Water resources and reservoir engineering : proceedings of the Seventh Conference of the British Dam Society held at the University of Stirling, 24-27 June 1992

413 Pages·1992·18.362 MB·English

by  Walker, Susan, Parr, Noel M., Charles, J. Andrew

Water resources and reservoir engineering
Water resources and reservoir
engineering
Proceedings of the seventh conference of the British Dam
Society held at the University of Stirling, 24-27 June 1992
Edited by Noel M. Parr, J. Andrew Charles
and Susan Walker
Thomas Telford, London
Conference organized by the British Dam Society, the British Hydrological
Society, the Scottish Hydrological Group and the Institution of Water and
Environmental Management
Organizing Committee
N. M. Parr, Chairman
Dr J.A.Charles
R. M. Jarvis
A. I. B. Moffat
A. C. Robertshaw
Dr Susan Walker
N.Tyler
First published 1992
A CIP catalogue record for this book is available from the British Library
ISBN 978-0-7277-1692-7
©The British Dam Society, 1992, unless otherwise stated
All rights, including translation, reserved. Except for fair copying, no part of this publication
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Thomas Telford House, 1 Heron Quay, London E14 9XF.
Papers or other contributions and the statements made or the opinions expressed therein are
published on the understanding that the author of the contribution is solely responsible for the
opinions expressed in it and that its publication does not necessarily imply that such
statements and or opinions are or reflect the views or opinions of the organizers or publishers.
Published on behalf of the organizers by Thomas Telford Services Ltd, Thomas Telford
House, 1 Heron Quay, London E14 9XF.
Contents
RESERVOIR PLANNING, OPERATION AND ENVIRONMENTAL
ASPECTS
The reliability of single, historic estimates of reservoir capacity.
A. J. ADELOYE 1
Optimal operation of local reservoir sources. A. H. BUNCH 11
Control rules for Tayside's linked system of reservoirs supplying two
demand zones. J. A. COLE and A. L GORDON 19
The South East Wales Conjunctive Resource Scheme.
S. A. GALLIMORE and J. C. MOSEDALE 33
Comparison of the yields of variants of the Broad Oak Water
scheme. J. K. HALL and D. E. MACDONALD 41
An investigation into the maintenance of high summer water levels
at recreationally important reservoirs using a simulation model of
the Tees reservoir system. A. I. HILL 53
Operational yields. W. L JACK and A. O. LAMBERT 65
The Balquhidder research catchments: development of the results
for application to water resources. R. C. JOHNSON 73
The water resources of Madras. M. C. D. LA TOUCHE and
P. SIVAPRAKASAM 81
Estimation of river flow requirements to meet electricity demands in
the Cameroon. P. E. ROBINSON 93
Evaluation impacts on environment of Narmada Sagar project,
India. H.SAHU 101
Reassessment of reservoir yields in North-West England in the light
of possible climate change. H. SMITHERS 107
Computer software for optimizing the releases from multiple
reservoirs operated for flow regulation. T. WYATT, E. V. HINDLEY
andT.C.MUIR 117
CONTENTS
RESERVOIR DESIGN AND CONSTRUCTION
Modelling the uncertainty of sediment deposition upstream of flood
control dams. G. w. ANNANDALE 125
The construction of a cut-off in a volcanic residual soil using jet
grouting. L J. S. ATTEWILL, J. D. GOSDEN, D. A. BRUGGEMANN and
G.C.EUINTON 131
Two embankment dams on alluvial foundation: Durlassboden and
Eberlaste. H. CZERNY 141
Reservoir competency study made in respect of limestone
formations found upstream of Kodasalli Dam, India.
H. V. ESWARAIAH, V. S. UPADHYAYA and C. R. RAMESH 147
The instrumentation, monitoring and performance of Roadford
Dam during construction and first filling. J. D. EVANS and
A.C.WILSON 157
Recent examples of reinforced grass spillways on embankment
dams based on CIRIA report 116. R. FREER 167
Reservoir construction development for irrigation in the United
Kingdom 1960-92. S. M. HAWES 175
The use of stepped blocks for dam spillways. H. w. M. HEWLETT
and R. BAKER 183
A review of spillway flood design standards in European countries,
including freeboard margins and prior reservoir level. F. M. LAW 191
The flood control works for the Cardiff Bay Barrage. P. J. MASON,
S. A. BURGESS and T. N. BURT 203
Numerical modelling of reservoir sedimentation.
I. C. MEADOWCROFT, R. BETTESS and C. E. REEVE 211
Triggers to severe floods: extreme rainfall and antecedent
wetness. D. W. REED 219
A statistical perspective on reservoir flood standards. D. w. REED
and C. W. ANDERSON 229
Trapping efficiency of reservoirs. C. E. REEVE 241
Small embankment-type reservoirs for water supply and amenity
use. B. H. ROFE, C. G. HOSKINS and M. F. FLETCHER 253
Rock for dam face protection and the CIRIA/CUR manual on rock
in coastal engineering. J. E. SMITH and J. D. SIMM 259
Design, construction and performance of Mengkuang Dam.
