Model help:Acronym1D: Difference between revisions

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__NOTOC__
__NOTOC__
==<big><big>{{PAGENAME}}</big></big>==
==<big><big>{{PAGENAME}}</big></big>==
“Acronym1_D” combines the scheme of “Acronym1_R” with a flow duration curve.  The bedload transport rate and bedload grain size distribution are computed for each flow of the curve, and then averaged to yield a mean bedload transport rate and a mean bedload grain size distribution.
This program acts the same way as the Acronym1 do, with the addition of a “flow duration curve;” the program calculates the same values (though taken as a mean annual) as well as the mean annual water discharge, and the characteristics of the flow duration curve.  


==Model introduction==
==Model introduction==
“Acronym1_D” simply adds a flow duration curve to the algorithm of “Acronym1_R” in order to compute the average volume gravel bedload transport rate per unit width q<sub>bTa</sub>, as well as the average bedload grain size distribution (D<sub>b,i</sub>, p<sub>af,i</sub>), i = 1..N+1.  In addition, it computes the values Q<sub>a</sub>, H<sub>a</sub>, u<sub>∗a</sub> and τ<sub>ga∗</sub> corresponding to annual mean values of the water discharge, depth, shear velocity and Shields stress based on surface geometric mean size. The values D<sub>alg</sub>, σ<sub>alg</sub>, D<sub>al90</sub>, D<sub>al70</sub>, D<sub>al50</sub> and D<sub>al30</sub> associated with the mean grain size distribution of the bedload are computed along with the corresponding values for the surface material, D<sub>sg</sub>, σ<sub>sg</sub>, D<sub>s90</sub>, D<sub>s70</sub>, D<sub>s50</sub> and D<sub>s30</sub>.  Finally, the program computes the volume gravel bedload transport rate per unit width q<sub>bT</sub>, the water discharge Q<sub>w</sub>, flow depth H, the shear velocity u<sub>∗</sub> and the Shields stress τ<sub>g∗</sub> associated with each range in the flow duration curve, along with the fraction of time p<sub>Q</sub> that the flow is in that range.
“Acronym1_D” simply adds a flow duration curve to the algorithm of “Acronym1_R” in order to compute the average volume gravel bedload transport rate per unit width, as well as the average bedload grain size distribution. In addition, it computes the annual mean values of the water discharge, depth, shear velocity and Shields stress based on surface geometric mean size. The values D<sub>alg</sub>, σ<sub>alg</sub>, D<sub>al90</sub>, D<sub>al70</sub>, D<sub>al50</sub> and D<sub>al30</sub> associated with the mean grain size distribution of the bedload are computed along with the corresponding values for the surface material, D<sub>sg</sub>, σ<sub>sg</sub>, D<sub>s90</sub>, D<sub>s70</sub>, D<sub>s50</sub> and D<sub>s30</sub>.  Finally, the program computes the volume gravel bedload transport rate per unit width, the water discharge, flow depth, the shear velocity and the Shields stress associated with each range in the flow duration curve, along with the fraction of time that the flow is in that range.  
 
The flow duration curve is specified in terms of the pairs (Q<sub>wd,k</sub>, p<sub>eQ,k</sub>), k = 1..M+1, where Q<sub>wd,k</sub> denotes the kth discharge and p<sub>eQ,k</sub> denotes the percentage of time this flow is exceeded.  Here k = 1 corresponds to the highest flow in the curve, with an exceedance percentage p<sub>eQ</sub> of zero, and k = M+1 corresponds to the lowest flow in the curve, with an exceedance percentage p<sub>eQ</sub> of 100.  The lowest flow on the curve Q<sub>wd,M</sub> must exceed zero.
 
<div id=CMT_MODEL_PARAMETERS>
<div id=CMT_MODEL_PARAMETERS>
==Model parameters==
==Model parameters==
= First tab header =
= Input Files and Directories =
{|{{Prettytable}} class = "wikitable unsortable"  cellspacing="0" cellpadding="0" style="margin:0em 0em 0em 0;"
{|{{Prettytable}} class = "wikitable unsortable"  cellspacing="0" cellpadding="0" style="margin:0em 0em 0em 0;"
|-
|-
!Parameter!!Description!!Unit
!Parameter!!Description!!Unit
|-valign="top"
|-valign="top"
|width="20%"|<span class="remove_this_tag">First parameter</span>
|width="20%"|Input directory
|width="60%"|<span class="remove_this_tag">Description parameter</span>
|width="60%"|path to input files
|width="20%"|<span class="remove_this_tag">[Units]</span>
|width="20%"|
|-
|Site prefix
|Site prefix for Input/Output files
|
|-
|Case prefix
|Case prefix for Input/Output files
|
|-
|}
|}


