PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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221 Niel, H., Paturel, J., & Servat, E., (2003). Study of parameter stability of a lumped hydrologic model in a context of climatic variability. Journal of Hydrology, 278, 213-230 Nii Consult (2001) Rapid Environmental Assessment and Action Planning of the Densu River Basin in Ghana. A Consultancy report. A United Nations Center for Human Settlements (Habitat) and, Water Resources Commission of Ghana funded. Accra, March-2001 NISO, National Information Standards Organization (2004) Understanding Metadata: A Revision and expansion on Metadata Made Simpler: Aguide for Libraries (2001). ISBN: 1-880124-62-9. www.niso.org Opoku Ankomah, Y. & Forson, M. A. (1998) Assessing surface water resources of the South-Western and Coastal basin systems of Ghana. Hydrological Sciences Journal. 43 (5). Pp 733-740. Opoku Ankomah, Y. (1986) Annual flow characteristics of major Ghanaian rivers. Water Resources Research Institute (CSIR), Accra, Ghana. Opoku-Ankomah, Y., Amisigo, B. A. (1998) Rainfall and runoff variability in the southwestern river system of Ghana. In: Water Resources Variability in Africa during the XXth Century Proceedings of the Abidjan ’98 Conference, Cote d’Ivoire, November 1998. E Servat, D Hughes, J. M Fritsch (eds). IAHS Publication No. 252. IAHS Press, Inst. Hyd. Wallingford UK. Pp. 307-314 OTUI & COMPTRAN (1996) The study of the ATMA Development and Investment Programme and the Rehabilitation /Replacement of Kpong –Tema- Accra Pipeline. Phase 2 Report, Hydrologic study. Pachepsky, Y. A., and Rawls, W. J., (1999). Accuracy and Relaibility of Pedotransfer functions as affected by grouping soils. Soil Sccience Society. Am J. 63: 1748-1757. http://soil.scijournals.org/cgi/reprint/63/6/1748 Patrurel J. E., Servat, B., Kouamé, B., Lubés, H., Quedraogo, M., Masson, J. M. (1997) Climatic variability in humid Africa along the Gulf of Guinea Part II: and integrated regional approach. Journal of Hydrology 191, pgs 16-36. Pearce. A, J. (1990) Streamflow Generation Processes: An Australian View. Water Resour. Res. 26 (12), 3037-3047. Penman, H. L., (1948) Irrigation timing and amounts. Journal of the Australian Institute of Agricultural Science, 175-196. Personal Communication (2003) With the Chief Executive of the Water Resources Commission of Ghana, Dr. Adom and the Chief Hydrologist, Mr. Odame Ababio on the state of data collection as initiated by the Densu River Basin Management Board. Emmanuel Obeng Bekoe PhD Thesis References
222 Pidwerny, M. (2005) Department of Geography, Okanaga University College, Canada @ physical geography.net. (Assessed, 25/04/2005) http://www.physicalgeography.net/fundamentals/8j.html Post, D. A., & Jakerman, A. J. (1999) Predicting the daily streamflow of ungauged catchments in S.E Australia, by regionalising the parameters of a lumped conceptual rainfall-runoff model. Ecological Modelling 123 (1999) 91- 104. Rawls, W. J., Brakensiek, D. L., (1989) Estimation of soils water retention and hydraulic properties. In: More-Seytoux, H. J. (Ed). Unsaturated flow in hydrologic Modeling theory and Practice. Nata ASI Series C: Mathematical and Physical Sciences, Vol. 275. Kluwer Academic, Dordredrecht, Holland. Richardson, C.W., Wright, D.A., (1984). WGEN: a model for generating daily weather variables. U.S. Dep. of Agric., Agric.Res. Service, ARS-8, 83 pp. Ringeoet et al., (1961) In. Balek, J, (1983). Hydrology and Water Resources in Tropical Regions. Developments in Water Science 18. Elsevier Russell, E. W. (1981) Role of Watershed Management for Arable Land Use in the Tropics. In: Tropical Agricultural Hydrology. Edited by R. Lal Said, A., Stevens, D. K., Sehlke, G. (2005) Estimating water budget in a regional aquifer using HSPF-modflow integrated model. Jorunal of the American Water Resources Association 41 (1): 55-66 FEB 2005 Schaeger, F., natschke, M. and Witham, D., (2005) quality Assurance for hydrometric Network Data as a Basis for Integrated River Basin Management. Proceedings at “The Fourth Inter-Celtic Colloquim on Hydrology and Management of Water Resources. Guimaraes, Portugal, July 11-14, 2005. Schulze, R. E. (1984) Hydrological models for application to small rural catchments in southern Africa: Refinements and development, Water Research Commission, Pretoria, Report 63/2/84. pp248 Schulze, R. E. (1995) Hydrology and Agrohydrology: A text to accompany the ACRU 3.00 Agrohydrological Modelling System. Water Research Commission, Pretoria, Technology Transfer Report TT 69/95. Pp 543. (ISBN 1 86845 136 4). Schulze, R. E., George, W. J., Arnold, H., and Mitchell, J. K. (1984) The coefficient of initial abstraction in the SCS as a variable. In: Shulze, R. E. (1984). 52-81 Schulze, R. E., Schater, N. W., & Lynch, S. D. (1990) As assessment of regional runoff production in Qwa Qwa: AGIS application of the ACRU Emmanuel Obeng Bekoe PhD Thesis References
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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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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
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
Page 201 and 202: 180 within a year of establishment
Page 203 and 204: 182 corrected soon after collection
Page 205 and 206: 184 One approach to assisting susta
Page 207 and 208: 186 of soil maps and landuse maps w
Page 209 and 210: 188 • the use of daily spot strea
Page 211 and 212: 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
Page 233 and 234: 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: 220 Mtetwa, S., Kusangaya, S., Schu
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
Page 253 and 254: 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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