PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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91 Figure 4.8. Soils of Ghana compared to soils of Southern Africa (Source: University of Minnesota (2005) Emmanuel Obeng Bekoe Phd Thesis Chapter 4 Data Availability, Model setup & Analysis
Figure 4.9. Soils of Southern Africa (source: University of KÖln 2005) 92 Emmanuel Obeng Bekoe Phd Thesis Chapter 4 Data Availability, Model setup & Analysis
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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
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
Page 73 and 74: 52 The SWAT model has become widely
Page 75 and 76: 54 divided according to land use, s
Page 77 and 78: 56 integrated physical conceptual m
Page 79 and 80: 58 water resource assessments in So
Page 81 and 82: 60 For runoff volume computation al
Page 83 and 84: 62 The data situation with regard t
Page 85 and 86: 64 developed in a mainframe environ
Page 87 and 88: Figure 3.7 The options of ACRU mode
Page 89 and 90: 68 Menubuilder includes a help faci
Page 91 and 92: 70 total evaporation. Evaporative d
Page 93 and 94: 72 potential maximum retention of t
Page 95 and 96: 74 4. Data Availability, Analysis a
Page 97 and 98: 76 (see Table 4.2) had some data ho
Page 99 and 100: 0.5 78 (n - 2) tt = Rsp -----------
Page 101 and 102: 80 means more common than the daily
Page 103 and 104: 82 not been repaired. As a conseque
Page 105 and 106: Figure 4.5 Land Use map of Densu Ba
Page 107 and 108: Table 4.4 ∗ * Land use parameters
Page 109 and 110: a b 88 Figure 4.7: Typical land use
Page 111: 90 Table 4.8: Soil class percentage
Page 115 and 116: 94 • Model 1 displays an increase
Page 117 and 118: 96 sub soil horizons and the redist
Page 119 and 120: 98 from the topsoil (A horizon) to
Page 121 and 122: 100 4.3.1 Temperature Daily maximum
Page 123 and 124: Mean Monthly Wind Speed . (knots) 2
Page 125 and 126: 104 network. Precipitation falling
Page 127 and 128: 106 catchment (2) and Manhia sub-ca
Page 129 and 130: 108 5. Hydrological Modelling of th
Page 131 and 132: 110 to this period. Typical output
Page 133 and 134: 112 basin is the streamflow, thus m
Page 135 and 136: 114 ranging from -18% to 34%. This
Page 137 and 138: Change in streamflow (%) 40 30 20 1
Page 139 and 140: Change in streamflow (%) 118 80 60
Page 141 and 142: 120 1. That the two sensitivities h
Page 143 and 144: 122 as given by performance criteri
Page 145 and 146: N ∑ t = 1 124 N sim obs 2 obs obs
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
Page 155 and 156: 134 might be data problems as discu
Page 157 and 158: 136 represented in the model by a c
Page 159 and 160: Weekkly Flows (mm) 80 70 60 50 40 3
Page 161 and 162: 140 simulated streamflows were deri
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Weekly Flows (mm) 80 70 60 50 40 30
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144 upper limits for the top soils
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146 6. Discussion In Chapter 5, the
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148 in the simulated streamflow of
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150 • The assumptions behind the
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152 data and rainfall distribution
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Monthly cummulative flows Manhia..
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156 response of ACRU at Nsawam in t
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158 underestimation in the calibrat
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160 the mountainous regions which r
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Cummulative Rainfall (mm) 8000 6000
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164 Figure 6.4a Rainfall for subcat
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166 cusecs) on day 26 to 11.9m 3 /s
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Monthly Means of Actual Evapotransp
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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
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184 One approach to assisting susta
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186 of soil maps and landuse maps w
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188 • the use of daily spot strea
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190 statistics suggest that the cur
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192 7.6.1 Density of Observation In
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194 • The long distances between
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196 up facilities/practices/routine
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198 7.7.1.2 Development of Data Arc
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200 Could there be the need to plac
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202 • Online sources of internati
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204 However, data improvement is re
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206 References Adu, S. V; & Asiama,
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208 Balek, J. (1972) An Application
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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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PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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