20 Future Perspectives
451
water resources problems and not the merging hydrologic science. Dozier (1992)
correctly points out that our historical data have not been able to represent the
wide variety of spatial and temporal scales encountered in hydrology and the resulting models reflect a simple, homogeneous view of the natural world. He concludes that "this forced oversimplification impedes scientific understanding and
management of water resources".
If the emerging Hydrological Sciences are to break away from the traditional engineering hydrology, a number of general and specific data needs are going to have
to be addressed and solved. Again, quoting from the "Opportunities in the Hydrological Sciences" (NRC, 1991) some of these needs are:
"Hydrologic data are needed to measure fluxes and reservoirs in the hydrologic cycle and to monitor hydrologic change over a variety of temporal and
spatial scales.
Detection of hydrologic change requires a committed international long-term
effort and requires also that the data meet rigorous standards for accuracy.
Synergism between models and data is necessary to design effective data
collection efforts to answer scientific questions.
A fundamental block to progress in using most hydrologic data is our poor
knowledge of how to interpolate between measurement points."
A very convincing case is made for the need to not make hydrologic data collection an after thought. In addition the issue of data accessibility and management is
addressed as part of the general data issue. This is a particularly important issue
not only because all the data in the world are useless unless one can access them
but also technology for storage, transmitting, displaying and analyzing data is
changing very rapidly. Other than to encourage hydrologists to keep abreast of
these rapidly changing developments, further discussions of this topic is beyond
the scope of this book.
The question must now be raised if one accepts the premise that "hydrologic science is data limited", what do we do about it? Two issues that traditional hydrologic instrumentation cannot address is the spatial variability of hydrologic processes and wide disparity of space and time scale that scientific hydrology must
address. Remote sensing does meet these needs. Remote sensing can address the
spatial heterogeneity and the scale disparity problems. For example, remote sensing may be the only viable approach to handle spatial variability of drainage basin
properties and hydrologic process because the basic data are spatial in nature.
Space borne instruments also have the ability to make measurements that span the
many scales from near point processes to global. However, to realize the potential
of remote sensing a number of carefully planned and executed studies must be
carried out that demonstrate the relationship between traditional point data and
remote sensing data.
451
water resources problems and not the merging hydrologic science. Dozier (1992)
correctly points out that our historical data have not been able to represent the
wide variety of spatial and temporal scales encountered in hydrology and the resulting models reflect a simple, homogeneous view of the natural world. He concludes that "this forced oversimplification impedes scientific understanding and
management of water resources".
If the emerging Hydrological Sciences are to break away from the traditional engineering hydrology, a number of general and specific data needs are going to have
to be addressed and solved. Again, quoting from the "Opportunities in the Hydrological Sciences" (NRC, 1991) some of these needs are:
"Hydrologic data are needed to measure fluxes and reservoirs in the hydrologic cycle and to monitor hydrologic change over a variety of temporal and
spatial scales.
Detection of hydrologic change requires a committed international long-term
effort and requires also that the data meet rigorous standards for accuracy.
Synergism between models and data is necessary to design effective data
collection efforts to answer scientific questions.
A fundamental block to progress in using most hydrologic data is our poor
knowledge of how to interpolate between measurement points."
A very convincing case is made for the need to not make hydrologic data collection an after thought. In addition the issue of data accessibility and management is
addressed as part of the general data issue. This is a particularly important issue
not only because all the data in the world are useless unless one can access them
but also technology for storage, transmitting, displaying and analyzing data is
changing very rapidly. Other than to encourage hydrologists to keep abreast of
these rapidly changing developments, further discussions of this topic is beyond
the scope of this book.
The question must now be raised if one accepts the premise that "hydrologic science is data limited", what do we do about it? Two issues that traditional hydrologic instrumentation cannot address is the spatial variability of hydrologic processes and wide disparity of space and time scale that scientific hydrology must
address. Remote sensing does meet these needs. Remote sensing can address the
spatial heterogeneity and the scale disparity problems. For example, remote sensing may be the only viable approach to handle spatial variability of drainage basin
properties and hydrologic process because the basic data are spatial in nature.
Space borne instruments also have the ability to make measurements that span the
many scales from near point processes to global. However, to realize the potential
of remote sensing a number of carefully planned and executed studies must be
carried out that demonstrate the relationship between traditional point data and
remote sensing data.