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Chintapalli, S.M. 
  
output per unit of water was computed based on proportionate allocation of canal supplies to paddy areas and satellite 
derived paddy production. This performance indicator showed increasing efficiency of water use for paddy production. The 
satellite data analysis had facilitated the identification of canals with poor performance in respect of irrigation intensity, 
paddy yield and water use efficiency. 
Table 2 System performance of Bhadra project through the years 
  
  
  
  
  
(tonnes/m°) 
Parameters Rabi season 
1986-87 . 1989-90 1992-93 . 1993-94 
Irrigated crop area (ha) 73,529 67,366 88,424 84,412 
Percentage of paddy area 56 31 69 69 
Average paddy (rough paddy) yield (tonnes/ha) 3.8 5.4 4.7 4.9 
Depth of water application (m/ha) 1.06 1.04 0.80 0.86 
Area irrigated per unit volume of water (ha/ham) 0.94 0.96 1.25 1.16 
Paddy (rough paddy) output per unit of land (tonnes/ha) 3.8 5.4 4.7 4.9 
Paddy (rough paddy) output per unit volume of water 0.3 0.4 0.5 0.5 
  
  
4.2 Chronological synchronization between crop calendar and water delivery 
An ideal irrigation system should meet the water requirements 
all crops in its command during all the physiological stages. 
The existing water discharge pattern is compared with crop 
calendar derived from satellite data. Here the emphasis is on 
the chronology of canal operation but not on the volume of 
water supplied. Multi date NDVI statistics over paddy area was 
generated for each distributary. The satellite over passes 
represent in general broad spectrum of paddy growth cycle from 
panicle initiation to grain formation. Analysis of NDVI profiles 
of various distributaries revealed three distinct growth patterns 
of paddy crop. Murthy et al, (1998) interpreted these growth 
profiles with the aid of ground truth and derived the crop 
calendar information for each profile indicating the estimated 
time of transplantation and crop harvest for paddy crop 
corresponding to each NDVI profile. Consequently, the 
distributaries of the command area were grouped in to three 
categories namely early transplantation (first fortnight of 
February), normal transplantation (second fortnight of 
February) and late transplantation (first fortnight of March). 
The spatial variability in canal opening and closure is derived 
from ground data and was compared with with satellite derived 
crop calendar. This analysis which was done in GIS 
environment, had resulted in the identification of 21 
distributaries in two categories. The first category of 
distributaries has a lag of 30 days and the second category has 
a lag of 20-30 days between canal closure i.e., cessation of 
water supply and crop harvesting (figure 3). The time lag 
between canal closure and harvesting could be explained in 
relation to paddy growth cycle and water requirements in 
various stages to infer the implications. About 4-7 days prior to 
maturity, water is let out completely, to facilitate harvesting. 
Therefore, in the first category distributaries, the effective 
duration water shortage for crop is 16 days assuming that one 
week before harvest no water is needed and the fields continue 
to get water for one week after canal closure. During this period 
  
  
  
  
Bhadra Project 
Command Area 
i 
| VANGER 
ax Ld, 
n hd 
MALEBENNUR X 
SANTI SAGAR 
LH Lag of 30 days 
BHADRAVATHI : 
Lag of 20-30 days 
BHADRA E 
m 
  
  
  
  
  
  
  
  
  
  
  
  
Figure 3 Time lag between cessation of water 
supply and crop harvest 
the crop would be in grain formation stage which may result in yield reduction subsequently. In the second category of 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000. 269