# Study of the sediment fluxes of the Lower Mekong River 2012 September 25 to October 6th field mission

Guillaume Dramais, Philippe Dussouillez, Stephanie A. Moore, Jérôme Le Coz, Benoît Camenen

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Guillaume Dramais, Philippe Dussouillez, Stephanie A. Moore, Jérôme Le Coz, Benoît Camenen. Study of the sediment fluxes of the Lower Mekong River 2012 September 25 to October 6th field mission. IRSTEA. 2013. [hal-05468984](https://hal.science/hal-05468984v1)

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https://hal.science/hal-05468984v1

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# Study of the sediment fluxes of the Lower Mekong River

2012 September 25 to October 6th field mission

<figure><img src="image_2.png" /></figure>

Authors: Guillaume Dramais, Philippe Dussouillez, Stephanie Moore, Jerôme Le Coz, Benoît Camenen

Final report- 2013/05/06
<table>
  <tr>
    <td>Executive summary</td>
    <td>1</td>
  </tr>
  <tr>
    <td>1. Introduction</td>
    <td>1</td>
  </tr>
  <tr>
    <td>2. Materials and methods</td>
    <td>3</td>
  </tr>
  <tr>
    <td>2.1 Van Dorn Water Sampler</td>
    <td>3</td>
  </tr>
  <tr>
    <td>2.2 Concentration measurements of water samples</td>
    <td>3</td>
  </tr>
  <tr>
    <td>2.3 LISST-Portable grain size measurements</td>
    <td>4</td>
  </tr>
  <tr>
    <td>2.4 Acoustic Doppler Current Profilers</td>
    <td>4</td>
  </tr>
  <tr>
    <td>2.5 Global Positioning System measurements</td>
    <td>5</td>
  </tr>
  <tr>
    <td>2.6 AQUAscat</td>
    <td>6</td>
  </tr>
  <tr>
    <td>2.7 Bed-load sampler</td>
    <td>7</td>
  </tr>
  <tr>
    <td>3. Field measurements</td>
    <td>8</td>
  </tr>
  <tr>
    <td>3.1 Field procedure</td>
    <td>8</td>
  </tr>
  <tr>
    <td>3.2 Luang Prabang, Lao PDR</td>
    <td>8</td>
  </tr>
  <tr>
    <td>3.2.1 Discharge measurements</td>
    <td>10</td>
  </tr>
  <tr>
    <td>3.2.2 Moving bed test</td>
    <td>11</td>
  </tr>
  <tr>
    <td>3.2.3 Concentration and ADCP backscatter data</td>
    <td>13</td>
  </tr>
  <tr>
    <td>3.2.4 Grain size analysis of water samples</td>
    <td>15</td>
  </tr>
  <tr>
    <td>3.2.5 AQUAscat data</td>
    <td>16</td>
  </tr>
  <tr>
    <td>3.3 Measurement at Khong Chiam, Thailand</td>
    <td>19</td>
  </tr>
  <tr>
    <td>3.3.1 Discharge measurements</td>
    <td>20</td>
  </tr>
  <tr>
    <td>3.3.2 Concentration and ADCP backscatter data</td>
    <td>21</td>
  </tr>
  <tr>
    <td>3.3.3 Grain size data measured in water samples</td>
    <td>23</td>
  </tr>
  <tr>
    <td>3.3.4 AQUAscat data</td>
    <td>24</td>
  </tr>
  <tr>
    <td>3.4 Measurement at Kratie, Cambodia</td>
    <td>26</td>
  </tr>
  <tr>
    <td>3.4.1 Discharge measurements</td>
    <td>28</td>
  </tr>
  <tr>
    <td>3.4.2 Moving bed test</td>
    <td>29</td>
  </tr>
  <tr>
    <td>3.4.3 Dune tracking testing</td>
    <td>29</td>
  </tr>
  <tr>
    <td>3.4.4 Concentration data and acoustic backscatter</td>
    <td>30</td>
  </tr>
  <tr>
    <td>3.4.5 Grain size analysis</td>
    <td>32</td>
  </tr>
  <tr>
    <td>3.4.6 AQUAscat data</td>
    <td>33</td>
  </tr>
  <tr>
    <td>4. Sediment flux calculations</td>
    <td>34</td>
  </tr>
  <tr>
    <td>4.1 ADCP measurements</td>
    <td>34</td>
  </tr>
  <tr>
    <td>4.1.1 Calibration of acoustic backscatter data</td>
    <td>34</td>
  </tr>
  <tr>
    <td>5. Concentration estimates from the AQUAscat data</td>
    <td>37</td>
  </tr>
  <tr>
    <td>6. Laboratory grain size analysis of the water samples</td>
    <td>40</td>
  </tr>
  <tr>
    <td>7. Bed-load Analysis</td>
    <td>43</td>
  </tr>
  <tr>
    <td>8. Modelling</td>
    <td>46</td>
  </tr>
  <tr>
    <td>8.1 A model for sand concentration profiles and local bed-load transport</td>
    <td>46</td>
  </tr>
  <tr>
    <td>8.1.1 Sand concentration profiles</td>
    <td>46</td>
  </tr>
  <tr>
    <td>8.1.2 Bed-load transport</td>
    <td>47</td>
  </tr>
  <tr>
    <td>8.2 A simple model to estimate total sand transport throughout a section</td>
    <td>48</td>
  </tr>
  <tr>
    <td>8.2.1 Hydrometric station</td>
    <td>48</td>
  </tr>
  <tr>
    <td>8.2.2 Sand transport</td>
    <td>49</td>
  </tr>
  <tr>
    <td>9. Project feedback</td>
    <td>50</td>
  </tr>
  <tr>
    <td>9.1 Concentration (total suspended solids) measurements</td>
    <td>50</td>
  </tr>
  <tr>
    <td>9.2 Problems related to subsampling and the representativeness of the samples</td>
    <td>51</td>
  </tr>
  <tr>
    <td>9.3 Discharge measurements with ADCPs</td>
    <td>52</td>
  </tr>
  <tr>
    <td>9.4 Concentration of total suspended solids from a turbidity meter</td>
    <td>52</td>
  </tr>
</table>
<table><tr><td>10. Comparison of results to previous studies</td><td>54</td></tr><tr><td>11. Conclusions</td><td>55</td></tr><tr><td>References</td><td>58</td></tr><tr><td>Appendix A: AQUAscat data</td><td>60</td></tr></table>
<table>
  <tbody>
    <tr>
      <td>Figure 1: The three sites at which measurements were made: Luang Prabang, Khong Chiam and Kratie. (Source MRC)</td>
      <td>2</td>
    </tr>
    <tr>
      <td>Figure 2: Van Dorn Water Sampler.</td>
      <td>1</td>
    </tr>
    <tr>
      <td>Figure 3: Sampler deployment in Khong Chiam.</td>
      <td>1</td>
    </tr>
    <tr>
      <td>Figure 4: LISST-Portable measurement in Pakse.</td>
      <td>4</td>
    </tr>
    <tr>
      <td>Figure 5: Image of an RDI ADCP.</td>
      <td>1</td>
    </tr>
    <tr>
      <td>Figure 6: ADCP deployment in Kratie.</td>
      <td>5</td>
    </tr>
    <tr>
      <td>Figure 7: Image of an AQUAscat.</td>
      <td>7</td>
    </tr>
    <tr>
      <td>Figure 8: AQUAscat deployment in Luang Prabang.</td>
      <td>7</td>
    </tr>
    <tr>
      <td>Figure 9: Bed-load sampler deployment in Kratie.</td>
      <td>8</td>
    </tr>
    <tr>
      <td>Figure 10: Water level at Luang Prabang for a two month period (blue line) and for the day on which measurements were made (red circle).</td>
      <td>9</td>
    </tr>
    <tr>
      <td>Figure 11: The rating data (black circles) and rating curve (black line) from Luang Prabang provided by the MRC, compared to the discharge measured by ADCP on 2012-10-02 (red square).</td>
      <td>9</td>
    </tr>
    <tr>
      <td>Figure 12: Satellite image of the Luang Prabang study site. The GPS data points depict the measurement section (in the middle), and the upstream and downstream cross sections. The flow is from top right to bottom left. N.B. This image does not correspond to the water level at the time of measurement.</td>
      <td>10</td>
    </tr>
    <tr>
      <td>Figure 13: The velocity measured with the ADCP during one transect at Luang Prabang. The left bank is on the left side of the figure.</td>
      <td>11</td>
    </tr>
    <tr>
      <td>Figure 14: Ship track at Luang Prabang during a two-way transect (starting on the right bank) as measured when using the GPS as the reference (GGA) and when using the bottom-tracking function of the ADCP (BT). The point at which the trajectories overlap is the start of the measurements.</td>
      <td>12</td>
    </tr>
    <tr>
      <td>Figure 15: Top panel: Magnitude of the apparent bed-load velocity at Luang Prabang calculated as the bed velocity vector referenced to the GPS trajectory minus the bed velocity vector referenced to ADCP bottom tracking (raw data in red, averaged data in blue). Bottom panel: the bathymetry measured with ADCP bottom tracking (blue) and the depth-averaged GPS-referenced water velocity (green).</td>
      <td>13</td>
    </tr>
    <tr>
      <td>Figure 16: Location and concentration of the samples collected at Luang-Prabang. Concentrations measured via filtration are given in mg/L. The depths of the samples correspond to the length of the cable that was let out. Note: a depth-integrated sampler was used as a point sampler.</td>
      <td>14</td>
    </tr>
    <tr>
      <td>Figure 17: Acoustic backscatter at 1200 kHz corrected for spreading and attenuation due to water.</td>
      <td>14</td>
    </tr>
    <tr>
      <td>Figure 18: Grain size distributions measured with the LISST portable for water samples collected at Luang Prabang. Note that sample LP10<sub>1</sub> is plotted twice.</td>
      <td>15</td>
    </tr>
    <tr>
      <td>Figure 19: Positions at which the AQUAscat was lowered at Luang Prabang.</td>
      <td>17</td>
    </tr>
    <tr>
      <td>Figure 20: Cable setting versus sensor measurement for sampling at Luang Prabang.</td>
      <td>18</td>
    </tr>
    <tr>
      <td>Figure 21: AQUAscat 1000 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</td>
      <td>18</td>
    </tr>
    <tr>
      <td>Figure 22: Water level at Khong Chiam for a two month period (blue line) compared to the value recorded on the day of measurements (red circle).</td>
      <td>19</td>
    </tr>
    <tr>
      <td>Figure 23: Rating curve and data at Khong Chiam for calendar year 2011 (provided by the MRC), compared to the ADCP measurements made October 4 (red square).</td>
      <td>19</td>
    </tr>
    <tr>
      <td>Figure 24: Khong Chiam measurement site. The flow is from top left to bottom right. The GPS data points depict the measurement section (bottom right), and the upstream cross sections (top left).</td>
      <td>20</td>
    </tr>
    <tr>
      <td>Figure 25: The measurement transect in Khong Chiam with velocity data measuring during one transect using the bottom tracking (BT) as the reference.</td>
      <td>21</td>
    </tr>
    <tr>
      <td>Figure 26: Location and concentration of the samples collected at Khong Chiam. Concentrations were measured via filtration and are given in mg/L.</td>
      <td>22</td>
    </tr>
    <tr>
      <td>Figure 27: Range-corrected acoustic backscatter recorded by the 600 kHz ADCP.</td>
      <td>23</td>
    </tr>
  </tbody>
</table>
<table>
  <tbody>
    <tr>
      <td>Figure 28: Grain size distributions measured with a LISST portable in water samples collected at Khong Chiam.</td>
      <td>23</td>
    </tr>
    <tr>
      <td>Figure 29: Across stream positions at which the AQUAscat was deployed.</td>
      <td>25</td>
    </tr>
    <tr>
      <td>Figure 30: Khong Chiam 1000 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</td>
      <td>25</td>
    </tr>
    <tr>
      <td>Figure 31: Water level at Kratie for a two month period (blue line) and for the day of measurements (red circle).</td>
      <td>26</td>
    </tr>
    <tr>
      <td>Figure 32: Rating Curve at Kratie established by the MRC with data from 2008 – 2010 compared to the discharge measured during this study (red square).</td>
      <td>26</td>
    </tr>
    <tr>
      <td>Figure 33: Locations of transects: upstream transect is across from the hydro/meteorological station and the downstream transect is where all gauging and sediment measurements were made. The flow is from top to bottom. N.B. This image does not correspond to the water levels when the measurements were made.</td>
      <td>27</td>
    </tr>
    <tr>
      <td>Figure 34: Bathymetry and velocity values measured at Kratie during one transect with a 1200 kHz ADCP.</td>
      <td>28</td>
    </tr>
    <tr>
      <td>Figure 35: Sample of the ADCP data collected as the boat moved downstream. The wavy bottom corresponds to sand dunes.</td>
      <td>30</td>
    </tr>
    <tr>
      <td>Figure 36: Location and concentration of the samples collected at Kratie. Concentrations were measured via filtration and are given in mg/L.</td>
      <td>31</td>
    </tr>
    <tr>
      <td>Figure 37: Acoustic backscatter at 1200 kHz corrected for spreading and attenuation due to water. The data have been averaged over two ensembles.</td>
      <td>31</td>
    </tr>
    <tr>
      <td>Figure 38: Grain size distributions measured with the LISST portable for water samples collected at Kratie.</td>
      <td>32</td>
    </tr>
    <tr>
      <td>Figure 39: Kratie AQUAscat data recorded at 1000 kHz, fluid corrected intensity data near the left bank (V1), middle (V2) and right bank (V3) of the section.</td>
      <td>34</td>
    </tr>
    <tr>
      <td>Figure 40: Demodulation of the grain size distributions measured in Kratie samples KR14 and KR24.</td>
      <td>35</td>
    </tr>
    <tr>
      <td>Figure 41: Estimates of the concentration of suspended sand at Luang Prabang obtained with Sediview by calibrating the backscatter data of Figure 17 with the water samples.</td>
      <td>36</td>
    </tr>
    <tr>
      <td>Figure 42: Time-averaged fluid-corrected intensity profile recorded at 20 m depth of vertical V2 at Khong Chiam.</td>
      <td>37</td>
    </tr>
    <tr>
      <td>Figure 43: Profiles of fine suspended sediment (silt) and suspended sand concentration at Kratie calculated from the 2500 and 400 kHz AQUAscat data.</td>
      <td>39</td>
    </tr>
    <tr>
      <td>Figure 44: Profiles of fine suspended sediment (silt) and sand concentration at Khong Chiam calculated from the 2500 and 400 kHz AQUAscat data. Sand concentration for V1 was always zero.</td>
      <td>39</td>
    </tr>
    <tr>
      <td>Figure 45: Profiles of fine suspended sediment (silt) and sand concentration at Luang Prabang calculated from the 2500 and 400 kHz AQUAscat data.</td>
      <td>40</td>
    </tr>
    <tr>
      <td>Figure 46: Magnified images of the sand-sized particles from samples KR15 (left) and KR5 (right) with a millimeter grid in the background.</td>
      <td>41</td>
    </tr>
    <tr>
      <td>Figure 47: Water sample KR5, comparison of grain size distributions measured with: a LISST portable (detectable range: d = 2.7 – 460 microns), a Cilas (detectable range: 50 nm – 2 mm) and a Laser Beckman Coulter LS 13 320 (detectable range: 40 nm – 2 mm). Note that different subsamples were used for each of the three instruments.</td>
      <td>42</td>
    </tr>
    <tr>
      <td>Figure 48: Water sample KR8, comparison of grain size distributions measured with: a LISST portable, a Cilas and a Laser Beckman Coulter LS13 320. Different subsamples were used for each of the three instruments.</td>
      <td>42</td>
    </tr>
    <tr>
      <td>Figure 49: Water sample KR15, comparison of grain size distributions measured with: a LISST portable, a Cilas and a Laser Beckman Coulter LS 13 320. Different subsamples were used for each of the three instruments.</td>
      <td>43</td>
    </tr>
  </tbody>
</table>
<table>
  <tbody>
    <tr>
      <td>Figure 50: Bathymetry and depth-average water velocity from an ADCP transect at Luang Prabang (top); Bed-load velocity measured from ADCP and GPS data for the same ADCP transect (middle); Modelled bed-load velocity.</td>
      <td>44</td>
    </tr>
    <tr>
      <td>Figure 51: Bathymetry and depth-average water velocity from an ADCP transect at Kratie (top); Bed-load velocity measured from the same ADCP transect at Kratie (middle); modelled bed-load velocity (bottom).</td>
      <td>45</td>
    </tr>
    <tr>
      <td>Figure 52: Vertical velocity profiles from ADCP measurements and model (a) and vertical concentration profiles (measured and modelled) (b) for the three verticals at Luang Prabang where concentrations were measured.</td>
      <td>47</td>
    </tr>
    <tr>
      <td>Figure 53: Stage-discharge relationship at Luang Prabang (a) and Kratie (b).</td>
      <td>48</td>
    </tr>
    <tr>
      <td>Figure 54: Estimation of the total bed-load and suspended sand load at Luang Prabang (a) and Kratie (b) together with experimental measurements (black symbols: bedload; red symbols: suspension; see detailed explanations in the text).</td>
      <td>50</td>
    </tr>
    <tr>
      <td>Figure 55: An example of the relationship between Total Suspended Sediment Concentration (TSS) and turbidity on the Arc river (France).</td>
      <td>53</td>
    </tr>
    <tr>
      <td>Figure 56: Photograph of a turbidity meter station on the Arc River (France).</td>
      <td>54</td>
    </tr>
    <tr>
      <td>Figure 57: AQUAscat 500 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</td>
      <td>60</td>
    </tr>
    <tr>
      <td>Figure 58: AQUAscat 1000 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</td>
      <td>61</td>
    </tr>
    <tr>
      <td>Figure 59: AQUAscat 2500 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</td>
      <td>61</td>
    </tr>
    <tr>
      <td>Figure 60: AQUAscat 4000 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</td>
      <td>62</td>
    </tr>
    <tr>
      <td>Figure 61: Khong Chiam 500 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</td>
      <td>63</td>
    </tr>
    <tr>
      <td>Figure 62: Khong Chiam 1000 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</td>
      <td>63</td>
    </tr>
    <tr>
      <td>Figure 63: Khong Chiam 2500 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</td>
      <td>64</td>
    </tr>
    <tr>
      <td>Figure 64: Khong Chiam 4000 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</td>
      <td>64</td>
    </tr>
    <tr>
      <td>Figure 65: AQUAscat acoustic backscatter data collected at 500 kHz, corrected for spreading and attenuation due to water. V1 was the closest position to the left bank. The instrument faced the left bank.</td>
      <td>65</td>
    </tr>
    <tr>
      <td>Figure 66: Kratie AQUAscat data at 1000 kHz.</td>
      <td>65</td>
    </tr>
    <tr>
      <td>Figure 67: Kratie AQUAscat data at 2500 kHz.</td>
      <td>66</td>
    </tr>
    <tr>
      <td>Figure 68: Kratie AQUAscat data at 4000 kHz.</td>
      <td>66</td>
    </tr>
  </tbody>
</table>
<table>
  <tbody>
    <tr>
      <td>Table 1: Discharge measurements (ref. GPS) at Luang Prabang on 2012-10-02 (ADCP WorkHorse Rio Grande 1200 kHz Irstea)</td>
      <td>11</td>
    </tr>
    <tr>
      <td>Table 2: A summary of the grain size distributions measured by the LISST in the second sample (see Figure 18).</td>
      <td>16</td>
    </tr>
    <tr>
      <td>Table 3: Discharge measurements at Khong Chiam (ref. BT) October 4, 2012 (ADCP WorkHorse Rio Grande 600 kHz CEREGE).</td>
      <td>21</td>
    </tr>
    <tr>
      <td>Table 4: A summary of the LISST measurements of the second subsample of the water samples collected at Khong Chiam.</td>
      <td>24</td>
    </tr>
    <tr>
      <td>Table 5: Discharge measurements at Kratie September 27th (ADCP WorkHorse Rio Grande 1200 kHz Irstea, Reference GPS)</td>
      <td>28</td>
    </tr>
    <tr>
      <td>Table 6: Discharge measurements at Kratie September 28th (ADCP WorkHorse Rio Grande 600 kHz DHRW. ADCP WorkHorse Rio Grande 1200 kHz Irstea, Reference GPS).</td>
      <td>29</td>
    </tr>
    <tr>
      <td>Table 7: A summary of the LISST measurements of the second subsample of water samples from Kratie.</td>
      <td>32</td>
    </tr>
    <tr>
      <td>Table 8: Summary of average discharge and sediment transport fluxes calculated at each site.</td>
      <td>36</td>
    </tr>
    <tr>
      <td>Table 9: The dry weight and median diameter of bed-load samples collected at Kratie (a) and Luang Prabang (b) during a 2 min period.</td>
      <td>45</td>
    </tr>
    <tr>
      <td>Table 10: Estimated bed-load fluxes.</td>
      <td>45</td>
    </tr>
    <tr>
      <td>Table 11: Total suspended solid concentrations measured in subsamples of five samples by the DHRW and the Irstea Lyon labs.</td>
      <td>50</td>
    </tr>
    <tr>
      <td>Table 12: Results of subsampling test.</td>
      <td>51</td>
    </tr>
    <tr>
      <td>Table 13: Discharge values calculated using bottom tracking and GPS data as the reference.</td>
      <td>52</td>
    </tr>
  </tbody>
</table>
Executive summary

