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Discussion by Bob Mussetter
Non-stationarity of basin scale sediment delivery
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The results from CAESAR compare favourably with those from Barry et al. (2004) and the coefficients and exponents shown in Fig. 12.8 fit within the ranges found in their work. This is encouraging, but possibly not too surprising as the range of exponent and coefficient values found by Barry et al. (2004) is wide. For a more detailed comparison, the grey line in Fig. 12.8 corresponds with the data Barry et al. (2004) present for the Boise River. This shows a similar exponent (angle of the line) to the centre 100–150 year cal. BP CAESAR example but a substantially different offset. Examining the data presented by Barry et al. (2004) the modelled Swale is considerably smaller than the Boise River (ca. 380 to 2500 km2) and should therefore have a much larger coefficient, raising the position of the line. The angle of the lines from the CAESAR simulations also changes with a shallower line in the wetter example (150–200 cal. BP) and a steeper gradient in the drier run (50–100 cal. BP). Barry et al. (2004) suggest that the exponent (controlling the angle of the curve) increases when there is a better formed (more distinct) armour layer and reduces when there is less difference between surface and subsurface grain sizes. This would concur with these simulations, where during high flow (wetter) conditions the armour layer is less well established, but during lower flow examples there is more opportunity for an armour to develop. As such, the dynamics of the simulations we have presented fit well with the theory used to explain the findings of Barry et al. (2004). However, as previously mentioned, the assumed channel width can have an important effect on these graphs, and the angle of the relationship in the simulation results could easily be manipulated by changing the width. There are also many low value data points from our data, which is possibly as the numerical model will record very small sediment yields that might not register in field sampling. In summary, there are some differences in the sediment discharge data that we have simulated and that measured by Barry et al. (2004). However, the modelled data fits comfortably within the range of coefficient and exponent values measured by Barry et al. (2004) and more importantly the dynamics of how that exponent changes corresponds with the field data. As such we conclude that this comparison provides an encouragingly good but not conclusive indication of model performance. Reference Barry, J.J., Buffington, J.M., King, J.G., 2004. A general power equation for predicting bed load transport rates in gravel bed rivers. Water Resour. Res. 40, W10401.
Discussion by Bob Mussetter The model provides some very interesting results regarding the long-term variability in sediment loads. Based on the presentation at the conference, the authors appear to interpret these results to mean that available sediment-transport relationships are flawed because they do not account for changes in sediment supply and climate. In reality, the equations used in the model predict the transport capacity (or potential) for the concurrent bed material and hydraulic conditions, which depend on the
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T.J. Coulthard, J. Lewin, M.G. Macklin
previous supply and hydraulic conditions. As a result, the model does not illustrate a flaw in the available transport equations, but rather likely helps explain at least part of the reason for the large variability that is observed in bed-material load measurements. Using bed-material transport relationships in this manner also does not address the dynamics of the wash (or fine sediment) load, which is nearly always supply-limited, but an important part of the sediment dynamics of the watershed scale. Discussion by Colin D. Rennie Coulthard et al. and Pizzuto et al. have tackled the important issue of the impact of climate change on river channels. River managers are increasingly concerned with climate change, and require informed estimates of likely changes in river channels (e.g., Ashmore and Church, 2001). Coulthard et al. employed a sophisticated cellular landscape evolution model (CAESAR), which calculates spatiotemporally distributed sediment delivery and transport, to understand channel changes in time with and without climate change. Pizzuto et al. employed a relatively simple sediment transport model for the same ends. They argued that a simple model was justified because data and theory were not available for a more complex model. Coulthard et al. describe well the limitations of empirical approaches to understanding climate change impacts on rivers. The existing record of fluvial measurements is too short to demonstrate morphological change due to climate change, and the record is convolved with channel changes due to changing land-use. The paleolimnological record from stratigraphy is too coarse and uncertain to demonstrate climate change impacts. As a consequence, numerical modelling has been employed to evaluate the influence of climate change on channels. However, numerical models require validation and calibration with measured data if they are to generate reliable predictions. The data problems that limit empirical approaches also limit validation of numerical models, as acknowledged by Coulthard et al., which renders suspect the numerical model outcomes. The model results are highly uncertain, even with respect to observed trends, thus models may not even serve as exploratory tools. This is a difficult dilemma, which the gravel-bed rivers community should begin to address. Gordon Grant suggested hindcasting numerical models to compare with the sedimentological record, which may be a good first step.
Reference Ashmore, P., Church, M., 2001. The impact of climate change on rivers and river processes in Canada, Geol. Surv. of Canada, Bulletin 555, 58pp.
