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Simulation and Optimization for Management of Water Resources in a Canal Command Area
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Paper number 022025, 2002 ASAE Annual Meeting . (doi: 10.13031/2013.9704) @2002Authors: S.S. Shirahatti, M.P. Kaushal, A.K.Jain, S.D. Khepar
Keywords: MODFLOW, groundwater modeling, water table profile, response matrix, water allocation modeling, optimal cropping pattern
The groundwater flow model MODFLOW and a chance constrained linear programming
model developed for surface water allocation were coupled using response matrix approach and
applied to the Upper Krishna Project irrigation command area in the south Indian state of Karnataka.
For this purpose total water resources availability, water needs and water balance of the area were
assessed. The groundwater model revealed that the average absolute simulation error between
observed and simulated heads was 0.332 m. The surface water model was developed with an
objective to optimize the annual net returns over the whole tract. The constraints on the water use,
land allocation, surface and groundwater availability as well as hydraulic heads were considered. Net
irrigation requirement at 95,85 and 75 per cent probability levels using two parameter Gamma
distribution; water application to crop at 25, 50, 75, and 100 per cent of net irrigation requirements at
each probability level were used for optimization modeling.
The application of the combined simulation and optimization model revealed that the integrated
model not in only ensured the rational use of land and water resources, but also resulted in the
higher economic returns. It was observed that, at any fixed level of groundwater supply, the net
returns per unit of water used increased with the increase in the canal water supply. The watertable
behavior in the study tract showed that there was an average rise of water table at the rate of 0.15 m/year during the study period. It was concluded that: MODFLOW was more sensitive to variations
in specific yield than to changes in hydraulic conductivity during model calibration; surface water
model resulted in optimal net returns at 25 per cent risk level of net irrigation requirement; the
simulation study could check the increasing trend of waterlogging in the study area by means of
conjunctive water management modeling. The conclusions drawn suggest that the strategy
developed here can be adopted elsewhere in the proper allocation of irrigation water.