The objective of this project was to measure the flux of sediment and the spatial distribution of both particle size and concentration at three locations in different physiographic regions of the Lower Mekong at the end of the 2012 rainy season. Measurements conducted at Luang Prabang, Khong Chiam and Kratie stations included flow speed and discharge measurements with Acoustic Doppler Current Profilers (ADCPs), high-resolution acoustic backscatter measurements with an AQUAscat, bed-load material measurements and water sampling at specific depths. The flux values of washload, suspended sand, and bed-load obtained at the 3 sites were [630; 70 or 730 depending on the method; 5.5] kg/s at Luang Prabang, [1100; 230; ~0] kg/s at Khong Chiam (no bed-load sampling was done), and [4900; 590; 150] kg/s at Kratie. We suspect that sand was undersampled at Luang Prabang: acoustic data suggest that the suspended sand load may have been as high as the washload. These flux values are consistent with available data in the literature. However, they must be used cautiously as orders of magnitude, recalling that sediment transport is much more intense during the rising limb of the annual flood.

While the flux of the homogeneous washload (median diameter ~10-20 µm) can be accurately quantified from water samples and ADCP gauging, the fluxes of sand as suspended load (d~70-200 µm) and bed-load (d~300-500 µm) are difficult to measure and estimate with acceptable uncertainty. Sampling suspended sand was potentially inaccurate due to the small sampled volumes, the difficulty subsampling, and the temporal and spatial fluctuations of the transport, especially around the dune crests, as revealed by acoustic measurements. Large-volume time-integrated samplers, such as a Delft bottle, are therefore to be preferred for sampling sand accurately, while washload can be sampled with a Van Dorn bottle. A swath echosounder would be helpful to know the position of both bed-load and suspended-load samplers within the bedform fields. The grain-size analysis of each sediment sample is always required to correctly interpret the different modes of solid transport. Hydro-acoustic measurements provided valuable data on the spatial distribution of sand and bed-load transport across the sections, improving the computation of flux estimates.

1. Introduction

The Mekong River spans nearly five thousand kilometres and flows through six countries. The Mekong Basin is one of the world's richest in terms of biodiversity. However, land-use changes, sediment extractions and the construction of dams on the Mekong and its tributaries are changing its sediment transport and morphology. Consequences of these changes may include increased bank erosion and a reduction in sediment supply to floodplains. These changes can have adverse effect on the agricultural productivity of the region, among other things. In order to monitor these changes, the current conditions must be well understood.

The four member countries of the Mekong River Commission (MRC), Cambodia, Lao PDR, Thailand and Viet Nam regularly monitor flow rates at a number of stations. In 2010 a discharge and sediment monitoring program was instigated by the Information and Knowledge Management Programme (IKMP) of the MRC (MRC IKMP 4th Bi-annual progress report, 2012). This has included the establishment of two laboratories in Cambodia and Lao for grain size analysis of sediment samples as well as the implementation of monitoring programs at sixteen sites. Despite these efforts, there is debate about the accuracy of the sediment transport fluxes that are measured because, until recently, sediment sampling consisted primarily of surface water samples, while the sediment that can be deposited is more likely transported near the bed (Walling, 2005). The
sediment in the upper part of the water column, the wash load, is fine sediment that is generally carried by the river but is not deposited. However, the bed and bank material over large stretches of the Lower Mekong are sand-sized particles and there is believed to be substantial amounts of sand transported near the bed. Few of the sediment samples collected to date include sand-sized sediments. This could be for a number of reasons, including the samplers not being lowered close enough to the bed and the loss of sand in the filtration or size analysis processes as larger particles settle out very quickly.

The objective of this project was to measure the flux of sediment and the spatial distribution of both particle size and concentration at three locations in different physiographic regions of the Lower Mekong at the end of the 2012 rainy season. This was a joint project between the World Wildlife Fund (WWF) and the MRC and its member countries. From upstream to downstream the sites were Luang Prabang in Lao PDR, Khong Chiam in Thailand and Kratie in Cambodia (Fig. 1). Measurements included flow speed and discharge measurements with Acoustic Doppler Current Profilers (ADCPs), high-resolution acoustic backscatter measurements with an AQUAscat, bed load material measurements and water sampling at specific depths. The water samples were used to determine the spatial distribution of both concentration and grain size of the particles in suspension throughout the cross section.

<figure><img src="image_3.png" /><figcaption>Figure 1: The three sites at which measurements were made: Luang Prabang, Khong Chiam and Kratie. (Source MRC)</figcaption></figure>
## 2. Materials and methods

### 2.1 Van Dorn Water Sampler

A Van Dorn water sampler was used to collect 2-L water samples at specific depths. The sampler consists of a cylinder that has two removable ends. It is attached to a rope and is lowered horizontally into the water. When it is at the desired depth a weight is dropped onto the sampler that closes the ends, which ensures that the sample corresponds to water at a specific depth. In high-flow conditions the rope will be carried by the current and the length of the rope may not correspond to the depth of the sampler. Therefore, at one of the study sites a Mini-Diver pressure sensor and logger was attached to the sampler to monitor the sampling depth.

Ideally, the recipient into which the water is poured should be the same volume as the sampler, but due to material availability, these recipients were empty 500 mL drinking water bottles. Two bottles were filled for each Van Dorn sample. This means that only half the sample from the sampler was retained and it had to be divided into two separate bottles. Despite our best efforts to distribute the sand-sized particles evenly by mixing the sample immediately prior to filling the bottles, coarse sediment within the sample may have remained within the sampler and/or been poured into only one of the two water bottles.

<figure><img src="image_4.png" /><figcaption>Figure 2: Van Dorn Water Sampler.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Figure 3: Sampler deployment in Khong Chiam.</figcaption></figure>

### 2.2 Concentration measurements of water samples

The concentration of sediment in the water samples was determined by filtration. For each depth and across stream distance at which a water sample was collected, one 500 mL bottle was returned to France. Concentration was determined at Irstea Lyon according to the European standard NF EN 872 (Water quality: Determination of suspended solids - method by filtration through glass fibre filters, June 2005), for which a dry residue of at least 2 mg is the requirement for a valid result. This was not an issue due to the high concentrations (> 100 mg/L) that were observed.
## 2.3 LISST-Portable grain size measurements

Grain size distributions of the sediment in the water samples were measured with a Laser In Situ Scattering and Transmissometry (LISST) Portable within a few days of sample collection. The LISST is a laser diffraction particle sizer (Figure 4) which measures the light diffracted by a suspension of particles and uses Mie theory to relate the scattering pattern to a grain size distribution, assuming that the particles are either spherical or randomly shaped. The size range of particles that can be measured with the instrument is between 2.5 and 400 microns (equivalent spherical diameter). Roughly 100 mL of each sample are required for the analysis. As will be seen in Part 7 of this report, the subsampling of the water samples can be problematic, especially for sand-sized particles.

<figure><img src="image_6.png" /><figcaption>Figure 4: LISST-Portable measurement in Pakse.</figcaption></figure>

## 2.4 Acoustic Doppler Current Profilers

Acoustic Doppler Current Profilers (ADCPs) (Figure 5) were used to measure flow speeds, bathymetry and discharge. Each transducer of an ADCP (shown in red in Figure 5) records the acoustic backscatter at a range of distances from the instrument, which can be converted to concentrations of suspended matter. This was achieved using the commercial software SediView (HR Wallingford) and sampled suspended sand concentrations as calibration data.

ADCPs also measure the distance to the river bed and the flow speed of the water along each vertical profile. By attaching an ADCP to a motor boat (Figure 6), the velocity of the water can be measured across an entire cross section as the boat traverses from one river bank to the other, which is known as “performing transects”. The trajectory of the boat relative to the river bed is measured by the ADCP.

At each site the ADCP's internal compass was calibrated prior to the discharge measurement. After the calibration, two or more transects were performed in order to measure the discharge. As a
standard procedure, four or six transects should be performed, but since the flow appeared steady and time was limited, two transects was standard for this field campaign. In addition to providing measurements of flow speed and bottom depth, the ADCP and Global Positioning System (GPS) measurements are used to detect movement of the bed, as will be described in the following section.

<figure><img src="image_7.png" /><figcaption>Figure 5 : Image of an RDI ADCP.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Figure 6 : ADCP deployment in Kratie.</figcaption></figure>

**2.5 Global Positioning System measurements**

Global Positioning System (GPS) measurements were made at all positions at which water samples were collected and where acoustic backscatter measurements were made. The GPS was used in differential mode, with a reference station on shore in order to determine the difference between the positions predicted by the satellites and their actual position. The uncertainty in the differential GPS positions is less than 10 cm. The GPS signal was relayed to the ADCP during the discharge measurements so that the velocity of the water could be accurately measured even if the bed was moving. Since the GPS correction was done after the acquisition, the differential GPS mode could not be used with the ADCP software; therefore GPS resolution for the ADCP measurements was 5 - 10 m.

The ADCP determines the water velocity relative to its frame of reference, which in this case moves with the speed of the boat. If the river bed is moving (i.e. there is bed-load transport), then the boat trajectory measured by the ADCP will not match that measured by the GPS since the reference frame for the ADCP is in motion. Thus, the speed of the bed-load transport can be estimated with ADCP and GPS data. The GPS data can also be used to determine the amount by which the boat drifted during water sampling. This is useful in the interpretation of the water sample data, since the across and along-stream positions were often difficult to maintain.

An attempt was made to do dune-tracking with the ADCP coupled to the GPS by recording data as the boat went downstream and then back upstream along the same trajectory. This was useful for the visualization of the dunes (wavelength and height can be determined, see Figure 36), however, the ADCP is not suitable for dune tracking; a multibeam or swath echosounder coupled with a GPS and
an inertial measurement unit would be required in order to ensure that measurements be made at
exactly the same position for both trajectories.

