1 Introduction
Unlike any natural resource, water resources are finite though cyclic. The hydrological cycle continuously renews the available water and keeps on providing us
with the much needed life giving resource time after time. The cycle is not uniform
like that of diurnal time and has random variations within it; there is also a multitude of cycles. On the other hand, demands of life are largely constant at the unit
level. We need fixed quantum of water at fixed points in time to sustain our food
and energy security regimes. There is a need to realize that water is a physical
resource and not an abstract resource like money. When we deal with a physical
resource, our strategies have to be built on the foundations of data—of supplies and
demands and their interplay with other physical resources like land, food and fibre.
Whereas other resources are attributed monetary values and, thereby, provided with
abstract formulations, water is traditionally not dealt in this manner. Being a
common pool resource, it has to be allocated amongst various stakeholders in a
rational manner, else, there can be societal imbalances and tensions. Quantification
of such apportionments requires information about the temporal and spatial availability and utilization priorities. Such quantification cannot be made without support of data. However, the availabilities are random, being dependent upon climate
phenomena, which are not fully understood, and the limitations of such knowledge
have to be compensated by treatment of the same as a random resource.
When we are dealing with the random resource, we also realize that the randomness is not confined to time alone but across space as well. Not all areas of a
region are equally well endowed with water. Some areas have in plenty and struggle
with the problem of surplus, while other areas are not capable of maintaining the
quality life as we all have collectively set as a standard. In such an inequitable
availability regime, our constant endeavour is to provide an equitable supply regime
for everyone as per their needs.
In order to solve this problem, we need to find trends and opportunities of
harnessing the water supply so as to make it available for our sustenance and
progress. Most of the processes of nature responsible for supply of water are too
complex to model in a deterministic sense. Hence, there are no unique solutions that
can be generated in mathematical terms. Granularity of water usage is also a
challenge. Every agricultural field (some times even parts of the same field) is a
unique response unit for water consumption. Similarly, each house hold and each
industrial unit are also unique in this sense. Similarly, each parcel of land of a
catchment area is a unique element having its own response characteristic towards
generating the surplus out of the precipitation that it receives. The atmospheric
process of precipitation is having its own complexity, which is well known.
Thus, we are required to resort to an observational approach where we observe the
phenomena (in this case water availability and consumption) and attempt to find
trends which can provide us clues about the match between demands and supplies.
Observations result in data of diverse kinds. Each of the class of data has to be
correlated with the other data sets so as to find the cause-and-effect relationships.
132
A. B. Pandya
Unlike any natural resource, water resources are finite though cyclic. The hydrological cycle continuously renews the available water and keeps on providing us
with the much needed life giving resource time after time. The cycle is not uniform
like that of diurnal time and has random variations within it; there is also a multitude of cycles. On the other hand, demands of life are largely constant at the unit
level. We need fixed quantum of water at fixed points in time to sustain our food
and energy security regimes. There is a need to realize that water is a physical
resource and not an abstract resource like money. When we deal with a physical
resource, our strategies have to be built on the foundations of data—of supplies and
demands and their interplay with other physical resources like land, food and fibre.
Whereas other resources are attributed monetary values and, thereby, provided with
abstract formulations, water is traditionally not dealt in this manner. Being a
common pool resource, it has to be allocated amongst various stakeholders in a
rational manner, else, there can be societal imbalances and tensions. Quantification
of such apportionments requires information about the temporal and spatial availability and utilization priorities. Such quantification cannot be made without support of data. However, the availabilities are random, being dependent upon climate
phenomena, which are not fully understood, and the limitations of such knowledge
have to be compensated by treatment of the same as a random resource.
When we are dealing with the random resource, we also realize that the randomness is not confined to time alone but across space as well. Not all areas of a
region are equally well endowed with water. Some areas have in plenty and struggle
with the problem of surplus, while other areas are not capable of maintaining the
quality life as we all have collectively set as a standard. In such an inequitable
availability regime, our constant endeavour is to provide an equitable supply regime
for everyone as per their needs.
In order to solve this problem, we need to find trends and opportunities of
harnessing the water supply so as to make it available for our sustenance and
progress. Most of the processes of nature responsible for supply of water are too
complex to model in a deterministic sense. Hence, there are no unique solutions that
can be generated in mathematical terms. Granularity of water usage is also a
challenge. Every agricultural field (some times even parts of the same field) is a
unique response unit for water consumption. Similarly, each house hold and each
industrial unit are also unique in this sense. Similarly, each parcel of land of a
catchment area is a unique element having its own response characteristic towards
generating the surplus out of the precipitation that it receives. The atmospheric
process of precipitation is having its own complexity, which is well known.
Thus, we are required to resort to an observational approach where we observe the
phenomena (in this case water availability and consumption) and attempt to find
trends which can provide us clues about the match between demands and supplies.
Observations result in data of diverse kinds. Each of the class of data has to be
correlated with the other data sets so as to find the cause-and-effect relationships.
132
A. B. Pandya