= Second tab header =
= Run Parameters =
{|{{Prettytable}} class = "wikitable unsortable"  cellspacing="0"  cellpadding="0" style="margin:0em 0em 0em 0;"
{|{{Prettytable}} class = "wikitable unsortable"  cellspacing="0"  cellpadding="0" style="margin:0em 0em 0em 0;"
|-
|-
!Parameter!!Description!!Unit
!Parameter!!Description!!Unit
|-valign="top"
|-valign="top"
|width="20%"|<span class="remove_this_tag">First parameter</span>
|width="20%"|Submerged Specific Gravity
|width="60%"|<span class="remove_this_tag">Description parameter</span>
|width="60%"|
|width="20%"|<span class="remove_this_tag">[Units]</span>
|width="20%"| -
|-
|Bed Slope
|
| -
|-
|Channel Width
|
| m
|-
|Roughness Factor
|
| -
|-
|}
|}


= Etc. tab header =
= About =
{|{{Prettytable}} class = "wikitable unsortable"  cellspacing="0"  cellpadding="0" style="margin:0em 0em 0em 0;"
|-
!Parameter!!Description!!Unit
|-valign="top"
|width="20%"|Model name
|width="60%"|name of the model
|width="20%"| -
|-
|Author name
|name of the model author
| -
|-
|}
<headertabs/>
<headertabs/>
</div>


