Integrated Applications - Transport in the Atmosphere-Vegetation-Soil Continuum - page 292

Table 8.2 Evapotranspiration, crop yield and water productivity as measured at
experimental stations and farmer ields in Sirsa District from October 2000 to
October 2001

Item Farmer ields Experimental stations

Wheat Cotton Wheat Cotton

Evapotranspiration (mm) 299 609 287 525

Crop yield (tons ha -1 ) 4.6 2.1 7.4 2.9

Water productivity (kg m -3 ) 1.54 0.34 2.58 0.55

farmer ields were related to crop management: proper land levelling, optimal sowing
time, and strict pest, weed and disease control. Thus with ordinary crop management
measures the water productivity in Sirsa District can be raised signiicantly.

8.3.6 Crop Yields at Field Scale
Table 8.3 contains the mean crop yields as derived by distributed SWAP modelling,
by remote sensing (SEBAL) and as measured at the farmer ields. Despite their dif-
ferent approach, both SWAP and SEBAL result in similar average yields for wheat,
rice and cotton. Therefore the calibrated SWAP model could be used to explore vari-
ous management options at farmer ields. For instance, the effect of deicit irrigation,
higher salinity levels and various sowing dates on the inal crop yield and water use
could be investigated (Bessembinder et al., 2003 ).
The standard deviation of the yield is underestimated by remote sensing, in com-
parison to distributed modelling and measurements in farmer ields. This can be
explained by the difference in resolution between remote sensing (30-1100 m) and
distributed modelling and measurements (1-30 m).

8.3.7 Water Productivity at a Regional Scale
SWAP and SEBAL determine ET and crop yield in entirely different ways: agrohy-
drological modelling versus analysis of remote sensing images. Therefore, it is inter-
esting to compare the water productivity values as derived by distributed modelling
and remote sensing ( Table 8.4 ). The mean WP values for the main crops are very
close. The WP standard deviation is larger for the results derived from distributed
modelling than for the results derived from remote sensing due to the higher resolu-
tion of distributed modelling (Singh et al., 2006a ).

8.3.8 Scenario Analysis
To realize the dual objectives of meeting the growing food demands and restricting
water use, water management in Sirsa District should aim at higher crop yields per