Author: Chloe Nunn 03-05-2018

Understanding Water and Sediment Flux at the Chaktomuk Junction Towards partial completion of an MSc Sustainability at the University of Southampton

Introduction During the Mekong’s wet season, peak flow reaches approximately 1.2x1012 litres of water per day (Darby et al 2016) which is equivalent to the average daily water use of 2 billion Americans, or 63 billion Cambodians (Shen 2010). Despite physically having enough water every day for approximately 4,000 times its population, Cambodians and millions of others living near the Mekong still face problems when it comes to accessing clean water, and sustaining their river dependent livelihoods (Cook et al. 2009).

Not only do residents of the Mekong watershed have to adapt to severe flooding for prolonged periods of the year caused by tropical cyclones, they must also adapt to anthropogenic impacts on the river, such as damming, which impacts sediment flux (Kummu & Varis 2007), and fish migration. The former maintains deltaic growth (Darby et al. 2016), provides nutrients to support ecosystem productivity (Wild & Loucks 2014), and builds up deposits used by fish (Baran & Guerin 2012). Whilst the latter means fish cannot reach spawning grounds to maintain their population, and consequently stocks are reduced, negatively impacting the financial and subsistence stability of individuals relying on fishing to make a living and feed their families (Nittrouer et al. 2017).

Climate change is an established effect of anthropogenic activities and will likely manifest itself as increased weather variability (Kirtman et al. 2013). This, along with plans for extensive damming, is set to bring about unknown change to flow and sediment dynamics heavily relied upon on the Mekong. With increasing subsidence at the delta mouth caused by climate related sea level rise (M. Allison et al. 2017; Minderhoud et al. 2017; Nittrouer et al. 2017), a reduced sediment flux will only compound this problem, putting more people and their livelihoods at risk. Author: Chloe Nunn 03-05-2018

Figure 1. Phnom Penh, Cambodia and the Chaktomuk Junction on the Mekong River.

By quantifying sediment flux and flow dynamics of the Mekong across multiple years and seasons, researchers will be better prepared to give management recommendations to government bodies in relation to future climate uncertainty. This study provides data on water and sediment flux at the Chaktomuk Junction, Phnom Penh, Cambodia (Figure 1) for the dry season. Currently, there is a lack of data at high spatial and temporal resolutions to determine sediment dynamics (M. A. Allison et al. 2017). Adding to the existing timeseries, the study also compliments research conducted over previous years during the wet seasons, filling in missing data points.

Author: Chloe Nunn 03-05-2018

The aim of this study is to develop an understanding of flow dynamics at the Chaktomuk Junction during the dry season and to do so, will answer the following questions:

1. What is the water flux through the tributaries and distributaries at the Junction? a. Do these add up correctly? 2. What is the sediment flux through the tributaries and distributaries at the Junction? 3. How do the values compare to previous records? 4. How do the values compare to wet season values? 5. Do the values agree with relevant literature, and what might they implicate for the future of the Mekong dynamics and individual livelihoods?

The following sections will outline the methodology used collecting and processing the data, as well as limitations. Visualisations of the data will be analysed, then discussed in the context of the overall aim, and sub-questions of the study. Finally, implications and conclusions will be drawn.

Methods The fieldwork was carried out on a river cruise boat making transects across six different sections of the river, shown in Figure 2. Each was repeated four times, with the exception of the Bassac River which was repeated six times as it was so narrow. Crossings needed to be repeated until the difference between the total flux for each repeat crossing was less than 5% of the average total flux. Four worked for most transects apart from the Bassac because half of the transect was used for turning the vessel, skewing the data. To measure water velocity and acoustic backscatter (needed for sediment flux calculations) a Teledyne Acoustic Dopplar Current Profiler (ADCP) was used at 600kHz. It was attached to the port bow on a structure which could be raised and lowered (Figure 3). The instrument was powered by a car battery and communicated with a laptop via a cable. WinRiver software on the laptop was used to configure and run the ADCP, as well as display and save the collected data. Sediment samples were collected using a Van Doorn sampler (Figure 5). The instrument was lowered to the desired depth, a manual trigger was fired, and the instrument was recovered to the boat deck where the sample was carefully transferred into sample bottles, ensuring as little sediment was lost as possible. One litre of each sample was measured and then transferred to the filtration system (Figure 4), consisting of several glass flasks and a pump, all connected in series to one another via rubber tubing. The pump filtered the sample through glass microfibers (GF/C, 47mm diameter) and collected the water in the flasks. The final filter paper was stored for further analysis in the lab. The remainder of the liquid sample, which did not go through the filtration system, was used with a ‘Laser in-situ Scatterometry and Transmissometry’ (LISST) sensor to measure sediment concentration and particle size Figure 2. Location of transects. distribution.