==Uses ports==
==Uses ports==
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==Main equations==
==Main equations==
* Grain Size:
* Characteristic grain size for the ith grain size range (spans (D<sub>b,i</sub>, D<sub>b,i+1</sub>)) (for i=1...N)
::::{|
::::{|
|width=500px|<math>\Psi= LN_{2}\left (D\right) = {\frac{log_{10}\left (D\right)}{log_{10}\left (2\right)}} </math>
|width=530px|<math>D_{i}= \sqrt{ D_{b, i} D_{b, i+1} }   </math>
|width=50px align="right"|(1)
|width=50p=x align="right"|(1)
|}
|}
* Fraction in the surface layer F<sub>i</sub> for the ith grain size range (for i=1...N)
::::{|
::::{|
|width=500px|<math>\Psi_{i}= LN_{2}\left ( D_{i}\right) = {\frac{log_{10}\left (D_{i}\right)}{log_{10}\left (2\right)}} </math>
|width=530px|<math>F_{i}= \left ( F_{f, i} - F_{f, i+1} \right ) / 100  </math>
|width=50px align="right"|(2)
|width=50p=x align="right"|(2)
|}
|}
* Grain Size on the base-2 logarithmic scale:
::::{|
::::{|
|width=530px|<math>D_{i}= Sqrt \left (D_{b, i} D_{b, i+1} \right )   </math>
|width=500px|<math>\Psi= LN_{2}\left (D\right) = {\frac{log_{10}\left (D\right)}{log_{10}\left (2\right)}} </math>
|width=50p=x align="right"|(3)
|width=50px align="right"|(3)
|}
|}
* Geometric mean size of the surface material
::::{|
::::{|
|width=530px|<math>F_{i}= \left ( F_{f, i} - F_{f, i+1} \right ) / 100  </math>
|width=500px|<math>D_{sg}=2^\left (\bar\Psi_{s} \right ) </math>
|width=50p=x align="right"|(4)
|width=50px align="right"|(4)
|}
|}
::::{|
::::{|
|width=500px|<math>D_{sg}=2^\Psi_{s} </math>
|width=500px|<math>\bar\Psi_{s}= \sum\limits_{i=1}^N \Psi_{i} F{i} </math>
|width=50px align="right"|(5)
|width=50px align="right"|(5)
|}
|}
* The geometric standard deviations
::::{|
::::{|
|width=500px|<math>\Psi_{s}= \Sigma \Psi_{i} F{i} </math>
|width=500px|<math>\sigma_{sg}= 2 ^\sigma </math>
|width=50px align="right"|(6)
|width=50px align="right"|(6)
|}
|}
* the arithmetic standard deviations
::::{|
::::{|
|width=500px|<math>\sigma_{sg}= 2 ^\sigma </math>
|width=500px|<math>\sigma ^2= \sum\limits_{i=1}^N \left (\Psi_{i} - \bar\Psi \right )^2 F_{i}  </math>
|width=50px align="right"|(7)
|width=50px align="right"|(7)
|}
|}
* The transport relation
::::{|
::::{|
|width=500px|<math>\sigma ^2= \Sigma \left (\Psi_{i} - \Psi \right )^2 F_{i} </math>
|width=530px|<math>W_{i}^*= {\frac{Rgq_{bi}}{F_{i}u_{*} ^3}}= 0.00218 G \left (\Phi \right )  </math>
|width=50px align="right"|(8)
|width=50p=x align="right"|(8)
|}
|}
::::{|
::::{|
|width=530px|<math>W_{i}^*= {\frac{Rgq_{bi}}{F_{i}u_{*} ^3}}= 0.00218 G \left (\Phi \right )  </math>
|width=530px|<math>\phi= \omega \phi_{sgo} \left ( {\frac{D_{i}} {D_{sg}}} \right )^ \left (-0.0951 \right )  </math>
|width=50p=x align="right"|(9)
|width=50p=x align="right"|(9)
|}
|}
::::{|
::::{|
|width=530px|<math>\phi= \omega \phi_{sgo} \left ( {\frac{D_{i}} {D_{sg}}} \right )^ \left (-0.0951 \right )  </math>
|width=530px|<math> \phi_{sgo}= {\frac{\tau_{sg} ^*}{\tau_{ssrg} ^*}}   </math>
|width=50p=x align="right"|(10)
|width=50p=x align="right"|(10)
|}
|}
::::{|
::::{|
|width=530px|<math> \Phi= {\frac{\tau_{sg} ^*}{\tau_{ssrg} ^*}}  </math>
|width=530px|<math>\tau_{sg} ^*={\frac{u_{*} ^2}{R g D_{sg}}}  </math>
|width=50p=x align="right"|(11)
|width=50p=x align="right"|(11)
|}
|}
::::{|
::::{|
|width=530px|<math>\tau_{sg} ^*={\frac{u_{*} ^2}{Rg D_{sg}}}  </math>
|width=530px|<math> G \left ( \phi \right )=\left\{\begin{matrix} 5474 \left ( 1 - {\frac{0.853}{\phi}} \right ) ^ \left (4.5 \right ) & \phi > 1.59 \\ exp[ 14.2\left ( \phi - 1\right ) - 9.28 \left ( \phi - 1 \right )^2  ] & 1 <= \phi <= 1.59 \\ \phi ^\left (14.2 \right ) &  \phi < 1 \end{matrix}\right. </math>
|width=50p=x align="right"|(12)
|width=50p=x align="right"|(12)
|}
|}
* φ> 1.59
::::{|
::::{|
|width=530px|<math> G \left ( \Phi \right )= 5474 \left ( 1 - {\frac{0.853}{\Phi}} \right ) ^ \left (4.5 \right )  </math>
|width=530px|<math>\omega= 1 + {\frac{\sigma}{\sigma_{O} \left ( \phi_{sgo} \right ) }} [ \omega_{O} \left ( \phi_{sgo} \right ) - 1 ] </math>
|width=50p=x align="right"|(13)
|width=50p=x align="right"|(13)
|}
|}
* 1<=φ<=1.59
* total volume gravel bedload transport rate per unit width summed over all sizes
::::{|
::::{|
|width=530px|<math> G\left (\Phi \right )= exp\left ( 14.2\left ( \Phi - 1\right ) - 9.28 \left ( \Phi - 1 \right )^2   \right )  </math>
|width=530px|<math>q_{bT}= \sum\limits_{i=1}^N q_{bi}   </math>
|width=50p=x align="right"|(14)
|width=50p=x align="right"|(14)
|}
|}
* φ< 1
* fraction of gravel bedload in the ith grain size range
::::{|
::::{|
|width=530px|<math> G\left (\Phi \right )= \Phi ^\left (14.2 \right )  </math>
|width=530px|<math>p_{i}= {\frac{q_{bi}}{q_{bT}}}  </math>
|width=50p=x align="right"|(15)
|width=50p=x align="right"|(15)
|}
|}
* Geometric mean of the bedload
::::{|
::::{|
|width=530px|<math>\omega= 1 + {\frac{\sigma}{\sigma_{O} \left ( \Phi_{sgo} \right ) }} \left ( \omega_{O} \left ( \Phi_{sgo} \right ) - 1 \right )  </math>
|width=530px|<math>D_{lg}= 2 ^\left (\bar\psi_{l} \right )   </math>
|width=50p=x align="right"|(16)
|width=50p=x align="right"|(16)
|}
|}
::::{|
::::{|
|width=530px|<math>q_{bT}= \Sigma q_{bi}   </math>
|width=530px|<math>\Psi_{l}= \sum\limits_{i=1}^\left (Np \right ) \Psi_{i} p_{i} </math>
|width=50p=x align="right"|(17)
|width=50p=x align="right"|(17)
|}
|}
* Geometric standard deviation of the bedload
::::{|
::::{|
|width=530px|<math>p_{i}= {\frac{q_{bi}}{q_{bT}}}  </math>
|width=530px|<math>\delta_{lg}= 2 ^\left ( \delta_{l} \right )  </math>
|width=50p=x align="right"|(18)
|width=50p=x align="right"|(18)
|}
|}
::::{|
::::{|
|width=530px|<math>D_{lg}= 2 ^\left (\psi_{l} \right )  </math>
|width=530px|<math>\delta_{l} ^2= \sum\limits_{i=1}^\left (Np \right ) \left ( \Psi_{i} - \bar\Psi_{l} \right )^2 p_{i}   </math>
|width=50p=x align="right"|(19)
|width=50p=x align="right"|(19)
|}
|}
* Grain sizes in the bedload material
::::{|
::::{|
|width=530px|<math>\Psi_{l}= \Sigma \Psi_{i} p_{i}  </math>
|width=530px|<math>D_{lx}= 2 ^\left (\Psi_{lx} \right )  </math>
|width=50p=x align="right"|(20)
|width=50p=x align="right"|(20)
|}
|}
::::{|
::::{|
|width=530px|<math>\delta_{lg}= 2 ^\left ( \delta_{l} \right ) </math>
|width=530px|<math>\Psi_{lx}= \Psi_{b, i+1} + {\frac{\Psi_{b, j} - \Psi_{b, i+1}}{p_{f, i} - p_{f, i+1}}}\left ( x - p_{f, i+1} \right ) </math>
|width=50p=x align="right"|(21)
|width=50p=x align="right"|(21)
|}
|}
::::{|
::::{|
|width=530px|<math>\delta_{l} ^2= \Sigma \left ( \Psi_{i} - \Psi_{l} \right )^2 p_{i}   </math>
|width=530px|<math>\Psi_{b, i}= Ln_{2} \left ( D_{b, j} \right )  </math>
|width=50p=x align="right"|(22)
|width=50p=x align="right"|(22)
|}
|}
* Characteristic flow in the kth range (k=1...M)
::::{|
::::{|
|width=530px|<math>D_{lx}= 2 ^\left (\Psi_{lx} \right )  </math>
|width=530px|<math>Q_{wr,k}= {\frac{1}{2}} \left ( Q_{wd,k} + Q_{wd, k+1} \right )  </math>
|width=50p=x align="right"|(23)
|width=50p=x align="right"|(23)
|}
|}  
* Fraction of time the flow is in the kth range
::::{|
::::{|
|width=530px|<math>\Psi_{lx}= \Psi_{b, i+1} + {\frac{\Psi_{b, j} - \Psi_{b, i+1}}{p_{f, i} - p_{f, i+1}}}\left ( x - p_{f, i+1} \right ) </math>
|width=530px|<math>P_{Q,k}= {\frac{p_{eQ,k+1} - p_{eQ,k}}{100}} </math>
|width=50p=x align="right"|(24)
|width=50p=x align="right"|(24)
|}
::::{|
|width=530px|<math>\Psi_{b, i}= Ln_{2} \left ( D_{b, j} \right )  </math>
|width=50p=x align="right"|(25)
|}
::::{|
|width=530px|<math>Q_{wr,k}= {/frac{1}{2}} \left ( Q_{wd,k} + Q_{wd, k+1} \right )  </math>
|width=50p=x align="right"|(26)
|}
::::{|
|width=530px|<math>P_{Q,k}= {\frac{p_{eQ,k+1} - p_{eQ,k}}{100}} </math>
|width=50p=x align="right"|(27)
|}
|}


