented proof-of- concept study demonstrates the usefulness of sedFlow for a range of practical applications in alpine mountain streams. Using sedFlow in an example application, we simulate the effect of climate change in terms of bed erosion during the incubation time of fish eggs i.e. during the winter months. Due to the simulated trends of increasing magnitudes and durations of winter scour, it is likely that the stable brown trout spawning habitat areas might decrease in the future, and erosion depths will more frequently exceed the average egg burial depth thus exerting stress on the trout population. Complementing the simulation studies, we analyse a unique high resolution time series of bedload transport data from a steep alpine mountain stream by 6 ABSTRACT 7 means of spectral analysis. Four scale ranges of different temporal dynamics are distinguished and described. In the presented pilot study, for the first time, the discharge-independent autoregressive dependency of bedload transport has been attributed to a clearly defined band of frequencies in field data. Furthermore we make suggestions for an optimised measurement strategy, based on the structure of the analysed data set. Altogether, the four studies of the present thesis contribute to an improved prediction of bedload transport in mountain catchments. With sedFlow an open- source modelling tool is provided that combines state of the art approaches for the calculation of fractional bedload transport in steep channels with fast simu- lations and with easy and straightforward pre- and postprocessing of simulation data.