Author: Chloe Nunn 03-05-2018

The filter papers were weighed in the lab and their pre-sediment weight was subtracted, giving the weight of the sediment collected. Using the weight in conjunction with the volume of the sample, the sediment concentration was calculated. The concentration was plotted against the corresponding acoustic backscatter value, obtained from the ADCP. The same had been done during a previous study to the Vietnamese Mekong using the same instrumentation and was combined with the data collected for this study. This dataset was imported to Matlab and using the Curve Fitting Toolbox, a power regression was carried out giving an equation of good fit for the data.

WinRiver was used to process the data collected with the ADCP. ASCII files were created and exported to the Velocity Mapping Toolbox (a Matlab function). The transects obtained at each station were averaged together. Using Dr Chris Hackney’s Matlab script (Appendix II) in conjunction with a power regression equation, and the averaged transects, a table (Table 1) of sediment fluxes was produced. Figures showing velocity and acoustic backscatter were produced using the Velocity Mapping Toolbox.

Many limitations in this study arise from the methodology. They can be split into technical, and human error. Technical: See Kostaschuk et al (2005) for a discussion of the limitations arising from the ADCP. In brief, the instrument cannot measure all portions of the water column across the river and therefore must extrapolate out to measure the missing portions. This creates error in the total flux calculations. Human: Due to the fact that the boat used could not motor up to the river bank, a researcher was required to estimate the distance between the shore and where the boat carried out its turn. This was input to the ADCP (see technical limitations). In addition, when conducting the water sampling to obtain sediment concentration a researcher was required to lower the Van Doorn sampler to the desired depth. However, due to current flow it was difficult to ensure the rope (measuring the depth) was vertical in the water column. Therefore, uncertainty around the exact depth at which the sample was obtained from exists.

This study was conducted over two days in January. While both days may have been characteristic of dry season weather and river dynamics, the data is still time limited. For the purposes of this study the data collected will be treated as ‘dry season’ data, however, this is a limitation when it comes to comparing it to other years and seasons as it is only a snapshot of dry season data for 2018.

Figure 3. ADCP mounted on bow. Figure 4. Filtration system. Figure 5. Van Doorn Sampler

Author: Chloe Nunn 03-05-2018

Results and Discussion ADCP profiles of current velocity and direction (not included due to the limited scope of this study), and acoustic backscatter were obtained for every crossing made at each transect, however there would be too many to discuss within the scope of this report so only the Chaktomuk Junction transect showing acoustic back scatter data will be analysed. All of the averaged backscatter data can be found in Appendix III.

Figure 6 shows the transects with corresponding averaged velocity data and total water flux shown underneath, given with a two standard deviations margin of error.

Figure 3. Averaged current velocity data for each transect. Total flux 'Q' (m3/s) is given below with two standard deviations as a margin of error. Red signifies faster flow and blue signifies slower flow. All transects are facing downstream.

The total water flux results from the Mekong True Left Bifurcation and Mekong True Right Bifurcation were used to assess the instrument, as the amounts of water flowing through each should add up to the total flux of the Mekong Upstream value. Doing these calculations gives:

(3800 ± 255) + (1900 ± 93) = 5700 ± 352

Considering the margin of error of the calculation, the measurements are satisfactory. The same calculations can be solved for other combinations; Tonle Sap + Mekong Upstream = Chaktomuk Junction, Chaktomuk Junction = Mekong Downstream + Bassac. However, these calculations fall just outside the margin of error. One theory for this mismatch is the influence of the tide. There are tidal influences reaching 300km up the Mekong, affecting Phnom Penh (Ogston et al. 2017). The hydrodynamic reach of the tide depends on gradient and channel morphology (Hoitink & Jay 2016), suggesting that the low lying Mekong can be affected by the tide well beyond the estuarine areas. The tidal influence can be seen in water level data collected by the Mekong River Commission (Figure 7). This may account for the discrepancies between the fluxes as they were measured at different points across the tidal cycle. Author: Chloe Nunn 03-05-2018

Figure 4. Hydrograph from the Mekong River Commission highlighting the daily oscillations hypothesized to be caused by tides.

