Abstract: In oases, the surface water resources are becoming
increasingly scarce and groundwater resources, which generally have
a poor quality due to the high levels of salinity, are often
overexploited. Water saving have therefore become imperative for
better oases sustainability. If drip irrigation is currently recommended
in Morocco for saving water and valuing, its use in the sub-desert
areas does not keep water safe from high evaporation rates. An
alternative to this system would be the use of subsurface drip
irrigation. This technique is defined as an application of water under
the soil surface through drippers, which deliver water at rates
generally similar to surface drip irrigation. As subsurface drip
irrigation is a recently introduced in Morocco, a better understanding
of the infiltration process around a buried source, in local conditions,
and its impact on plant growth is necessarily required. This study
aims to contribute to improving the water use efficiency by testing
the performance of subsurface irrigation system, especially in areas
where water is a limited source. The objectives of this research are
performance evaluation in arid conditions of the subsurface drip
irrigation system for young date palms compared to the surface drip.
In this context, an experimental test is installed at a farmer’s field in
the area of Erfoud (Errachidia Province, southeastern Morocco),
using the subsurface drip irrigation system in comparison with the
classic drip system for young date palms. Flow measurement to
calculate the uniformity of the application of water was done through
two methods: a flow measurement of drippers above the surface and
another one underground. The latter method has also helped us to
estimate losses through evaporation for both irrigation techniques. In
order to compare the effect of two irrigation modes, plants were
identified for each type of irrigation to monitor certain agronomic
parameters (cumulative numbers of palms and roots development).
Experimentation referred to a distribution uniformity of about 88%;
considered acceptable for subsurface drip irrigation while it is around
80% for the surface drip irrigation. The results also show an increase
in root development and in the number of palm, as well as a
substantial water savings due to lower evaporation losses compared
to the classic drip irrigation.
The results of this study showed that subsurface drip irrigation is
an efficient technique, which allows sustainable irrigation in arid
areas.
Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.