E. H. TAYLOR, C. M. WAGNER and J. H. MELDRUM 271
CONTENTS
RESERVOIR MONITORING AND MAINTENANCE
Implementation of the Reservoirs Act 1975 and monitoring of
dams. D. C. BEAK 287
Response of a clay embankment to rapid drawdown.
C. J. A. BINNIE, D. J. SWEENEY and M. W. REED 301
The role of instrumentation and monitoring in safety procedures for
embankment dams. J. A. CHARLES, P. TEDD and K. S. WATTS 311
Investigation, monitoring and remedial works at Tiga Dam,
Nigeria. H. S. EADIE, D. J. COATS and N. LEYLAND 321
Vegetation and embankment dams. C. G. HOSKINS and
P. R. RICE 329
Resume of maintenance contracts on hydroelectric reservoirs.
C. K. JOHNSTON and N. M. SANDILANDS 339
Performance of blockwork and slabbing slope protection subject to
wave action. H. T. LOVENBURY and R. A. READER 353
Surveillance and monitoring methods for Italian dams.
D. MORRIS 361
Site investigation of existing dams. J. M. REID 373
Dam ageing. G. P. SIMS 383
Development of a three-dimensional computer system for dam
surveillance data management. D. M. STIRLING and
G. L. BENWELL 395
The BRE dams database. P. TEDD, I. R. HOLTON and
J. A. CHARLES 403
The reservoir safety research programme of the Department of
the Environment. C. E. WRIGHT, D. J. COATS and J. A. CHARLES 411
The reliability of single, historic estimates of reservoir
capacity
A. J. ADELOYE, PhD, MIWEM, Imperial College of Science,
Technology and Medicine
SYNOPSIS. Direct-supply reservoirs are the oldest form of artificial,
man-made surface water impoundments. Hydrological analysis to determine
the capacity-yield relationships of such reservoirs is often carried out
empirically, using a record of observed streamflow data at the site with
one of several techniques which come under the general rubric of "critical
period methods". The major problem with this approach is that it does
not provide, explicitly, an estimate of the reliability of the reservoir
system. Information on the reliability is extremely important for a system
whose failure to meet targets is often accompanied by huge economic
losses. In this paper an attempt is made, using Monte Carlo simulation
techniques, to quantify the reliability of single historic estimates of
reservoir capacity. The results show that the reliability is not unique but
varies depending on the length of data record, the statistical
characteristics of the inflow series and the yield level.
INTRODUCTION
1. The analysis of direct-supply reservoirs using one of the many
critical period techniques (ref. 1) with a historic data record at the
project site gives a single estimate of reservoir capacity. However, by
their nature, traditional critical period techniques, e.g. the mass curve and
its automated version the sequent peak algorithm (SPA) (ref. 2), when
used in this way do not give a measure of reliability for the capacity
estimate; they merely design for the worst drought on record.
2. The fact that no explicit estimate of the reliability is produced
by these techniques does not mean the capacity estimate has no reliability.
In fact, analysts have made different assumptions regarding the inherent
reliability of this single estimate. For example it is sometimes assumed
that, since the critical period respresents a period of extreme low flows in
the record, the probability of the single capacity estimate will be that of
the lowest, i.e. rank 1, event (ref. 1). Another common assumption is
that the single estimate is the median of the probability distribution of
reservoir capacity, i.e. the capacity with a probability of 50% (refs 3-4).
3. There are other assumptions, and this divergence of opinion
has resulted from the fact that no systematic assessment of the inherent
reliability of single estimates of reservoir capacity has been carried out.
Yet the practice (of using single historic records) remains popular with
hydrology practitioners, and often is the only one that can be used in
certain situations, particularly in developing countries where paucity of
Water resources and reservoir engineering. Thomas Telford, London, 1992 1
RESERVOIR PUNNING AND OPERATION
data is commonplace.
4. In this work, the results of an operational hydrology method
for assessing the reliability of capacity estimates obtained from single
historic records are presented. For ease of tractability, only systems
dominated by over-year storage requirements have been considered. For
such systems, annual streamflow sequences can be analysed to derive the
required information (ref. 5).
METHOD OF RESERVOIR STORAGE-YIELD ANALYSIS
5. The technique of reservoir storage-yield analysis adopted is the
double cycling sequent peak algorithm, SPA (ref. 2). This technique has
been chosen for two main reasons: first it is the automated version of the
traditional mass curve analysis which, because it is sequential, takes into
account all the pertinent streamflow statistics characterising the data
record; and second, the marginal distribution of capacity estimates from
the technique has been found to be the Extreme Value Type 1 (EVI)
(ref. 6).