While the results of this study may not indicate much on their own, they reaffirm results of past studies which quantify water and sediment flux. 85% of the water flux flows down the Mekong during the wet season, with only 15% during the dry season (MRC 2005). This roughly agrees with our results, indicating that the wet season flux (Chaktomuk Junction: 7200m3/s) is 21% of the flux from the 2013 dry season data.

Referring again to Figure 6, it can be seen that the majority of the transects indicate faster flow at the surface (red) and slower flow near the riverbed and banks (blue). The Bassac River, Tonle Sap River, and Chaktomuk Junction transects deviate most from this, all showing more variable flow velocities. This is most likely due to the way in which the data was averaged in the Velocity mapping Toolbox. The former two retain the slower flow near the riverbed, but the Bassac shows an area of faster flow along the riverbed. Shear stress causes the flow to slow down near the riverbed and banks, agreeing with the above results. The anomaly in the Bassac river indicating fast flow along the river bed may be due to the fact that the river was very narrow compared to the boat and therefore the data collected may be inaccurate. Alternatively, if the river bed is characterised by fine sediment, the sediment could have been flowing along with the current making it difficult for the instrument to distinguish the actual riverbed (Darby, pers comms). Author: Chloe Nunn 03-05-2018

Figure 5. Transects collected during the dry season in 2013 (Darby, unpublished, 2015).

Comparing the collected flow data (Figure 6), to wet season data (Figure 8) shows the huge impact tropical cyclones have on the hydrology of southeast Asia. The Mekong downstream branch sees 2.8 times as much water flow through it during September compared to January. The Bassac has a flux 17 times larger; Chaktomuk is 3.7 times larger, Mekong true right is 4.5 times larger, and Mekong True Left is 5 times larger. The Tonle Sap, however, appears to decrease in flux. This is caused by a ‘flood pulse’ system controlling the flow of water to and from the Tonle Sap lake (Darby et al. 2016). As precipitation increases at the beginning of the wet season, the water level in the Mekong increases, reaching a tipping point when its high-water mark exceeds the level in the Tonle Sap river (Junk et al. 1989). This forces the flow of the Tonle Sap river to reverse direction and flow into the lake. It can be deduced that the dry season flux of the Tonle Sap river is determined by the gradient from the lake to the point at which it joins the Mekong. As that gradient is decreased, and eventually caused to reverse, the water in the Tonle Sap will be relying almost entirely on volume to determine the speed at which is flows and will consequently have lower flux values for portions of the year. This can be seen in Figure 8 where the Tonle Sap flux is 2.4 times lower than its dry season value and flowing in the opposite direction.

Author: Chloe Nunn 03-05-2018

Figure 6. Velocity of water flowing downstream at the Mekong Downstream transect.

The velocity transects for the Mekong Downstream can be seen in Figure 9. It shows faster flowing water nearer the surface, at approximately 80cm/s, with areas of low flow near the banks and riverbed. The fastest flowing water can be found at the surface above the deepest section of the river, while slowest flowing water can be found at the riverbed at the deepest part of the river. This transect can be compared to data collected at the same location in September 2013, during the wet season (Figure 10). The fastest flow can be found in the middle of the river, at approximately 150cm/s, almost twice as fast as the dry season flow (Figure 9).

Figure 7. Mekong Downstream flow velocity from (Darby, unpublished, 2015)

To obtain the sediment flux for each transect, backscatter values were used in conjunction with the sediment concentration measurements. Backscatter measures the strength of sound reflections received from particles in the water column (Thorne et al. 1991). The higher the backscatter, the higher the concentration of sediment particles, or the larger the particles; type of particle also has an effect (Kostaschuk et al. 2005). Figure 11 plots the power function obtained for the data, overlaid on a scatter plot of backscatter against sediment concentration. The equation is provided alongside the r-squared value of 0.7219, indicating that the relationship fits the power function with some confidence, and therefore the equation can be used to estimate sediment flux. Author: Chloe Nunn 03-05-2018

Figure 8. Calibration curve using acoustic backscatter data and in-situ sediment samples collected by the researchers for this study and a previous study in the Vietnamese Mekong using the same ADCP instrument.