## 2.6 AQUAscat

The AQUAscat (Figure 7) is an acoustic backscatter system that can be used to measure the spatial distribution of suspended particles. This instrument was loaned by Aquatec Group Ltd. to S. Moore who won the 2012 Aquatec Equipment Award.

Sound waves are transmitted by the instrument and scattered by the particles in the water. The instrument records the portion of sound that is scattered in its direction (the backscatter) over a range of distances from the instrument. The maximum range depends on the frequency of the instrument since higher frequency signals are more heavily attenuated. At a given range from the instrument, the intensity of the backscattered signal depends on (1) the ratio between the size of the particles and the wavelength of the incident wave and (2) the concentration of the particles. It also depends on the distance from the instrument to the measurement location because the intensity of the sound decreases with range from the instrument as the sound waves spread and are attenuated by the water and by the particles in the water. The acoustic attenuation is a function of frequency, particle size and concentration. The higher is the frequency, the higher the attenuation, similarly, higher concentrations lead to higher attenuation. Therefore, by analyzing the intensity and attenuation of the backscatter data at different frequencies, one can get an idea of the size and concentration of particles in the water, which in this case are primarily sediment. The transducers used in this study operated at 500 kHz, 1 MHz, 2.5 MHz and 4 MHz.

At each of the three sites the AQUAscat was deployed horizontally (Fig. 8) at three or four across-stream positions and four to seven depths per vertical. It was attached to the frame of the bed-load sampler for weight. The instrument was deployed horizontally in order to simplify interpretation of the data, the sensors measured spanwise. The interpretation of horizontal backscatter profiles is simpler than that of vertical profiles because there are rarely horizontal gradients in grain size or concentration, whereas there are vertical gradients. Backscatter profiles were acquired with a resolution of 4 cm; they were 2 - 10 m long, depending on the frequency of the transducer. The instrument's pressure logger was used to determine the depth of measurements. Temperature data recorded by the instrument were used to determine the theoretical sound speed (used to determine measurement cell sizes) and attenuation due to water. In all figures presented in this report, the backscattered intensity profiles have been corrected for acoustic spreading and attenuation due to water. They depict the scattering and attenuation from the suspended sediment. We refer to these values as the fluid-corrected intensity.
<figure><img src="image_9.png" /><figcaption>Figure 7: Image of an AQUAscat.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Figure 8: AQUAscat deployment in Luang Prabang.</figcaption></figure>

## 2.7 Bed-load sampler

A bed-load sampler modelled on the US BL84 (Fig. 9) was used to sample bed-load material, that is the sediment transported near the bed. It consisted of a fish-shaped metal frame around a 7x7 cm square mouth connected to a cloth bag in which the sample was collected. It weighed approximately 30 kg. It was lowered to the river bed and remained there for 2 minutes. Bed-load samples were collected at Luang Prabang and Kratie, but not at Khong Chiam because of concerns that it would get caught on the rocky bottom. At each site, five samples were collected at different across stream positions. Forty samples are typically recommended for reliable estimates of bed-load transport rates (e.g. Edwards and Glysson, 1999). This was not possible due to time constraints, therefore an accurate estimate of bed-load sediment fluxes cannot be obtained but rather an idea of transport rates can be given. The bed-load samples that were collected were analyzed for grain size, as will be seen later in this report. The apparent bed-load velocity provided by the ADCP bottom-tracking function was used to infer the distribution of the bed-load intensity across the river section, in order to assess the bed-load flux from the local bed-load sampling.
<figure><img src="image_11.png" /><figcaption>Figure 9: Bed-load sampler deployment in Kratie</figcaption></figure>

# 3. Field measurements

## 3.1 Field procedure

The primary goal of the field work was to make simultaneous measurements of flow speeds and the spatial distribution of sediment (both suspended and bed-load) using acoustic data (ADCP and AQUAscat) and physical samples. These direct measurements (water samples) and indirect measurements (acoustics) were combined in order to calculate sediment fluxes (distinguishing between fine sediment and sand) within each cross section and to demonstrate (1) the presence of sand in suspension, which until now was difficult to capture, and (2) the transport of sediment as bed-load. At each site, the measurement campaign began with a measurement of discharge at the gauging cross-section of the hydrometric station. This was done using the ADCP coupled to the GPS. Next, water samples and acoustic backscatter data (AQUAscat) were collected throughout the same cross-section. Additional measurements of bathymetry and bed-load were made at Luang Prabang and Kratie. The field measurements are presented in the remainder of this report from upstream to downstream, hence they are not in chronological order.

## 3.2 Luang Prabang, Lao PDR

Measurements were made at Luang Prabang on October 2, 2012 during the recession limb of the annual monsoon flood with the help of the Lao Department of Meteorology and Hydrology (DMH). The water level at Luang Prabang in October and November 2012 is shown in Figure 10. The level that was observed during the present measurements is shown in red. The rating curve that is used by the MRC (Figure 11) is compared to the discharge measured by ADCP and the water level measured during this campaign. It can be seen that the measurements lie perfectly on the rating curve. The DMH routinely measures discharge at Luang Prabang using a current meter.
<figure><img src="image_12.png" /><figcaption>Figure 10: Water level at Luang Prabang for a two month period (blue line) and for the day on which measurements were made (red circle).</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>Figure 11: The rating data (black circles) and rating curve (black line) from Luang Prabang provided by the MRC, compared to the discharge measured by ADCP on 2012-10-02 (red square).</figcaption></figure>

Measurements made at Luang Prabang (Date: October 2, 2012):

* Water samples at 3 - 5 depths at 4 across-stream positions throughout the gauging cross-section. A depth-integrated sampler used as a point sampler by lowering it to the desired depth as quickly as possible.

* Multifrequency acoustic backscatter measurements with the AQUAscat at 4-6 depths at 4 across-stream positions. The transducers were deployed horizontally, facing the right bank.
* ADCP gauging

* Bed-load sampling at 3 across-stream positions

* Two ADCP transects 1 km upstream of the measurement section (Figure 12)

* ADCP measurements along a 2 km trajectory over the deepest part river (Figure 12)

* Two ADCP transects 1 km downstream of the measurement section (Figure 12)

<figure><img src="image_14.png" /><figcaption>Figure 12: Satellite image of the Luang Prabang study site. The GPS data points depict the measurement section (in the middle), and the upstream and downstream cross sections. The flow is from top right to bottom left. N.B. This image does not correspond to the water level at the time of measurement.</figcaption></figure>

### 3.2.1 Discharge measurements

The velocity data measured by the ADCP during one transect are presented in Figure 13. The GPS track was used as the reference for the trajectory since a moving bed was observed. From Figure 13 it can be seen that flow at Luang Prabang is faster in the left two-thirds of the section. The discharge values calculated from the ADCP data using the software WinRiver II are presented in Table 1. The water level was recorded three times throughout the day. The average discharge was 4812 m³/s. The water level dropped 16 cm between the first and the last measurement. The water level and discharge that were measured were in very good agreement with MRC's rating curve for this site.
<table><caption>Table 1: Discharge measurements (ref. GPS) at Luang Prabang on 2012-10-02 (ADCP WorkHorse Rio Grande 1200 kHz Irstea)</caption><thead><tr><th>File</th><th>Date / Start Time</th><th>Discharge (m/s)<sup>3</sup></th><th>Comment</th></tr></thead><tbody><tr><td>LuangPrabang_0_000.pd0</td><td>12/10/02 6:47</td><td>5027</td><td>Water level 8.64m (06:22)</td></tr><tr><td>LuangPrabang_0_002.pd0</td><td>12/10/02 7:38</td><td>4736</td><td></td></tr><tr><td>LuangPrabang_0_002.pd0</td><td>12/10/02 7:47</td><td>4721</td><td></td></tr><tr><td>LuangPrabang_p_m_000.pd0</td><td>12/10/02 14:12</td><td>4739</td><td></td></tr><tr><td>LuangPrabang_p_m_000.pd0</td><td>12/10/02 14:19</td><td>4804</td><td>Water level 8.55m (15:07)</td></tr><tr><td>LuangPrabang_p_l_002.pd0</td><td>12/10/02 15:56</td><td>4810</td><td>Upstream cross section</td></tr><tr><td>LuangPrabang_p_l_002.pd0</td><td>12/10/02 16:06</td><td>4850</td><td>Water level 8.48m (16:30)</td></tr><tr><td>Average</td><td></td><td>4812</td><td></td></tr><tr><td>Standard deviation</td><td></td><td>106</td><td></td></tr></tbody></table>

<figure><img src="image_15.png" /><figcaption>Figure 13: The velocity measured with the ADCP during one transect at Luang Prabang. The left bank is on the left side of the figure.</figcaption></figure>

### 3.2.2 Moving bed test

By comparing the boat's trajectory (ship track) when using the ADCP's bottom tracking function as the reference and when using the GPS data as the reference, one can monitor the movement of the bed material. If there is active bed-load, i.e. if a substantial amount of sediment is being transported along the bed, then the apparent bottom-track is biased upstream since the bed that is perceived by the ADCP is moving downstream. The ship tracks of a two-way transect are presented in Figure , which was plotted with Winriver II software. It appears as though there was a moving bed since the ship tracks calculated using bottom tracking and GPS data differed noticeably.
The difference between the bottom velocity vectors measured using either GPS or bottom tracking as the reference gives the apparent bed-load velocity (see top panel of Figure 15). The width of the active layer (the zone in which sediment is transported as bed-load) can be determined from the distribution of apparent bed-load velocity across the section. By multiplying the active layer width by the mass of sediment collected with the bed-load sampler per unit width per unit time, we can estimate total bed-load sediment fluxes throughout the river section. A restrictive assumption of this method is that the sampler mouth is exposed to the full height of the active bed-load layer.

From Figure 15 it can be seen that the average apparent bed-load velocity is less than 0.1 m/s towards the right bank, but it reaches 0.25 m/s in the middle and left-bank half of the section where the average water velocity was higher (see bottom panel of Figure 15). This is consistent with higher flow speeds leading to the transport of more material.

<figure><img src="image_16.png" /></figure>

Figure 14: Ship track at Luang Prabang during a two-way transect (starting on the right bank) as measured when using the GPS as the reference (GGA) and when using the bottom-tracking function of the ADCP (BT). The point at which the trajectories overlap is the start of the measurements.
<figure><img src="image_17.png" /><figcaption>Figure 15: Top panel: Magnitude of the apparent bed-load velocity at Luang Prabang calculated as the bed velocity vector referenced to the GPS trajectory minus the bed velocity vector referenced to ADCP bottom tracking (raw data in red, averaged data in blue). Bottom panel: the bathymetry measured with ADCP bottom tracking (blue) and the depth-averaged GPS-referenced water velocity (green).</figcaption></figure>

### 3.2.3 Concentration and ADCP backscatter data

The points in the cross section at which water samples were collected are presented in Figure 16. It can be seen that concentrations of suspended sediment ranged from 118 mg/L (LP6 at 2m depth) to 174 mg/L (LP4 at 10m) and the average was 155 mg/L. There is no noticeable increase in concentration of suspended sediment towards the bed, likely because a depth-integrated sampler was used in place of the Van Dorn sampler due to instrument availability. Though it was lowered to the desired depth as quickly as possible, it likely filled with water before reaching the location of interest. It took approximately 50 seconds for the sampler to be lowered to the bottom, while it took only 48 seconds for it to fill completely when at the surface.

Figure 17 depicts the acoustic backscatter corrected for range (spherical spreading and attenuation due to water), which is a proxy for the distribution of sediment. Recalling that higher concentrations of particles and/or larger particles lead to higher backscatter, these acoustic data indicate that there was more suspended sediment on the left side of the river than towards the right bank, which would be consistent with the higher flow speeds on the left. They also indicate that there were vertical
gradients in the suspended sediment (either concentration or grain size), with higher backscatter values observed both at the surface and near the bed. This was not reflected in the water samples because a depth-integrated sampler cannot be used as a point-integrated sampler, so the concentrations attributed to the different depths also contain water collected between the surface and that point.

<figure><img src="image_18.png" /><figcaption>Figure 16: Location and concentration of the samples collected at Luang-Prabang. Concentrations measured via filtration are given in mg/L. The depths of the samples correspond to the length of the cable that was let out. Note: a depth-integrated sampler was used as a point sampler.</figcaption></figure>

<figure><img src="image_19.png" /><figcaption>Figure 17: Acoustic backscatter at 1200 kHz corrected for spreading and attenuation due to water.</figcaption></figure>
### 3.2.4 Grain size analysis of water samples

Grain size analysis was performed on the samples using a LISST-Portable. For each sampling position, one of the two 500-mL samples was divided in three. Two parts were used for repeat measurements with the LISST and the third was returned to France for further grain size analysis in some cases. The second 500 mL sample was used for concentration analysis. The grain size results are presented in Figure 18 and Table 2. The distributions have been truncated at 5 microns because of the uncertainty of laser grain size measurements of the finest sediments. The position of each sample is shown in Figure 16.

These results suggest that two size classes of sediment are being transported:

- fine silts (peak in the distribution around 14 µm)

- fine to medium sand (peak from 170 - 230 µm)

In order to determine the median value and width of the distributions of fine and coarse sediments at each point, the two corresponding Gaussian distributions can be separated from the grain size distributions. Such division of the grain-size distributions is more representative of the actual sediment populations in the sample than the usual separation based on arbitrary grain size thresholds, typically at 63 µm. The distributions of the two size fractions are required in the interpretation of the ADCP data, among other things. At each sampling position, the percent breakdown between the two size fractions is multiplied by the concentration measured in the corresponding sample to obtain the concentration of fine suspended sediment and of suspended sand at each sampling position. The underlying assumption is that the grain size distribution measured in one subsample can be applied to the concentration measured in a corresponding subsample. The Gaussian mode separation results for the second LISST measurements are summarized in Table 2 along with the break-down of each sample between fine and coarse sediment.

<figure><img src="image_20.png" /><figcaption>Figure 18: Grain size distributions measured with the LISST portable for water samples collected at Luang Prabang. Note that sample LP10₁ is plotted twice.</figcaption></figure>
According to the LISST measurements (Table 2), fine sediments composed 91% by volume of the total suspended load while fine to medium sand accounted for the rest. The sample LP9, which was collected at 9 m is noticeably different from the rest, with the fraction of sand sized sediment being 28%. The peak at sand sizes is more or less pronounced depending on the sample. Additionally, there appears to be the start of a third peak at sizes greater than 450 µm in many of the samples, but analysis with another instrument would be required to confirm the existence of these peaks since the measurement range of the LISST-portable is only 2.7 µm to 460 µm. Grain size analysis was performed on the water samples that were shipped to France using a laboratory laser grain sizer with a measurable range of 50 nm – 2 mm (the Cilas). A sample of these results is presented in Section 6 (Laboratory grain size analysis of the water samples4.1.6 Laboratory grain size analysis of the water samples).

Based on these measurements, a first estimate of the total suspended load for an average concentration of 155 mg/L and a discharge of 4812 m³/s is 750 kg/s.

