TECHNICAL PAPERS
May 1, 2000

Optimal Irrigation Allocation: A Multilevel Approach

Publication: Journal of Irrigation and Drainage Engineering
Volume 126, Issue 3

Abstract

Optimal resources allocation strategies for a canal command in the semiarid region of Indian Punjab are developed in a stochastic regime, considering the competition of the crops in a season, both for irrigation water and area of cultivation. The proposed strategies are divided into two modules using a multilevel approach. The first module determines the optimal seasonal allocation of water as well as optimal cropping pattern. This module is subdivided into two stages. The first stage is a single crop intraseasonal model that employs a stochastic dynamic programming algorithm. The stochastic variables are weekly canal releases and evapotranspiration of the crop that are fitted to different probability distribution functions to determine the expected values at various risk levels. The second stage is a deterministic dynamic programming model that takes into account the multicrop situation. An exponential seasonal crop-water production function is used in this stage. The second module is a single crop stochastic dynamic programming intraseasonal model that takes the output of the first module and gives the optimal weekly irrigation allocations for each crop by considering the stress sensitivity factors of crops.

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Published In

Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 126Issue 3May 2000
Pages: 149 - 156

History

Received: Aug 20, 1998
Published online: May 1, 2000
Published in print: May 2000

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Authors

Affiliations

Member, ASCE
Grad. Res. Asst., 142 Scoates Hall, Dept. of Agric. Engrg., Texas A&M Univ., College Station, TX 77843. E-mail: [email protected]
Asst. Prof., Dept. of Agric. and Food Engrg., Indian Inst. of Technol., Kharagpur, 721 302, India; corresponding author. E-mail: snp@agfe. iitkgp.ernet.in
Asst. Prof., Dept. of Civ. Engrg., Indian Inst. of Technol., Kharagpur 721 302, India. E-mail: [email protected]

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