The output from the Matlab code produced the sediment flux values shown in Table 1. The greatest sediment flux originates from the Tonle Sap (TS) transect at 55.03kg/s. This is greater than the Mekong Downstream (MEKD) and Chaktomuk Junction (CHJ) values of approximately 54kg/s. The smallest flux originates from the Bassac River (BASS) transect at only 1.69kg/s.

Figure 9. Backscatter across the Chaktomuk Junction transect.

Obtaining in-situ sediment measurements and using them to calculate sediment flux not only calibrates the ADCP, but also contributes to improving satellite imagery based estimates of sediment flux (Binding et al. 2005; Birkinshaw et al. 2010; Meselhe et al. 2017). Sediment can be seen very clearly in satellite images, as can be seen in Figure 6. The clearly defined line extending from where the Mekong and Tonle Sap rivers meet indicates that the Tonle Sap river is contributing a greater quantity of sediment to the system. This is confirmed by the sediment flux values in Table 1, as does the structure shown in Figure 12. The Tonle Sap river enters the Mekong just prior to the right-hand side of Figure 12. The water column on the right-hand side shows a much stronger backscatter value, indicating the higher sediment concentration as compared to the Mekong water on the left-hand side. Author: Chloe Nunn 03-05-2018

Matlab Output

Discharge (m3/s) of the mean % cross-section Reach average SSC (mg/l) SS Flux (kg/s) BASS 153.07 12.039 1.6872 CHJ 6226.8 21.403 54.003 MEKD 7347.9 24.985 54.453 MEKL 1555.6 12.139 9.6064 MEKR 3101.9 18.945 23.65 MEKU 5195.6 18.815 45.56 TS 1607.1 70.156 55.03

Table 1. Matlab output: The first column is total sediment discharge, the second is average sediment concentration and the far-right column giving sediment flux in Kg/second. Acronyms: BASS - Bassac River, CHJ - Chaktomuk Junction, MEKD – Mekong Downstream, MEKL – Mekong True Left Bifurcation, MEKR – Mekong True Right Bifurcation, TS – Tonle Sap River.

Sediment flux (column 3 of Table 1) should be equal to column 1 times column 2, however when this calculation was completed there was a significant difference. This can be accounted for in the methods behind the Matlab script. The script obtains discharge and sediment concentration values for each cell in the transect data files, multiplies them, then adds all of the cell values to get the sediment flux. This is a more refined method than multiplying the total discharge and sediment concentration per transect file.

Unlike water flux, which will, in general, balance between branches of a river system, sediment flux can be unbalanced. Differently sized and shaped sediment particles can become trapped along a stretch of river, and the chemical properties of particles can cause some to flocculate and sink to the river bed (Wolanski & Gibbs 1995). The shape of a river channel can cause build up in one area (Hackney et al. 2018), and anthropogenic activity can add or remove sediment in the system. In the case of the Mekong, sand dredging, damming, and alterations to the flood pulse system, will have impacts on the sediment flux (Kummu & Varis 2007). Despite being illegal, sand dredging is a common sight along the Mekong in Phnom Penh. Sand is a highly sought-after commodity around the world (anon. 2017), but when it is removed from a river system it can have knock on effects downstream. Damming has been evidenced to reduce sediment flow downstream to the delta (Kummu & Varis 2007), by up to a 90% (Kondolf et al. 2014; Meselhe et al. 2017). By expanding the database of sediment flux measurements, future research will be able to discern whether or not damming is having the predicted results. Likewise, it is expected that tropical cyclone frequency and intensity will change along with the climate, having a direct impact on the flood dynamics of the region (Darby et al. 2016). Flooding brings nutrient rich sediment to agricultural land and fish habitats (Baran & Guerin 2012; Wild & Loucks 2014), seriously impacting livelihoods of locals should it alter its patterns unpredictably. Not only will people have to adapt to a changing flood pattern, but also to a change in their access to food and the subsequent financial effects. Some of these changes have already been seen, with some fishermen and women noting over a fifty percent decrease in catch rates over the last decade (Lavington et al, in the field).