<table><caption>Table 2: A summary of the grain size distributions measured by the LISST in the second sample (see Figure 18).</caption><thead><tr><th></th><th>Mode 1<br>[µm]</th><th>Mode 2<br>[µm]</th><th>Lambda 1<br>[%]</th><th>Lambda 2<br>[%]</th><th>TSS<br>Concentration [g/L]</th><th>Silt<br>Concentration [g/L]</th><th>Sand<br>Concentration [g/L]</th></tr></thead><tbody><tr><td>LP1</td><td>9.73</td><td>82.67</td><td>90.7</td><td>9.3</td><td>0.154</td><td>0.139</td><td>0.014</td></tr><tr><td>LP2</td><td>10.31</td><td>127.44</td><td>97.7</td><td>2.3</td><td>0.169</td><td>0.166</td><td>0.004</td></tr><tr><td>LP3</td><td>10.11</td><td>111.5</td><td>96.5</td><td>3.5</td><td>0.169</td><td>0.163</td><td>0.006</td></tr><tr><td>LP4</td><td>11.53</td><td>121.36</td><td>77.5</td><td>22.5</td><td>0.174</td><td>0.135</td><td>0.039</td></tr><tr><td>LP5</td><td>10.24</td><td>93.76</td><td>90</td><td>10</td><td>0.168</td><td>0.151</td><td>0.017</td></tr><tr><td>LP6</td><td>9.83</td><td>76.31</td><td>93.9</td><td>6.1</td><td>0.118</td><td>0.110</td><td>0.007</td></tr><tr><td>LP7</td><td>11.52</td><td>164.5</td><td>83.8</td><td>16.2</td><td>0.154</td><td>0.129</td><td>0.025</td></tr><tr><td>LP8</td><td>10.44</td><td>138.58</td><td>93.8</td><td>6.2</td><td>0.149</td><td>0.140</td><td>0.009</td></tr><tr><td>LP9</td><td>8.61</td><td>52.46</td><td>72.3</td><td>27.7</td><td>0.131</td><td>0.095</td><td>0.036</td></tr><tr><td>LP10</td><td>10.35</td><td>81.14</td><td>93.1</td><td>6.9</td><td>0.149</td><td>0.139</td><td>0.010</td></tr><tr><td>LP12</td><td>10.72</td><td>109.15</td><td>94.8</td><td>5.2</td><td>0.157</td><td>0.149</td><td>0.008</td></tr><tr><td>LP13</td><td>10.4</td><td>91.81</td><td>94</td><td>6</td><td>0.159</td><td>0.149</td><td>0.010</td></tr><tr><td>LP14</td><td>11.47</td><td>120.9</td><td>93.7</td><td>6.3</td><td>0.139</td><td>0.130</td><td>0.009</td></tr><tr><td>LP15</td><td>10.8</td><td>97.37</td><td>93.4</td><td>6.6</td><td>0.160</td><td>0.150</td><td>0.011</td></tr><tr><td>LP16</td><td>10.4</td><td>137.36</td><td>95.1</td><td>4.9</td><td>0.158</td><td>0.150</td><td>0.008</td></tr><tr><td>LP17</td><td>11.04</td><td>141.27</td><td>87.8</td><td>12.2</td><td>0.173</td><td>0.152</td><td>0.021</td></tr></tbody></table>

### 3.2.5 AQUAscat data

The across-stream positions at which the AQUAscat was deployed are superimposed on the ADCP data in Figure 19. The AQUAscat was lowered using the winch on the boat. In order to ensure that the counter on the winch was accurate, a pressure sensor was attached to the cable that is attached to the winch. The length of the cable and the depth according to the pressure sensor are presented in Figure 20. The cable setting and the depth measurements are consistent; we find a maximal deviation of 0.4 m.

A sample of the AQUAscat data are presented in Figure 57, the rest is given in Appendix A. The data have been corrected for spreading of the sound and attenuation due to water and are therefore labelled “fluid corrected intensity”. The AQUAscat data are in very good agreement with the ADCP data. For one, the backscatter at the across-stream position located closest to the right bank is less than the backscatter at all other positions. Secondly, there is often increased scatter (increased concentrations and/or grain size) near the bed. What is more, the near-bed AQUAscat data show that there is not only temporal variation in the suspended sediment, but also spatial variation. It
appears as though sand is being transported in bursts.

In Section 5, estimates of the concentration of both fine and coarse suspended sediment will be obtained using the attenuation values calculated from the AQUAscat data.

<figure><img src="image_21.png" /><figcaption>Figure 19: Positions at which the AQUAscat was lowered at Luang Prabang.</figcaption></figure>
<figure><img src="image_22.png" /><figcaption>Figure 20: Cable setting versus sensor measurement for sampling at Luang Prabang.</figcaption></figure>

<figure><img src="image_23.png" /><figcaption>Figure 21: AQUAscat 1000 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</figcaption></figure>
### 3.3 Measurement at Khong Chiam, Thailand

Measurements were made at Khong Chiam on October 4, 2012 during the recession limb of the annual monsoon flood with the help of Thailand's Department of Water Resource (DWR). The water level recorded in October and November 2012 is shown in Figure 22. The level that was observed during the measurements is shown in red. The rating curve obtained by the MRC at Khong Chiam for the 2011 calendar year is compared to the discharge and water level measured during this campaign in Figure 23. There is good agreement between the value measured during our campaign and the rating curve.

<figure><img src="image_24.png" /><figcaption>Figure 22: Water level at Khong Chiam for a two month period (blue line) compared to the value recorded on the day of measurements (red circle).</figcaption></figure>

<figure><img src="image_25.png" /><figcaption>Figure 23: Rating curve and data at Khong Chiam for calendar year 2011 (provided by the MRC), compared to the ADCP measurements made October 4 (red square).</figcaption></figure>
Measurements at Khong Chiam (Date: October 4, 2012):

* Water sampling at 5 depths at 4 across-stream locations using the Van Dorn sampler

* Multifrequency acoustic backscatter measurements at 4 – 7 depths at 3 across-stream locations using the AQUAscat, with the transducers facing the right bank.

* ADCP transects for gauging (including 2 transects 400 m downstream of the measurement cross section and 3 at the section, see Figure 24)

* 1 km along stream ADCP profile between the downstream site and the measurement section

* 2 ADCP transects upstream of the gauging section

<figure><img src="image_26.png" /><figcaption>Figure 24: Khong Chiam measurement site. The flow is from top left to bottom right. The GPS data points depict the measurement section (bottom right), and the upstream cross sections (top left).</figcaption></figure>

**3.3.1 Discharge measurements**

The velocity values measured during one ADCP transect at the gauging station are shown in Figure 25 and the discharge data are summarized in Table 3. Since the bed did not appear to be moving substantially based on the ADCP/GPS data and since there were no bed-load samples collected at this site, the instrument's bottom tracking function is used as the reference. Slightly higher velocities were seen in the right half of the cross section. The average discharge was 9025 m³/s, which is nearly twice that observed at Luang Prabang. This site was noticeably deeper than Luang Prabang: the maximum depth was 35 m, whereas it was 12 m at Luang Prabang.
<figure><img src="image_27.png" /><figcaption>Figure 25: The measurement transect in Khong Chiam with velocity data measuring during one transect using the bottom tracking (BT) as the reference.</figcaption></figure>

<table><caption>Table 3: Discharge measurements at Khong Chiam (ref. BT) October 4, 2012 (ADCP WorkHorse Rio Grande 600 kHz CEREGE).</caption><thead><tr><th>File</th><th>Date / Start Time</th><th>Discharge (m³/s)</th><th>Comment</th></tr></thead><tbody><tr><td></td><td>12/10/04 7:25</td><td></td><td>Water level 6 m</td></tr><tr><td>KhongChiam_0_000.pd0</td><td>12/10/04 8:21</td><td>9245</td><td>Cross-section downstream of the gauging station</td></tr><tr><td>KhongChiam_0_001.pd0</td><td>12/10/04 8:42</td><td>8765</td><td>Cross-section downstream of the gauging station</td></tr><tr><td>KhongChiam2_0_001.pd0</td><td>12/10/04 9:14</td><td>8985</td><td></td></tr><tr><td>KhongChiam2_0_001.pd0</td><td>12/10/04 9:21</td><td>9077</td><td></td></tr><tr><td>KhongChiam4_000.pd0</td><td>12/10/04 13:29</td><td>9053</td><td>Water level 5.88 m (13:15)</td></tr><tr><td>Average</td><td></td><td>9025</td><td></td></tr><tr><td>Standard deviation</td><td></td><td>174</td><td></td></tr></tbody></table>

### 3.3.2 Concentration and ADCP backscatter data

The positions at which water samples were collected are depicted in Figure 26. Concentrations ranged from 104 mg/L (KC1 at 2 m depth) to 195 mg/L (KC5 at 30 m depth) with an average of 140 mg/L. Aside from the two deepest samples (KC5 and KC10), no strong vertical gradients in concentration were observed. The measured concentrations were fairly homogeneously distributed throughout the section. The average backscatter data measured with the 600 kHz ADCP are shown
in Figure 27. The fluid-corrected backscatter values varied by less than 10 dB throughout the section and no strong vertical gradients were seen. Therefore, both the physical and acoustical data suggest that the sediment was essentially homogeneously distributed throughout the section, i.e. it is predominantly washload.

<figure><img src="image_28.png" /></figure>

Figure 26: Location and concentration of the samples collected at Khong Chiam. Concentrations were measured via filtration and are given in mg/L.
<figure><img src="image_29.png" /><figcaption>Figure 27: Range-corrected acoustic backscatter recorded by the 600 kHz ADCP.</figcaption></figure>

### 3.3.3 Grain size data measured in water samples

The grain size distributions measured with the LISST portable are presented in Figure 28 and the mode separation results are presented in Table 4.

<figure><img src="image_30.png" /><figcaption>Figure 28: Grain size distributions measured with a LISST portable in water samples collected at Khong Chiam.</figcaption></figure>
<table><caption>Table 4: A summary of the LISST measurements of the second subsample of the water samples collected at Khong Chiam.</caption><thead><tr><th></th><th>Mode 1<br>[µm]</th><th>Mode 2<br>[µm]</th><th>Lambda 1<br>[%]</th><th>Lambda 2<br>[%]</th><th>TSS<br>Concentration [g/L]</th><th>Silt<br>Concentration [g/L]</th><th>Sand<br>Concentration [g/L]</th></tr></thead><tbody><tr><td>KC1</td><td>8.86</td><td>115.99</td><td>96.2</td><td>3.8</td><td>0.104</td><td>0.100</td><td>0.004</td></tr><tr><td>KC2</td><td>9.62</td><td>82.77</td><td>91.7</td><td>8.3</td><td>0.130</td><td>0.119</td><td>0.011</td></tr><tr><td>KC3</td><td>9.24</td><td>63.87</td><td>85.9</td><td>14.1</td><td>0.147</td><td>0.127</td><td>0.021</td></tr><tr><td>KC4</td><td>9.88</td><td>92.61</td><td>70.3</td><td>29.7</td><td>0.149</td><td>0.105</td><td>0.044</td></tr><tr><td>KC5</td><td>9.26</td><td>71.74</td><td>85.3</td><td>14.7</td><td>0.195</td><td>0.166</td><td>0.029</td></tr><tr><td>KC6</td><td>8.57</td><td>45.63</td><td>94</td><td>6</td><td>0.131</td><td>0.123</td><td>0.008</td></tr><tr><td>KC7</td><td>9.41</td><td>64.38</td><td>84.6</td><td>15.4</td><td>0.116</td><td>0.098</td><td>0.018</td></tr><tr><td>KC8</td><td>9.29</td><td>61.61</td><td>92.3</td><td>7.7</td><td>0.134</td><td>0.123</td><td>0.010</td></tr><tr><td>KC9</td><td>9.32</td><td>80.91</td><td>79.9</td><td>20.1</td><td>0.140</td><td>0.111</td><td>0.028</td></tr><tr><td>KC10</td><td>9.13</td><td>72.82</td><td>82.9</td><td>17.1</td><td>0.165</td><td>0.136</td><td>0.028</td></tr><tr><td>KC11</td><td>9.75</td><td>64.15</td><td>90.3</td><td>9.7</td><td>0.128</td><td>0.115</td><td>0.012</td></tr><tr><td>KC12</td><td>9.16</td><td>55.81</td><td>92.3</td><td>7.7</td><td>0.154</td><td>0.143</td><td>0.012</td></tr><tr><td>KC13</td><td>9.54</td><td>66.43</td><td>86.4</td><td>13.6</td><td>0.146</td><td>0.126</td><td>0.020</td></tr><tr><td>KC14</td><td>11.1</td><td>71.38</td><td>87.3</td><td>12.7</td><td>0.128</td><td>0.111</td><td>0.016</td></tr><tr><td>KC15</td><td>10.34</td><td>95.58</td><td>75.2</td><td>24.8</td><td>0.128</td><td>0.096</td><td>0.032</td></tr><tr><td>KC16</td><td>10.2</td><td>86.35</td><td>90.6</td><td>9.4</td><td>0.138</td><td>0.125</td><td>0.013</td></tr><tr><td>KC17</td><td>9.4</td><td>85.59</td><td>88.3</td><td>11.7</td><td>0.140</td><td>0.124</td><td>0.016</td></tr></tbody></table>

Observations:

According to the grain size measurements, the grain size distributions were often bimodal, demonstrating that two size classes of sediment were being transported:

- fine silts ($D_{50}$ around 9 µm)

- sand ($D_{50}$ of 64-115 µm)

Based on the LISST measurements, on average fine sediments represented 87% of the total suspended sediments by volume. The fraction of sand-sized particles in each sample increased with depth of sample. The samples with the largest fractions of sand-sized particles were collected near the bottom of the water column.

The total suspended sediment load for an average concentration of 140 mg/L and a discharge of 9025 m³/s is 1300 kg/s.

### 3.3.4 AQUAscat data

The across-stream positions at which the AQUAscat was deployed are superimposed on the ADCP velocity data in Figure 29. The 1000 kHz AQUAscat data are presented in Figure 30. The remainder of the results are given in Appendix A. These data show that the distribution of suspended sediment is more or less homogeneous and there is little to no temporal and spatial variation, apart from the higher backscatter and attenuation values recorded at the deepest position of Vertical 1. Considering the uniform backscatter values from the ADCP throughout the cross-section, we suspect that the AQUAscat hit the bed, thereby re-suspending sediment.

Estimates of the concentration of both fine and coarse suspended sediment will be obtained from the AQUAscat data and presented in Section 5.
<figure><img src="image_31.png" /><figcaption>Figure 29: Across stream positions at which the AQUAscat was deployed.</figcaption></figure>

<figure><img src="image_32.png" /><figcaption>Figure 30: Khong Chiam 1000 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</figcaption></figure>
## 3.4 Measurement at Kratie, Cambodia

Measurements were made at Kratie on September 27 and 28, 2012 during the recession limb of the annual monsoon flood with the help of the Department of Hydrology and River Works (DHRW) of Cambodia. The water level recorded at the hydrometric station in September and October 2012 is shown in Figure 31. Figure 10. The level that was observed during the measurements is shown in red. The rating curve that is used by the MRC is presented in Figure 32. Discharge measurements at this site are routinely made using a 600 kHz ADCP made by RDI.

