Water has emerged as a resource that is essential to the development of civilisation. Population growth, which necessitates extensive expansion and development in many areas, has put a tremendous amount of strain on water resources. A country's economic and agricultural development is governed by water scarcity. Water scarcity necessitates careful planning, development, and management in order to use it effectively and sustainably. When there is a shortage of water, water resource managers' main goal is to make the best use of the water that is already available from a variety of sources while taking into account socioeconomic, ecological, and environmental factors. It has been observed that the inflows into the reservoirs frequently fall short of meeting the demand. In these situations, it is necessary to investigate the possibilities of combining the usage of abundant groundwater in the area with surface water to alleviate the shortage. Understanding of reservoir process and infield process is necessary for a reservoir system to operate optimally for the efficient usage of both surface and groundwater resources concurrently. By using optimization models, which are characterised by a mathematical definition of the objective function subjected to a set of constraints to produce global optimum solutions, this knowledge makes it easier to decide how to operate reservoirs and how to plant crops. The reservoir's storages are unclear due to the reservoir's poor operation and fluctuating weather conditions that affect its inflows. Crops' Net Irrigation Requirement (NIR), which introduces uncertainty into irrigation requirements, is stochastic in nature. Even while weather conditions have a significant impact on additional irrigation needs, crop type, market conditions, planting and harvesting times, and market conditions also have an impact. The operating requirements of the reservoir system are typically used to set the storage and release targets for a reservoir operation. The decision-makers demand that all of these factors be taken into account. The best methodological technique for modelling reservoir operation may frequently be fuzzy logic. Through the inclusion of model parameter uncertainties and the interpretation of those uncertainties as fuzzy sets rather of as individual values, the applicability of the reservoir operating model is enhanced in the current study. A membership function illustrates the level of satisfaction with a certain value of the parameter within the fuzzy set. As a result, it is suggested that an optimization model be developed to provide the best reservoir operation policies for sustainable irrigation planning that uses both surface and groundwater simultaneously in a fuzzy environment. It involves estimating groundwater potential under the reservoir's control using the GEC-97 methodology currently in use [19] and the data that is currently available, formulating a Linear Programming (LP) conjunctive use model, determining the best operating policies for the reservoir by taking into account its storage continuity equation, and creating a Fuzzy Linear Programming (FLP) model to account for the uncertainties in the parameters related to the reservoir. By taking into account six different situations, the developed model is applied to the study region of Jayakwadi Project Stage-I on the Godavari River close to the town of Paithan in the State of Maharashtra, India. The hypothetical model takes surface water into account without taking into account socioeconomic factors. In the second example, the social economic restrictions are taken into account to have a specific minimum yield of the crops that are left without allocation of space of the model. In the third scenario, combined use of surface and groundwater is taken into consideration without any socioeconomic restrictions, while in the fourth instance, combined use is taken into consideration with socioeconomic restrictions. A FLP model is taken into consideration in the fifth instance to account for the fuzziness in the resources, and in the sixth case an FLP model with technical coefficients as fuzzy is taken into consideration. All of the examined parameters are taken into account when applying the model created in the current study to the six instances mentioned above. The ideal cropping pattern and ideal release policies are obtained by solving it using the Language for INteractive General Optimization (LINGO). Being a multipurpose reservoir, the model is used to determine the best releases for power generation and irrigation after prioritising the supply of water for industrial and drinking purposes. The crops Rabi Wheat, Rabi Jowar, and Hot Weather Groundnuts were not given space in the global optimal solution of the LP Model, which was derived for the first instance in which just accessible surface water was taken into account without imposing socioeconomic limitations. With an average irrigation intensity of 55.51%, it produced net benefits of Rs. 3563.78 million. So, in order to attain a particular minimum output to satisfy the needs of the local population in the second situation, socioeconomic limits must be placed on these crops. The ideal net benefit in the second example, as opposed to the first, is decreased from Rs 3563.78 million to Rs 3373.45 million by the implementation of such socioeconomic constraints. The net benefits from the crops in the third case increased to Rs 3715.57 Million from Rs 3563.78 Million and the intensity of irrigation to 60.73% from 55.51% as compared to the first case by using the available groundwater as well as the surface water concurrently. However, the model does not allocate any space for the crops Rabi Jowar and Hot Weather Groundnut. To meet the needs of the local population, these crops are therefore subject to socioeconomic limits in the fourth scenario. As a result, each crop has been given its own area, resulting in an irrigation intensity of 60.04% and optimum net benefits of Rs 3590.02 Million. In the fifth scenario, an FLP model has taken into account the resource-related uncertainty. The objective function's maximum and lower bounds, or the net profit from the crops, are 3590.0 million and 3279.72 million rupees, respectively. Lamda (), which measures the degree to which the optimised values satisfy the constraints and aim, comes out to be 0.511. The example also yields optimal outcomes in terms of net benefits, cropping pattern, surface water discharges, groundwater pumpage, storages at the end of each month, and matching head above the turbine.
Author(s) Details:
N. G. Nikam,
Department of Civil Engineering, Government College of Engineering, Aurangabad, India.
D. G. Regulwar,
Department of Civil Engineering, Government College of Engineering, Aurangabad, India.
Please see the link here: https://stm.bookpi.org/COSTR-V3/article/view/8188
No comments:
Post a Comment