Optimal Irrigation Water Management in parts of Hirakud Command Area Sambalpur India using Benchmarking and Artificial Intelligence Techniques

Abstract

Water is a precious gift of nature and valuable resource for the society. It is essential for the survival of all living organisms, and for this, there is a saying Water is life . In addition to other uses of water, a major share of water is used to meet the agricultural demand; and this work addresses the relevant problems related to canal irrigation and evolves strategies to solve them. The present experiment is carried on different parts of the command area of the Hirakud canal system, Odisha, India, where two third of total workforce is engaged in agriculture. This area is known as the rice bowl of the state of Odisha, India. Hence an integrated planning and management of available land and water resources is advocated in this research to maximize the economic returns from the crop land, while keeping an eye on acceptability, and the environment. It aims at improving the net beneand#64257;ts obtained from the farming activities with available water allocation. CROPWAT 8.0 is used in finding the crop water and irrigation requirements for various crops cultivated in the study area using the soil, climate and crop data. The work of evaluation of performance using Bench-Marking Techniques was conducted on the command area of Paramanpur distributary and Senhapali distributary. State-of-the-art instruments, such as Flow Tracker ADV and micro ADV were used to measure the flow in the canals to ascertain water availability in the command area. A novel technique for the flow measurement in lined canals was developed by considering the relation between the mean and maximum velocity of flow using Entropy theory, which will be helpful for irrigation Engineers. Artificial Intelligence Techniques viz. Genetic Algorithm (GA), Cuckoo Search (CS) and Particle Swarm Optimization (PSO) techniques are applied to develop an efficient cropping pattern for getting maximum net benefits from agriculture. The results are compared with the output from Linear Programming (LP) model to evaluate the eand#64259;ciency of the models newline