S Mohan

An artificial neural network (ANN) model has been developed to generate the multisite streamflows and the results are compared with the classical multsite streamflow generation model developed by Hydrologic Engineering Centre named HEC-4. Both the models have been applied to the case study of Upper Krishna River Basin to evaluate their performances. Important statistical parameters, namely, mean, standard deviation, correlation coefficient of the historical and generated streamflows are compared for the evaluation. Hurst ratio has bem used to' evaluate the strength of persistence of the generated streamflows. This study shows that the streamflows predicted with simple ANN model are more satisfactory than the HEC-4 model in case of multisite streamflow generation.

Irrigation has been practised in India from ancient time. Even now, India has the largest area under irrigation. Tamilnadu state in India stands one among the few states in successfully harnessing and utilising the available water. Future development and management of available water resources can be achieved through optimisation techniques. Water management at farm level is one of the most important activities to be carried out for optimal use of water. Evapotranspiration is the most important variable next to rainfall in the context of irrigation to crops. In this paper, the results of the comparative study on crop water requirements estimation by two methods namely FAO-Penman method and Duty-delta method are reported. It is found that duty-delta method underestimates the crop water requirements.

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.

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.

An optimization model has been formulated to maximize the net benefit from a tank command with conjunctive use of surface water from the tank and ground water from wells and community well in the tank area. The Kannangudi tank in Pudukkottai district, Tamil Nadu, India has been taken as the case study. Six crops were found in the command area and are considered for arriving the optimal cropping pattern. The study result shows that, the wells and community well in a tank command contributes to a sustainable irrigation and apparently maximize the net benefit from that tank command.