<figure><img src="image_33.png" /><figcaption>Figure 31: Water level at Kratie for a two month period (blue line) and for the day of measurements (red circle).</figcaption></figure>

<figure><img src="image_34.png" /><figcaption>Figure 32: Rating Curve at Kratie established by the MRC with data from 2008 – 2010 compared to the discharge measured during this study (red square).</figcaption></figure>
Measurements at Kratie (Date: September 27 & 28, 2012):

* ADCP gauging (4 transects)

* Two ADCP transects across from the water level gauge (2 km upstream of the gauging section, see Figure 33)

* ADCP and GPS measurements along the thalweg (2 km) for dune visualization

* Water sampling at 5 depths at 5 across-stream positions with a 2L Van Dorn sampler

* Bed-load sampling with Helley-Smith sampler (7 x 7 cm) belonging to DHWR at 5 across-stream positions, two of which corresponded to water sampling verticals

* Multi-frequency acoustic backscatter measurements with the AQUAscat deployed horizontally (facing the left bank) at 3 – 7 discrete depths at 3 across-stream positions

<figure><img src="image_35.png" /></figure>

Figure 33: Locations of transects: upstream transect is across from the hydro/meteorological station and the downstream transect is where all gauging and sediment measurements were made. The flow is from top to bottom. N.B. This image does not correspond to the water levels when the measurements were made.
### 3.4.1 Discharge measurements

An example of the flow velocities and bathymetry measured during one ADCP transect at Kratie is shown in Figure 34. The velocity data have been averaged over two-ensembles. It can be seen that the section was just over a kilometre wide and the maximum depth was 24 m. The discharge values calculated from the ADCP data using the software WinRiver II are presented in Table 5 and Table 6, along with the water level data. The average discharge on September 27 was 24,402 m³/s with a standard deviation of 1071 m³/s, while the average discharge on Sept 28 was 21,872 +/- 983 m³/s.

<figure><img src="image_36.png" /><figcaption>Figure 34: Bathymetry and velocity values measured at Kratie during one transect with a 1200 kHz ADCP.</figcaption></figure>

<table><caption>Table 5: Discharge measurements at Kratie September 27th (ADCP WorkHorse Rio Grande 1200 kHz Irstea, Reference GPS)</caption><thead><tr><td>File</td><td>Date / Start Time</td><td>Discharge (m³/s)</td><td>Comment</td></tr></thead><tbody><tr><td>Kratie_1200_0_000.pd0</td><td>12/09/27 9:09</td><td>23513</td><td>Water level 17.11m (07:00)</td></tr><tr><td>Kratie_1200_0_000.pd0</td><td>12/09/27 9:41</td><td>23437</td><td></td></tr><tr><td>Kratie_1200_0_001.pd0</td><td>12/09/27 10:03</td><td>25359</td><td></td></tr><tr><td>Kratie_1200_0_002.pd0</td><td>12/09/27 10:22</td><td>25297</td><td></td></tr><tr><td>Average</td><td></td><td>24402</td><td></td></tr><tr><td>Standard deviation</td><td></td><td>1071</td><td></td></tr></tbody></table>
<table><caption>Table 6 : Discharge measurements at Kratie September 28th (ADCP WorkHorse Rio Grande 600 kHz DHRW. ADCP WorkHorse Rio Grande 1200 kHz Irstea, Reference GPS).</caption><thead><tr><th>File</th><th>Date / Start Time</th><th>Discharge (m³/s)</th><th>Comment</th></tr></thead><tbody><tr><td>Kratie_Stations_0_002.pd0</td><td>12/09/28 9:28</td><td>21100</td><td>Water level (m) 16.61 m (7:00)</td></tr><tr><td>Kratie_Stations_0_004.pd0</td><td>12/09/28 11:14</td><td>21537</td><td></td></tr><tr><td>Kratie_28092012_0_001.pd0</td><td>12/09/28 16:32</td><td>22978</td><td>Water level (m) 16.59 m (17:00)<br>WHRG 1200 kHz</td></tr><tr><td>Average</td><td></td><td>21872</td><td></td></tr><tr><td>Standard deviation</td><td></td><td>983</td><td></td></tr></tbody></table>

### 3.4.2 Moving bed test

Comparison of the bed velocity measured using GPS as the reference and using bottom tracking as the reference showed there to be a moving bed at Kratie. The measured and predicted bed-load velocities will be presented in Section 7.

### 3.4.3 Dune tracking testing

A 4 km along-stream profile was performed while the 600 kHz ADCP and the GPS were recording (Figure 35). All efforts were made to navigate along the thalweg of the river. Five hours later, the same trajectory was taken using the GPS data from the previous trajectory to guide the driver. These measurements were made with the aim of monitoring the movement of the dunes, but since it was impossible to maintain the same trajectory for both passages, dune tracking is not possible. Actual dune-tracking would require measurements made with a multibeam (swath) echosounder or at least a single beam echosounder linked to a Differential Global Positioning System.

The backscatter and bottom track data in Figure 35 are the average values from the 4 beams of the ADCP. Since the beams form an angle of 20 degrees with the vertical, the measured topography is a smoothed version of the actual topography. These data can be used to estimate dune height and wavelength. It can be seen that the wavelength of the smoothed dunes was between 60 and 150 m and the peak to trough height was between 2 and 5m. Local increase in the backscatter suggests that sand transport is much more intense in the vicinity of dune crests.
<figure><img src="image_37.png" /><figcaption>Figure 35: Sample of the ADCP data collected as the boat moved downstream. The wavy bottom corresponds to sand dunes.</figcaption></figure>

### 3.4.4 Concentration data and acoustic backscatter

The positions at which water samples were collected are depicted in Figure 36. The concentrations measured by filtration in the samples collected at Kratie were higher than at the two upstream sites: minimum of 145 mg/L (KR12 at 5 m depth), maximum of 804 mg/L (KR14 at 15 m) and average of 263 mg/L. Three samples had concentrations exceeding 500 mg/L: KR14 (15 m) at 804 mg/L, KR15 (20 m) at 543 mg/L and KR24 (10 m) at 560 mg/L. Concentrations generally increased with depth.

The fluid corrected acoustic backscatter recorded with the 1200 kHz ADCP at this site is shown in Figure 37. From the backscatter data it can be seen that the sediment is more or less evenly distributed throughout the section, although slightly higher backscatter values were recorded near the right bank, where velocities were higher, especially near the bed. The sample with the highest concentration (KR14, 804 mg/L) was collected in this region of the cross section. Lower backscatter values were recorded towards the left bank, indicating lower concentration. No water samples were collected in this zone to confirm this observation.
<figure><img src="image_38.png" /><figcaption>Figure 36: Location and concentration of the samples collected at Kratie. Concentrations were measured via filtration and are given in mg/L.</figcaption></figure>

<figure><img src="image_39.png" /><figcaption>Figure 37: Acoustic backscatter at 1200 kHz corrected for spreading and attenuation due to water. The data have been averaged over two ensembles.</figcaption></figure>
### 3.4.5 Grain size analysis

The grain size distributions measured with the LISST portable are shown in the following figure and summarized in Table 7.

<figure><img src="image_40.png" /><figcaption>Figure 38: Grain size distributions measured with the LISST portable for water samples collected at Kratie.</figcaption></figure>

<table><caption>Table 7: A summary of the LISST measurements of the second subsample of water samples from Kratie.</caption><thead><tr><th></th><th>Mode 1</th><th>Mode 2</th><th>Lambda 1</th><th>Lambda 2</th><th>TSS</th><th>Silt</th><th>Sand</th></tr><tr><th></th><th>[µm]</th><th>[µm]</th><th>[%]</th><th>[%]</th><th>Concentration [g/L]</th><th>Concentration [g/L]</th><th>Concentration [g/L]</th></tr></thead><tbody><tr><td>KR1</td><td>12.17</td><td>318.26</td><td>73.9</td><td>26</td><td>0.178</td><td>0.132</td><td>0.046</td></tr><tr><td>KR2</td><td>12.67</td><td>116.71</td><td>97.3</td><td>2.7</td><td>0.247</td><td>0.241</td><td>0.007</td></tr><tr><td>KR3</td><td>13.4</td><td>12.08</td><td>50.9</td><td>49.1</td><td>0.243</td><td>0.124</td><td>0.120</td></tr><tr><td>KR4</td><td>13.62</td><td>102.79</td><td>91.2</td><td>8.8</td><td>0.287</td><td>0.261</td><td>0.025</td></tr><tr><td>KR5</td><td>10.11</td><td>73.09</td><td>96.1</td><td>3.9</td><td>0.294</td><td>0.282</td><td>0.011</td></tr><tr><td>KR6</td><td>8.83</td><td>65.9</td><td>96.4</td><td>3.6</td><td>0.165</td><td>0.159</td><td>0.006</td></tr><tr><td>KR7</td><td>10.94</td><td>86.24</td><td>95.6</td><td>4.4</td><td>0.210</td><td>0.201</td><td>0.009</td></tr><tr><td>KR8</td><td>11.15</td><td>72.78</td><td>97.3</td><td>2.7</td><td>0.199</td><td>0.194</td><td>0.005</td></tr><tr><td>KR9</td><td>10.11</td><td>80.06</td><td>95.6</td><td>4.4</td><td>0.208</td><td>0.199</td><td>0.009</td></tr><tr><td>KR10</td><td>10.6</td><td>81.9</td><td>83.5</td><td>16.5</td><td>0.264</td><td>0.221</td><td>0.044</td></tr><tr><td>KR11</td><td>9.71</td><td>69.22</td><td>81</td><td>19</td><td>0.152</td><td>0.123</td><td>0.029</td></tr><tr><td>KR12</td><td>10.16</td><td>85.81</td><td>95.5</td><td>4.5</td><td>0.145</td><td>0.138</td><td>0.007</td></tr><tr><td>KR13</td><td>11.92</td><td>98.37</td><td>89</td><td>11</td><td>0.263</td><td>0.234</td><td>0.029</td></tr><tr><td>KR14</td><td>10.05</td><td>131.51</td><td>45.5</td><td>54.5</td><td>0.804</td><td>0.366</td><td>0.438</td></tr><tr><td>KR15</td><td>9.44</td><td>117.9</td><td>52.2</td><td>47.8</td><td>0.543</td><td>0.283</td><td>0.259</td></tr><tr><td>KR17</td><td>9.21</td><td>84.76</td><td>88.5</td><td>11.5</td><td>0.197</td><td>0.175</td><td>0.023</td></tr><tr><td>KR18</td><td>9.59</td><td>102.79</td><td>97.4</td><td>2.6</td><td>0.184</td><td>0.179</td><td>0.005</td></tr><tr><td>KR19</td><td>9.82</td><td>68.23</td><td>88.7</td><td>11.3</td><td>0.218</td><td>0.193</td><td>0.025</td></tr><tr><td>KR20</td><td>10.63</td><td>98.94</td><td>96.8</td><td>3.2</td><td>0.180</td><td>0.174</td><td>0.006</td></tr><tr><td>KR21</td><td>10.93</td><td>112.8</td><td>98.3</td><td>1.7</td><td>0.172</td><td>0.169</td><td>0.003</td></tr><tr><td>KR22</td><td>8.7</td><td>83.36</td><td>98.4</td><td>1.6</td><td>0.148</td><td>0.146</td><td>0.002</td></tr><tr><td>KR23</td><td>9.79</td><td>76.52</td><td>93.8</td><td>6.2</td><td>0.210</td><td>0.197</td><td>0.013</td></tr><tr><td>KR24</td><td>9.95</td><td>117.18</td><td>67.9</td><td>32.1</td><td>0.560</td><td>0.381</td><td>0.180</td></tr><tr><td>KR25</td><td>10.69</td><td>115.97</td><td>75.7</td><td>24.3</td><td>0.298</td><td>0.225</td><td>0.072</td></tr><tr><td>KR26</td><td>9.42</td><td>73.22</td><td>90.5</td><td>9.5</td><td>0.208</td><td>0.189</td><td>0.020</td></tr></tbody></table>
Observations:

The grain size distributions are bimodal, containing:

- Fine silts ($d_{50}$ around 10 µm)

- Sand ($d_{50}$ of 70 - 130 µm depending on sample)

While these size distributions are similar to those measured at the upstream sites, the peaks at sand-sizeds are more pronounced (KR14 and KR15, for example). The fraction of fine sediments is on average 86% of the measured suspended sediments. The fraction of sand-sized particles was much higher in the samples with concentrations exceeding 500 mg/L (KR14, KR15, KR24) than in the rest, being 55%, 48% and 32%, respectively.

The total suspended sediment load across the section calculated using an average concentration of 263 mg/L and a discharge of 24402 m³/s is 6.4 tonnes/s.

3.4.6 AQUAscat data

The AQUAscat was deployed horizontally (facing the left bank) at three across-stream positions: towards the left bank (vertical V1), in the middle (V2) and near the right bank (V3). The fluid-corrected intensity data recorded at 1000 kHz are shown in Figure 39 and the remainder of the data is presented in Appendix A. It can be seen that at all frequencies, the average fluid corrected backscatter tends to increase with depth, especially at the position closest to the right bank (V3) where the flow speeds were the highest. For the measurements made in the middle of the section (V2), the highest backscatter was at 17 m depth, not at 18 or 19 m. This can be explained by the fact that the boat drifted downstream substantially during one vertical, meaning that all measurements of one vertical were not necessarily at the same along-stream position. Given that the peak to trough height of the dunes at Kratie ranged from 2 – 5 m, it is very possible that the measurements at 17m were made near the crest of a dune where there was much sediment transport, while measurements made at 18 and 19 m were near the trough of a dune where the sediment transport would be less. A similar thing was observed with the water samples (Figure 36), where the concentration of sample KR14 exceeded that of KR15, despite KR15 being collected at a deeper depth.
<figure><img src="image_41.png" /></figure>

Figure 39: Kratie AQUAscat data recorded at 1000 kHz, fluid corrected intensity data near the left bank (V1), middle (V2) and right bank (V3) of the section.

## 4. Sediment flux calculations

The average concentration and average discharge measured at each site can be used to calculate approximate values of the sediment fluxes. These values were presented earlier in this report, but are summarized here. At Luang Prabang the total suspended load for an average concentration of 155 mg/L and a discharge of 4812 m³/s is 750 kg/s. At Khong Chiam, the total suspended load for an average concentration of 140 mg/l and a discharge of 9025 m³/s is 1.3 tonnes/s. At Kratie the total suspended sediment load for an average concentration of 263 mg/L and a discharge of 24402 m³/s is 6.4 tonnes/s. In order to have more refined estimates of the sediment flux, discriminating the homogeneous suspension of washload and the heterogeneous suspension of sand, one can use the ADCP data as shown in the following section.

### 4.1 ADCP measurements

#### 4.1.1 Calibration of acoustic backscatter data

The procedure by which sediment fluxes are calculated from the combination of ADCP data and concentration and grain size data measured in the water samples is detailed in the following section. There are theoretical relationships that describe how an acoustic signal is backscattered by suspended particles in the water. These relationships are used by the commercial software Sediview (HR Wallingford) to calculate distributions of particle concentration from ADCP backscatter data.
However, Sediview can only be used to accurately estimate the amount of sand-sized particles in suspension because the backscatter from sand grains greatly exceeds that from finer particles. Since bimodal grain size distributions of the suspended sediment were observed at all sites, with sand present in small fractions, Sediview is only used to calculate the distribution of sand throughout the section.

In order to determine the proportion of silts and sand in each water sample, the grain size distribution curves were demodulated. This enabled us to determine the amount of fine suspended sediment and suspended sand at each water sampling location. Two examples of demodulated grain size distributions are shown in Figure 40. The grain size distributions were measured by a LISST portable.

<figure><img src="image_42.png" /><figcaption>Figure 40: Demodulation of the grain size distributions measured in Kratie samples KR14 and KR24.</figcaption></figure>

The fine suspended sediment is equivalent to the washload and corresponds to the part of the distribution which has a mode around 10 - 20µm, while the suspended sand has a mode around 70 - 200 µm. Demodulation enables the calculation of the concentration of fine suspended sediment and sand suspension for each water sample. This is done by assuming that the grain size distribution measured in one subsample can be applied to the concentration measured in the corresponding subsample. The flux of the fine suspended sediment is obtained by multiplying the average discharge by the average concentration of fine sediment in all water samples collected throughout the section. The flux of sand is obtained from the ADCP data using Sediview after calibrating with the sand concentration values from the water samples. The attenuation due to the fine suspended sediment is accounted for by increasing the attenuation due to water (an input parameter for Sediview) accordingly.

