Interseasonal Irrigation System Planning for Waterlogged Sodic Soils

Abstract

Irrigation system planning and management of a semiarid region in Indian Punjab is imperative for sustainable agriculture. For the management of soil and water resources of these regions, three nonstructural management models have been developed and linked together to aid in planning the optimum allocation of land and water resources to achieve the objective of maximizing return in the command area of a canal distributary. A ground-water simulation model uses the mass-balance approach to simulate water-table depths. The seasonal crop water response models are developed to compute crop yields. Interseasonal irrigation system planning models maximize net annual return through conjunctive use of surface water and gypsum-treated sodic ground water to achieve an optimal cropping pattern using a linear programming algorithm. The linear programming models are operated at five water mixing indexes (mixing of surface water and poor quality ground water in different proportions) and seven probability of exceedence levels where rainfall, crop water requirements, and canal water supply are assumed as random variables. These random variables are fitted well to the gamma probability density function.