TY  - BOOK
AU  - Priya, G Nair
AU  - Asha Joseph (Guide)
TI  - Irrigation planning and management of a canal irrigated command using geospatial tools
U1  - 631.3 
PY  - 2023///
CY  - Tavanur
PB  - Department of irrigation and drainage engineering, Kelappaji college of agricultural engineering and technology
KW  - Irrigation
KW  - water
KW  - agriculture
KW  - wells
KW  - power generation
KW  - irrigation and drainage engineering
N1  - PhD
N2  - Most of the irrigation command in India is facing low water use efficiency
and in unequitable distribution of water. The current canal water release policies in 
India are supply based and not meeting the actual water requirement of the existing 
cropping pattern of the command area. Hence most of the major irrigation 
command areas in India suffer from inadequate and unreliable supply of water. The
water is to be delivered over a large area in a canal command with spatially 
variable soils, crops and weather conditions. This spatial and temporal variability
in soil, crop and climate are to be addressed to estimate the actual irrigation 
demand in a canal command.
Distributary is the basic unit in a canal irrigation system. Hence the
estimation of distributary wise irrigation demand and water delivery schedule is 
very important for proper planning and management of irrigation water. Spatial 
data management tool like Geographic Information System (GIS) can effectively 
handle the spatial variability of soil, crop, and weather conditions. GIS with water 
balance model can deal this complex problem of irrigation water demand 
estimation in a quick and easy way. Hence a study was conducted in Gayathri 
Irrigation Project command area to assess the crop-based water demand using GIS 
and water balance model and to develop a demand-based water delivery schedule.
The Gayathri irrigation project (GIP), is one of the medium irrigation 
projects in Palakkad district. The canal network consists of 19 distributaries with 
11 distributaries in left bank canal (LBC) and 8 distributaries in right bank canal 
(RBC). The study area comes under rain shadow area of Palakkad gap and comes 
under the Agro ecological unit (AEU) 23. Geo spatial data base for canal network, 
land use, and soil was created in ArcGIS. ArcMap for distributary command, its 
land use, soil and land use-soil intersect maps were generated to identify the crop 
in a specific soil series.
CROPWAT 8.0 model was used as the field water balance model for 
finding the net water requirement (NIR) of different crops in the command area of 
the distributary. The gross irrigation water requirement (GIWR) of the command 
area was calculated by adding the seepage loss with NIR of various crops in the 
command area. A demand-based water delivery schedule for the operation of 
distributaries were developed based on the existing canal water releasing schedule.
This new water delivery schedule was compared with the prevailing canal roster
for demand supply analysis and to find the surplus/deficit in various distributaries
of the canal command for efficient planning and management.
The paddy was the major crop which occupies about 48 per cent of total
gross command area. The other crops were coconut, mango, vegetables, banana 
and arecanut. The various soil series identified in the command area were Bhavani 
Nagar, Karinganthodu, Mungilmada, Tolanur, Kozhinjampara and Vadavannur,
which occupies 30.99, 28.56, 14.77, 11.62, 10.83 and 3.40 per cent of command 
area respectively. The Bhavani Nagar series was with sandy clay texture, while all 
other series were with sandy clay loam texture.
The NIR of different crops estimated by CROPWAT 8.0 model showed that
NIR varied with respect to for season, soil, crop and climatic condition. NIR of 
rice (mundakan) varied from 1004.5 to 1576.3 mm between head and tail reaches.
The high value in tail reach was due to high infiltration rate of the soil series 
‘Karinganthode’. The variation in NIR of rice (mundakan) was also found in the
same soil series among the different distributaries (Bhavani Nagar series with 
1056.5mm and 1004.5 mm in head and middle reaches respectively). This was
mainly due to the variations of rainfall in the area. The average NIR values for
other crops viz. rice (virippu), coconut, mango, vegetable, banana and arecanut 
were found 1081mm, 483.3, 372 and 417.4, 752.3 and 166.9 mm respectively. The 
total annual NIR of different distributaries showed that it was more than 10000 
m3
/ha for all the distributaries. The highest NIR of about 25000 m3
/ha was 
obtained for DB14 (Peringhotukavu) followed by DB7 (Ootara). The lowest NIR
of below 5000 m3
/ha was obtained for DB1 (Parakkalchalla)
The estimated seepage loss for computation of GIWR showed that the
seepage loss values ranged from 0.003 to 0.029 m3
/m2
/day. The gross irrigation 
requirement was found more for distributaries in middle and tail reaches than the
head reach. The highest GIWR of 25369.71 m3
/ha was obtained for DB14 
(Peringhotukavu) followed by DB7 (Ootara). The lowest GIWR of 4390.965 m3
/ha
was obtained for DB 1 (Parakkalchalla). The newly developed crop water demandbased water delivery schedule consists of 12 irrigation cycles which starts from 
20th of October and ends on 14th May. The water demand was found high in 1st and 
10th
irrigation cycles in almost all distributaries. The maximum water demand of 
3.017 Mm3 was seen in DB19 (Kollengode distributary) which is having the 
highest total irrigable area of 554.837 ha. The lowest water demand of 0.002 Mm3
was seen in DB1 (Parakkalchalla) followed by DB2 (Pappanchalla). The water 
demand of other distributaries ranged from 0.003 to 1.497 Mm3
.
The newly developed water delivery schedule was compared with the 
existing water delivery schedule for demand supply analysis and it showed that 
actual supply was very low in majority of the distributaries, which was below 1.6 
Mm3
. Demand supply gap was found maximum in DB19 (Kollengode distributary)
with +7.447 Mm3
. The demand was also compared with design volume of 
distributaries. Both the actual water supply and design volume was found more for 
DB19, (Kollengode distributary) than other distributaries. The distributaries in the 
head reach of canal irrigation system showed negative value (supply more than the
demand) while all other distributaries showed positive values (supply less than 
demand). The demand and design volume gap showed negative values for
distributaries DB1, DB3, DB4, DB 5, DB 6, DB11, DB12 and DB13 (supply more 
than design volume) while all other distributaries showed positive values (supply 
less than design demand). The highest negative value was found for in DB12
(Peruvemb -2.486 Mm3
). The highest positive value was found for DB19,
Kollengode distributary (+ 5.438 Mm3
).
Canal performance by adequacy indicator showed that the distributaries in 
head reach of canal irrigation system, are getting sufficient water and showed good 
performance with performance adequacy (PA) value near to one. All other 
distributaries were having PA value less than 0.7 indicated poor performance. The 
performance indices equity (PIE) and efficiency (PIEF) of different distributaries 
were also determined. The distributaries DB1 and DB6 showed poor equity (PIE)
values of 0.704 and 0.375 indicated the spatial distribution of irrigation water is 
not equal with respect to demand. All other distributaries were showed fair or 
good performance. In case of efficiency (PIEF), distributaries DB1 and DB6 
showed values of 0.37 and 0.57 showed poor efficiency and the system was not 
efficient to meet the requirements of the region. The PIEF values were observed
greater than 0.7 for all other distributaries indicated that system was efficient to 
meet the requirement of the region.
Thus, it could be concluded that spatial variations in climate, soil and crop 
are to be considered for the estimation of irrigation water demand in the canal 
command. GIS with water balance model was found an effective tool for 
addressing this spatial variability in water demand. The effective planning and 
management of water resources of the canal command should be based on the 
optimum use of irrigation water. A crop water demand-based delivery schedule is 
essential for achieving this goal
ER  -