PhD Thesis Emmanuel Obeng Bekoe - Cranfield University

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a simple persistence model and even for the periods that it was positive it was
only 39%-54% better than the simple persistence model for the aggregated
daily into monthly simulations.
As noted by Wallace and Oliver (1990), complete information on all the terms of
the water balance equation is rarely available in a catchment. However having
analysed the modelling results from both the lumped and semi-distributed
modes within the context of the available data the strengths and weaknesses of
the ACRU model are highlighted below together with a summary of the
contributory factors for the poor model performance.
Strong Points of ACRU:
• The simulated streamflows generally follow the observed streamflow,
showing runoff peaks in wet seasons as in the observed streamflow data;
• The model performs better in the wet seasons of the year rather than in the
dry seasons;
• The aggregated daily into monthly simulations were superior over the
aggregated weekly and also the daily in as far as the appraisal statistics are
concerned making ACRU model more suitable for long term planning for
irrigation and water supply;
• The lumped simulations performed better than the semi distributed mode
simulations though not for PBIAS.
Weak Points of ACRU:
• There is overestimation in simulated flows during the rainy season which
was very pronounced in 1968 (an exceptionally wet year on record;
• The model performance in the drier periods is poor where PBIAS was
overestimating by over 60% for the validation period and underestimated for
the calibration periods (about 23%) and nearly overestimated 300% for
specific years like 1970 for the semi distributed Manhia simulations. The
NSE for the period failed the NSE criteria according to Henrikson et al.,
(2003). The PME statistic also failed in this period.
Emmanuel Obeng Bekoe Phd Thesis Chapter 6 Discussion