In addition to the aforementioned impacts, a reduction in sediment flux to the delta mouth increases the subsidence of the delta (Erban et al. 2014; M. Allison et al. 2017; Liu et al. 2017; Minderhoud et al. 2017). With sea levels increasing in the region (Ogston et al. 2017; M. Allison et al. 2017), it is ever increasingly important for the river to maintain its sediment flux levels to prevent the disappearance of large areas of land whom many depend on for their homes and livelihoods. Author: Chloe Nunn 03-05-2018

Implications and Conclusions While this study seems small, it adds data to long-term databases which will ultimately develop the understanding of the Mekong’s water and sediment flux dynamics. This will help further the research into current trends in relation to climate change, including sea level rise and the frequency and timing of cyclone events. The sediment samples, combined with data from a previous study, contributed to a calibration of the ADCP instrument used so that in future studies it is easier to assess sediment flux in the Mekong.

The data provided here is accurate overall, once methodological issues and the potential impact of the tide have been considered. The sediment calibration curve produced had a good match with the data. The water flux was found to be comparable to previous studies, as did the sediment flux. Due to the limited time of this study no conclusions can be drawn concerning increasing or decreasing water and sediment fluxes, but the data will contribute to long term studies assessing those factors. It is important to build up the understanding of the Mekong system as it stands so that as the countries along its course build dams, dredge sand, and develop there will be an understanding of how the system might change and the impacts it will have ecologically and socially.

Author: Chloe Nunn 03-05-2018

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Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press. Available at: http://www.ipcc.ch/pdf/assessment- report/ar5/wg1/WG1AR5_Chapter11_FINAL.pdf [Accessed May 2, 2018]. Kondolf, G.M., Rubin, Z.K. & Minear, J.T., 2014. Dams on the Mekong: Cumulative sediment starvation. Water Resources Research, 50(6), pp.5158–5169. Available at: http://doi.wiley.com/10.1002/2013WR014651 [Accessed May 2, 2018]. Kostaschuk, R. et al., 2005. Measuring flow velocity and sediment transport with an acoustic Doppler current profiler. Geomorphology, 68(1–2), pp.25–37. Available at: https://www.sciencedirect.com/science/article/pii/S0169555X04002879 [Accessed May 2, 2018]. Kummu, M. & Varis, O., 2007. Sediment-related impacts due to upstream reservoir trapping, the Lower Mekong River. Geomorphology, 85(3–4), pp.275–293. Liu, P. et al., 2017. Stratigraphic Formation of the Mekong River Delta and Its Recent Shoreline Changes. Oceanography, 30(3), pp.72–83. Available at: https://tos.org/oceanography/article/stratigraphic-formation-of-the-mekong-river-delta-and- its-recent-shoreline [Accessed May 2, 2018]. Meselhe, E. et al., 2017. Modeling the Process Response of Coastal and Deltaic Systems to Human and Global Changes: Focus on the Mekong System. Oceanography, 30(3), pp.84–97. Available at: https://tos.org/oceanography/article/modeling-the-process-response-of-coastal-and- deltaic-systems-to-human-and-g [Accessed May 3, 2018]. Minderhoud, P.S.J. et al., 2017. Impacts of 25 years of groundwater extraction on subsidence in the Mekong delta, Vietnam. Environmental Research Letters, 12(6), p.64006. Available at: http://stacks.iop.org/1748- 9326/12/i=6/a=064006?key=crossref.687693ccba9bba2f8d848aa7018a5625 [Accessed May 3, 2018]. MRC, 2005. Overview of the Hydrology of the Mekong Basin, Vietiane. Available at: http://www.mekonginfo.org/assets/midocs/0001968-inland-waters-overview-of-the- hydrology-of-the-mekong-basin.pdf [Accessed May 3, 2018]. Nittrouer, C. et al., 2017. The Mekong Continental Shelf: The Primary Sink for Deltaic Sediment Particles and Their Passengers. Oceanography, 30(3), pp.60–70. Available at: https://tos.org/oceanography/article/the-mekong-continental-shelf-the-primary-sink-for- deltaic-sediment-particle [Accessed May 2, 2018]. Ogston, A. et al., 2017. How Tidal Processes Impact the Transfer of Sediment from Source to Sink: Mekong River Collaborative Studies. Oceanography, 30(3), pp.22–33. Available at: https://tos.org/oceanography/article/how-tidal-processes-impact-the-transfer-of-sediment- from-source-to-sink [Accessed May 2, 2018]. Shen, J., 2010. Average Water Use Per Person Per Day. Available at: http://www.data360.org/dsg.aspx?Data_Set_Group_Id=757 [Accessed April 21, 2018]. Thorne, P.. et al., 1991. Measuring suspended sediment concentrations using acoustic backscatter devices. Marine Geology, 98(1), pp.7–16. Available at: https://www.sciencedirect.com/science/article/pii/002532279190031X [Accessed May 2, 2018]. Wild, T.B. & Loucks, D.P., 2014. Managing flow, sediment, and hydropower regimes in the Sre Pok, Se San, and Se Kong Rivers of the Mekong basin. Water Resources Research, 50(6), pp.5141– Author: Chloe Nunn 03-05-2018

