PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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161 6.2.2 Quality of Rainfall Data Rainfall analysis of the two stations, Koforidua and Manhia (Chapter 4) showed no anomaly for the period 1967-1972 which was the modelling period after tabulating daily totals and visualizing to detect whether the observations have been consistently or accidentally credited to the wrong day, whether they show gross errors (e.g. from weekly readings instead of daily ones) or whether they contain misplaced decimal points (Daymen and Hall, 1990). These totals were then plotted (Figure 4.1) according to the annual time step and detecting any trends or discontinuities through visualization undertaken, as the period of analysis for the modelling was too short for trend analysis (Daymen and Hall, 1990). A cumulative annual rainfall and weekly totals of Nsawam and Koforidua are shown in Figures 6.3a and 6.3b. Cumulative Annual Rainfall (mm) 8000 7000 6000 5000 4000 3000 2000 1000 0 1968 1969 1970 Period (Water Year) 1971 1972 Nsawam Koforidua Figure 6.3a Cumulative annual rainfall at Nsawam and Koforidua Emmanuel Obeng Bekoe PhD Thesis Chapter 6 Discussion of Results
Cummulative Rainfall (mm) 8000 6000 4000 2000 0 04/03/68 04/09/68 04/03/69 04/09/69 04/03/70 162 Emmanuel Obeng Bekoe PhD Thesis Chapter 6 Discussion of Results 04/09/70 Period (weeks) 04/03/71 Nsawam Koforidua Figure 6.3b. Cumulative weekly rainfall at Nsawam and Koforidua From the plots it is observed that the two stations have almost the same pattern of annual rainfall even though the curves occasionally cross each other. However, not much could be said about the quality of data even though from streamflow analysis (next Section 6.2.3) some concern is raised about certain rainfall recordings and for the fact that for year 1971 Koforidua seemed to have recorded much higher than usual rainfalls because it crosses the Nsawam line in the annual plot of Figure 6.3a. 6.2.3 Quality of Streamflow Data The quality of the streamflow data during very high flows in 1968 has already been mentioned. However, the quality of the streamflow data may be further affected by the: • method of data collection, and; • quality of the data recording. 04/09/71 04/03/72 04/09/72
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Cranfield University at Silsoe Inst
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Dedication iii I dedicate this PhD
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v historical data available to the
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vii 3.3.6 Comparison of the ANSWERS
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ix 7.7.2 Guidance On How Best To De
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xi Table 6.1 Performance Statistics
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xiii Figure 4.4 Annual Streamflow d
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xv Abbreviations and Acronyms ABRES
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xvii GWCL Ghana Water Company Limit
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xix SWAT Soil Water Assessment Tool
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xxi = Equals to ft Foot or feet ms
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Emmanuel Obeng Bekoe Phd Thesis Cha
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Figure 1.3 The four principles as b
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2. Hydrology of Tropical West Afric
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18 million inhabitants with an aver
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Figure 2.4 Mean annual rainfalls (m
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Figure 2.7 Mean Evaporation in Marc
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38 computer speed and the developme
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Figure 3.4. Model Components (sourc
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42 input is lumped, and even some o
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44 • Should be able to output dai
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46 (Young et al, 1995, Borah and Be
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48 parameterizing hydrologic models
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50 2. The definition of the catchme
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52 The SWAT model has become widely
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54 divided according to land use, s
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56 integrated physical conceptual m
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58 water resource assessments in So
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60 For runoff volume computation al
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62 The data situation with regard t
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64 developed in a mainframe environ
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Figure 3.7 The options of ACRU mode
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68 Menubuilder includes a help faci
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70 total evaporation. Evaporative d
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72 potential maximum retention of t
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74 4. Data Availability, Analysis a
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76 (see Table 4.2) had some data ho
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0.5 78 (n - 2) tt = Rsp -----------
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80 means more common than the daily
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82 not been repaired. As a conseque
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Figure 4.5 Land Use map of Densu Ba
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Table 4.4 ∗ * Land use parameters
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a b 88 Figure 4.7: Typical land use
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90 Table 4.8: Soil class percentage
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Figure 4.9. Soils of Southern Afric
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94 • Model 1 displays an increase
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96 sub soil horizons and the redist
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98 from the topsoil (A horizon) to
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100 4.3.1 Temperature Daily maximum
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Mean Monthly Wind Speed . (knots) 2
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104 network. Precipitation falling
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106 catchment (2) and Manhia sub-ca
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108 5. Hydrological Modelling of th
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Page 141 and 142: 120 1. That the two sensitivities h
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Page 147 and 148: 126 • Initial best estimate value
Page 149 and 150: 128 5.4 Results of Calibration and
Page 151 and 152: 130 Table 5.4 Performance statistic
Page 153 and 154: 5.5 Water Balance for the lumped si
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Page 165 and 166: 144 upper limits for the top soils
Page 167 and 168: 146 6. Discussion In Chapter 5, the
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Page 171 and 172: 150 • The assumptions behind the
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Page 175 and 176: Monthly cummulative flows Manhia..
Page 177 and 178: 156 response of ACRU at Nsawam in t
Page 179 and 180: 158 underestimation in the calibrat
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Page 185 and 186: 164 Figure 6.4a Rainfall for subcat
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Page 191 and 192: 170 lumped simulation at Manhia (Ta
Page 193 and 194: 172 be corrected by calibration. Ne
Page 195 and 196: 174 The figures show that there is
Page 197 and 198: 176 a simple persistence model and
Page 199 and 200: 178 Based on the above analysis, it
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Page 203 and 204: 182 corrected soon after collection
Page 205 and 206: 184 One approach to assisting susta
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Page 209 and 210: 188 • the use of daily spot strea
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Page 213 and 214: 192 7.6.1 Density of Observation In
Page 215 and 216: 194 • The long distances between
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Page 219 and 220: 198 7.7.1.2 Development of Data Arc
Page 221 and 222: 200 Could there be the need to plac
Page 223 and 224: 202 • Online sources of internati
Page 225 and 226: 204 However, data improvement is re
Page 227 and 228: 206 References Adu, S. V; & Asiama,
Page 229 and 230: 208 Balek, J. (1972) An Application
Page 231 and 232: 210 Brown, C.D., & Hollis, J. M. (1
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212 Davy, E., Mattei, F., & Solomon
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214 FAO_2 (2004) http://www.fao.org
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216 Herpertz, D. (1994) Modellierun
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218 Kouwen, N. (2000) WATFLOOD/SPL:
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220 Mtetwa, S., Kusangaya, S., Schu
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222 Pidwerny, M. (2005) Department
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224 Singh, V. P. & Woolhiser, D. A.
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226 United Nations (1994b) Agenda 2
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228 WRC (2000) Water Resources Comm
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Drainage from the topsoil to subsoi
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Step 8: Generation of Quickflow fro
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horizon and its drainage coefficien
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Annex C The Calibrated parameter va
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Emmanuel Obeng Bekoe PhD Thesis Ann
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