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

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The closer the interviewer is to the respondent, the better the interviewers understandingof the interview material becomes. Even if there is a need for an interpreter, theinterviewer still has a fairly direct contact with the respondent. An advantage of havingan interpreter is the possibility of he or she providing information about the area, theculture and practical things (Devereux & Hoddinott 1993).4.1.1 Rural Electrification AgencyIn order to find out more about how Uganda fights their problems with rural electricity,we visited the Rural Electrification Agency (REA). We used a semi-structured interviewmethod, to get a discussion about the purpose of this newly started institution as well asinformation of how they work. We got help from our assistant field supervisor to get aninterview. It took place at the 10 th floor of the Workers House in central Kampala. Theinterviewees were a female spokesman from REA and an engineer, for more technicalanswers. A summary of the interview is found in section 3.3.4 and the questions can befound in Appendix 9.1.4.1.2 Rural PopulationWhen evaluating our result of our GIS-analysis, we also made numerous interviews withpeople in the countryside of our study area. Our intention with these interviews was toinvestigate the population’s attitude to, and need for, electricity and small-scalehydropower. As mentioned earlier, Anderson et al. (1999) claim that many energyprojects have failed because of a number of reasons (see section 3.3.2), which we basedour questions upon. In contradiction to the semi-structured qualitative interviewmethods used before, the questions in a structured quantitative method are asked in apredefined way. All respondents are asked the same questions and no discussion ispresent. Since English is rarely spoken in the study area, an interpreter was used toperform the interviews and to guide us in the countryside. The sample population forthe interviews was chosen along the way. The selection is not statistically valid, but weconsider it to be representative with respect to the objectives of our study. Questions areattached as Appendix 9.2.32
4.2 GIS AnalysisThe following section describes the technical part of our method, where we describe achain of processes with main focus on a specially designed algorithm. The main part ofour work has been performed on a laptop computer with a 1.6 GHz Intel processor andby the usage of the following software:o ArcGIS 8.3 & 9o Matlab 7.0.1o Microsoft Excel 20004.2.1 Data CollectionBy the beginning of our study there were no digital data over the study area in Ugandaavailable in Sweden. After some time we realized that the enormous bureaucracy anddifficulties in contacting ministries made it impossible to receive data from a distance.Instead we had to wait until we were in Uganda to collect the needed data. Oneinstitution to collect data from is the National Forestry Authority (NFA) within theMinistry of Water Lands and Environment (MWLE), in Kampala. They are the formerNational Biomass Study who started in 1992, sponsored by NORAD, to do land coverstratification (vegetation mapping) of the whole country. They also produced digital datasets from 1:50,000 maps, covering administrative boundaries down to parish level,infrastructure down to motorable tracks, boundaries of all protected areas such as ForestReserves and National Parks, rivers and land cover.Uganda has not a well-organized cooperation for sharing data among the ministries.Often the same work is performed at different ministries, without knowing of eachother’s existence. NFA only had digital data over administrative boundaries down toparish level, but we found that village data in paper form were available at a differentlocation, Ugandan Bureau of Statistics (UBOS) in Entebbe.The data we received from NFA are either discrete physical objects, e.g. a road,continuous physical surfaces, e.g. land cover (use), or discrete virtual objects, e.g.administrative units. All data are digitised in Arc 1960 UTM Zone 36N projection. TheArc Datum 1960 is referenced to the modified Clarke 1880 ellipsoid, TransverseMercator projection with coordinates on the UTM grid. The digital maps of Uganda aredivided into a grid system (see Figure 4.2), where our study area falls in the cells 93/1-4 –94/1-3.33
Page 1: Seminar series nr 121Finding Potent
Page 5: AbstractOver 2 billion people, most
Page 9: AcknowledgmentsFirst of all, we wou
Page 12 and 13: 5 Result ..........................
Page 14 and 15: For the specific case of Uganda, a
Page 17 and 18: 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 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 70 and 71: projects are supposed to be finance
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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