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{| {{Prettytable}} class="wikitable sortable"
{| {{Prettytable}} class="wikitable sortable"
!Symbol!!Description!!Unit
!Symbol!!Description!!Unit
|-
| D
| grain size
| L
|-
|-
| D<sub>i</sub>
| D<sub>i</sub>
| characteristic grain size (for i =1~N)
| characteristic grain size for the ith grain size range (i=1...N)
| mm
| L
|-
|-
| F<sub>i</sub>
| F<sub>i</sub>
| surface layer (for i =1~N)
| fraction in surface layer for the ith grain size range(for i =1...N)
| -
| -
|-
|-
| ψ
| τ<sub>ssrg</sub> <sup>*</sup>
| grain sizes
| equals to 0.0386
| mm
|-
| D<sub>sg</sub>
| geometric mean size of the surface material
| mm
|-
| σ<sub>sg</sub>
| geometric standard deviations
| -
| -
|-
|-
| σ
| ψ
| arithmetic standard deviations
| grain sizes on the base-2 logarithmic ψ scale
| -
|  
|-
|-
| ρ
| ρ
| density of water
| density of water
| kg/m<sup>3</sup>
| M / L<sup>3</sup>
|-
|-
| ρ<sub>s</sub>
| ρ<sub>s</sub>
| density of sediment
| density of sediment
| kg/m<sup>3</sup>
| M / L<sup>3</sup>
|-
|-
| R
| R
| submerged specific gravity, R +1
| submerged specific density of sediment, equals to (ρ<sub>s</sub> /ρ-1)
| -
| -
|-
| u
| shear velocity of flow
| L / T
|-
|-
| g
| g
| acceleration of gravity
| acceleration of gravity
| m / s<sup>2</sup>
| L / T<sup>2</sup>
|-
|-
| τ<sub>b</sub>
| τ<sub>b</sub>
| boundary shear stress on the bed
| boundary shear stress on the bed
| kg / (m s)
| M / (L T)
|-
| u<sub>*</sub>
| shear velocity on the bed, equals to sqrt(τ<sub>b</sub> / ρ )
| L / T
|-
|-
| u
| p<sub>i</sub>
| shear velocity on the bed
| fraction of gravel bedload in the ith grain size range
| m / s
| L
|-
| ψ<sub>s</sub>
| equals to τ<sub>bs</sub> / τ<sub>b</sub>
|
|-
| W<sub>i</sub> <sup>*</sup>
| dimensionless bedload transport rate for ith grain size
| -
|-
|-
| q<sub>bi</sub>
| q<sub>bi</sub>
| volume gravel bedload transport per unit width of grains in the ith size range
| volume gravel bedload transport per unit width of grains in the ith size range
| m <sup>2</sup>
| L <sup>2</sup> / T
|- 
| ω
| straining relation in Parker (1990a,b) bedload relation for mixtures
|
|-
| G(Φ)
| function in Parker (1990a, b) and Wilcock and Crowe (2003) bedload relation for gravel mixture
|
|-
|-
| u<sub>*</sub>
| ω<sub>0</sub>
| shear velocity
| function relation in Parker (1990a, b) bedload relation for mixture
| m / s
| -
|-
|-
| D<sub>lg</sub>
| Φ
| geometric mean of the bedload
| parameter in Parker (1990a, b) bedload relation for mixures
| mm
|  
|-
|-
| σ<sub>lg</sub>
| Φ<sub>sgo</sub>
| geometric standard deviation of the bedload
| equals to  τ<sub>sg</sub> <sup>*</sup> / τ<sub>ssrg</sub> <sup>*</sup>
| -
|- 
| ψ<sub>l</sub>
| grain sizes on the base-2 logarithmic ψ scale for bedload
| -
| -
|-   
|-   
| D<sub>sx</sub>
| ψ<sub>lx</sub>
| size in the surface material, such that x percentage of the material is finer
| grain sizes on the base-2 logarithmic ψ scale for bedload such that x percent of the material is finer
| mm
| -
|-
| D<sub>g</sub>
| geometric mean size
| L
|-
|-
| D<sub>lx</sub>
| σ<sub>g</sub>
| size in the bedload material, such that x percentage of the material is finer
| geometric standard deviation
| -
| -
|-
|-
| D<sub>sx</sub>
| D<sub>x</sub>
| size in the surface material, such that x percentage of the material is finer
| diameter such that x% of the distribution is finer
| mm
| L
|-
|-
| Q<sub>wd,k</sub>
| Q<sub>wd,k</sub>
| the kth discharge
| The kth discharge
| m<sup>3</sub> / s
| L<sup>3</sup> / T
|-
|-
| Q<sub>wr,k</sub>
| Characteristic flow in the kth range
| L<sup>3</sup> / T
|-
| p<sub>eQ,k</sub>
| p<sub>eQ,k</sub>
| percentage of time that flow is exceeded (here k=1 corresponding to the highest flow in the curve, with an exceedance percentage p<sub>eQ</sub> of zero, and k=M+1 corresponds to the lowest flow in the curve, with an exceedance percentage p<sub>eQ</sub> of 100)
| the percentage of time the kth flow is exceeded
| -
| -
|-
|-
| S
| p<sub>Q,k</sub>
| bed slope
| fraction of time that the flow is in the kth range
| -
| -
|-
|-
| B
| channel width
| m
|-
| n
| roughness factor
| -
|-     
|}
|}


