| Abstract | Extensive literature review reveals that water resources planning and management modeling
for a tidal reservoir-river basin with salinity constraints is very rare and complicated. The
complexity is due to the nonlinearity of hydropower benefits, groundwater investment costs, and
the implicit nonlinear salinity constraints in the optimization model. Salinity distribution depends
on the hourly tidal water level and unknown decision variables (reservoir release and extracted
discharge). In tum, the decision variables have to be solved properly to satisfy with the salinity
constraints. To overcome these obstructions, a new integrated water management model is
proposed. The linearization of hydropower benefits and groundwater investment costs is suitably
implemented. A new changed constraint approach is developed for solving the implicit nonlinear
salinity constraint through a proposed solving tool, the linked extended Lingo-Excel-HFTM
(Hydrodynamic flow and transport model) program. In the study modeling system, there are six
stages of analysis each with different models:
• Data collection stage: This is concerned the physical, environmental, social-economic and
institutional factors that affect the water demands for agriculture, public water supply and
hydropower production.
• Data processing stage: The artificial neural network model is used to generate or forecast the
monthly inflows at upstream boundaries to expand its time series data, if necessary. The statistical
model is used to compute the low ( 4-year drought) inflow at upstream boundaries.
• Global water balance stage: Hydrologic model, with time step of year and time horizon of over
ten years, is used for the evaluation, and figure out the distribution of water sources and demands
to support the selection of scenarios in next stage.
• Scenario set up stage: It is implemented on the basis of the results obtained from previous
stages. It should be considered both existing and future scenarios, constructional and nonconstructional
measures in this process.
• Optimization process stage: The proposed integrated water management model is essentially a
linked optimization and hydrodynamic flow and transport models. After linearization of
hydropower benefit and groundwater investment cost and applying the changed constraint
approach, the optimization model is conversed into and solved by linear programming. In the
changed constraint approach, the lower bounds of monthly discharge at control points were used
instead of salinity constraints. These lower bound discharges will be updated gradually through
the iterative computing process of the linked models. The integrated water management model is
used to search for the optimal solution for each scenario, that satisfies all the physical,
environmental, social and institutional constraints. If there is one solution whose total net benefit
is apparently and significantly highest. This solution was chosen as the best alternative.
Othe1wise, the competitive solutions should be forwarded to the next stage for selection of the
best one.
• Multi-criteria decision process stage: In this stage, the best alternative among all competitive
solutions obtained from previous stage is selected, using the analytical hierarchy algorithm. The
resulting values from previous stages, that are used for comparison, and managerial weighting
factors for all selected criteria given by the water managers, that reflect their tendencies and
preferences, are the input data. The proposed system has been applied to the water resources planning and management
problem in the Lower Dong Nai River Basin. The study basin is a complex reservoir-river system
with five main rivers and many small rivers and channels, three reservoirs at upstream, one
hydropower plant, two surface water treatment plants, one groundwater treatment plant and eight
irrigation sites. The execution time was about one to two hours using a Pentium-Pro PC 333
MHZ, storage of 4 GB and memory of 32 MB. The error between the nonlinear and approximated
linear values of hydropower benefit was -0.39% in term of hydropower net benefit or - 0.09% of
total net benefit. Hence, the linearization of hydropower benefit is acceptable. The results also
showed that the salt concentration at control points were properly satisfied with the water quality
standard (salinity) of withdrawal for water supply and irrigation. This is a reasonable result from
the link between optimization and hydrodynamic flow and transport models.
The hydrologic model showed a surplus of 16.57% (year 2010) for global water balance.
However, in the case of monthly time step with low (four-year drought) inflow and the increase of
water demand for the Ho Chi Minh City in year 2010 applied, the optimal solution showed that
water sources did not meet the demand for development of all agricultural areas in the basin.
Therefore, the constrnction of Phuoc Hoa Res~rvoir and its diversion should be implemented to
regulate and divert flow from Be River to Dau Tieng Reservoir to improve the efficiency of water
use. The results also showed that the surface water source on Dong Nai River was much larger
than that of others. For selected alternative, the optimal solution showed that Tri An hydropower
production obtained 38.49 % of its mean annual productivity. The water supply for municipal and
industrial uses was taken from both surface water (about 70%: Hoa An on Dong Nai River and
Ben Than on Sai Gon River) and groundwater (about 30%) sources. It also advised that the
withdrawal of groundwater for the irrigation should not be done in coastal zones to avoid the
adverse impacts due to the over-exploitation (salt intrnsion). Contrarily, using groundwater for the
irrigation at upstream zones, where the recharge was available and abundant was possible.
The sensitivity analysis has been implemented, as well. It is worth considering the effect of
changes of tidal characteristics, sources, demands, and benefit and cost units to the final optimal
solution in the context of the linked optimization and hydrodynamic flow and transport models. It
has been shown that the tidal amplitude had very strong effect while mean sea water level had less
effect on optimal solution. The Tri An sources, irrigational benefit and cost had rather significant
effects on optimal solutions, as well. |