17 Irrigation and Drainage
385
drainage studies. Even in the latter case one would need to estimate soil water
content in the root zone on the basis of microwave observations applying to, say,
the upper 5 to 10 cm soil depth (L-band). For detection and monitoring of soil
salinity this restriction in the observable soil depth may not be as severe, since
salts tend to accumulate in the top soil (Taylor et al., 1996),
G. Monitoring of extensive irrigated lands. All the methods mentioned above
may in principle be applied to monitor large irrigated lands. Because of the
emphasis on repetitive analysis of large amounts of data, examples found in
literature tend to cluster around the use of relatively simple methods. We may
distinguish between applications based on data at high and low spatial resolution.
In both cases most applications rely on the use of spectral reflectance measurements. Spectral indices are widely used to monitor both, conditions and extension
of irrigated lands.
High spatial resolution. Determination of irrigated area using the spectral
observations provided by MSS, TM, SPOT, LISS etc. has achieved a semioperational status. Although precise mapping of individual crops remains a
problem in most cases, groups of crops (e.g. summer cereals) can be mapped
satisfactorily to obtain a measure of actual crop water requirements. Determination
of year to year changes of irrigated area, possibly cropwise, would be a major
contribution towards better irrigation management. Moreover, the same
information is necessary to assess whether collected irrigation fees are paid
consistently with land use. Determination of waterlogged areas and bare salt
affected soils identifies the sectors within an irrigation scheme where water
management has to be improved.
Low spatial resolution. Sensors on-board meteorological satellites have the
capability of providing consistent observations at rather short intervals of time,
although at a relatively low spatial resolution. The multispectral observations
obtained worldwide with the NOAA! A VHRR sensors at a 1 km x 1 km spatial
resolution can be and have been (see examples of applications in the next section)
used to assess the temporal variability of land surface characteristics relevant to
irrigation management. Spatial resolution determines to a significant extent the
practical relevance of remote sensing for irrigation and drainage. Literature (see
Current Applications) points to an overwhelming interest for observations at high
spatial resolution. In some cases, however, even data at very low spatial resolution
may provide useful information on irrigated lands. Choudhury (1997), for
example, determined global potential evaporation at a 270 km x 270 km resolution
by combining satellite and meteorological data. Although not meant for local use,
results compared well with lysimeter observations at a number of locations.
GIS applications. The information obtained with airborne and space-borne
sensors provides a range of useful indicators on irrigation and drainage (see Chap.
4 and Current Applications). The scope of the remotely sensed data, however, can
significantly be enhanced through integration with other types and sources of data
385
drainage studies. Even in the latter case one would need to estimate soil water
content in the root zone on the basis of microwave observations applying to, say,
the upper 5 to 10 cm soil depth (L-band). For detection and monitoring of soil
salinity this restriction in the observable soil depth may not be as severe, since
salts tend to accumulate in the top soil (Taylor et al., 1996),
G. Monitoring of extensive irrigated lands. All the methods mentioned above
may in principle be applied to monitor large irrigated lands. Because of the
emphasis on repetitive analysis of large amounts of data, examples found in
literature tend to cluster around the use of relatively simple methods. We may
distinguish between applications based on data at high and low spatial resolution.
In both cases most applications rely on the use of spectral reflectance measurements. Spectral indices are widely used to monitor both, conditions and extension
of irrigated lands.
High spatial resolution. Determination of irrigated area using the spectral
observations provided by MSS, TM, SPOT, LISS etc. has achieved a semioperational status. Although precise mapping of individual crops remains a
problem in most cases, groups of crops (e.g. summer cereals) can be mapped
satisfactorily to obtain a measure of actual crop water requirements. Determination
of year to year changes of irrigated area, possibly cropwise, would be a major
contribution towards better irrigation management. Moreover, the same
information is necessary to assess whether collected irrigation fees are paid
consistently with land use. Determination of waterlogged areas and bare salt
affected soils identifies the sectors within an irrigation scheme where water
management has to be improved.
Low spatial resolution. Sensors on-board meteorological satellites have the
capability of providing consistent observations at rather short intervals of time,
although at a relatively low spatial resolution. The multispectral observations
obtained worldwide with the NOAA! A VHRR sensors at a 1 km x 1 km spatial
resolution can be and have been (see examples of applications in the next section)
used to assess the temporal variability of land surface characteristics relevant to
irrigation management. Spatial resolution determines to a significant extent the
practical relevance of remote sensing for irrigation and drainage. Literature (see
Current Applications) points to an overwhelming interest for observations at high
spatial resolution. In some cases, however, even data at very low spatial resolution
may provide useful information on irrigated lands. Choudhury (1997), for
example, determined global potential evaporation at a 270 km x 270 km resolution
by combining satellite and meteorological data. Although not meant for local use,
results compared well with lysimeter observations at a number of locations.
GIS applications. The information obtained with airborne and space-borne
sensors provides a range of useful indicators on irrigation and drainage (see Chap.
4 and Current Applications). The scope of the remotely sensed data, however, can
significantly be enhanced through integration with other types and sources of data