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| q<sub>bT</sub>
| q<sub>bT</sub>
| total volume gravel bedload transport rate per unit width summed over all sizes
| total volume gravel bedload transport rate per unit width summed over all sizes
| L<sup>2</sup> / T
|-
| τ<sub>sg</sub> <sup>*</sup>
| Shields number based on surface geometric mean size
| -
| -
|-
|-
| τ<sub>g<sub>
| D<sub>sg</sub>
| shields number
| geometric mean size of the surface material
| L
|-
| σ<sub>sg</sub>
| geometric standard deviations of the surface material
| -
| -
|-
|-
| H
| D<sub>lg</sub>
| water depth
| geometric mean of the bedload material
| m
| L
|-
|-
| u<sub>*</sub>
| σ<sub>lg</sub>
| shear velocity
| geometric standard deviations of the bedload material
| m / s
| -
|-
|-
| Q<sub>wa</sub>
| D<sub>alg</sub>
| mean annual water discharge
| geometric mean size of the bedload
| m<sup>3</sup> / s
| L
|-
|-
| D<sub>g</sub>
| σ<sub>alg</sub>
| geometric mean
| geometric standard deviations of the bedload
| mm
| -
|-
|-
| σ<sub>g</sub>
| σ
| geometric standard deviation
| arithmetic standard deviations of the surface materials
| -
| -
|-
|-
| D<sub>x</sub>
| σ<sub>lg</sub>
| diameter such that x% of the distribution is finer
| geometric standard deviation of the bedload
| mm
| -
|- 
| D<sub>sx</sub>
| grain size in the surface material, such that x percentage of the material is finer
| L
|-
|-
| Q<sub>wr</sub>
| D<sub>lx</sub>
| mean water discharge for each range
| grain size in the bedload material, such that x percentage of the material is finer
| m<sup>3</sup> / s
| L
|-
|-
| pQ
| D<sub>alx</sub>
| fraction of time in that range
| mean grain size in the bedload material, such that x percentage of the material is finer
| L
|-
| σ<sub>l</sub>
| arithmetic standard deviations of bedload materials
| -
| -
|-
|-
| u<sub>*</sub>
| Q<sub>a</sub>
| shear velocity on the range
| mean water discharge
| m / s
| L<sup>3</sup> / T
|-
| H<sub>a</sub>
| mean water depth
| L
|-
| u<sub>*a</sub>
| mean shear velocity
| L / T
|-
|-
| τ<sub>*</sub>
| τ<sub>ga</sub>
| shields number on the range
| mean Shields stress
| -
| -
|-
|-  
|}
|}
   </div>
   </div>
</div>
</div>
==Notes==
==Notes==
* Note on equations
* Note on the program
In order to implement the equations 10~16, it is necessary to specify a) the surface grain size distribution (D<sub>f</sub>,i, F<sub>f</sub>,i) and b) the shear velocity u<sub></sub>.  This results in a predicted values of q<sub>bi</sub>.
The flow duration curve is specified in terms of the pairs (Q<sub>wd,k</sub>, p<sub>eQ,k</sub>), k = 1..M+1.  Here k = 1 corresponds to the highest flow in the curve, with an exceedance percentage p<sub>eQ</sub> of zero, and k = M+1 corresponds to the lowest flow in the curve, with an exceedance percentage p<sub>eQ</sub> of 100The lowest flow on the curve Q<sub>wd,M</sub> must exceed zero.


