Abstract:
One of the primary objectives of river basin planning and management is to assess the behavior of the river towards man-made and natural changes. In recent times, the self-purifying capacity of the river is found to be substantially affected because of extensive use of water for agricultural and industrial purposes. Any variation in the flow regime of a river poses a severe impact on the aquatic ecosystem, which affects its self-purifying capacity. Diverting river water for industrial and agricultural uses through dams and barrages reduces the natural flow rate of the river. The present study develops a novel approach by coupling Watershed Modeling System (WMS ver. 10.1) with linear optimization to provide an alternate means of water supply for such users. To explain the effectiveness of the model, a case study on the Ganges river basin of India has been considered. The ecosystem of the Ganges provides such a magnificent biological fabric, that its self-purifying capacity exceeds that of any other river water across the globe. However, the industries found in the river’s most polluted stretch consume around 1200 million liters of water every day. In addition, 80% of the river water diverts at Narora barrage for agricultural purposes. As a result, the flow of the river in dry seasons is as less as 300 m3/s. The study suggests the need to develop economically feasible and efficient storage reservoirs to store the rainwater, which can be used to supply industrial and agricultural needs. The WMS software is used to acquire the watershed basin, outlet location, simulated runoff volume, proposed reservoir site, and the hydrograph using the monitored rainfall data of 5 years (2010–2014). The simulated runoff volume is then used to develop an optimization model to determine the required capacity of each reservoir using LINGO software (ver. 16.0). Four different storage reservoirs are proposed in the selected industrial sites of Unnao district, Uttar Pradesh, India. These reservoirs can supply the needs of industries, and thus reducing their dependency on the river Ganges.