The distribution of suspended sand at Luang Prabang calculated using Sediview is presented in Figure 41. It is interesting to see that Figure 41 allows us to clearly distinguish the vertical gradient in sand concentration. This gradient was not as clear from the water samples because of the inappropriate sampling tool (attempting to use a depth-integrated sampler as a point sampler) and also because of the large measurement uncertainties.
<figure><img src="image_43.png" /><figcaption>Figure 41: Estimates of the concentration of suspended sand at Luang Prabang obtained with Sediview by calibrating the backscatter data of Figure 17 with the water samples.</figcaption></figure>

Values of the average discharge and the fluxes of fine suspended sediment, suspended sand and total suspended sediment calculated at each site are presented in Table 8. The total suspended sediment fluxes are consistent with the fluxes presented at the start of this section which were the simple product of the average TSS concentration and the river discharge. When Sediview is used to determine suspended sand fluxes from ADCP transects not used in the calibration, the results are consistent with those presented below.

<table><caption>Table 8: Summary of average discharge and sediment transport fluxes calculated at each site.</caption><thead><tr><th>Location<br>Date</th><th>Discharge<br>[m³/s]</th><th>Fine suspended<br>sediment flux<br>[kg/s and t/d]</th><th>Suspended sand<br>flux<br>[kg/s and t/d]</th><th>Total suspended<br>sediment flux<br>[kg/s and t/d]</th></tr></thead><tbody><tr><td>Luang Prabang<br>(02/10/2012)</td><td>4800</td><td>630<br>54432</td><td>68<br>5895</td><td>698<br>60327</td></tr><tr><td>Khong Chiam<br>(04/10/2012)</td><td>9025</td><td>1088<br>94023</td><td>232<br>20086</td><td>1320<br>114109</td></tr><tr><td>Kratie<br>(27/09/2013)</td><td>23360</td><td>4920<br>425088</td><td>590<br>50976</td><td>5510<br>476064</td></tr></tbody></table>
## 5. Concentration estimates from the AQUAscat data

In the following section we outline how concentrations of fine suspended sediment and suspended sand were calculated from the AQUAscat data. Specifically, these values were calculated from the attenuation due to the suspended sediment calculated from the AQUAscat profiles. The attenuation due to the suspended sediment is calculated from the slope of the time-averaged fluid-corrected intensity profiles. Figure 42 is an example of time-averaged fluid-corrected intensity profiles recorded at 2500 kHz and 4000 kHz at Khong Chiam. The attenuation values, calculated from the slopes of these profiles, are 0.57 dB/m at 2500 kHz and 1.28 dB/m at 4000 kHz.

<figure><img src="image_44.png" /><figcaption>Figure 42: Time-averaged fluid-corrected intensity profile recorded at 20 m depth of vertical V2 at Khong Chiam.</figcaption></figure>

At each site, the measured suspended sediment attenuation values calculated at the shallowest depth of each vertical are averaged. Assuming that only fine suspended sediment exists at the surface, dividing this value by the average concentration measured in the surface water samples yields the empirical attenuation constant for the fine suspended sediment, $\langle\xi_{silt}\rangle$. The assumption that only fine suspended sediment is found at the surface is good for Khong Chiam and Kratie, but is only ok at Luang Prabang. The attenuation constant for the suspended sand, $\langle\xi_{sand}\rangle$, is calculated using a theoretical relationship (example Thorne and Meral 2008) that describes the dependence of the attenuation by suspensions of sand-sized sediments at MHz frequencies on the ratio between grain size and acoustic frequency.

At frequency $i$, the total attenuation due to suspended sediment can be written as:

$$ \alpha_i = M_{silt} \langle\xi_{silt,i}\rangle + M_{sand} \langle\xi_{sand,i}\rangle. $$

With measurements of attenuation at two frequencies, the above equation can be used twice to determine the concentration of both fine suspended sediment and suspended sand. The resulting equations are
$$M_{sand} = \frac{\langle \zeta_{silt,i} \rangle \alpha_j - \langle \zeta_{silt,j} \rangle \alpha_i}{\langle \zeta_{silt,i} \rangle \langle \zeta_{sand,j} \rangle - \langle \zeta_{sand,i} \rangle \langle \zeta_{silt,j} \rangle}$$

$$M_{silt} = \frac{\alpha_i - M_{sand} \langle \zeta_{sand,i} \rangle}{\langle \zeta_{silt,i} \rangle}$$

Thus at each position at which the AQUAscat recorded data, we have a measure of both the concentration of fine suspended sediment and suspended sand. The results are shown in the following figures for the three study sites. In all cases $\langle \zeta_{sand} \rangle$ was calculated assuming a lognormal grain size distribution with $d_{50} = 120$ µm and $\sigma = 0.3$ $d_{50}$. The suspended silt attenuation constants were determined empirically using the average surface water concentration, which was 160 mg/L at Luang Prabang, 130 mg/L at Khong Chiam and 175 mg/L at Kratie.

Vertical gradients of the suspended sand were anticipated, while it was expected that the concentration of fine suspended sediment would not vary at a given vertical. This is what was observed at Kratie (Figure 43): the concentration of fine sediments fluctuated throughout each vertical (range: 140 - 200 mg/L), but no strong vertical gradients were observed. Sand concentration, on the other hand, increased from 0-40 mg/L at the surface to 80 - 180 mg/L near the bed. One's eye may be drawn to the sand concentration at 16 m depth in V1 which greatly exceeded that at 17 and 18 m. This observation is consistent with the water samples. As explained earlier in this report, we believe it to indicate that sampling occurred at different locations relative to the dunes (peak versus trough).

The total suspended sediment concentration from the AQUAscat data at Kratie ranged from 170 – 320 mg/L for all positions. These values are consistent with the water samples for the most part. The high concentrations observed in the water samples collected near the bed towards the right bank (540 and 800 mg/L) were not seen with the AQUAscat. This is likely because the instrument was not lowered as close to the bed as was the water sampler at this site for fear that the strong currents and weight on the winch would tip the boat.

Based on the multi-frequency acoustic data from Khong Chiam (Figure 44), there was very little sand in suspension (maximum concentration of 60 mg/L at 25 m depth). Secondly, the concentration profiles were predominantly straight vertical lines. This observation is consistent with the ADCP backscatter data, in which roughly the same value was observed throughout the section. (N.B. the AQUAscat measurements made at 20 m at V1 were excluded from the analysis since it was believed that the instrument hit the bed, thereby increasing suspended sediment concentration). The total concentration predicted with the AQUAscat data range from 130 – 180 mg/L. These values are consistent with the water samples collected at this site.
<figure><img src="image_45.png" /><figcaption>Figure 43: Profiles of fine suspended sediment (silt) and suspended sand concentration at Kratie calculated from the 2500 and 400 kHz AQUAscat data.</figcaption></figure>

<figure><img src="image_46.png" /><figcaption>Figure 44: Profiles of fine suspended sediment (silt) and sand concentration at Khong Chiam calculated from the 2500 and 400 kHz AQUAscat data. Sand concentration for V1 was always zero.</figcaption></figure>

The estimated concentration profiles at Luang Prabang are more complicated. For one, the estimated concentrations of fine suspended sediment increased towards the bed for three of the four verticals. Secondly, the predicted concentrations are higher than the values that were observed. The predicted concentrations of the total suspended sediment range from 150 – 650 mg/L, while the measured values ranged from 120 – 170 mg/L. Since a depth-integrated sampler was used at this
site, samples at depth contained water from shallower water; therefore sand-sized particles were likely under sampled. What is more, as will be discussed in Section 9.2, it is hard to retain all the sand collected within a water sampler when transferring it between recipients. Therefore, if a considerable amount of sand is lost in the subsampling process, concentrations measured in the lab may be underestimated.

The acoustic data showed substantial variations in the backscatter from the suspended sediment at Luang Prabang with both space (ADCP and AQUAscat) and time (AQUAscat). If sand is being transported in bursts near the bed, as appears to be the case (see for example Figure 58), even a point-integrated sampler may fill before a bursting event occurs. Considering the good agreement between acoustic estimates of concentration and water samples at Kratie and Khong Chiam, the authors believe the concentration estimates from the AQUAscat at Luang Prabang to be representative of reality. For a discharge of 4800 m³/s and an average sand concentration of 150 mg/L, the sand flux would be 720 kg/s, and the revised total sediment flux from Table 8 would be 1350 kg/s.

<figure><img src="image_47.png" /><figcaption>Figure 45: Profiles of fine suspended sediment (silt) and sand concentration at Luang Prabang calculated from the 2500 and 400 kHz AQUAscat data.</figcaption></figure>

**6. Laboratory grain size analysis of the water samples**

A laboratory laser grain sizer (the Cilas) was used to determine grain size distributions of the samples that were returned to France. Three samples were also analyzed with a Laser Beckman Coulter LS 13 320. Both instruments measure grain size using the same principle as the LISST. Since different subsamples were used for the analysis with each instrument, the grain size
distributions from the different instruments were not expected to be identical.

High resolution photographs were taken of the sand size particles that were retained on a sieve once the samples were dried. Figure 46 presents magnified photographs of the sand that was collected in the Kratie water samples KR5 and KR15. These samples were collected at depths of 17 and 18 m, respectively. It can be seen that the sediment is primarily well rounded crystals of shiny quartz, which is characteristic of hydraulic transport of the bed-load over long distance. Some of the grains appear quite altered (possibly originating from soils). There are also small amounts of other minerals, including mica and magnetic minerals.

From the photographs, it appears as though the sediment in sample KR5 was, on average, larger than that in sample KR15. This is confirmed by the grain size distributions measured with the Cilas and the Laser Beckman Coulter: there was a mode at 200µm for sample KR15 (Figure 49), while there was a mode at 400µm for sample KR5 (Figure 47). Note: the LISST distributions were not truncated at 5 microns, as was done elsewhere in the report, in order to highlight the instrument's tendency to overestimate the amount of fine sediment when particles outside of its measurements range are present.

<figure><img src="image_48.png" /><figcaption>Figure 46: Magnified images of the sand-sized particles from samples KR15 (left) and KR5 (right) with a millimeter grid in the background.</figcaption></figure>
<figure><img src="image_49.png" /></figure>

Figure 47: Water sample KR5, comparison of grain size distributions measured with: a LISST portable (detectable range: d = 2.7 – 460 microns), a Cilas (detectable range: 50 nm – 2 mm) and a Laser Beckman Coulter LS 13 320 (detectable range: 40 nm – 2 mm). Note that different subsamples were used for each of the three instruments.

<figure><img src="image_50.png" /></figure>

Figure 48: Water sample KR8, comparison of grain size distributions measured with: a LISST portable, a Cilas and a Laser Beckman Coulter LS13 320. Different subsamples were used for each of the three instruments.
<figure><img src="image_51.png" /></figure>

Figure 49: Water sample KR15, comparison of grain size distributions measured with: a LISST portable, a Cilas and a Laser Beckman Coulter LS 13 320. Different subsamples were used for each of the three instruments.

## 7. Bed-load Analysis

Coupled ADCP and GPS data are necessary to compute river discharge in moving bed conditions. As explained earlier, these ADCP/GPS coupled data highlighted a moving bed at Kratie and Luang Prabang. The bed-load velocities measured at Luang Prabang are shown in Figure 50 and those measured at Kratie are shown in Figure 51. The maximum bed-load velocity observed at Luang Prabang was about 0.3 m/s. Bed-load transport was not observed within 50 m of each bank, but occurred throughout the remainder of the section, with values ranging from 0.1 – 0.25 m/s. The least amount of bed-load material collected at Luang Prabang was at the position nearest the right bank. This is consistent with the ADCP bed-load velocity measurements.

Note that the apparent bed-load velocity derived from the bottom-track pulses of the ADCP is likely to be partly related to near-bed saltating sand particles, which move faster than bed-load particles. Nevertheless, ADCP apparent bed velocity is considered to be representative of bed-load, since saltation is usually coupled to bed-load transport.

Very high bed-load velocities were seen at Kratie (0.8 m/s) in a localized area (between 900 and 1050 m from the left bank). Bed-load transport was confirmed by the samples collected with the Helley-Smith sampler (Table 9). The largest amounts of bed-load material at Kratie were collected in the right half of the cross-section, which corresponds to the zone in which the apparent bed-load velocity was highest.

Bed-load velocities were modelled using three approaches: (1) the Meyer-Peter Müller (1948) formula, (2) the Camenen and Larson (2008) formula and (3) the Shields parameter. The models are
introduced in Section 8.1.2 (Bed-load transport) and the results are presented in the bottom panels of Figure 50 and Figure 51. It can be seen that the modeled values are qualitatively consistent with the estimates from the ADCP data.

The samples collected with the bed-load samplers were analyzed for grain size using a sieve stack in the Irstea Lyon laboratory. The median diameter measured in each sample is presented in Table 9. Rough estimates of the bed-load fluxes were obtained by dividing each cross-section into three subsections and assigning the average rate of bed-load transport measured in that zone (in kg/s*m) to that width. The transport rate in each subsection is multiplied by the width of the zone and these values are summed across the section. The results are presented in Table 10. These results must be regarded as approximations, since as explained in § 2.7 it would have been necessary to have many measurements across the section and to repeat each measurement to have a representative result. The limits of this method, which cause a lot of uncertainty are (1) uncertainty in the position of the bed-load sampler when it hits the bottom of the river and during sampling, (2) the unknown thickness of the active part of width, which is not taken into consideration (it is assumed to be fully sampled by the sampler) and (3) the zoning of the cross-section and the assumption that the bed-load measured in each zone is representative of the entire zone.

Comment: At Khong Chiam bed-load sampling was not possible because of security problems with the samplers (the sampler could easily catch on the rocky bottom).