If the boundary shear stress at the bed includes a component of form drag, the component must be removed before computing u<sub></sub>.
Let Y<sub>k</sub> be any parameter defined for each of the flow ranges k = 1..M. The mean value Y<sub>a</sub> averaged over the flow duration curve is then given as


Once the parameters q<sub>bi</sub> are known the total volume bedload transport rate per unit width q<sub>bT</sub> and the fractions pi in the bedload can be calculated as equations 17, 18.
Y<sub>a</sub> = Sum(Y<sub>k</sub> p<sub>Q,k</sub>), k=1...M


The results are presented in terms of q<sub>bT</sub> and the grain size distribution of the bedload, which is computed from the values of pi.  These same fractions pi are used to compute the geometric mean and geometric standard deviation of the bedload D<sub>lg</sub> and σ<sub>lg</sub>, respectively, from the relations of equations 19, 20, 21, 22.
For example, if the fractions in the bedload in each grain size range within flow range k are given as p<sub>k,i</sub> then the average fractions of the bedload p<sub>ai</sub> are given as
 
The percent finer in the bedload p<sub>f,i</sub> for the grain size D<sub>f,i</sub> is obtained from the fractions p<sub>i</sub> as follows:
p<sub>f,1</sub> = 100
p<sub>f,i</sub> = p<sub>f,i-1</sub> - 100 p<sub>i-1</sub> (i=2~N+1)
 
Let D<sub>sx</sub> and D<sub>lx</sub> denote sizes in the surface and bedload material, respectively, such that x percent of the material is finer.  For example, if x = 50 then Ds50 and D<sub>l50</sub> denote the median sizes of the surface and bedload material, respectively.  Once F<sub>f,i</sub> is specified (p<sub>f</sub>,i is computed) the value D<sub>sx</sub> (D<sub>lx</sub>) can be computed by interpolation.  The interpolation should be done using a logarithmic scale for grain size.  For example, consider the computation of Dlx where p<sub>f,i</sub> ≤ x ≤ p<sub>f,i+1</sub>.  Then we got equation 23, 24, using equation 25.
 
The characteristic flow Q<sub>wr,k</sub> in each range and fraction of time the flow is in that range p<sub>Q,k</sub> are computed with equation 26, 27, here k is ranged from 1 to M.


