Role of Remote Sensing and GIS inputs in physically based hydrological modelling
Dr. S. M. Seth
Director, National Institute of Hydrology, Roorkee-247667 (U.P.)
INDIA
The scope of hydrological applications has broadened
dramatically over the past four decades. Although the problems of flood
protection and water resources management continue to be of importance and
relevance for the security of communities and for human, social and economic
development, many applied problems relating to the wider role of hydrology have
come into focus.
The management of waste and pollution in the environment
requires the characterisation of hydrological flow and transport processes in
freshwater, soils and groundwater systems. These depend on complex and poorly
understood hydrobiological and hydrogeochemical interactions. Furthermore,
changes must be characterised at a range of scales, including global, and this
requires an integrated approach in which hydrological processes are central to
the global ecosystem.
Underlying applied problems is a set of scientific issues to
which answers must be found in order to make progress. One requirement is to
improve process understanding, key uncertainties include hydrological and
associated biological and geochemical processes. Some limitations are due to
problems of observability (the ability to estimate process parameters from
observations). This is partly due to a need for new measurement techniques (for
example for subsurface flows) and partly results from difficulties in describing
spatial variability identified by measurements at appropriate spatial and
temporal scales. The combination of these issues is a known restriction on the
application of computer modelling to many important applied problems.
Watersheds, catchments, river basins are subjected to many
types of modifications by human and natural activities. Such changes can be
distinguished as point changes and non-point changes and affect virtually all
elements of hydrologic cycle. Structural changes such as dam construction,
channel improvement, detention storage etc. are examples of point changes.
Forestry, agriculture, mining, urbanization etc. are non-point land use changes.
There has been a growing need to study, understand and quantify the impact of
major landuse changes on hydrologic regime, both water quantity and quality.
This is necessary to anticipate and minimize potential environmental detriment
and to satisfy water resources requirements.
Hydrological Modelling
Hydrological modelling is
a powerful technique of hydrologic system investigation for both the research
hydrologists and the practising water resources engineers involved in the
planning and development of integrated approach for management of water
resources. Hydrologic models are symbolic or mathematical representation of
known or assumed functions expressing the various components of a hydrologic
cycle. However, the term hydrological model is often understood to be and is
used more narrowly as a computer based mathematical model. With the current
rapid developments within computer technology and hydrology the application of
computer based hydrologic models can only continue to increase in the near
future.
Various techniques are available in the literature for
modelling hydrologic system. Simulation is one of them where a system is
represented as a model and its behaviour is studied. Digital simulation is
needed in watershed research because it is a complex system to be analysed by
exact mathematical techniques. In digital simulation, system model is developed
by a number of mathematical expressions that represent the various processes of
the system and simulation is done by using a computer.
Hydrological models can be classified in different ways.
Broadly many of the models presented in the literature can be divided into
deterministic and stochastic categories. A deterministic model is one in which
the processes are modelled based on definite physical laws and no uncertainties
in prediction are admitted. It has no component with stochastic behaviour i.e.
the variables are free from random variation and have no distribution in
probability. Deterministic models can be further classified according to whether
the model gives a spatially lumped or distributed description of the catchment
area, and whether the description of the hydrological processes is empirical,
conceptual or fully physically based.
The familiar
classification of model classification is to classify them in three categories:
a) Black box models, b) Lumped models and, c) Physically based models.