<figure><img src="image_52.png" /></figure>

Figure 50: Bathymetry and depth-average water velocity from an ADCP transect at Luang Prabang (top); Bed-load velocity measured from ADCP and GPS data for the same ADCP transect (middle); Modelled bed-load velocity.
<figure><img src="image_53.png" /><figcaption>Figure 51: Bathymetry and depth-average water velocity from an ADCP transect at Kratie (top); Bed-load velocity measured from the same ADCP transect at Kratie (middle); modelled bed-load velocity (bottom).</figcaption></figure>

<table><caption>Table 9: The dry weight and median diameter of bed-load samples collected at Kratie (a) and Luang Prabang (b) during a 2 min period.</caption><thead><tr><th>Distance from left bank (m)</th><th>Dry weight (g)</th><th>d50 (mm)</th></tr></thead><tbody><tr><td>150</td><td>231</td><td>0.45</td></tr><tr><td>380</td><td>449</td><td>0.76</td></tr><tr><td>500</td><td>1939</td><td>0.62</td></tr><tr><td>650</td><td>1444</td><td>0.61</td></tr><tr><td>800</td><td>3303</td><td>0.77</td></tr><tr><td>1025</td><td>278</td><td>0.35</td></tr><tr><td>1030</td><td>1943</td><td>0.65</td></tr></tbody></table><p>(a)</p>

<table><caption>Table 10: Estimated bed-load fluxes.</caption><thead><tr><th>Distance from left bank (m)</th><th>Dry weight (g)</th><th>d50 (mm)</th></tr></thead><tbody><tr><td>140</td><td></td><td>225</td><td>0.41</td></tr><tr><td>255</td><td></td><td>221</td><td>0.35</td></tr><tr><td>346</td><td></td><td>58</td><td>0.38</td></tr></tbody></table><p>(b)</p>

<table><thead><tr><th>Estimated bedload flux</th><th>kg/s</th><th>Tons/day</th></tr></thead><tbody><tr><td>Luang-Prabang (12/10/02)</td><td>5.5</td><td>477</td></tr><tr><td>Kratie (12/09/27)</td><td>146</td><td>12600</td></tr></tbody></table>
# 8. Modelling

## 8.1 A model for sand concentration profiles and local bed-load transport

### 8.1.1 Sand concentration profiles

Knowing the main hydraulic parameters from the ADCP measurements (i.e. local water depth $^h$, depth averaged velocity $^U$, and bottom roughness height $^k_{st}$), it is possible to estimate local bed shear stresses and sediment transport rates using some semi-empirical formulas. The median grain size, $^d_{50}$ (in m), and the standard deviation, $^\sigma$, of the sand mode were used for the calculation. The Shields parameter, $^\theta$, is obtained using the following equation:

$$ \theta = \frac{u_*^2}{g(s-1)d_{50}} = \frac{C_d U^2}{g(s-1)d_{50}} \quad (1) $$

where $u_*$ is the friction velocity, $g=9.81$ m/s² the acceleration of gravity, $s \approx 2.65$ the relative density of sand, and $C_d$ is a friction factor (or drag coefficient) based on the hypothesis of a logarithmic profile for the velocity:

$$ C_D = \left( \frac{\kappa}{1 + \log(z_0/h)} \right) \quad (2) $$

with $\kappa=0.41$ the Von Karman constant, $z_0=k_s/30$ the roughness length, $k_s$ the roughness height. For the calculation of bed-load or bed concentration (reference concentration close to the bottom for the concentration profiles), the grain related roughness is used, i.e. $k_s=2d_{84}$. For the calculation of the energy dissipation in the water column, the total roughness is used, i.e. $k_s=k_{st}$ where $k_{st}$ is fitted so that the measured velocity profiles are properly described by the logarithmic law. The suspended sediment concentration may be estimated using the Camenen and Larson (2008) formula, which assumes constant sediment diffusivity $\epsilon_s$ over the water depth, which leads to an exponential concentration profile:

$$ \epsilon_s = \frac{\sigma_c}{6} \kappa u_* h \quad (3) $$

where $\sigma_c$ is consistent with a Schmidt number, $u_*$ the friction velocity assuming $k_s=k_{st}$. Camenen and Larson (2008) introduced a formula for $\sigma_c$, which is function of the ratio $W_s/u_*$, where $W_s$ is the settling velocity of the particles. As a first approximation, we assume $\sigma_c=1$. The exponential concentration profile is written:

$$ c(z) = c_R \exp \left( \frac{W_s}{\epsilon_s} z \right) \quad (4) $$

where the reference concentration, $c_R$, was written assuming a relationship with bed-load transport such as $q_{sb} \propto c_R u_*$ where $q_{sb}$ is the bed-load flux. Using the bed-load formula introduced by Camenen and Larson (2005), Camenen and Larson (2008) suggested:

$$ c_R = 1.5 \times 10^{-3} \exp(-0.2 d_*) \exp\left(-4.5 \frac{\theta_{cr}}{\theta}\right) \quad (5) $$

with $d_*=[(s-1)g/v^2]^{1/3}d_{50}$ ($v \approx 10^{-6}$ m²/s, the viscosity of water)

In Figure 52 are presented the measured and modelled velocity and concentration profiles for three selected verticals at Luang Prabang. Verticals V1, V2 and V3 are located 70, 275, and 350m from the left bank, respectively. For vertical V1 the corresponding water samples were LP6, 7 and 8. For
vertical V2, they were LP15, 16 and 17. For vertical V3 they were LP1, 2, 3, 4 and 5. The velocity profiles were fitted using roughness heights of $k_{st} = 0.5$ m, 3 m, and 0.05 m with depth averaged velocity equal to 1.12, 1.05, and 0.88 m/s, respectively. These roughness heights suggest that large bedforms were present under the vertical V1 and especially V2, whereas no bedforms were present at the vertical V3. These results are consistent with the attempt of dune tracking for which typical dune sizes of approximately 1-m height were measured around V2. These values of total roughness were used to estimate the sediment diffusivity (Eq. 3) whereas the grain-related roughness height $k_s=2d_{84}$ was used to estimate the reference concentration (Eq. 4). A median grain size of 150 µm was used for the computation, which corresponds to the larger values observed throughout the section at Luang Prabang. As observed in Figure 52(b), the modelled vertical concentration profiles are largely overestimated compared to the experimental profiles, especially close to the bottom. Some explanations could be the sensitivity of the model to the grain size and calibration of the roughness height or that fine sediment availability at Luang Prabang is relatively low at the end of the rainy season (September) since the model estimates the transport capacity, which supposes that the transport is at equilibrium, is uniform and that there is not sediment supply shortage. The overestimation of the modelled concentration relative to the water samples could also indicate that sand concentrations could be underestimated when water samples are collected with a Van Dorn bottle.

<figure><img src="image_54.png" /><figcaption>Figure 52: Vertical velocity profiles from ADCP measurements and model (a) and vertical concentration profiles (measured and modelled) (b) for the three verticals at Luang Prabang where concentrations were measured.</figcaption></figure>

### 8.1.2 Bed-load transport

The Meyer-Peter and Müller (1948) and Camenen and Larson (2005) formulas were used to estimate the volume bed-load transport rate (in m³/s/m):

$$q_{sb,MPM} = 8 \sqrt{(s-1) g d_{50}^3} (\theta - \theta_{cr})^{3/2} \quad (6)$$

$$q_{sb,MPM} = 8 \sqrt{(s-1) g d_{50}^3} \theta^{3/2} \exp(-4.5 \frac{\theta_{cr}}{\theta}) \quad (7)$$

Assuming that bed-load transport is homogeneous throughout a layer of thickness $\delta_s$, the bed-load velocity, $V_b$, can be easily estimated:
$$V_b = \frac{q_{sb}}{\delta_s} \qquad (8)$$

As a first approximation, we related the bed-load layer thickness to the grain related roughness height as $\delta_s=k_s$. The above models were used to estimate the bed-load transport velocities in Figure 50: Bathymetry and depth-average water velocity from an ADCP transect at Luang Prabang (top); Bed-load velocity measured from ADCP and GPS data for the same ADCP transect (middle); Modelled bed-load velocity. Figure 50 and Figure 51.

## 8.2 A simple model to estimate total sand transport throughout a section

### 8.2.1 Hydrometric station

Assuming a uniform flow, we can apply the Manning-Strickler formula, which may be simplified assuming the hydraulic radius $R_h=H$ where $H$ is the mean water depth and the section area $A=BH$, with $B$ the width of the river:

$$Q = B K_s S^{1/2} H^{5/3} \qquad (9)$$

where $Q$ is the water discharge in m³/s, $K_s$ a Strickler coefficient, and $S$ the mean slope of the reach. If a hydrometric station is located along a long straight reach with no influence from dykes or weirs, the stage-discharge relationship may be written as follows (Camenen et al., 2012):

$$Q = a (z_m - z_0)^{5/3} \qquad (10)$$

with $z_m$ the measured elevation and the constant $a$ and the reference elevation $z_0$ are both fitted to measured data. Eq. 10 was applied to the Luang Prabang and Kratie rating curve data (Figure 53).

From Eqs. 9 and 10, it is possible to get an estimation of the Strickler coefficient $K_s$ for the site of the gauging station ($K_s=a/(BS^{1/2})$ when $H = z_m - z_0$). An application to the Luang Prabang and Kratie gauging station yield $K_s=21$ m¹³/s, which is consistent with the 1D numerical model from the MRC (CNR, personal communication).

<figure><img src="image_55.png" /><figcaption>Figure 53: Stage-discharge relationship at Luang Prabang (a) and Kratie (b).</figcaption></figure>
### 8.2.2 Sand transport

Based on Eq. 10 and the specific bathymetry of the gauging stations, it is possible to estimate section-averaged velocity and water depth $^H$. Eqs. 1 to 7 can be used to estimate section-averaged values of sand transport by replacing the local values $^h$ and $^U$ by the section-averaged values $^H$ and $^V$, respectively. An estimation of the total sand transport (in kg/s) throughout the section is thus given by the following equation:

$$Q_s = Q_{sb} + Q_{ss} = \rho_s (q_{sb} + q_{ss}) B_a \quad (11)$$

where $\rho_s \approx 2650$ kg/m$^3$ is the density of sand, and $B_a$ is the active width of the river. For the bed-load transport, Eq. 6 was used (Camenen and Larson, 2005) whereas for the suspended load transport the Camenen and Larson (2008) formula was used (see also Eqs. 3 to 5):

$$q_{ss} = Vc_R \frac{\Box_s}{W_s} \left[ 1 - \exp\left( \frac{-W_s}{\Box_s H} \right) \right] \quad (12)$$

Results from this model are presented in Figure 54, where two classes of sands equally distributed were used for the computations (i.e. bimodal population of sands with 50% with a diameter $d = d_1$ and 50% with $d = d_2$): $d_1 = 0.2$ mm and $d_2 = 0.4$ mm for Kratie and $d_1 = 0.2$ mm and $d_2 = 0.6$ mm for Luang Prabang. These values are based on sieved sizes of the suspended load and bed-load samples measured for the two sites. Calculations are presented for both bedload and suspended load in Figure 54. As observed in Figure 54, the proposed model yields a good order of magnitude for the bed-load transport but tends to overestimate suspended load transport. This may be due to the period of the field campaign that is situated at the end of the monsoon, for which less sediment supply from the tributaries is generally observed. It should also be noted there are significant uncertainties for both bedload and suspended load measurements. At Luang Prabang, only three bedload samples were measured at three different verticals. Using an averaged value of these three samples attributed to an assumed active width $B_a = 350$ m ($Q_{sb} = \rho_s q_{sb,i} B_a$; black circle on Figure 54a) yields different results compared to the classic methodology for which a sediment discharge is estimated for each vertical affecting a sub-active width ($Q_{sb} = \rho_s \sum q_{sb,i} B_{a,i}$; black triangle on Figure 54a). At Kratie, more bedload samples were achieved and so both methods yield similar results. In the same way, for the suspended load, the methodology for the calculation of sand concentrations throughout the section based on ADCP measurements (red square on Figure 54a) yields very different results compared to the results from AQUAscat measurements (red five-pointed star on Figure 54a). Based on a report from STSGreen (2012), who measured fluxes of sand in suspension in August 2012 at Xayaburi (located 200km downstream of Luang Prabang) using a Delft bottle, the suspended load transport rate was $9 \times 10^3$ kg/s when the water discharge was 14,500m$^3$/s. This value is much closer to the one predicted by the model at Luang Prabang.
<figure><img src="image_56.png" /><figcaption>Figure 54: Estimation of the total bed-load and suspended sand load at Luang Prabang (a) and Kratie (b) together with experimental measurements (black symbols: bedload; red symbols: suspension; see detailed explanations in the text).</figcaption></figure>

# 9 Project feedback

## 9.1 Concentration (total suspended solids) measurements

An inter-laboratory comparison of filtration methods was done in which the concentration of two sub-samples of five water samples were analysed by the Phnom Penh DHRW laboratory and by the Irstea Lyon laboratory. In the Irstea laboratory the international standard for determination of suspended solid by the filtration through glass fibre filters [ISO, 2005] is used, the Phnom Penh laboratory uses another standard. Results are presented in Table 11. The concentrations measured by both laboratories are very similar for 4 of the 5 samples (less than 10 % difference). The large difference for the Kr 15 sample concentration (310%) cannot be attributed to sub-sampling. The difference may be due to an incorrect volume being used or noted during the analysis process.

<table><caption>Table 11: Total suspended solid concentrations measured in subsamples of five samples by the DHRW and the Irstea Lyon labs.</caption><thead><tr><th colspan="6">TSS concentration [mg/l]</th></tr><tr><th>Sample code</th><th>KR1</th><th>KR15</th><th>KR2<br>3</th><th>KC<br>1</th><th>LP1</th></tr></thead><tbody><tr><td>DHRW Lab.</td><td>163,<br>3</td><td>2226,<br>4</td><td>210,6</td><td>100</td><td>161,4</td></tr><tr><td>Irstea Lab.</td><td>178</td><td>543</td><td>210</td><td>104</td><td>154</td></tr><tr><td>Deviation</td><td>-8%</td><td>310%</td><td>0%</td><td>-4%</td><td>5%</td></tr></tbody></table>
## 9.2 Problems related to subsampling and the representativeness of the samples

As alluded to earlier in the report, subsampling of water samples can result in an uneven distribution of coarse sediment between the subsamples. When the Van Dorn sampler (2-L volume) was brought to the surface, it was shaken in order to keep the sediment in suspension as it was quickly transferred into two 500 mL water bottles using a funnel. The 500 mL samples were further subdivided for filtration and grain size analysis procedures. Between 100 and 400 mL of each subsample were used for filtration at the Irstea lab. Approximately 100 mL were required for grain size measurements. With each division, it is hard to ensure that the sand is evenly divided between subsamples as it quickly settles out despite intentional mixing. Thus grain size and concentration values may differ substantially between subsamples.

To estimate the uncertainty in the concentration estimates resulting from this process, two subsampling tests were performed at the Irstea lab. Results are presented in Table 12. For sample KR24, subsamples of 150 mL were used and for sample KR10, subsamples of 200 mL were used. Much sand was visible in sample KR24, whereas less was seen in KR10. Despite best efforts to properly subsample, a difference of 38% was seen between the KR24 subsample concentrations while a difference of only 3% was seen for the more dilute sample.

<table><caption>Table 12: Results of subsampling test.</caption><thead><tr><th>Sample code</th><th>KR24-1</th><th>KR24-2</th><th>Sample code</th><th>KR10-1</th><th>KR10-2</th></tr></thead><tbody><tr><td>Concentration [mg/L]</td><td>692</td><td>429</td><td>Concentration [mg/L]</td><td>261</td><td>268</td></tr><tr><td>Deviation</td><td>38%</td><td></td><td>Deviation</td><td>-3%</td><td></td></tr></tbody></table>

The problem of different concentration measurements obtained from different subsamples can be avoided by not subsampling. One solution is to follow the following procedure:

1. Put the entire sample into one bottle.

2. Weigh the entire sample (suspended matter and water).

3. Filter the entire sample through a pre-weighed filter.

4. Weigh the filter containing all of the sediment once it has been dried.

5. Subtract the weight of the sediment from the weight of the original water sample to determine the volume of the original water sample.

6. Calculate the concentration by dividing the total weight of sediment by the volume calculated in step 5.

Another solution would be to sieve the entire sample (through a 63 µm opening sieve, for example) prior to filtration in order to remove the sand. The water containing the fine sediment could be filtered as usual, but the total weight of the sediment would be the dry weight of the two size fractions of sediment.
The errors in concentration estimates arising from subsampling of water samples containing sand can be reduced by adapting the procedures listed above. A sampler better adapted to measuring sand transport could also be used. A Delft Bottle is an instrument specifically designed for this purpose. In future studies at these sites we recommend comparing sand transport rates measured using a Delft Bottle to those measured using a point-integrated sampler.