Let Y<sub>k</sub> be any parameter defined for each of the flow ranges k = 1..M. The mean value Ya averaged over the flow duration curve is then given as
p<sub>ai</sub> = Sum(p<sub>k,i</sub> p<sub>Q,k</sub>)
Y<sub> = /Sigma Y<sub>k</sub> p<sub>Q,k</sub>
For example, if the fractions in the bedload in each grain size range within flow range k are given as p<sub>k,i</sub> then the average fractions of the bedload p<sub>ai</sub> are given as
p<sub>ai</sub> = /Sigma p<sub>k,i</sub> p<sub>Q,k</sub>


==Examples==
==Examples==
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<span class="remove_this_tag">Follow the next steps to include images / movies of simulations:</span>
<span class="remove_this_tag">Follow the next steps to include images / movies of simulations:</span>
* <span class="remove_this_tag">Upload file: http://csdms.colorado.edu/wiki/Special:Upload</span>
* <span class="remove_this_tag">Upload file: https://csdms.colorado.edu/wiki/Special:Upload</span>
* <span class="remove_this_tag">Create link to the file on your page: <nowiki>[[Image:<file name>]]</nowiki>.</span>
* <span class="remove_this_tag">Create link to the file on your page: <nowiki>[[Image:<file name>]]</nowiki>.</span>


Line 363: Line 428:


==References==
==References==
* Parker, G. 1990a Surface based bedload transport relation for gravel rivers.  Journal of Hydraulic Research, 28(4), 417 436.
* Parker, G., 1990a. Surface based bedload transport relation for gravel rivers.  Journal of Hydraulic Research, 28(4), 417~436.(DOI:[http://dx.doi.org/10.1080/00221689009499058 10.1080/00221689009499058])


* Parker, G. 1990b The "ACRONYM" series of Pascal programs for computing bedload transport in gravel rivers.  External Memorandum M 220, St. Anthony Falls Hydraulic Laboratory, University of Minnesota.
* Parker, G.,1990b. The "ACRONYM" series of Pascal programs for computing bedload transport in gravel rivers.  External Memorandum M 220, St. Anthony Falls Hydraulic Laboratory, University of Minnesota.


==Links==
==Links==
* [[http://csdms.colorado.edu/wiki/Model:Acronym1D Model:Acronym1]]
* [[Model:Acronym1D]]


[[Category:Utility components]]
[[Category:Utility components]]

Latest revision as of 17:16, 19 February 2018

The CSDMS Help System

Acronym1D

This program acts the same way as the Acronym1 do, with the addition of a “flow duration curve;” the program calculates the same values (though taken as a mean annual) as well as the mean annual water discharge, and the characteristics of the flow duration curve.

Model introduction

“Acronym1_D” simply adds a flow duration curve to the algorithm of “Acronym1_R” in order to compute the average volume gravel bedload transport rate per unit width, as well as the average bedload grain size distribution. In addition, it computes the annual mean values of the water discharge, depth, shear velocity and Shields stress based on surface geometric mean size. The values Dalg, σalg, Dal90, Dal70, Dal50 and Dal30 associated with the mean grain size distribution of the bedload are computed along with the corresponding values for the surface material, Dsg, σsg, Ds90, Ds70, Ds50 and Ds30. Finally, the program computes the volume gravel bedload transport rate per unit width, the water discharge, flow depth, the shear velocity and the Shields stress associated with each range in the flow duration curve, along with the fraction of time that the flow is in that range.

Model parameters

Parameter Description Unit
Input directory path to input files
Site prefix Site prefix for Input/Output files
Case prefix Case prefix for Input/Output files
Parameter Description Unit
Submerged Specific Gravity -
Bed Slope -
Channel Width m
Roughness Factor -
Parameter Description Unit
Model name name of the model -
Author name name of the model author -