6. The SPA can be formulated thus (ref. 2)
Let K = storage capacity required at the beginning of period t,
t
Y = required release during the period,
t
Q = corresponding inflow during period t.
t
If we define
{Y - Q + Kt_i ; if positive
t t
K = { for t c 2T (1)
t
{0 ; otherwise
then the reservoir capacity C required is given by
C - max (K ); t = 1,2,..T,T+1,..2T (2)
t
7. To implement eq. (1), the reservoir is assumed to be initially
full, i.e. K = 0.0. Also, eq. (1) is applied over 2T, where T is the
o
length of data record, to take care of a situation in which the critical
period is close to the end of record T. Hence eq. (1) is termed the
double cycling SPA and the capacity C thus obtained represents the
minimum storage required over the T-year period to supply the desired
yield Y without shortages (ref. 7). In our simulations, T was also assumed
to be equal to the useful life of the reservoir.
8. If eq. (1) is applied to several T-year records, then a
distribution can be fitted to the reservoir capacities; this will ultimately
enable the determination of reservoir capacity with a desired reliability
(i.e. probability of non-exceedance) p over the T-year period. In this
work, this distribution was assumed, following Burges and Linsley (ref. 6),
to be EVI. The density function and the cdf of the EVI are respectively
(ref. 8)
f (x) = a exp(-a(x-u)) exp(-exp(-a(x-u))) (3a)
x
F (x) - exp(-exp(-a(x-u))) (3b)
x
where a is the scale parameter and u is the location parameter. Moment
ADELOYE
estimates of the parameters can be obtained from
\k - u + 7/a (4a)
a2 - 7r2/6a2 (4b)
where y = Eulers constant — 0.577216,
\i = sample estimate of the mean of the distribution
of capacity, and
0" = sample estimate of the standard deviation of the
distribution of capacity.
MONTE CARLO SIMULATION
9. Synthetic annual streamflow data records of various lengths
were generated assuming alternately the normal, 2-p log-normal and the
gamma density functions. These flows were assumed to be generated by a
Markov (AR-1) persistence process thus
Qt+i - H + r(Qt " ^q> + zoq ^-r2) (5)
where Q j, O are the flows in periods t+1 and t respectively, /* is the
t+ t q
mean flow (MAF), a is the standard deviation of flow, r is the lag-1
q
serial correlation coefficient and z is the random standard normal variate.
This simple model is adequate for our purpose since, according to
previous studies, the results of the analysis are not expected to be very
sensitive to moderate departures from the true model.
10. In the analysis, annual streamflow statistics used in eq. (5)
were pre-specified and were assumed to be known with certainty; this
eliminated the problem of parameter estimation variability. The parameters
j* , 0- and r specified are directly applicable to the normal model. For
q q
the log-normal model, the specified parameters were transformed using
moment transformation equations, while for the gamma model, the normal
variates, z, were transformed using the Wilson-Hilferty transformation
(ref. 1).
11. The mean annual flow /i was taken throughout to be unity;
q
this was to simplify the analysis, r was varied between 0.0-0.4 and CV
values were varied between 0.2-0.6. These ranges cover typical values
often encountered in most European streams. For the gamma model,
estimates of the skewness coefficient are also required; these were
obtained as (ref. 2)
S = 2CV (6)
k
12. The simulation experiment was similar in all cases. Using eq.
(5) and the combinations of streamflow statistics, 1000 synthetic traces of
annual streamflow data record of length T years were generated. In the
study, T values of 5, 10, 20, 50, 80, 90 and 100 years were considered.
Each of the 1000 traces was routed through the reservoir using the SPA
(eqs 1&2) and the capacity required to satisfy the yield Y without failure
over the T-year period was determined. To ensure that over-year storages
predominate for the assumed combinations of streamflow statistics, very
high yields (ranging from 0.7 to 0.98 of /i) were considered. Using all
q
RESERVOIR PLANNING AND OPERATION
Table 1. Summary of results for normal, log-normal and
gamma functions
cv r T Y a Hist p-Hist c99 c95 C90
(Yrs)
1 2 3 4 5 6 7 8 9 10 11
0. 2 0. 0 5 0.7 IHM
^ 8*. «QQ
H 0.028
0. 8 111; Hi
0. 9
10 0. 7 Mil
0. 8
0. 9 KM; lit \\ I;3H 1
50 0. 7
054 Q:015
066 0.216
0. 8
0. 9
100 0. 7 fl! I
0. 8 Hi I
0. 9 m i;i
0.4 0.0 5 0.7 f!H:l
0. 8
0. 9 liliM
10 0. 7 HI I: iff
nn
0. 8 514 0 fl? I; Hi
566 Q
116 0
0. 9 f ; H
50 0. 7
i.w m
0.8 h m 8 181
0 842 0 278 0.834 559 1.713 1 359 1 204
0. 9
100 0. 7 111 §287 0.738 Q
f61 Q.&Q1 Q
I 93 0.908 0
0. 8