Reply by the authors We agree with both sets of comments. This work was not designed to out of hand discount sediment-transport formulae, but to point out that there were some
333
The results from CAESAR compare favourably with those from Barry et al. (2004) and the coefficients and exponents shown in Fig. 12.8 fit within the ranges found in their work. This is encouraging, but possibly not too surprising as the range of exponent and coefficient values found by Barry et al. (2004) is wide. For a more detailed comparison, the grey line in Fig. 12.8 corresponds with the data Barry et al. (2004) present for the Boise River. This shows a similar exponent (angle of the line) to the centre 100–150 year cal. BP CAESAR example but a substantially different offset. Examining the data presented by Barry et al. (2004) the modelled Swale is considerably smaller than the Boise River (ca. 380 to 2500 km2) and should therefore have a much larger coefficient, raising the position of the line. The angle of the lines from the CAESAR simulations also changes with a shallower line in the wetter example (150–200 cal. BP) and a steeper gradient in the drier run (50–100 cal. BP). Barry et al. (2004) suggest that the exponent (controlling the angle of the curve) increases when there is a better formed (more distinct) armour layer and reduces when there is less difference between surface and subsurface grain sizes. This would concur with these simulations, where during high flow (wetter) conditions the armour layer is less well established, but during lower flow examples there is more opportunity for an armour to develop. As such, the dynamics of the simulations we have presented fit well with the theory used to explain the findings of Barry et al. (2004). However, as previously mentioned, the assumed channel width can have an important effect on these graphs, and the angle of the relationship in the simulation results could easily be manipulated by changing the width. There are also many low value data points from our data, which is possibly as the numerical model will record very small sediment yields that might not register in field sampling. In summary, there are some differences in the sediment discharge data that we have simulated and that measured by Barry et al. (2004). However, the modelled data fits comfortably within the range of coefficient and exponent values measured by Barry et al. (2004) and more importantly the dynamics of how that exponent changes corresponds with the field data. As such we conclude that this comparison provides an encouragingly good but not conclusive indication of model performance. Reference Barry, J.J., Buffington, J.M., King, J.G., 2004. A general power equation for predicting bed load transport rates in gravel bed rivers. Water Resour. Res. 40, W10401.
Discussion by Bob Mussetter The model provides some very interesting results regarding the long-term variability in sediment loads. Based on the presentation at the conference, the authors appear to interpret these results to mean that available sediment-transport relationships are flawed because they do not account for changes in sediment supply and climate. In reality, the equations used in the model predict the transport capacity (or potential) for the concurrent bed material and hydraulic conditions, which depend on the
334
T.J. Coulthard, J. Lewin, M.G. Macklin
previous supply and hydraulic conditions. As a result, the model does not illustrate a flaw in the available transport equations, but rather likely helps explain at least part of the reason for the large variability that is observed in bed-material load measurements. Using bed-material transport relationships in this manner also does not address the dynamics of the wash (or fine sediment) load, which is nearly always supply-limited, but an important part of the sediment dynamics of the watershed scale. Discussion by Colin D. Rennie Coulthard et al. and Pizzuto et al. have tackled the important issue of the impact of climate change on river channels. River managers are increasingly concerned with climate change, and require informed estimates of likely changes in river channels (e.g., Ashmore and Church, 2001). Coulthard et al. employed a sophisticated cellular landscape evolution model (CAESAR), which calculates spatiotemporally distributed sediment delivery and transport, to understand channel changes in time with and without climate change. Pizzuto et al. employed a relatively simple sediment transport model for the same ends. They argued that a simple model was justified because data and theory were not available for a more complex model. Coulthard et al. describe well the limitations of empirical approaches to understanding climate change impacts on rivers. The existing record of fluvial measurements is too short to demonstrate morphological change due to climate change, and the record is convolved with channel changes due to changing land-use. The paleolimnological record from stratigraphy is too coarse and uncertain to demonstrate climate change impacts. As a consequence, numerical modelling has been employed to evaluate the influence of climate change on channels. However, numerical models require validation and calibration with measured data if they are to generate reliable predictions. The data problems that limit empirical approaches also limit validation of numerical models, as acknowledged by Coulthard et al., which renders suspect the numerical model outcomes. The model results are highly uncertain, even with respect to observed trends, thus models may not even serve as exploratory tools. This is a difficult dilemma, which the gravel-bed rivers community should begin to address. Gordon Grant suggested hindcasting numerical models to compare with the sedimentological record, which may be a good first step.
Reference Ashmore, P., Church, M., 2001. The impact of climate change on rivers and river processes in Canada, Geol. Surv. of Canada, Bulletin 555, 58pp.
Reply by the authors We agree with both sets of comments. This work was not designed to out of hand discount sediment-transport formulae, but to point out that there were some