PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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xviii Nov November NSE Nash and Sutcliffe Efficiency Oct October ODE Ordinary Differential Equation PBIAS Percent BIAS PDE Partial Differential Equation <strong>PhD</strong> Doctor of Philosophy PME Performance Model Efficiency PO1 Porosity of topsoil (m 3 .m -3 ). PO2 Porosity of subsoil (m 3 .m -3 ). PTF Pedo Transfer Functions PWP Permanent Wilting Point PWP1 Permanent Wilting Point for top soil PWP2 Permanent Wilting Point for sub soil RMSE Root Mean Square Errorr ROOTA Fraction of the effective root system in the topsoil horizon, specified month by month RORB Rainfall Routing Model Rsp Spearman’s Rank Correlation Coefficient S Slightly sensitive SCS Soil Conservation Service SD Sustainable development SEE Standard Error of Estimate Sept September SHE Systeme Hydrologique European SMMDEP Effective (critical) depth of soil (m) from which stormflow generation takes place SRID Statistics, Research and Information Directorate SSARR Streamflow Synthesis and Reservoir Regulation StDEV Standard DEViation STOIMP Surface storage capacity (i.e. depression storage, or initial abstraction) of impervious surface, which needs to be filled before stormflow commences STORM Storage, Treatment, Overflow Runoff Model
xix SWAT Soil Water Assessment Tools SWMM Storm Water Management Model SWRRB Simulator for Water Resources in Rural Basins TOPMODEL Physically Based Runoff Production Model tt T Test Statistics UN United Nations UNCHS United Nations Centre for Human Settlements UNEP United Nations Environment Programme US United States USA United States of America USDA United States Department of Agriculture USGS United States Geological Survey VEGINT Interception loss (mm.rainday-1) by vegetation, specified month by month WARM WAter Resources Management study WMO World Meteorological Organization WP1 Permanent Wilting Point of topsoil (m 3 .m -3 ) WP2 Permanent Wilting Point of Subsoil (m 3 .m -3 ) WRC Water Resources Commission
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: xvii GWCL Ghana Water Company Limit
Page 21 and 22: xxi = Equals to ft Foot or feet ms
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
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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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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
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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
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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
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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
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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
Page 215 and 216:
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
Page 227 and 228:
206 References Adu, S. V; & Asiama,
Page 229 and 230:
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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