Uses ports

This will be something that the CSDMS facility will add

Provides ports

This will be something that the CSDMS facility will add

Main equations

  • Characteristic grain size for the ith grain size range (spans (Db,i, Db,i+1)) (for i=1...N)
[math]\displaystyle{ D_{i}= \sqrt{ D_{b, i} D_{b, i+1} } }[/math] (1)
  • Fraction in the surface layer Fi for the ith grain size range (for i=1...N)
[math]\displaystyle{ F_{i}= \left ( F_{f, i} - F_{f, i+1} \right ) / 100 }[/math] (2)
  • Grain Size on the base-2 logarithmic scale:
[math]\displaystyle{ \Psi= LN_{2}\left (D\right) = {\frac{log_{10}\left (D\right)}{log_{10}\left (2\right)}} }[/math] (3)
  • Geometric mean size of the surface material
[math]\displaystyle{ D_{sg}=2^\left (\bar\Psi_{s} \right ) }[/math] (4)
[math]\displaystyle{ \bar\Psi_{s}= \sum\limits_{i=1}^N \Psi_{i} F{i} }[/math] (5)
  • The geometric standard deviations
[math]\displaystyle{ \sigma_{sg}= 2 ^\sigma }[/math] (6)
  • the arithmetic standard deviations
[math]\displaystyle{ \sigma ^2= \sum\limits_{i=1}^N \left (\Psi_{i} - \bar\Psi \right )^2 F_{i} }[/math] (7)
  • The transport relation
[math]\displaystyle{ W_{i}^*= {\frac{Rgq_{bi}}{F_{i}u_{*} ^3}}= 0.00218 G \left (\Phi \right ) }[/math] (8)
[math]\displaystyle{ \phi= \omega \phi_{sgo} \left ( {\frac{D_{i}} {D_{sg}}} \right )^ \left (-0.0951 \right ) }[/math] (9)
[math]\displaystyle{ \phi_{sgo}= {\frac{\tau_{sg} ^*}{\tau_{ssrg} ^*}} }[/math] (10)
[math]\displaystyle{ \tau_{sg} ^*={\frac{u_{*} ^2}{R g D_{sg}}} }[/math] (11)
[math]\displaystyle{ G \left ( \phi \right )=\left\{\begin{matrix} 5474 \left ( 1 - {\frac{0.853}{\phi}} \right ) ^ \left (4.5 \right ) & \phi \gt 1.59 \\ exp[ 14.2\left ( \phi - 1\right ) - 9.28 \left ( \phi - 1 \right )^2 ] & 1 \lt = \phi \lt = 1.59 \\ \phi ^\left (14.2 \right ) & \phi \lt 1 \end{matrix}\right. }[/math] (12)
[math]\displaystyle{ \omega= 1 + {\frac{\sigma}{\sigma_{O} \left ( \phi_{sgo} \right ) }} [ \omega_{O} \left ( \phi_{sgo} \right ) - 1 ] }[/math] (13)
  • total volume gravel bedload transport rate per unit width summed over all sizes
[math]\displaystyle{ q_{bT}= \sum\limits_{i=1}^N q_{bi} }[/math] (14)
  • fraction of gravel bedload in the ith grain size range
[math]\displaystyle{ p_{i}= {\frac{q_{bi}}{q_{bT}}} }[/math] (15)
  • Geometric mean of the bedload
[math]\displaystyle{ D_{lg}= 2 ^\left (\bar\psi_{l} \right ) }[/math] (16)
[math]\displaystyle{ \Psi_{l}= \sum\limits_{i=1}^\left (Np \right ) \Psi_{i} p_{i} }[/math] (17)
  • Geometric standard deviation of the bedload
[math]\displaystyle{ \delta_{lg}= 2 ^\left ( \delta_{l} \right ) }[/math] (18)
[math]\displaystyle{ \delta_{l} ^2= \sum\limits_{i=1}^\left (Np \right ) \left ( \Psi_{i} - \bar\Psi_{l} \right )^2 p_{i} }[/math] (19)
  • Grain sizes in the bedload material
[math]\displaystyle{ D_{lx}= 2 ^\left (\Psi_{lx} \right ) }[/math] (20)
[math]\displaystyle{ \Psi_{lx}= \Psi_{b, i+1} + {\frac{\Psi_{b, j} - \Psi_{b, i+1}}{p_{f, i} - p_{f, i+1}}}\left ( x - p_{f, i+1} \right ) }[/math] (21)
[math]\displaystyle{ \Psi_{b, i}= Ln_{2} \left ( D_{b, j} \right ) }[/math] (22)
  • Characteristic flow in the kth range (k=1...M)
[math]\displaystyle{ Q_{wr,k}= {\frac{1}{2}} \left ( Q_{wd,k} + Q_{wd, k+1} \right ) }[/math] (23)
  • Fraction of time the flow is in the kth range
[math]\displaystyle{ P_{Q,k}= {\frac{p_{eQ,k+1} - p_{eQ,k}}{100}} }[/math] (24)

Notes

  • Note on the program

The flow duration curve is specified in terms of the pairs (Qwd,k, peQ,k), k = 1..M+1. Here k = 1 corresponds to the highest flow in the curve, with an exceedance percentage peQ of zero, and k = M+1 corresponds to the lowest flow in the curve, with an exceedance percentage peQ of 100. The lowest flow on the curve Qwd,M must exceed zero.

Let Yk be any parameter defined for each of the flow ranges k = 1..M. The mean value Ya averaged over the flow duration curve is then given as

Ya = Sum(Yk pQ,k), k=1...M

For example, if the fractions in the bedload in each grain size range within flow range k are given as pk,i then the average fractions of the bedload pai are given as

pai = Sum(pk,i pQ,k)

Examples

An example run with input parameters, BLD files, as well as a figure / movie of the output

Follow the next steps to include images / movies of simulations:

See also: Help:Images or Help:Movies

Developer(s)

Gary Parker

References

  • Parker, G., 1990a. Surface based bedload transport relation for gravel rivers. Journal of Hydraulic Research, 28(4), 417~436.(DOI:10.1080/00221689009499058)
  • Parker, G.,1990b. The "ACRONYM" series of Pascal programs for computing bedload transport in gravel rivers. External Memorandum M 220, St. Anthony Falls Hydraulic Laboratory, University of Minnesota.

Links