S Mohan

A combined optimization-simulation approach was used to develop and evaluate the alternate priority-based policies for operation of surface and groundwater systems and is demonstrated with a case study. An optimization model was used to find optimal cropping pattern with and without the conjunctive use of surface and groundwater, as well as with and without socio-economic constraints. The optimization model, based on linear programming, maximizes the net benefit from irrigation activities subject to various physical, economical, and social constraints. A simulation model was used to evaluate the conjunctive operation of the system using the optimal cropping pattern derived from the optimization model. The developed policies have been verified with long-generated stream flow sequences. Three alternate priority-based policies differing in level of groundwater pumping and area of cultivation of rice crop have been evaluated: (1) irrigation with surface water only (Policy-1); (2) irrigation with conjunctive use of surface and groundwater, without socio-economic constraints (Policy-2); and (3) irrigation with conjunctive use operation and with socio-economic constraints (Policy-3). It was found that the use of available groundwater within three meters below ground level (Policy-2) to be optimal, and these results were used in simulation for further evaluation of policies. It was also found that the policy-3 of conjunctive use operation with a priority of 75 percent of maximum possible rice area (using groundwater available within four meters below ground level) resulted in a better scenario. Thus the conjunctive use Policy-2 and Policy-3 with 75 percent of maximum possible rice crop area can be used as better policies for the system studied. © 2003 Taylor & Francis Group, LLC.

Crop coefficients (Kc) were estimated for cotton, sorghum and millet for tropical South India based on lysimeter measured actual evapotranspiration (ET) and reference crop ET computed by the modified Penman method. The estimated crop coefficients were 0.46, 0.70, 1.01, and 0.39 in the four crop stages for cotton. Kc value of the last stage was significantly lower than the FAO Kc value. The estimated Kc values were considerably lower than FAO crop coefficients in the third and fourth stages for sorghum, for which the estimated stagewise Kc values were 0.42, 0.71, 0.62 and 0.23. For millet, the estimated Kc values for four stages were 0.51, 0.78, 0.87 and 0.50 and found to differ markedly from FAO Kc values. Crop coefficient relationships with respect to time were developed using mean crop coefficients derived from multi-year data. The developed crop coefficients and relationships would be of great use for the estimation of crop water requirements under tropical climatic conditions. © 1994.

A fuzzy linear programming model (FLP) is formulated to derive optimal crop plans for an irrigation system with the aim of conjunctive utilization of water from surface reservoir and ground water aquifer, and demonstrated with a case study. The results of FLP model were compared with classical linear programming model (LP). The LP model model maximizes the net benefits from irrigation activities subject to various physical, economical, and water availability constraints. The fuzziness involved in the input variables such as inflows and ground water pumpage are considered in the FLP model. The FLP model maximizes the degree of satisfaction or truthness subject to object function, physical and economic constraints involving the fuzziness in the input variables. The increase in the degree of satisfaction or the truthness with increase in number of fuzzy variables was studied and the results are reported. It was found that the fuzziness in the ground water pumpage plays a prominent role in deriving the optimal operational strategies. From the optimal results it was found that the FLP model has resulted an optimal crop plan with a degree of truthness of 0.78 taking into account the fuzziness in different variables.

Due to the complexity of irrigation management problems, reliance on experience and experts is necessary for effective decision-making in this domain. Expert systems (ES) are efficient means for providing decision support to tasks that primarily require experience-based knowledge. This paper reviews the adoptability and suitability of ES applications in the domain of irrigation management. Core concepts of ES are briefly discussed. A detailed review of the existing applications of ES is presented under three classes of ES applications: (a) expert systems proper, (b) intelligent front-ends, and (c) hybrid systems. This review of literature shows that the ES approach is applied more recently to broader domain areas in contrast to the earlier systems that were focused on narrower domain problems. Additional research on ES application to domains such as real-time irrigation scheduling, reservoir operation involving stochastic nature of inflows and evapotranspiration demand, and integrated operation of irrigation system components is needed to evolve guidelines for optimal water use. The problem of handling multiple experts to evolve decisions that are less biased than an individual expert needs to be addressed. A methodology that takes into account the uncertainty of the ES decisions is also warranted. Further, there is a need for practical evaluation of the quality of recommendations made by the ES which would result in the successful implementation of the ES. © 1997 Elsevier Science B.V.