PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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List of Symbols m 3 xx m Cubic metre Metre m 3 /day Cubic metres per day m 3 . day -1 Cubic metres per day mm millimetres min minutes Fig Figure % Percentage cm centimetre et al. And others m/a Metres per annum mm day -1 Millimetres per day o C Degree celsius km 2 Square kilometre m 3 .m -3 Cubic metre per cubic metre km kilometre o degree o N Degree north o S Degree south Mg m -3 Milligrams per cubic metre mm hr -1 Millimetres per hour < Less than > Greater than ≤ Less than or equal to ≥ Greater than or equal to mm/a Millimetres per annum km 3 Cubic kilometre m 3 /s Cubic metres per second m 2 Square metre Tmin Minimum daily temperature Tmax Maximum daily Temperature
xxi = Equals to ft Foot or feet ms -1 Metres per second
Page 1 and 2: Cranfield University at Silsoe Inst
Page 3 and 4: Dedication iii I dedicate this PhD
Page 5 and 6: v historical data available to the
Page 7 and 8: vii 3.3.6 Comparison of the ANSWERS
Page 9 and 10: ix 7.7.2 Guidance On How Best To De
Page 11 and 12: xi Table 6.1 Performance Statistics
Page 13 and 14: xiii Figure 4.4 Annual Streamflow d
Page 15 and 16: xv Abbreviations and Acronyms ABRES
Page 17 and 18: xvii GWCL Ghana Water Company Limit
Page 19: xix SWAT Soil Water Assessment Tool
Page 23 and 24: Emmanuel Obeng Bekoe Phd Thesis Cha
Page 25 and 26: Figure 1.3 The four principles as b
Page 37 and 38: 2. Hydrology of Tropical West Afric
Page 39 and 40: 18 million inhabitants with an aver
Page 43 and 44: Figure 2.4 Mean annual rainfalls (m
Page 47 and 48: Figure 2.7 Mean Evaporation in Marc
Page 59 and 60: 38 computer speed and the developme
Page 61 and 62: Figure 3.4. Model Components (sourc
Page 63 and 64: 42 input is lumped, and even some o
Page 65 and 66: 44 • Should be able to output dai
Page 67 and 68: 46 (Young et al, 1995, Borah and Be
Page 69 and 70: 48 parameterizing hydrologic models
Page 71 and 72:
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
Page 125 and 126:
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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110 to this period. Typical output
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112 basin is the streamflow, thus m
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114 ranging from -18% to 34%. This
Page 137 and 138:
Change in streamflow (%) 40 30 20 1
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Change in streamflow (%) 118 80 60
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120 1. That the two sensitivities h
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122 as given by performance criteri
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N ∑ t = 1 124 N sim obs 2 obs obs
Page 147 and 148:
126 • Initial best estimate value
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128 5.4 Results of Calibration and
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130 Table 5.4 Performance statistic
Page 153 and 154:
5.5 Water Balance for the lumped si
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134 might be data problems as discu
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136 represented in the model by a c
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Weekkly Flows (mm) 80 70 60 50 40 3
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140 simulated streamflows were deri
Page 163 and 164:
Weekly Flows (mm) 80 70 60 50 40 30
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144 upper limits for the top soils
Page 167 and 168:
146 6. Discussion In Chapter 5, the
Page 169 and 170:
148 in the simulated streamflow of
Page 171 and 172:
150 • The assumptions behind the
Page 173 and 174:
152 data and rainfall distribution
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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160 the mountainous regions which r
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Cummulative Rainfall (mm) 8000 6000
Page 185 and 186:
164 Figure 6.4a Rainfall for subcat
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166 cusecs) on day 26 to 11.9m 3 /s
Page 189 and 190:
Monthly Means of Actual Evapotransp
Page 191 and 192:
170 lumped simulation at Manhia (Ta
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172 be corrected by calibration. Ne
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174 The figures show that there is
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176 a simple persistence model and
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178 Based on the above analysis, it
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180 within a year of establishment
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182 corrected soon after collection
Page 205 and 206:
184 One approach to assisting susta
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186 of soil maps and landuse maps w
Page 209 and 210:
188 • the use of daily spot strea
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190 statistics suggest that the cur
Page 213 and 214:
192 7.6.1 Density of Observation In
Page 215 and 216:
194 • The long distances between
Page 217 and 218:
196 up facilities/practices/routine
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
Page 235 and 236:
214 FAO_2 (2004) http://www.fao.org
Page 237 and 238:
216 Herpertz, D. (1994) Modellierun
Page 239 and 240:
218 Kouwen, N. (2000) WATFLOOD/SPL:
Page 241 and 242:
220 Mtetwa, S., Kusangaya, S., Schu
Page 243 and 244:
222 Pidwerny, M. (2005) Department
Page 245 and 246:
224 Singh, V. P. & Woolhiser, D. A.
Page 247 and 248:
226 United Nations (1994b) Agenda 2
Page 249 and 250:
228 WRC (2000) Water Resources Comm
Page 251 and 252:
Drainage from the topsoil to subsoi
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Step 8: Generation of Quickflow fro
Page 255 and 256:
horizon and its drainage coefficien
Page 257 and 258:
Annex C The Calibrated parameter va
Page 259:
Emmanuel Obeng Bekoe PhD Thesis Ann
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PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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