Finding Potential Sites for Small-Scale Hydro Power in Uganda: a ...

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projects are supposed to be financed by subsidies from the government, NGOs and aidorganizations, but the remaining part must come from the rural population itself. Since itis hard to quantify these costs, we asked the question in a way that gave us information ifthe interviewees had any liquid assets at all to buy electricity for. The question does notanswer how much money they have, instead it lets us know if they have any money or ifthey just trade goods or use self-catering.6.2 InterpolationWhen interpolating a DEM, the best result is usually received when the data points areevenly distributed throughout the interpolation area. Contour lines are practical whenvisualizing a landscape, but they do not represent the surface in a statistically correct waysince points along the lines are over-represented compared with the ones perpendicularto them (Eklundh, 1999). This over-representation of data points can lead to terracingproblems as can be seen in Figure 6.1a. A slight occurrence of terracing can be discernedin our DEM (see Figure 5.6) but in a comparison to the relief in Figure 6.1a we considerour terracing problems to be of minor importance. Our method is designed to find a 20-meter height difference over a distance of 100 meters, which means that smallervariations, such as terraces, within this distance are leveled out. Eklundh and Mårtensson(1995) argue that contour lines can only be used if a sophisticated interpolationalgorithm, such as ANUDEM is available, otherwise the terracing problems will be toopronounced, see Figure 6.1.(a)(b)Figure 6.1 Contour interpolation using a) Inverse Distance Weighted and b) ANUDEM. Source:Peralvo.In order to create a DEM a number of different techniques are available, such as Kriging,Spline and Inverse Distance Weighted (IDW) interpolation. In ArcGIS it is not possibleto use contour lines as input data when interpolating with these methods. To be able touse our received data in these methods we either had to digitize a new layer with evenly58
distributed elevation points or to convert the lines to points and use a generalizationroutine that reduces the over-representation of points along the lines. Since the study wasperformed under limited conditions, there was no possibility to try these differentmethods, therefore we used the ANUDEM based interpolation method TOPOGRID inArcGIS. Asserup and Eklöf (2000) say that when the highest possible accuracy is needed,advanced algorithms like ANUDEM offer more flexibility and higher precision, due toits drainage enforcement algorithm and the possibility to incorporate streamline data intothe interpolation. Also Peralvo (www.crwr.utexas.edu) found, when performing aquantitative comparison measurement, that TOPOGRID outperformed IDW, Krigingand Radial Basis Functions (RBF) when creating hydrologically correct DEMs.TOPOGRID consistently produced high quality results for both areas with steeperslopes and well-defined valley bottoms as well as river junctions, which substantiate theappropriateness of the locally adaptive approach used in the algorithm.When using contours as input data in the interpolation method ANUDEM the result isof course dependent on the quality of input data. As can be seen in Figure 5.6a, the badquality of digitalisation could have caused the loss of potential sites for small-scalehydropower stations. Bigger errors arisen by incorrect digitalisation and by outliers withhigh amplitude is likely to be detected and edited and therefore not causing muchproblems. Hence, bad quality of contours can be critical for the outcome, but errors arerelatively easy detected and eliminated through a visual inspection and editing of the data.In our study we tried interpolations with 100, 30 and 10-meter cell size in order to reacha suitable resolution. The reason for choosing the 10-meter resolution DEM is that it hasthe best accuracy regarding both terrain structure and absolute elevation, compared tothe 100 and 30-meter resolution. A reason not to choose the 10-meter resolution wouldbe the slight occurrence of terracing, which is not as noticeable in the other resolutions.After studying the shaded relief images, we found that in most cases there is no terracingwhere there are rivers and they have therefore no or little influence on our furtheranalysis of locating potential sites for small-scale hydropower. A reason for this is thedrainage enforcement function that we used in the ANUDEM interpolation, whichforces the interpolation to be as hydrological correct as possible. Our intention was alsoto interpolate with a 5-meter resolution, but the large amount of data that the contoursover Kisoro and Kabale involve, made it impossible to perform. The computationalcapacity required in virtual memory for an operation like this could neither be met onour laptop nor on one of the most powerful computers at the Department of PhysicalGeography and Ecosystem Analysis.59
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Seminar series nr 121Finding Potent
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AbstractOver 2 billion people, most
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AcknowledgmentsFirst of all, we wou
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5 Result ..........................
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For the specific case of Uganda, a
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2 Study AreaThe main reason for us
Page 19 and 20: In the 1960’s Uganda was one of t
Page 21 and 22: 2.1.3 TopographyMost of Uganda is s
Page 23: Figure 2.4 The highest volcano in K
Page 26 and 27: e able to manually write the data,
Page 28 and 29: Depending on the appearance of the
Page 30 and 31: o Then the water flows from the for
Page 32 and 33: and generator is 65% and 80% effici
Page 34 and 35: Table 3.2 Capacity and production o
Page 36 and 37: Table 3.5 Small-scale hydropower ca
Page 38 and 39: technology was supplied to an area
Page 40 and 41: component to all of these issues, g
Page 42 and 43: The Rural Electrification project t
Page 44 and 45: The closer the interviewer is to th
Page 46 and 47: Over this area we bought the follow
Page 48 and 49: The primary erosive force determini
Page 50 and 51: There are a set of tolerances used
Page 52 and 53: ivers are seasonal, since the hydro
Page 54 and 55: (a) (b) (c)Figure 4.8 An example sh
Page 56 and 57: 4.2.6 Post Processing of Output Dat
Page 58 and 59: A = ( b ⋅ h)2(4.3)Where A equals
Page 60 and 61: elinquish because of too expensive
Page 62 and 63: The first step when performing the
Page 64 and 65: more obvious in their geographic co
Page 66 and 67: By using a smaller area it is possi
Page 68 and 69: 5.3 Summary of Resultso The general
Page 72 and 73: Sinks are a reoccurring problem whe
Page 74 and 75: UTM Zone 36N projection. The study
Page 76 and 77: As described in chapter 3.3.3 all r
Page 78 and 79: and if good financing possibilities
Page 80 and 81: Hutchinson M. F., Dowling T. I., 19
Page 83 and 84: 9 Appendix9.1 Interview: Rural Elec
Page 85 and 86: 9.3 Digital DataAll data layers are
Page 87 and 88: Frame creationThis is made in order
Page 89 and 90: time2=clock;%starts timer on clock
Page 91 and 92: next(1,2)=(y-1);cell_height=(highes
Page 93 and 94: endendif height>=20;%if the accumul
Page 95: Site 16 (147486,78619)Site 20 (1560
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