Role of Remote Sensing and GIS inputs in physically based hydrological modelling
Black box models
Black box models are based on transfer
functions which relate inputs with outputs. These models, as the name suggests,
generally do not have any physical basis.
Conceptual model
Lumped conceptual models occupy an
intermediate position between the fully physically- based approach and empirical
black box analysis. Such models are formulated on the basis of a relatively
small number of components, each of which is a simplified representation of one
process element in the system being modelled.
Physically based models:
The physically based models are
based on our understanding of the physics of the hydrological processes which
control the catchment response and use physically based equations to describe
these processes. Also, these models are spatially distributed since the
equations from which they are formed generally involve one or more space
coordinates. A discretization of spatial and temporal coordinates is made and
the solution is obtained at the node points of this discretized representation.
This implies that these models can be used for forecasting the spatial as well
temporal pattern of more than one hydrological variable. Such models require
much of computational time and also require advance computers as well as a broad
data base. Physically based distributed models do not consider the transfer of
water in a catchment to take place in a few defined storage as in case of lumped
conceptual models. From their physical basis such models can simulate the
complete runoff regime, providing multiple outputs (e.g. river discharge,
phreatic surface level and evaporation loss) while black box models can offer
only one output. In these models transfer of mass, momentum and energy are
calculated directly from the governing partial differential equations which are
solved using numerical methods, for example the St. Venant equations for surface
flow, the Richards equation for unsaturated zone flow and the Boussinesq
equation for ground water flow. As the input data and computational requirements
are enormous, the use of these models for real-time forecasting has not reached
the `production stage' so far, particularly for data availability situations
prevalent in developing countries like India.
Role of Physically Based Distributed
Models
Physically-based distributed models can in principle be
applied to almost any kind of hydrological problem. Obviously, there are many
problems for which the necessary solutions can be obtained using cheaper and
less sophisticated empirical, lumped conceptual or statistical models. However,
for the more complicated problems there may be little alternative, but to use a
physically-based distributed model. Some examples of typical fields of
application are:
Catchment changes
These include both natural and man-made
changes in land-use, such as the effects of forest fires, urbanization and
forest clearance for agricultural purposes. The parameters of a
physically-based, distributed model have a direct physical interpretation, which
means that they can be evaluated for the new state of the catchment before the
change actually occurs. This enables the effects of changes to be examined in
advance of such changes. In addition, the characteristically localized nature of
catchment changes can easily be accounted for within the spatially distributed
model structure.
Ungauged Catchments
An application in a previously ungauged
catchment requires the initiation of a programme of field work to provide data
and parameters for calibration. Here, the physical significance of its model
parameters enables e.g. the SHE to be applied on the basis of a much shorter,
and therefore more cheaply obtained, hydrometeorlogical records than is
necessary for more conventional models. Similarly the catchment parameters can
be estimated from intensive short-term field investigations.
Spatial variability
Spatial variability in catchments
inputs and outputs. Distributed models can be used to examine the effects on
flood flow of different directions of storm propagation across a catchment and
also the effects of localized river and groundwater abstractions and recharge.
This facility is beyond the capability of lumped catchment models which can deal
only with quantities averaged across the catchment.
Movement of Pollutants and Sediments
Movements of
pollutants and sediments. In order to model the movement of pollutants and
sediments, it is first necessary to model the water flows which provide the
basic dispersion mechanism. Most water quality and sediment problems are
distributed in nature, so distributed models are the most suitable for supplying
the basic information on water flows.