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Author: Chloe Nunn 03-05-2018

Appendix I: Reflection The first day in Phnom Penh was spent sightseeing. I went to the National Museum which was conveniently located down the street from our hotel. The building itself was beautiful and contained ancient stone work from the Khmer empire and older empires in the region. Unlike, British museums, visitors were allowed to touch the exhibitions. I’m not sure that having a policy like that is the best way to preserve historical artefacts however. Following that excitement, we attempted to go to the royal palace, but it was closed for lunch. We headed to the central market where we perused the goods for sale, and Elle began haggling. It was difficult to get my head around bartering, but it was evident that the sellers were expecting it and marked their initial prices up. Lunch was obtained at the hotel due to the reluctance of certain members of my group to try any restaurants.

Growing up in two countries meant that I was adapted to travel from a relatively young age. I have always been fascinated by other cultures and don’t see the point in going abroad if you don’t experience the different components of the culture. I enjoyed interacting with our boat driver during the fieldwork because it offered me some insight to the social side of things, which wasn’t present in my actual project. It was a shame that no Cambodian young scientists were able to join us for the river based fieldwork as it would have enhanced learning for both groups.

I enjoyed the food and have since made an Amok fish curry at home. I feel that trying a new cuisine is key to experiencing a new culture, and often an enjoyable way to do so. Depending on the locales visited to try new foods it also exposes you to other aspects of culture socially.

Visiting the S-21 Museum and the Killing Fields was a sobering activity. Having done an extensive project on the Holocaust it was interesting to draw parallels between the two, but also the stark differences that were evident.

Travelling by coach to Siem Reap allowed me to see some of the more rural areas between the two cities. While not extravagant, many of the elevated houses we passed were elegant and had artistic trim. We passed several schools which were connected to a monastery. I had just read the book, The Road to Angkor by Christopher Pym, which gave mention to a program developed by the French during their occupation of Cambodia. In order to address educational in rural areas, they set up training schools where they educated monks who would return to their town and, funded by the French government, set up a school. This greatly increased the percentage of students overall, and the percentage who finished each level of schooling. Seeing the schools made me wonder whether they were still educated by monks, or if they had just retained the location in close proximity to monasteries.

Missing the first day of projects in Siem Reap was disappointing as I had been excited about the project options in regards to sampling on the lake. However, finding myself exhausted and feeling unwell in the morning I stayed at the hotel. In the end I felt fine most of the day, but taking some time to relax was good too. It gave me an opportunity to complete some tasks in preparation for an interview on my return to the UK.

Projecting on the Tonle Sap lake was a different experience to the Mekong. Seeing the unique lives in floating villages was almost inspiring and I am in some ways jealous of the connectivity between the local people and their environment. However, the trip also heightened my appreciation for the luxuries I am afforded as a resident of a developed country.

The Angkor complex was astounding; however I think the logistics of the group trip could have been handled better. Having read Pym’s book it was amazing seeing the structures he’d spoken of in real Author: Chloe Nunn 03-05-2018 life. The size of the temples is phenomenal given the technology they were constructed with. The trip did make me ponder the motives behind tourism form the tourist’s end. As humans we reproduce and cover the planet, but also have a desire to see beautiful human-free locations. I rather enjoyed getting pictures full of tourists because they are a better depiction of the situation.

While I’m sure it isn’t always the case, I felt safer in the cities of Cambodia than I feel when I go to London. The Cambodians I met were some of the friendliest strangers I’ve met, and I would love to go back. I may have seen the positives to the country, because as someone from a developed world, I have bags of money which will go very far in a developing country like Cambodia. However, I am an educated individual and am well aware of the struggles experienced by the populations of developing nations. Cambodia may have a long way to go in terms of developing infrastructure and improving living conditions, and perhaps politically (the Khmer Rouge was in its recent past), but if the people I met while there having any role in its development I believe their future could be very bright.

