Civil Engineering Reference
In-Depth Information
wetlands; water levels at specific locations for significant trees or wetlands
to access groundwater; high flow event timings for fish breeding and
migration; minimum flows at points to meet water needs for recreation such
as river rafting; or minimum waterhole levels for hippo survival (see further
discussion later in this chapter regarding environmental water assessments).
Whatever these parameters are, the model selected should be able to generate
the outputs needed to assess the extent to which the services and benefits can
be influenced by water resource management.
Dynamic water resource models need to integrate information on current
management rules including:
O
how decisions are made for day-to-day operation of infrastructure such as
dams and weirs and diversion works. This can include obligations to meet
water levels for navigation, channel capacity constraints, flood control, etc.;
O
obligations to supply water, for example where there are legal or contractual
requirements to supply water from dams to meet town water supply,
hydropower, recreational water levels, environmental needs, or water
licences or permits;
O
priorities and methods for sharing water when demand exceeds availability;
O
any rules and methods that protect water from being extracted for purposes
such as ecosystem health or water quality maintenance.
Such information is normally readily available from government agencies and
infrastructure operators.
In addition to understanding the conceptual basis for models, it is
important for water resource planners as well as key stakeholders to appre-
ciate the uncertainties in model results. Water resource models, of necessity,
are always a simplification of a complex reality. While parameters such as
aquifer transmissivity, channel roughness and resource boundary conditions
can be estimated by physical observations at points, they cannot be measured
at all points, and so models use representative parameters. The representative
parameters are often determined by a process of model calibration, which in
simple terms means applying known inputs (e.g. rainfall, river inflows, water
levels, extraction quantities) and adjusting the unknown parameters until the
model as closely as possible simulates a known output (e.g. river outflows,
storage levels, water levels). For example in a river system model, data from
gauged inflows and metered water extractions over a period of time might be
used as model inputs, and various internal model parameters such as channel
roughness are adjusted until the simulated flow at a point closely represents
the measured flow that occurred during the same time period. Validation of
the calibration can be done by calibrating the model parameters using part
of the available time series of data, then validating the calibration by testing
how well the model simulates the remaining available time series of data.
Confidence in the calibration is increased where the calibration and validation
periods cover a wide range of the possible inflow and extraction sequences.