## 9.3 Discharge measurements with ADCPs

Considering that a moving bed was detected at Luang Prabang and Kratie during our measurements, the results of this report indicate that if ADCPs are used to measure discharge they should be coupled with a GPS. Otherwise discharge values will be biased by the movement of the bed, and will tend to be underestimated. A GPS with precision on the order of a meter is sufficient for such purposes, the critical part being that the GPS be linked to the computer that is acquiring the ADCP data by a RS232 or a USB cable and that a compass calibration is performed prior to measurements. The post-processing of the ADCP data is then done using the GPS as the trajectory reference. This is simply a matter of selecting the appropriate option (GPS as the reference, not bottom tracking) in the ADCP data acquisition and processing software (e.g. Winriver). Examples of the differences between the discharges measured at Luang Prabang using the two references are shown in Table 13. The underestimation is between 8 and 9% when a GPS is not used. This error will increase with discharge and with increased sediment transport capacity of the river, but it also depends on the frequency of the ADCP that is used.

<table><caption>Table 13: Discharge values calculated using bottom tracking and GPS data as the reference.</caption><thead><tr><th rowspan="2">File</th><th colspan="2">Discharge [m³]</th><th rowspan="2">Deviation</th></tr><tr><th>Bottom track</th><th>GPS</th></tr></thead><tbody><tr><td>Luang_Prabang000</td><td>4592</td><td>5027</td><td>- 9%</td></tr><tr><td>Luang_Prabang002</td><td>4350</td><td>4722</td><td>- 8%</td></tr><tr><td>Luang_Prabang_p_m.000</td><td>4378</td><td>4733</td><td>- 8%</td></tr></tbody></table>

## 9.4 Concentration of total suspended solids from a turbidity meter

Turbidity measurement stations would be useful at study sites that are of interest for sediment transport studies. A turbidity meter measures the amount of particles in the water based on light scattering. A turbidity station consists of a turbidity meter in the water cabled to the shore where there is a current supply and data logger. If well maintained and calibrated, a turbidity meter can provide a continuous measure of suspended sediment concentration. Turbidity stations require regular calibration with water samples collected at the study site.

As with hydrometric stations at which one establishes a relationship between water level and discharge, one must establish a relationship between the turbidity and the concentration of
suspended sediment in order to convert the turbidity measurement to concentration. Turbidity is expressed in different units depending on the instrument (for example, NTU). Its relation to concentration depends on particle composition and primarily on grain size, and can therefore change with time and location depending on the origin of the sediments. An example of a turbidity/concentration calibration relationship is shown in Figure 55, while a photograph of the on-land equipment at a turbidity station in France is shown in Figure 56.

Turbidity stations enable continuous monitoring of the homogeneous washload concentration. They do not provide measurements of the sand, which is preferentially transported near the bed. The face of the sensor must be cleaned regularly since algae can grow on it and prevent it from working properly. It must therefore be installed in a location where it can be easily removed on a regular basis for cleaning.

<figure><img src="image_57.png" /><figcaption>Figure 55: An example of the relationship between Total Suspended Sediment Concentration (TSS) and turbidity on the Arc river (France).</figcaption></figure>
<figure><img src="image_58.png" /><figcaption>Figure 56: Photograph of a turbidity meter station on the Arc River (France)</figcaption></figure>

1. Electrical protections and distribution

2. GSM Modem

3. Turbidity meter set up and display module (Hach Lange SC100)

4. Fan and heating

5. Power regulation

6. Data Logger (Ott Logosens)

7. Power supply

Continuous measurements of concentration using a turbidity meter would improve estimates of sediment fluxes, especially on yearly time scales. Though there are questions surrounding how the concentration near the bank compares to the average concentration in the section, a turbidity meter would, without a doubt, improve estimates of sediment fluxes and budgets. The installation and calibration of these stations does, however, require regular maintenance and water sampling.

## 10. Comparison of results to previous studies

Most reports on the Mekong River that present total suspended solids concentration express concentration in ppm (parts per million, $10^{-6}$) (e.g. Walling, 2005; STS Green, 2012). However, this unit is often used without explanation of whether it is a mass fraction, a volume fraction, or mass of solids divided by volume of water. SI (International System) units of kg/m$^3$ (equivalent to g/L) should therefore be used, the unit of mg/L, which is better adapted to total suspended solids concentrations measured in rivers, could also be acceptable. Expression of concentration in SI units makes for more straight-forward flux calculations.

In Walling's 2005 report he stated the following: "Further empirical studies are required to establish the extent to which surface grab samples are capable of providing representative values of the mean sediment concentration in a cross section, either directly or via the use of correction factors". For the results presented in this study, the average concentration values measured in the samples collected closest to the surface were [152; 123; 168] mg/L at Luang Prabang, Khong Chiam and Kratie, respectively, while the average values measured throughout each cross section were [155; 140; 267] mg/L. Disregarding the Luang Prabang results, it can be seen the concentration of the near-surface samples was 88% of the mean concentration at Khong Chiam, while it was only 63% at Kratie. Alternatively, comparing the washload fluxes (equivalent to what would be seen at the
surface) to the suspended sand fluxes (results presented in Table 8, and at the end of Section 5), if
only washload is sampled than the suspended sediment fluxes will be underestimated by 10 – 50%.

A main motivator for this study was the IKMP Discharge and Sediment Monitoring Program Review (Koehnken, 2012). One of the things noted in that report was that no suspended sand was observed during peak flow periods at Kratie and downstream. The present report definitively shows that sand was in suspension at Kratie during our measurements, even though these measurements occurred on the descent of the monsoon flood and therefore well after peak sediment transport would have been expected.

In Koehnken (2012) the discharge observed at the end of September 2011 were 5000m³/s at Luang Prabang, 25000 m³/s at Khong Chiam and 42000 m³/s at Kratie. These values indicate that at that time of the year in 2011 the flood water had begun subsiding at Luang Prabang, but not at the two downstream sites. The discharge observed at Luang Prabang is similar to that observed during our measurements, but the values at the downstream sites were twice what we observed. Koehnken calculated relationships between discharge and total suspended solids using all available 2011 data (see Section 4.2.1 of her report). Applying those relationships to our discharge measurements we obtain total suspended solids concentrations of:

Luang Prabang: 236 mg/L for 4800 m³/s

Khong Chiam: 131mg/L for 9000 m³/s

Kratie: 161 mg/L for 22000 m³/s

These values are the same order of magnitude as our observations. Our results can also be compared
to the suspended sediment concentrations measured at Xayaburi by STS Green in August 2012.
Interpreting their results in ppm to be equivalent to mg/L total suspended sediment the minimum,
maximum and average concentrations that they observed throughout the cross-section were [85;
990; 300] mg/L. The highest concentration they observed is roughly three times the highest
concentration measured in October at Luang Prabang. Sampling errors aside, this difference is
indicative of the range in concentration values that can be observed between the start and the end of
the monsoon flood.

It should be noted that small scale sand mining operations were underway in the vicinity of our
measurements at Kratie, sometimes within a few hundred meters. The extraction of sand and gravel
from the river bed occurs in the Lower Mekong River on both small and large scales and it appears
to be largely unregulated. If sediment budgets are to be calculated for the Lower Mekong River,
then the extraction of sediment from the river bed must be accounted for. Otherwise the missing
information about the amount and location of sand extractions will greatly increase uncertainty in
sediment budget calculations. With questions surrounding the impact that the Xayaburi dam will
have on the sediment transport of the Lower Mekong, it is important to also account for the impact
of sand mining on the river's sediment transport budget.

**11. Conclusions**

The results presented in this report indicate that there is a heterogeneous distribution of sand at the
sites along the Lower Mekong River that were selected for this study by the WWF and the MRC,
namely Luang Prabang, Khong Chiam and Kratie. Estimates of the fluxes of suspended sediment and bed-load sediment were presented in Table 8 and at the end of Section 5.

The positive outcomes of this study include confirmation that the following techniques and instruments were appropriate for a study of this nature on rivers as large as the Mekong:

* The use of ADCPs (two frequencies were tested) coupled to GPS to accurately measure discharge and to detect a moving river bed.

* Successful collection of water samples at distinct depths throughout a cross section using a Van Dorn water sampler lowered by hand at depths as much as 30 m.

* The deployment of bed-load samplers weighing ~30 kg from suitable boats with winches and the successful collection of bed-load material.

* The use of high frequency acoustic backscatter profilers (an AQUAscat deployed on a bed-load sampling frame) to demonstrate temporal and spatial fluctuations of the suspended sediment transported near the bed at Luang Prabang.

* The use of multi-frequency data from the AQUAscat to determine concentrations of fine and coarse suspended sediment at different locations: vertical gradients in the concentration of sand were noted.

* Mainly successful use of a LISST portable for grain size analysis of water samples within 72 hours of sampling.

* Determination of concentrations of the fine suspended sediment and sand-sized particles via demodulation of the grain size results.

* Post-processing of the ADCP backscatter data (calibrated with the concentrations of fine suspended sediment and suspended sands) to estimate fluxes of fine sediment and sands separately.

Things to be improved in future studies:

* Some questions remain about the validity of the sand concentrations obtained from the Van Dorn samples because of the relatively low volume (2L) and because this sampler is not isokinetic. The use of Point Integrating Suspended-Sediment Samplers (for example USP63, see http://water.usgs.gov/fisp/catalog_index.html) can be a solution to obtain isokinetic samples but the volume (1 or 2L) remains too low to limit uncertainties in concentration and grain size analysis. A Delft bottle may be more accurate to characterize suspended sand fluxes.

* Filtration and grain size analysis of samples containing sand grains: the subsampling of water samples for concentration analysis can be avoided, but the problem remains for grain size analysis. Sand, when present, is rarely evenly distributed throughout the subsamples since it settles quickly. No simple solution exists to avoid these problems. Future test and procedures are needed.

* Commercial software marketed for the estimation of sediment fluxes needs improvement since they only consider unimodal grain size distributions. The authors continue to work on code to provide what we hope to be more accurate estimates of sediment fluxes.

* The amount of time spent at each measurement site was insufficient (1 day each at Luang
Prabang and Khong Chiam and 2 days at Kratie).

* Agreements with local embassies and governments could enable studies of this nature to be done in the MRC member countries, possibly avoiding the considerable amount of money that was spent at border crossings (both intercontinental and in Southeast Asia)
## References

Benaglia, T., Chauveau, D., Hunter, D.R. & Young, D.S. (2009) Mixtools: An R Package for Analyzing Finite Mixture Models.

Camenen B. & Larson M. (2005). A bed-load transport formula for the nearshore, *Estuarine Coastal and Shelf Science*, 63: 249-260.

Camenen B. & Larson M. (2008). A suspended load sediment transport formula for the nearshore. *Journal of Coastal Research*, 24(3): 615-627.

Camenen, B., Jaballah, M., Geay, T., Belleudy, P., Laronne, J.B., & Laskowski, J.P. (2012). Tentative measurements of bed-load transport in an energetic alpine gravel bed river. *River Flow, San Jose, Costa Rica, Sept. 2012*. pp. 379-386.

European standard NF EN 872, Water quality: Determination of suspended solids - method by filtration through glass fibre filters, June 2005.

Edwards & Glysson (1999). Field methods for measurement of fluvial sediment, in "Techniques of water-resources investigations of the U.S. Geological Survey, Book 3, Applications of Hydraulics.

Koehnken, L. (2012). IKMP Discharge and sediment monitoring program review, recommendations and data analysis, Part 2: Data analysis of preliminary results.

Meyer-Peter, E. & Müller, R. (1948), Formulas for bed-load transport, in "Proceedings of the 2nd Meeting of the International Association for Hydraulic Structures Research.", Stockholm, Sweden, pp. 39-64.

Moore, S.A., Le Coz, J., Hurther, D. & A. Paquier (2013), Using multi-frequency acoustic attenuation to monitor grain size and concentration of suspended sediment, *J. Acoustical Society of America*, 133(4), 1959-1970.

Mekong River Commission Information and Knowledge Management Programme 4th Bi-annual progress report and bi-annual workplan, 2012.

STS Green (2012). Sedimentation study for the Xayaburi Hydroelectric power project, Lao PDR, Monthly Report of August 2012 (First sampling).

Thorne, P.D. and Meral, R. (2008), Formulations for the scattering properties of suspended sandy sediments for use in the application of acoustics to sediment transport processes, *Continental Shelf Research*, 28, 309-317.

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Acknowledgements

Firstly, we would like to thank Marc Goichot from the WWF for co-ordinating this study. We are extremely grateful to the field crews of the Department of Hydrology and River Works (DHRW) in Cambodia, the Department of Meteorology and Hydrology (DMH) in Lao PDR and the Department of Water Resource (DWR) in Thailand. We thank Hourt Khieu, Felix Seebacher, Erland Jensen from the Mekong River Commission (MRC) for their work in the planning, coordination and implementation of the measurements. We specifically thank Hourt Khieu and Felix Seebacher for the exchanges about the data after the experiments. We thank Marina Launay (Irstea) for her work on the mixture model, Marie Courtel (Irstea) for the laboratory help, Doriane Sabatier (CEREGE) for some of the grain size analysis and Colin Rennie (University of Ottawa) for his feedback on this report. SM thanks Aquatec Group Ltd for the loan of the AQUAscat.
# Appendix A: AQUAscat data

One example of the AQUAscat data from each site was presented in the main body of the report. In the following appendix we present the data at all four frequencies for each site.

## Luang Prabang

The 500 kHz data (Figure 57) collected at the three shallowest depths are affected by scattering from the surface, as evidenced by the higher intensity values seen at 2, 4 and 6 m range at 2.2, 3.8 and 5.8 m depth. As the instrument position deepens, the interference occurs at longer ranges. These lines should be ignored.

<figure><img src="image_59.png" /><figcaption>Figure 57: AQUAscat 500 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.</figcaption></figure>
<figure><img src="image_60.png" /></figure>

Figure 58: AQUAscat 1000 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.

<figure><img src="image_61.png" /></figure>

Figure 59: AQUAscat 2500 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.
<figure><img src="image_62.png" /></figure>

Figure 60: AQUAscat 4000 kHz data: Fluid-corrected intensity at different across stream positions at Luang Prabang, shown from right bank to left bank.

## Khong Chiam

The horizontal streaks seen in the 500 kHz data (Figure 61) are the result of interference from the 600 kHz ADCP. The latter was operated during the AQUAscat measurements to monitor bottom depth in order to avoid catching the instrument on the rocky bed. Since only the data from the two highest frequency transducers were used to calculate suspended sediment concentration, this is not a problem.
<figure><img src="image_63.png" /><figcaption>Figure 61: Khong Chiam 500 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</figcaption></figure>

<figure><img src="image_64.png" /><figcaption>Figure 62: Khong Chiam 1000 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.</figcaption></figure>
<figure><img src="image_65.png" /></figure>

Figure 63: Khong Chiam 2500 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.

<figure><img src="image_66.png" /></figure>

Figure 64: Khong Chiam 4000 kHz AQUAscat data: fluid-corrected intensity shown from right to left bank.
## Kratie

<figure><img src="image_67.png" /></figure>

Figure 65: AQUAscat acoustic backscatter data collected at 500 kHz, corrected for spreading and attenuation due to water. V1 was the closest position to the left bank. The instrument faced the left bank.

<figure><img src="image_68.png" /></figure>

Figure 66: Kratie AQUAscat data at 1000 kHz.
<figure><img src="image_69.png" /><figcaption>Figure 67: Kratie AQUAscat data at 2500 kHz.</figcaption></figure>

<figure><img src="image_70.png" /><figcaption>Figure 68: Kratie AQUAscat data at 4000 kHz.</figcaption></figure>