poster - International Conference of Agricultural Engineering

eleases at period t; I(t) = reservoir inflow at period t; R i (t) = release at ith outlet at time
period t; n = number of total outlets; S LS and S max = lower and upper bounds on reservoir
storage amount; R i
min
and R i
max
= lower and upper bounds on reservoir release at ith outlet;
and T p = number of total periods, respectively.
2.2.2 Optimal value searching method
Among optimization algorithms, global search methods have been reported to efficiently
discover the minimum of multi-modal functions, irrespective of where in the variable space
the search procedure is started. There are well known global optimization methods, such
as Uniform Random Search (URS), Adaptive Random Search (ARS), Multiple Start
Simplex (MSX), Genetic Algorithm (GA), simulated annealing method, Annealing-Simplex
(A-S) method, and SCE-UA method. Particularly, the SCE-UA method has been tested
by comparing it with other methods, and it proved to be consistent, effective, and efficient
in locating the globally optimal variables (Duan et al., 1994). In this study, the SCE-UA
method is employed to search for optimal variables during reservoir operation periods.
3. Application and Results
The model’s applicability is evaluated through the reviews of the results from its
applications to optimal water allocations of both Balan Reservoir and Seomjin Dam in
South Korea that are an irrigation reservoir and a multi-purpose, multi-outlet dam,
respectively.
3.1 Single-Purpose, Irrigation Reservoir Operations
The model is applied to the optimal operation of a single-purpose reservoir. The case
study reservoir is Balan Reservoir in the Balan watershed, which is 2,649ha in area and
includes two irrigation reservoirs, as shown in Fig. 2. To simulate daily inflows for the
reservoir, the streamflow network model, SSARR, is utilized using the system
configuration as shown in Fig. 3. In this study, to generate the demand for agricultural
water, a water demand computation sub-model is used, taking into account the amounts
of water required by irrigated rice paddy fields and the application efficiency of irrigation
districts. During the optimal operations, the differences in amounts of total water
releases between the observed and simulated range from -2.6 % to 10.5 %, varying with
each simulation case, and the operation results indicate that optimal release patterns are
similar to those of the observed as shown in Fig. 4.
HS#5
1
Kicheon
reservoir
A-4
IG#4
2
A
A4
R-4 RT#4
Figure 2: Watershed boundary of
the Balan watershed
RT#1
IG#1
Balan
reservoir
R-1
A-1
A1
HS#1
3
6
C
7
HS#4
5 B 4
HS#2
HS#3
Legend
Reservoir
Watershed
Transfer
point
Channel
reach
Figure 3: Configuration of the study
watershed system