The trip gave me a better appreciation for the difficulties in funding developing nations because it is difficult to identify the most important aspects of infrastructure to improve first and differences in culture make it even more so. In the future I would love to see more of the rural areas and the Mekong basin during the wet season. I am interested in the ways in which residents adapt when the flood phenomenon occurs every year, in stark contrast to our seasonal adaptations.

Author: Chloe Nunn 03-05-2018

Appendix II: Chris Hackney’s Matlab Script m = 8.092*10^(-20) c = 11 BinSize = 0.5 function[Files,Results] = ADCPbackscatter(m,c,BinSize)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % backscatter = function to calibrate ADCP backscatter readings with % measured susupended sediment concentrations and produce a calibration % curve to enable to the extraction of suspended sediment concentrations % from ADCP measurements. % % Inputs: m = the coefficient of the x % c = the exponent of the x % BinSize = the vertical length of the ADCP bin (m). Normally 0.5m for 600 kHz units and 0.25m for 1200 kHz units. % % Ouputs: Files - A string array containing the names of the files % processed % Results - a n x 3 matrix, where n is the number of files % selected. Column 1 = Discharge (m3/s) of the mean % cross-section % Column 2 = Reach average SSC (mg/l) % Column 3 = SS Flux (kg/s) % % % The routine requires that acoustic backscatter values are exported from % WinRiver II as follows: % Ascii output files from WinRiver II % - Classic format % - Backscatter output % - Metric units % - Ensure no spaces are in the file names (replace with underscore % if necessary). Spaces can cause problems in MatLab. % - Files should be of the format “*_ASC.TXT” (case does matter). % If the files you have do not work (maybe from a previous % version of WR or WRII), try outputting new ascii files from the % latest version of WRII and trying again. % These outputs are then analysed in the Velocity Mapping Toolbox (VMT; % Parsons et al. 2013) and .mat files are saved of the processed files. % % % % Created by C.Hackney 03/10/2014 % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Select and load *.MAT files for each site. [filename,pathname]=uigetfile('*.mat','Select the *.MAT files to read','MultiSelect','on'); if iscell(filename) numfiles=size(filename,2); elseif filename~=0 numfiles = 1; else numfiles = 0; end Author: Chloe Nunn 03-05-2018

Results=zeros(numfiles,3); for i=1:numfiles; fullfile=[pathname filename{1,i}]; load(fullfile);

Results(i,1)=V.Qp/100;

% Convert backscatter values into SSC based on calibration curves SSC=m.*(V.mcsBack.^c); % mg/l

% Compute section-averaged SSC SSC_avg=nanmean(SSC); % mg/l sy(i,1)=nanmean(SSC_avg); % mg/l Results(i,2)=nanmean(sy(i,1)); %disp('Section-averaged SSC (mg/L)'); %disp(ssc);

% Calculate sediment flux of the cross-section % flux=(ssc.*((V.u/100)*((V.mfd/size(V.mcsBack,2))*BinSize)))*1000; % multiply concentration by velocities and convert from cumecs to cubic litres per second. discharge=((((V.dl/size(V.mcsBack,2))*BinSize)*(V.u/100))*1000); flux=SSC.*discharge; flux=flux/1000000; %convert from mg to kg flux=nansum(flux); Results(i,3)=nansum(flux); % flux=(nansum(flux))/1000000; %disp('Section-averaged suspended sediment flux (Kg/s)'); %disp(flux); end Files=filename'; %Clean workspace clear -regexp ^ensemble; %clear workspace of unneeded variables end

Published with MATLAB® R2018a

Author: Chloe Nunn 03-05-2018

Appendix III: Backscatter Data for all Transects

Figure 10. Backscatter for the Tonle Sap River.

Figure 11. Backscatter for the Bassac River.

Figure 12. Backscatter for the Mekong True Left Bifurcation. Author: Chloe Nunn 03-05-2018

Figure 13. Backscatter for the Mekong True Right Bifurcation.

Figure 14. Backscatter for the Mekong Upstream transect.

Figure 15. Backscatter for the Mekong Downstream transect.

Figure 16. Backscatter for the Chaktomuk Junction